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Food, Fibre and Other
Ecosystem Products
Coordinating Lead Authors:
Rachel Bezner Kerr (USA/Canada), Toshihiro Hasegawa (Japan),
Rodel Lasco (Philippines)
Lead Authors:
Indra Bhatt (India), Delphine Deryng (Germany/France), Aidan Farrell (Trinidad
and Tobago/Ireland), Helen Gurney-Smith (Canada/UK), Hui Ju (China), Salvador Lluch-Cota
(Mexico), Francisco Meza (Chile), Gerald Nelson (USA), Henry Neufeldt (Denmark/Germany),
Philip Thornton (Kenya/UK)
Contributing Authors:
Almut Arneth (Germany),
Guleid Artan (Kenya/Somalia), Ayansina
Ayanlade (Nigeria), Ermias Aynkulu (Kenya/Ethiopia), Marta Baraibar (Kenya/Spain), Manuel
Barange (South Africa/Italy), Mucahid Mustafa Bayrak (the Netherlands), Göran Berndes (Sweden),
Jörn Birkmann (Germany), Luisa F. Cabeza (Spain), Donovan Campbell (Jamaica), Edwin Castellanos
(Guatemala), William Cheung (Canada), Priscilla Claeys (Belgium), Jennifer Clapp (Canada), Jofre
Carnicer Cols (Spain), Annette Cowie (Australia), Verónica Crespo-Pérez (Ecuador), Vassilis Daioglou
(Greece), Shouro Dasgupta (Italy/Bangladesh), Deborah Delgado Pugley (Peru), Alice Favero (USA),
Jennifer Franco (the Netherlands), Eranga Galappaththi (Canada/Sri Lanka), Amelie Gaudin (USA/
France), Adugna Gemeda (Ethiopia), Patrick Gonzalez (USA), Jack Heinemann (New Zealand/USA),
Kirstin Holsman (USA), Joanna House (UK), Ann Kingiri (Kenya), Adrian Leip (Belgium/Germany),
Xiaoyue Li (China), Ana Maria Loboguerrero (Colombia), Angelo Maggiore (Italy), Dianne Mayberry
(Australia), Kathleen Miller (USA), Christian Möllmann (Germany), Michael Morecroft (UK), Kenneth
Kemucie Mwangi (Kenya), Gert-Jan Nabuurs (the Netherlands), Christine Negra (USA), Kari Marie
Norgaard (USA), Hanson Nyantakyi-Frimpong (USA/Ghana), Elizabeth A. Nyboer (Canada), Elena
Ojea (Spain), Camille Parmesan (France/UK/USA), Gretta Pecl (Australia), Patricia Pinho (Brazil), John
Pinnegar (UK), Julio C. Postigo (USA/Peru), Bronwen Powell (Canada), Amy Quandt (USA), Marie-
Fanny Racault (UK/France), Victoria Reyes-García (Spain), Marta Rivera-Ferre (Spain), Abubakr
A.M. Salih (Kenya/Sudan), Arnim Scheidel (Spain/Austria), Anna Schlingmann (Spain/Germany),
Matthew Schnurr (Canada), Rupert Seidl (Germany), Gudeta W. Sileshi (Zambia/Ethiopia), Pramod
K. Singh (India), Raphael Slade (UK), Pete Smith (UK), Doris Soto (Chile), Elizabeth Sprout (UK/USA),
M. Cristina Tirado-von der Pahlen (USA/Spain), Jennifer Vanos (Canada), Hitomi Wakatsuki (Japan),
Lewis Ziska (USA), Robert Zougmoré (Burkina Faso)
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Review Editors:
Pauline Dube (Botswana), James Morison (UK)
Chapter Scientists:
Emily Baker (USA), Hitomi Wakatsuki (Japan), Elizabeth Sprout (UK/USA)
This chapter should be cited as:
Bezner Kerr, R., T. Hasegawa, R. Lasco, I. Bhatt, D. Deryng, A. Farrell, H. Gurney-Smith, H. Ju, S. Lluch-Cota, F. Meza,
G. Nelson, H. Neufeldt, and P. Thornton, 2022: Food, Fibre, and Other Ecosystem Products. In:
Climate Change 2022:
Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck,
A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press, Cambridge,
UK and New York, NY, USA, pp. 713–906, doi:10.1017/9781009325844.007.
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Chapter 5
Executive Summary
Current Impacts
Climate change impacts are stressing agriculture, forestry,
fisheries and aquaculture, increasingly hindering efforts to
meet human needs (
high confidence
1
)
. Human-induced warming
has slowed growth of agricultural productivity over the past 50 years
in mid and low latitudes (
medium confidence
). Crop yields are
compromised by surface ozone (
high confidence
). Methane emissions
have negatively impacted crop yields by increasing temperatures
and surface ozone concentrations (
medium confidence
). Warming is
negatively affecting crop and grassland quality and harvest stability
(
high
co
nfidence
). Warmer and drier conditions have increased tree
mortality and forest disturbances in many temperate and boreal
biomes (
high confidence
), negatively impacting provisioning services
(
medium confidence
). Ocean warming has decreased sustainable yields
of some wild fish populations (
high confidence
). Ocean acidification
and warming have already affected farmed aquatic species (
high
co
nfidence
). {5.2.1, 5.4.1, 5.5.1, 5.6.1, 5.7.1, 5.8.1, 5.9.1}
Warming has altered the distribution, growing area suitability
and timing of key biological events, such as flowering and
insect emergence, impacting food quality and harvest stability
(high confidence)
. It is
very likely
2
that climate change is altering
the distribution of cultivated, wild terrestrial, marine and freshwater
species. At higher latitudes, warming has expanded potential area
but has also altered phenology (
high confidence
), potentially causing
plant–pollinator and pest mismatches (
medium confidence
). At low
latitude, temperatures have crossed upper tolerance thresholds, more
frequently leading to heat stress (
high
co
nfidence
). {5.4.1, 5.7.4, 5.8.1,
Cross-Chapter Box MOVING PLATE this chapter , 5.12.3.4}
Climate-related extremes have affected the productivity of all
agricultural and fishery sectors, with negative consequences for
food security and livelihoods (
high confidence
).
The frequency
of sudden food production losses has increased since at least mid-
20th century on land and sea (
medium evidence
,
high agreement
).
Droughts, floods and marine heatwaves contribute to reduced food
availability and increased food prices, threatening food security,
nutrition and livelihoods of millions (
high confidence
). Droughts
induced by the 2015–2016 El Niño, partially attributable to human
influences (
medium confidence
), caused acute food insecurity in
various regions, including eastern and southern Africa and the dry
corridor of Central America (
high confidence
). In the northeast Pacific,
a recent 5-year warm period impacted the migration, distribution
and abundance of key fish resources (
high confidence
). Increasing
variability in grazing systems has negatively affected animal fertility,
mortality and herd recovery rates, reducing livestock keepers’ resilience
1
In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of confidence is
expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g.,
medium confidence
. For a given evidence and agreement statement, different confidence levels
can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence.
2
In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as
likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, and exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%, more likely than not >50–100%, and extremely unlikely
0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g.,
very likely
. This Report also uses the term ‘likely range’ to indicate that the assessed likelihood of an outcome
lies within the 17–83% probability range.
3
Disability-adjusted life years or DALYs.
(
medium confidence
). { 5.2.1, 5.4.1, 5.4.2, 5.5.2,5.8.1, 5.9.1, 5.12.1,
5.14.2, 5.14.6, Cross-Chapter Box MOVING PLATE this chapter; WGI
AR6 Sections 11.2–11.8}
Climate change impacts everybody, but vulnerable groups
,
such as women, children, low-income households, Indigenous
or other minority groups and small-scale producers, are often
at higher risk of malnutrition, livelihood loss, rising costs
and competition over resources (
high confidence
).
Increasing
competition for land, energy and water exacerbates impacts of climate
change on food security (
high confidence
). {5.4.2.2, 5.5.2.6; 5.8.2.2,
5.9.2.1, 5.12.2, 5.12.3.1; 5.12.3.2; 5.12.3.3; 5.13.1, 5.13.3, 5.13.4}
Projected Impacts
Climate change will make some current food production areas
unsuitable (
high confidence
).
Current global crop and livestock
areas will increasingly become climatically unsuitable under a high-
emission scenario (
high confidence
) (e.g., 10% by 2050, over 30%
by 2100 under SSP-8.5 versus below 8% by 2100 under SSP1-2.6).
Increased, potentially concurrent climate extremes will periodically
increase simultaneous losses in major food-producing regions
(
medium confidence
). {5.2.2, 5.4.1, 5.4.3, 5.5.2, 5.5.3, Cross-Chapter
Box MOVING PLATE in this chapter, Section 5.12.4; WGI Section 11.8}
Impacts on food availability and nutritional quality will increase
the number of people at risk of hunger, malnutrition and diet-
related mortality (
high confidence
).
Climate change will increase
the number of people at risk of hunger in mid-century, concentrated in
Sub-Saharan Africa, South Asia and Central America (
high confidence
)
(e.g., between 8 million under SSP1-6.0 and 80 million people under
SSP3-6.0). Increased CO
2
concentrations will reduce nutrient density of
some crops (
high confidence
). Climate change will increase loss of years
of full health
3
by 10% in 2050 under Representative Concentration
Pathway (RCP) 8.5 because of undernutrition and micronutrient
deficiencies (
medium evidence
,
high agreement
). {5.2.2, 5.4.2, 5.4.3,
5.12.1.2, 5.12.4; Cross-Chapter Box MOVING PLATE this chapter}
Climate change will increasingly expose outdoor workers and
animals to heat stress, reducing labour capacity, animal health,
and dairy and meat production
(
high confidence
). The number of
days with climatically stressful conditions for outdoor workers will
increase by up to 250 workdays per year by century’s end in some parts
of South Asia, tropical sub-Saharan Africa and parts of Central and
South America under Shared Socioeconomic Pathway (SSP) 5-8.5, with
negative consequences such as reduced food productivity, higher costs
and prices (
medium confidence
). From early- to end-century, cattle,
sheep, goats, pigs and poultry in the low latitudes will face 72–136
additional days per year of extreme stress from high heat and humidity
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under SSP5-8.5. Meat and milk productivity will be reduced (
medium
confidence
). {5.5.3.4; 5.12.4}
Climate change will further increase pressures on terrestrial
ecosystem services supporting global food systems (
high
co
nfidence
).
Climate change will reduce the effectiveness of pollinator
agents as species are lost from certain areas, or the coordination of
pollinator activity and flower receptiveness is disrupted in some regions
(
high confidence
). Greenhouse-gas emissions will negatively impact air,
soil and water quality, exacerbating direct climatic impacts on yields
(
high
co
nfidence)
.
{5.4.3, Box 5.3, Box 5.4, 5.5.3.4; 5.7.1, 5.7.4, 5.10.3}
Climate change will significantly alter aquatic food provisioning
services and water security with regional variances (
high
confidence
).
Climate change will reduce marine fisheries and
aquaculture productivity, altering the species that will be fished or
cultured, and reducing aquaculture habitat in tropical and subtropical
areas (
high confidence
). Global ocean animal biomass will decrease by
5–17% under RCP2.6 and 8.5, respectively, from 1970 to 2100 with
an average decline of 5% for every 1°C of warming, affecting food
provisioning, revenue value and distribution (
medium confidence
).
Global marine aquaculture will decline under warming and
acidification from 2020 to 2100, with potential short-term gains for
temperate finfish and overall negative impacts on bivalve aquaculture
from habitat reduction (50–100% for some countries in the Northern
Hemisphere) (
medium confidence
). Changes in precipitation, sea level,
temperature and extreme climate events will affect food provisioning
from inland and coastal aquatic systems (
high confidence
). Sea
level rise and altered precipitation will increase coastal inundation
and water conflicts between water-dependent sectors, such as rice
production, direct human use and hydropower (
medium confidence
).
{5.8.3, 5.9.3, 5.13, Cross-Chapter Box SLR in Chapter 3}
The occurrence and distribution of pests, weeds and diseases,
including zoonoses, in agricultural, forest and food systems
(terrestrial and aquatic) will be altered, and their control will
become costlier (
medium confidence
).
Changes in
the rates of
reproduction and distribution of weeds, insect pests, pathogens and
disease vectors will increase biotic stress on crops, forests and livestock,
and will increase the risk of biodiversity loss and ecosystem degradation
(
medium evidence
,
high agreement
). Risks will increase for climate-
driven emerging zoonoses (
medium evidence
,
high agreement
). {5.4.1.3,
5.9.4, Cross-Chapter Box MOVING PLATE this chapter}
Forest production systems will have variable responses to
climate change across regions, with negative effects being more
predominant in tropical forests (
high confidence
).
In temperate and
boreal regions, some productivity gains are projected, but tree mortality
will increase in some areas (
high confidence
). In tropical forests, change
in species composition and forest structure will lower production
(medium confidence
). Some models project a possible increase in global
wood supply and lowering of average wood prices, but they do not
account for the negative impacts of extreme events and thus possibly
overestimate the wood supply (
medium confidence
). {5.6.2}
Climate change will negatively impact food safety (
high con-
fidence
).
Higher temperatures and humidity will favour toxigenic fungi,
plant and animal-based pathogens, and harmful algal blooms (HABs)
(
high confidence
). More frequent and intense flood events and in-
creased melting of snow and ice will increase food contamination (
high
confidence
). Incidence and severity of HABs and water-borne diseases
will increase, as will indirect effects from infrastructure damage during
extreme events (
high confidence
). {5.4.3, 5.5.2.3, 5.8.1, 5.8.2, 5.8.3,
5.9.1, 5.11.1, 5.11.3, 5.12.3; Cross-Chapter Box ILLNESS in Chapter 2}
Adaptation
Many autonomous adaptation options have been implemented
in both terrestrial and aquatic systems, but on-farm adaptations
are insufficient to meet Sustainable Development Goal (SDG) 2
(
high confidence
).
Autonomous responses include livestock and farm
management, switching varieties/species and altered timing of key
farm activities such as planting or stocking (
high confidence
). However,
because of limited adaptive capacities and non-climatic compounding
drivers of food insecurity, SDG2 will not be met (
high confidence
).
{Table 5.1, 5.4.4; 5.5.4, 5.9.4, 5.10.4; 5.12.4}
Various adaptation options are currently feasible and effective
at reducing climate impacts in different socio-cultural, economic
and geographical contexts (
high confidence
), but some lack
adequate economic or institutional feasibility or information on
limits (
medium confidence
).
Feasible and effective options include
cultivar improvements, community-based adaptation, agricultural
diversification, climate services, adaptive eco-management in fisheries
and aquaculture.
There is
limited evidence
,
medium agreement
on the
institutional feasibility or cost effectiveness of adaptation activities,
and the limits to such adaptations. {5.4.4, 5.5.4, 5.6.3, 5.8.4, 5.9.4,
5.10.4, 5.11.4, 5.12.4, 5.14.1}
Ecosystem-based approaches such as diversification, land
restoration, agroecology and agroforestry have the potential
to strengthen resilience to climate change with multiple co-
benefits, but trade-offs and benefits vary with socio-ecological
context (
high confidence
).
Ecosystem-based approaches support
long-term productivity and ecosystem services such as pest control,
soil health, pollination and buffering of temperature extremes (
high
confidence
), but potential and trade-offs vary by socioeconomic context,
ecosystem zone, species combinations and institutional support
(
medium confidence
). {5.4.4.4, 5.6.3, 5.10.4, 5.14.1, Cross-Chapter
Box NATURAL in Chapter 2; Cross-Working Group Box BIOECONOMY
this chapter}
Bio-based products as part of a circular bioeconomy have potential
to support adaptation and mitigation, with sectoral integration,
transparent governance and stakeholder involvement key to
maximising benefits and managing trade-offs (
high confidence
).
A sustainable bioeconomy relying on bioresources will need to be
supported by technology innovation and international cooperation
and governance of global trade to disincentivise environmental and
social externalities (
medium confidence
). {Cross-Working Group
Box BIOECONOMY this chapter}
Sustainable resource management in response to distribution
shifts of terrestrial and aquatic species under climate change is
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an effective adaptation option to reduce food and nutritional
risk, conflict and loss of livelihood (
medium confidence
).
Adaptive
transboundary governance and ecosystem-based management, livelihood
diversification, capacity development and improved knowledge-sharing
will reduce conflict and promote the fair distribution of sustainably
harvested wild products and revenues (
medium confidence
). Other
options include shared quotas and access rights considering trade-offs,
shifting livelihoods to follow target species, new markets for emerging
species, and technology {Cross Chapter Box MOVING PLATE this chapter,
5.8.4, 5.14.3.4}
Implemented adaptation in crop production will be insufficient to
offset the negative effects of climate change (
high confidence
).
Currently available management options have the potential to
compensate global crop production losses due to climate change up
to ~2°C warming, but the negative impacts even with adaptation
will grow substantially from the mid-century under high temperature
change scenarios (
high confidence
). Regionally, the negative effects
will prevail sooner where current temperatures are already higher as
in lower latitudes (
high confidence
). {5.2.2, 5.4.3, 5.4.4, 5.8.4, 5.9.4,
5.14.2.4}
Supportive public policies will enhance effectiveness and/or
feasibility of adaptation in ecosystem provisioning services
(
medium confidence
).
Policies that support system transitions
include shifting subsidies, removing perverse incentives, regulation
and certification, green public procurement, investment in sustainable
value chains, support for capacity-building, access to insurance
premiums, payments for ecosystem services, and social protection,
among others (
medium confidence
). {5.4.4.3; 5.4.4.4; 5.10.4.4;
5.12.6; 5.13.4; 5.14.1.3; 5.14.2.4; Box 5.13, Cross-Working Group
Box BIOECONOMY in Chapter 2}
Harnessing youth innovation and vision alongside other SDGs
such as gender equity, Indigenous knowledge, local knowledge,
and urban and rural livelihoods, will support effective climate
change adaptation to ensure resilient economies in food
systems (
high confidence
).
Adaptation strategies that address
power inequities lead to co-benefits in equity outcomes and resilience
for vulnerable groups (
medium confidence
). Indigenous knowledge
and local knowledge facilitate adaptation strategies for ecosystem
provisioning, especially when combined with scientific knowledge using
participatory and community-based approaches (
high confidence
).
{5.4.4.3, Table 5.6, 5.6.3, 5.8.4, 5.9.2, 5.9.4.1, 5.9.5, 5.10.2.2, 5.12.7,
5.12.8, 5.13.4, 5.13.5, 5.14.1.1, 5.14.1.2, 5.14.1.4,5.14.2.1, Box 5.13,
5.14.2.2 }
Policy decisions related to climate change adaptation and
mitigation that ignore or worsen risks of adverse effects
for different groups and ecosystems increase vulnerability,
negatively affect capacity to deal with climate impacts, and
impede sustainable development (
medium confidence with
robust evidence, medium agreement
)
.
Lacking sufficient stakeholder
participation, large-scale land acquisitions have had mostly negative
implications for vulnerable groups and climate change adaptation (
high
confidence
). Policy and programme appraisal of adaptation options
that consider the risks of adverse effects across different groups at
different scales and use inclusive rights-based approaches help avoid
maladaptation (
medium confidence
). Successful forest adaptation
involves recognition of land rights and cooperation with Indigenous
Peoples and other local communities who depend on forest resources
(
high confidence
). {5.6.3; 5.12.3, 5.13.1; 5.13.2; 5.14.2.1}
Financial barriers limit implementation of adaptation options in
agriculture, fisheries, aquaculture and forestry, and vastly more
public and private investment is required (
high confidence)
.
Public-sector investment in adaptation of agriculture, forestry and
fisheries has grown four-fold since 2010, but adaptation costs will be
much higher to meet future adaptation needs (
medium confidence
).
Expanding access to financial services and pooling climate risks will
enable and incentivise climate change adaptation (
medium confidence
).
{5.14.3, 5.14.5., Cross-Chapter Box FINANCE in Chapter 17}
Climate resilient development pathways offer a way forward to
guide climate action in food system transitions, but operationa-
lisation is hampered by limited indicators and analyses (
medium
confidence
).
Robust analyses are needed that detail plausible path-
ways to move towards more resilient, equitable and sustainable food
systems in ways that are socially, economically and environmentally
acceptable through time (high confidence). Appropriate monitoring and
rapid feedback to food system actors will be critical to the success of
many current and future adaptation actions (high confidence). {5.14.4}
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5.1 Introduction
5.1.1
Scope of the Chapter
This chapter assesses the scientific literature produced after the
Intergovernmental Panel on Climate Change (IPCC) 5th Assessment
Report (AR5) dealing with past, current and future climate change
effects on managed ecosystems that provide provisioning and cultural
services. It spans low- and high-intensity production systems for food,
feed, fibre and other ecosystem products.
Climate change has already had global impacts, including in high-
income countries. Special emphasis is placed on the assessment of
vulnerabilities of particular groups that are context- and location-
specific, such as Indigenous Peoples and other minorities, women and
small-scale food producers. The report builds on the IPCC AR5 and
recent Special Reports. This chapter combines food systems, fibre, wood
and other products from ecosystems previously detailed in separate
chapters of AR5, with an increased focus on ecosystem services,
including the long-term sustainability of the global food system
(Figure 5.1). The chapter focuses on key climate risks, implementation
and outcomes of adaptation solutions for different groups as well as
limits to adaptation.
5.1.2
Starting Point: AR5 and Recent IPCC Special Reports
AR5 Chapter 7 (Porter et al., 2014) reported with
high confidence
that food production systems were being negatively impacted by
climate change, including both terrestrial and aquatic food species
(Porter et al., 2014). Increased temperatures will have large negative
impacts on the food production system under 2°C warming by late
20th century, with temperatures exceeding 4°C posing even greater
risk to global food security (Porter et al., 2014). Adaptation options are
needed to reduce the risk from climate change, but there was limited
information of their effectiveness.
The 1.5°C Special Report concluded that climate-related risks to food
security will rise under 1.5°C and will increase further under 2°C
or higher. Above 1.5°C, currently available adaptation options will
be much less effective and site-specific limits to adaptation will be
reached for vulnerable regions and sectors. There was
high confidence
that limiting warming to 1.5°C will result in smaller net reductions in
yields of major crops affecting food availability and nutrition, and that
rising temperatures will adversely affect livestock via changes in feed
quality, fertility, production, spread of diseases and water availability.
The IPCC Special Report on Climate Change and Land (SRCCL) expanded
beyond the 1.5°C report to provide more in-depth information on
climate change interactions with food security, desertification and
degradation. There was
high confidence
that climate risks, both for
slow changes and extreme events, are interlinked with ecosystem
services, health and food security, often cascading and potentially
reinforcing effects. Climate change already affects all dimensions of
food security, namely availability, access, utilisation and stability, by
disrupting food production, quality, storage, transport and retail. These
effects exacerbate competition for land and water resources, leading
to increased deforestation, biodiversity reduction and loss of wetlands.
With
high certainty
, limiting global warming would lower future
risks related to land, such as water scarcity, fire, vegetation shifts,
degradation, desertification and food insecurity and malnutrition,
particularly for those most vulnerable today: small-scale food
producers in low-income countries, Indigenous communities, women,
and the urban poor. SRCCL assessed a range of adaptation pathways
to increase food resilience.
The IPCC Special Report on the Ocean and Cryosphere in a Changing
Climate (SROCC) identified climate change impacts of warming,
deoxygenation and acidification of the ocean and reductions in snow,
sea ice and glaciers as having major negative impacts on fisheries and
crops watered from mountain runoff and agriculture. These impacts
affect food provisioning of food and directly threaten livelihoods and
food security of vulnerable coastal communities and glacier-fed river
basins. Climate change impacts on fisheries will be particularly high in
tropical regions, where reductions in catch are expected to be among
the largest globally, leading to negative economic and social effects
for fishing communities and with implications for the supply of fish
and shellfish (
high confidence
). While specific impacts will depend on
the level of global warming and mitigative action to improve fisheries
and aquaculture management, some current management practices
and extraction levels may not be viable in the future.
5.1.3
Chapter Framework
This chapter is taking a food systems approach similar to the food
security chapter in SRCCL (Mbow et al., 2019), with close attention to
food system linkages, interactions and impacts on ecosystem services
and biodiversity (Steffen et al., 2015; Raworth, 2017; Gerten et al., 2020).
Food security
is defined as “a situation that exists when all people, at
all times, have physical, social and economic access to sufficient, safe
and nutritious food that meets their dietary needs and food preferences
for an active and healthy life” (FAO, 2020). Food insecurity is often
experienced as chronic hunger reported in the annual UN Food Security
and Nutrition in the World (FAO, 2020), when a person is unable to
consume enough food over an extended period. The chapter gives special
attention to climate change impacts on acute food insecurity, which can
occur at any time with a severity that threatens lives, livelihoods or both,
regardless of the causes, context or duration, as a result of shocks risking
determinants of food security and nutrition, and used to assess the need
for humanitarian action (IPC Global Partners, 2019).
Climate change directly affects food systems, and the impacts on
terrestrial or aquatic food production will become increasingly negative,
although regionally some changes may be beneficial in the near future
(Porter et al., 2014). Current food system trajectories are leading to
biodiversity loss and land and aquatic ecosystem degradation without
delivering food security, nutrition, and sustainable and healthy
livelihoods to many (Steffen et al., 2015). Addressing climate change
in isolation ignores these interconnections, which is why the chapter
considers integrated adaptation solutions to allow humanity to thrive
in the long term. At the same time, social foundations of equality,
justice and political participation are crucial in order to move towards
a safe operating space for humanity (Raworth, 2017). The SDGs
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provide the most comprehensive set of metrics of humanity’s progress
in achieving equitable and thriving socio-ecological systems. Therefore,
while the focus of this chapter is climate change impacts, vulnerability
and adaptation of food systems, feed, fibre and other ecosystem
products, other environmental and social challenges are considered
concomitantly.
Food system and natural systems interact via political, economic,
social, cultural and demographic factors in complex ways, leading
to food security and sustainability outcomes. The food system has a
supply (production) and demand (consumption) side, connected via
processing, trade and retail, with loss and waste streams all along the
food chain. Natural ecosystems provide multiple services (regulating,
supporting, provisioning, cultural) to the food system. Food security
and nutrition strongly depend on the driving forces connecting food
and natural systems while at the same time positively or negatively
influencing them. Climate change frequently exacerbates the effects of
other drivers of change, further limiting the environment within which
humanity can safely operate and thrive. The chapter assesses how
climate change affects the four pillars of food security and nutrition
and how these effects can be mediated by various factors, including our
adaptation responses, social equity, underlying ecosystem services and
governance (Figure 5.1). Adaptation solutions are a major emphasis
of this chapter, including many ecosystem-based adaptation options
(Table 5.1), which fall under the broader umbrella of nature-based
solutions (Seddon et al., 2020).
Adaptation and mitigation
Climate resilient development pathways
Collective resource
management
Land
restoration
Genetic
improvements
Climate
diversification
Policy and
planning
Bio-base
products
Livelihood
diversification
Gender
equity
Youth
innovation
Animal
feeds
Dietary
choice
Early warning
systems
Community
based
Species
diversification
Alternative
energies
Technology
improvements
Best
practices
Waste and
trade
Mixed
production
Knowledge systems
(Indigenous, local)
Sustainable Development Goals
Greenhouse
gas emissions
Maladaptation
Barriers
Trade-offs
Conceptual framework of Chapter 5
Climate change drivers
Rising
temperatures
Altered
precipitation
Acidification
increase
Oxygen
decrease
Sea level
rise
Extreme
events
Increased storms
and cyclones
Increased climate
variability
Droughts
and floods
Food, fibre and other ecosystem products
Climate change impacts
Air, soil and
water quality
Crop and
animal
yields
Grassland
quality
Tree
mortality
Distribution
shifts
Altered
phenology
Plant and
animal
fertility
Suitable
production
habitat
Food
nutritional
quality
Heat
stress
Pests and
pollinators
Biodiversity
loss
Ecosystem
degradation
Food
availability
Food
security
Livelihoods
Land use
competition
Vulnerability
of marginal
groups
Hunger
Mal-
nutrition
Heat stress
for
workers
Food
prices
Food
safety
Risks for people
Diet-related
mortality
Figure 5.1 | Conceptual framework of Chapter 5.
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Table 5.1 |
Adaptation strategies assessment in food, fibre and other ecosystem provisioning services.
Adaptation strategies/options
Systems
Benefits
Constraints or enablers
Confidence
Relevant sections
–
Ecosystem-based integrated
approaches such as agroecology
that increase soil organic
matter, enhance soil and water
conservation, and diversify food
production systems
–
Certain types of urban agriculture
Crops
– Improve resilience of food systems
– Provide mitigation measures and
co-benefits in health, ecosystem
services and other SDGs
– Improve productivity and yield
stability
Secure tenure arrangements are
often critical for delivering successful
ecosystem-based adaptation
High
(5.4.4.5,
5.6.3, 5.12.3,
Cross-Chapter
Box NATURAL
in Chapter 2,
5.14.3.6, 5.14.3.11;
Cross-Chapter
Box HEALTH in
Chapter 7)
–
Increasing agroecosystem
diversification through-expanding
crop, animal, fish and other species
genetic diversity-varying spatial and
temporal arrangements including
mixed planting, crop rotations,
integrated crop, livestock and
agroforestry systems
Crops,
livestock,
aquaculture,
mixed,
agroforestry
systems
– Increase resilience, productivity,
and sustainability of farming
systems under climate change
Policies and technologies that support
diversification at landscape and
farm levels: programmes that reward
farmers for diversification practices,
reduced incentives for intensified
monocultures, extension support
and market infrastructure for diverse
crops, and productivity research on a
greater variety of crops with support
for post-harvest processing and
regional markets
High
(5.4.4.4, 5.14.3.1,
5.14.3.6)
–
Changing the relative emphasis on
crops and livestock
–
Changing crop varieties and
livestock breeds and species
Crops–
livestock
mixed system
particularly
in the tropics
and subtropics
– Increase resilience
Gender inequalities can act as a risk
multiplier
Medium
(5.5.4; 5.10.4)
–
Indigenous and local knowledge
including participatory plant
breeding or community-based
adaptation
Crops, forestry,
fisheries
– Increase resilience and
sustainability of food, fibre,
forest and small-scale fisheries
production
Indigenous knowledge and
local knowledge can facilitate
adaptation when combined with
scientific knowledge and utilised in
management regimes
High
(5.4.4.5, 5.6.3,
5.14.3)
–
Land restoration
–
Agroforestry
–
Silvo-pasture
Forestry
– Improve resilience and productivity
Partnerships between key
stakeholders such as researchers,
forest managers, and Indigenous and
local forest dependent communities
will facilitate sustainable forest
management
Medium
(5.6.3)
–
Improved management practices
that consider fish stocks and
the ecosystem (ecosystem-
based management, adaptive
management, co-management,
adaptive eco-management, and
active adaptive management)
–
Adopting complementary
productive activities to reduce
economic dependence on fisheries
–
Developing capacity
–
Improving information flows
in adaptive co-management
transboundary resource
management
–
Gear or vessel modifications
Fisheries
– Promote sustainable harvesting
and fair distribution of wild fish
products and revenues
– Proactive dynamic fisheries
management and diversification
based on scientific, Indigenous
and local knowledge will facilitate
adaptive fisheries planning and
reduce conflict (national and
international) over resources
Medium
(5.14.3.4;
Cross-Chapter
Box MOVING PLATE
this chapter)
–
Adaptation options that incorporate
ecological knowledge and risk into
management decisions in the near
and long term
Aquaculture
– Enhance sustainable aquaculture
production
Governance that recognises
unexploited biological and
socioeconomic food system synergies
and equity would lead to positive
adaptation strategy development and
implementation, but options may be
limited for those most at risk due to
technological cost and low financial
access
High
(5.14.3.5)
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Ecosystem-based adaptation, defined as the ‘use of ecosystem
management activities to increase the resilience and reduce the
vulnerability of people and ecosystems to climate change’ (Campbell
et al., 2009), has at its core the recognition that there are unexploited
synergies in agricultural systems that can increase productivity and
resilience. These can result from increasing biodiversity, adding organic
matter to soils, integrating livestock and aquatic species, including
aquaculture, into farming practices, broadening landscape practices to
exploit crop–forestry synergies, supporting beneficial insect populations
and altering pest management practices that have unintended negative
consequences. In addition, the chapter considers socioeconomic
strategies to build resilience in the food system, strengthening local
and regional economies, building on Indigenous and local knowledge,
and addressing social inequity, through inclusive, participatory and
democratic governance of food systems (HLPE, 2019; Wezel et al., 2020).
5.2
Observed Impacts and Key Risks
5.2.1
Detection and Attribution of Observed Impacts
Detection and attribution of climate change impacts on the food system
remain challenging because many non-climate drivers are involved
(Porter et al., 2014) but have been improved by recently developed
Adaptation strategies/options
Systems
Benefits
Constraints or enablers
Confidence
Relevant sections
–
Effective linkage of freshwater
aquatic food provisioning
management to the adaptation
plans of other water-using sectors,
considering trade-offs of production
with community nutritional needs
Freshwater
fisheries and
aquaculture
systems
– Reduce the risk of food insecurity
and livelihood loss for those reliant
on freshwater for inland fisheries
and aquaculture
Changing precipitation patterns
will increase competition for limited
freshwater supplies
Medium
(5.8.4, 5.9.4.)
–
Agricultural production systems that
integrate crops, livestock, forestry,
fisheries and aquaculture
Mixed system
– Increase food production per unit
of land
– Reduce climate risks
– Reduce GHG emission
– Confer buffering capacity
– Increasing household resilience,
though the benefits and challenges
depend on local context
Uncertainties exist concerning the
scalability of integrated systems;
their uptake faces particular
barriers around risk, land tenure,
social inclusion, information and
management skill, and the nature and
timing of benefit flows
High
(5.10.4)
–
Investments in improved humidity
and temperature control in storage
facilities for perishable items, and
changes in public policy that control
international trade and domestic
market transactions
Post-harvest
– Improve food utilisation and
access and thereby resilience to
climate change
The extent to which adaptation
activities beyond harvest are
cost-effective, and the limits to such
adaptation, are location-specific and
largely unknown
Medium
(5.11.4)
–
Integrated multi-sectoral food
system adaptation approaches
that address food production,
consumption and equity issues
–
Nutrition and gender-sensitive
agriculture programmes, adaptive
social protection and disaster risk
management are examples
Production
and
post-harvest
– Protect vulnerable groups against
livelihood risks
– Enhance responsiveness to
extreme events
Differentiated responses based on
food security level and climate risk
can be effective
Medium
(5.12.4)
–
Rights-based approaches, including
legislation, gender transformative
approaches to agriculture,
recognition of rights to land, seeds,
fishing areas and other natural
resources, and community-based
adaptation
Production
and
post-harvest
– Improved food security and
nutrition for marginalised groups
– Increased resilience through
capacity-building of marginalised
groups
– Address questions of access to
resources for marginalised groups
Focus on meaningful participation
in governance, design and
implementation of adaptation
strategies of those groups who are
vulnerable, including gender. Can
be conflicts and trade-offs, such as
between addressing land rights or
traditional fishing grounds
Medium
(5.12.4)
–
Climate services
Production
– Can support decision makers in
agriculture by providing tailored
information that can inform
the implementation of specific
adaptation options
For some high- and medium-income
countries, evidence suggests
that climate services have been
underutilised. In low-income
countries, use of climate services
can increase yields and incomes
and promote changes in farmers’
practices, but
low confidence
that
climate services are delivering on their
potential, whether they are being
accessed by the vulnerable, and how
these services are contributing to food
security and nutrition
Medium
(5.14.1)
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climate model outputs tailored for impact attribution (Iizumi et al.,
2018; Moore, 2020; Ortiz-Bobea et al., 2021).
Climate change has caused regionally different, but mostly negative,
impacts on crop yields and quality and marketability of products (
high
confidence
) (see Section 5.4.1 for observed impacts). There is
medium
evidence
and
high agreement
that the effects of human-induced
climate warming since the pre-industrial era has had significantly
negative effects on global crop production, acting as a drag on the
growth of agricultural production (Iizumi et al., 2018; Moore, 2020;
Ortiz-Bobea et al., 2021). One global study using an empirical model
estimated the negative effect of anthropogenic warming trends from
1961 to 2017 to be on average 5.3% for three staple crops (5.9%
for maize, 4.9% for wheat and 4.2% for rice) (Moore, 2020). Another
study using a process-based crop model found a yield loss of 4.1%
(0.5–8.4%) for maize and 4.5% (0.5–8.4%) for soybean between
1981 and 2010 relative to the non-warming condition, even with
CO
2
fertilisation effects (Iizumi et al., 2018). Human-induced warming
trends since 1961 have also slowed down the growth of agricultural
total factor productivity by 21% (Ortiz-Bobea et al., 2021). Regionally,
heat and rainfall extremes intensified by human-induced warming in
West Africa have reduced millet and sorghum yields by 10–20%, and
5–15%, respectively (Sultan et al., 2019).
Methane emissions significantly impact crop yields by increasing
temperatures as a greenhouse gas (GHG) and surface ozone
concentrations as a precursor (
medium confidence
) (Shindell, 2016;
Van Dingenen, 2018; Shindell et al., 2019). Shindell (2016) estimated a
net yield loss of 9.5±3.0% for four major crops due to anthropogenic
emissions (1850–2010), after incorporation of the positive effect of
CO
2
(6.5±1.0%) and the negative effects of warming (10.9±3.2%) and
tropospheric ozone elevation (5.0±1.5%). Although these estimates
were not linked with historical yield changes, more than half of the
estimated yield loss is attributable to increasing temperature and
ozone concentrations from methane emissions, suggesting the
importance of methane mitigation in alleviating yield losses (
medium
confidence
) (Section 5.4.1.4).
Climate change is already affecting livestock production (
high
confidence)
(Section 5.5.1). The effects include direct impacts of heat
stress on mortality and productivity, and indirect impacts have been
observed on grassland quality, shifts in species distribution and range
changes in livestock diseases (Sections 5.5.1.1–5.5.1.3). Quantitative
assessment of observed impacts is still limited.
In aquatic systems, more evidence has accumulated since AR5 on
warming-induced shifts (mainly poleward) of species (
high confidence
)
(Section 5.8.1, Cross-Chapter Box MOVING PLATE this chapter),
causing significant challenges for resource allocation between
different countries and fishing fleets. Quantitative assessments of
climate change impacts on production are still limited, but Free et al.
(2019) estimated a 4.1% global loss of the maximum sustainable yield
of several marine fish populations from 1930 to 2010 due to climate
change. The effects of climate change on aquaculture are apparent
but diverse, depending on the types and species of aquaculture (
high
confidence
) (Section 5.9.1). Temperature increases, acidification, salt
intrusion, oxygen deficiency, floods and droughts have negatively
impacted production via reduced growing suitability, mortalities or
damages to infrastructure (Section 5.9.1).
The impacts of climate change on food provisioning have cascading
effects on key elements of food security, such as food prices,
household income, food safety and nutrition of vulnerable groups
(Peri, 2017; Ubilava, 2018; 5.11, 5.12). Climate extreme events are
frequently causing acute food insecurity (Section 5.12.3, FSIN, 2021).
There is growing evidence that human-induced climate warming
has amplified climate extreme events (Seneviratne et al., 2021), but
detection and attribution of food insecurity to anthropogenic climate
change is still limited by a lack of long-term data and complexity of
food systems (Phalkey et al., 2015; Cooper et al., 2019). A recent event
attribution study by Funk (2018) demonstrated that anthropogenic
enhancement of the 2015/2016 El Niño increased drought-induced
crop production losses in Southern Africa. Human-induced warming
also exacerbated the 2007 drought in southern Africa, causing
food shortages, price spikes and acute food insecurity in Lesotho
(Verschuur et al., 2021).
Cascading impacts of climate hazards
on food and nutrition
Climatic
hazards
More frequent and intensified
heat/droughts, floods
Reduced
soil moisture
& health
Labour
capacity
Access to
food
Food
availability,
consumption
+utilization
Household
income
Quality
of life
Food yield
and quality
losses
Food prices
Malnutri-
tion
Infectious
diseases
Drought
Heat
Food
production
system
Figure 5.2 | Cascading impacts of climate hazards on food and nutrition.
The factors involved the impacts on crop production and prices (black arrows) and
interaction among food-health interaction (white arrows). Adapted and revised from
(Phalkey et al., 2015).
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5.2.2
Key Risks
Key risks in this chapter are grouped into those related to food
security, food safety and dietary health, livelihoods of people in
related sectors and ecosystem services (Table 16.9). Determining
when a risk is considered severe is challenging to quantify because
of the complexity of the food system, uncertainty about the effects
and ethical challenges.
Current levels of food insecurity are already high in some parts of
the world, and often exacerbated by short-term food shortages and
price spikes caused by weather extremes partly linked to climate
change (Sections 5.2.1, 5.12.3, 16.5.2). Climate change will increase
malnourished populations through direct impacts on food production
and have cascading impacts on food prices and household incomes,
all of which will reduce access to safe and nutritious food (
high
confidence)
(Figure 5.2, 5.12).
Extreme climate events will become more frequent and force some of
the current food production areas beyond the safe climatic space for
production (
high confidence
) (Sections 5.4.3, 5.5.2). Globally, 10% of
the currently suitable area for major crops and livestock is projected
to be climatically unsuitable in mid-century and 31–34% by the end
of the century under SSP5-8.5 (Kummu et al., 2021). Adverse effects
of climate change on food production will become more severe when
global temperatures rise by more than 2°C (Sections 5.4.4.1, 5.12.4.1).
One study estimated that the heat stress from projected 3°C warming
above baseline (1986–2005) would reduce labour capacity by 30–50%
in Sub-Saharan Africa and Southeast Asia, leading to a 5% increase
in crop prices because of higher labour cost and production losses,
thereby undermining food availability, access and livelihood (de Lima
et al., 2021). Thiault et al. (2019) projected that, by 2100, climate
change under RCP8.5 could have negative impacts on both agriculture
and marine fisheries productivity in countries where 90% of the world
population live. A global analysis of shellfish aquaculture estimated
that habitat suitability will decline beyond 2060 globally, but much
sooner in some Asian countries (Stewart-Sinclair et al., 2020; 5.9.1).
These negative effects in the second half of the century will be much
less under RCP2.6.
Climate change impacts will increase the number of people at risk of
hunger, in 2050 ranging from 8 million people under SSP1 to 80 million
people under SSP3 scenarios (RCP6.0), compared with a world with no
climate change (Mbow et al., 2019). Estimates also vary depending on
the adaptation and mitigation assumptions (Hasegawa et al., 2018;
Janssens et al., 2020). Geographically, nearly 80% of the population at
risk of hunger are projected to reside in Africa and Asia (Nelson et al.,
2018). Projections of risk of hunger beyond 2050 are limited, but it will
grow from the mid-century towards the end of the century, with more
people at risk under RCP8.5 compared with RCP4.5 (Richardson et al.,
2018). Regional disparity is projected to increase, particularly under a
high-emission scenario.
Climate change will increase the costs and management challenges
of providing safe food. The safety challenges arise from contamination
caused by increased prevalence of pathogens, HAB and toxic inorganic
bioaccumulation (
high confidence
) (Sections 5.8, 5.9, 5.11, 5.12).
Micronutrient deficiency is prevalent across many regions and will
continue to be a problem at least during the first half of the century
(Nelson et al., 2018), with significant implications for human health
(Section 5.12.4).
Food security and healthy balanced diets will also be undermined
by reduced livelihoods and health of people in agriculture and food-
related sectors (Sections 5.12.3, 5.12.4), diminished ecosystem
services provided by pollinators, the soil biome (Section 5.4.3) and
water systems, and climate-mitigation related policies that solely focus
on reducing GHG emissions without considering their potential to
increase competition with food production for scarce land and water
(Section 5.13.3).
5.3
Methodologies and Associated
Uncertainties
Chapter text draws on previous IPCC reports, other reports (i.e., High
Level Panel of Experts (HLPE), Food and Agriculture Organization (FAO),
and Intergovernmental Science-Policy Platform on Biodiversity and
Ecosystem Services (IPBES)), and literature published since 2014. This
section highlights key trends in research topics and methods since AR5.
5.3.1
Methodologies for Assessing Impacts and Risks
Since AR5, there are more examples of observed impacts from past
climate change in cropping systems (Section 5.4.1), pastoral systems
(Section 5.5.1), forests (Section 5.6.1), fisheries (Section 5.8.1) and
mixed farming systems (Section 5.10.1). These assessments of observed
impacts make use of historical data on climate, production area and
yield to attribute the role of climate in driving changes in suitability,
production, yield, food quality or total factor productivity (Ortiz-Bobea
et al., 2021). Observations across the global food systems have been
analysed (Cottrell et al., 2019), with the advantage that unexpected
impacts due to changes in seasonality and biotic interactions can be
detected. Quantitative analysis is only possible in places with adequate
historical data; in many cases, studies rely on qualitative assessments,
often drawing on farmers’ perceptions of climate impacts.
Projecting future climate impacts relies on modelling that combines
climate data with data from experimental studies testing how species
respond to each climate factor. In cropping and forest systems, a
network of experimental studies with plants exposed to elevated CO
2
concentrations, ozone and elevated temperature provides data on the
fundamental responses to climate and atmospheric conditions (i.e.,
free-air carbon dioxide enrichment (FACE) and temperature free-air
controlled enhancement (T-FACE) systems). FACE results have been
combined and assessed more extensively since AR5 (Bishop et al.,
2014; Haworth et al., 2016; Kimball, 2016; Ainsworth and Long, 2021).
Field-based FACE studies have several advantages over more enclosed
testing chambers, although results from more controlled experiments
and coordination between different methods continue to give new
insights into crop responses to climate change and variability (Drag
et al., 2020; Ainsworth and Long, 2021; Sun et al., 2021). Experimental
results have limitations and can be difficult to scale up (Porter
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et al., 2014; Haworth et al., 2016), but generally the conclusions
follow known plant responses (Lemonnier and Ainsworth, 2018). As
highlighted in AR5, there is a scarcity of FACE infrastructure in the
tropics and subtropics (Leakey et al., 2012; Lemonnier and Ainsworth,
2018; Toreti et al., 2020). One area that has been investigated further
is the negative impact of elevated CO
2
on crop nutritional value,
which has important implications for human nutrition (Scheelbeek
et al., 2018; Smith and Myers, 2018; Toreti et al., 2020; Ainsworth and
Long, 2021). Increasingly, experimental studies seek to examine the
interaction between climatic factors such as temperature, drought and
ozone, or the responses of understudied food systems, crop species,
cultivars and management interventions (Kimball, 2016; Ainsworth
and Long, 2021). The use of experimental data to improve projections
has also expanded in other systems. There has been an increased
focus on the impact of warming on livestock health and productivity
(5.5.3)
.
Aquatic system studies have incorporated projected impacts
on physiology, distribution, phenology and productivity (5.8.3).
Table 5.2 |
A comparison of modelling approaches and their application in climate change impact projections. Model types are categorised by: food system, with labels representing
the food systems from this chapter where each model type is used (
{CROP}
,
{TREE}
,
{LIVES}
,
{FISH}
,
{MIX}
,
{FOOD}
); scale over which each model type is usually applied
local [()], regional [( )], global [( )], or a combination of these); and sensitivity to climate change where the colour intensity indicates the ability of each model type to incorporate
each of the listed factors. After Van Wijk et al. (2014), Kanter et al. (2018) and Thornton (2018). Integrated assessment models are discussed in the main text.
Description
Applications for each food-system
Scale
Sensitivity to climate change
factors and responses
Climate
CO
2
Biotic
Adaptation
System responses
Empirical
Agroclimatic
indices
Use simple equations to link agricultural performance
to key climate factors, such as drought or heat
stress, or summarise agricultural requirements using
multiple environmental descriptors.
Comparing regions; matching crops to regions; early
warning systems: e.g Agro-ecological zones, Ecocrop,
Palmer Drought Severity Index
{CROP}
.
(( ))
Statistical
models
Use quantitative associations between agricultural
performance and climate, based on past
observations. Can include projections for biotic
factors such as pest and disease.
Productivity and production area projections; annual
climate variability; attribution: e.g. Traditional:
regression, statistical emulators
{CROP}
{TREE}
{LIVES}
{FISH}
; e.g. Spatial suitability models /niche models:
MaxEnt, CLIMEX, Ecocrop
{CROP}
{TREE}
{FISH}
.
(( ))
Pr
ocess-based (dynamic simulation models)
Vegetation
focussed
Use combinations of land-surface energy and soil
water balance models to simulate the growth of crop
species along with natural vegetation, typically using
plant and crop functional types.
Productivity projections; interactions with non-climate
variables (e.g. CO
2
): e.g. PEGASUS, Agro-IBIS, DayCent,
LPJmL, LPJ-GUESS, ORCHIDEE
{CROP}
{TREE}
.
( )
Species focussed
Use mechanistic models based on the known
responses of species to key environmental
descriptors over time. Typically based on detailed
information for a particular species within a
region, but also applied to mixed systems such as
agroforestry and globally.
Productivity projections; matching tree species
to locations; species interactions; interactions
with non-climate variable s (e.g.CO
2
); adaptation
projections: e.g. point-based versions: APSIM,
AquaCrop, DayCent, DSSAT, EPIC, Infocrop, SARRA-H,
STICS
{CROP}
IBIS
{TREE}
LIVSIM, RUMINANT
{LIVES}
Fish-MIP
{FISH}
Yield-SAFE, WaNuLCAS, Hi-sAFe
{MIX}
;
e.g. global gridded version: pDSSAT, pAPSIM, GEPIC,
GLAM, MCWLA, PEGASUS, SARRA-O
{CROP}
.
(( ))
Integr
ated Models
Optimization
methods
Mathematical representations of systems with regard
to key indicators, constraints, and objectives. Allows
prioritisation of different climate change response
options using the defined indicators.
Adaptation projections; food security projections;
livelihood projections; trade-offs; live cycle assessment:
e.g. Global Timber Model
{TREE}
CSAP toolkit,
FarmDESIGN
{CROP}
{MIX}
{FOOD}
()
Economic (Econometric,
Economic surplus)
Used to integrate the broad impacts of climate
change with other economic drivers, to quantify the
economic costs and assess the value of adaptation/
mitigation interventions.
Adaptation projections; food security projections;
livelihood projections: e.g. GFPM
{TREE}
FUND 3.8,
DICE 2010, IMPACT
{FOOD}
( )
Household and village
models
Use detailed site-specific data to generate rules that
describe the current behaviour of stakeholders such
as households or villages. Can be integrated with
other model approaches to consider climate response
and adaptation interventions.
Adaptation projections (case specific); behavioural
responses; trade-offs; participatory monitoring: e.g.
DECUMA, PALM, MPMAS, MIDAS, TOA-MD
{LIVES}
{MIX}
{FOOD}
(())
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Modelling approaches differ widely and serve different purposes
(Table 5.2; Porter et al., 2014; Jones, 2017a). The use of process-based and
statistical modelling alongside remote sensing and other spatial data
has grown. Projections increasingly draw on a combination of modelling
approaches and coordinated efforts for model intercomparisons and
ensemble techniques, using standardised emission scenarios (RCPs).
For major crops, models of global yield impacts from CO
2
concentration,
air temperature and precipitation have been refined and compared
(Challinor et al., 2014; Iizumi et al., 2017; Ruane et al., 2017; Zhao et al.,
2017; Rojas et al., 2019). Despite advances since AR5, modelling is still
constrained by limited data from field experiments (Ruane et al., 2017).
Increasingly, studies attempt to incorporate effects of elevated CO
2
,
ozone and climate extremes (Barlow et al., 2015; Schauberger et al.,
2019a; Vogel et al., 2019), as well as attempts to incorporate more
complex interactions with soil and crop management (Basso et al.,
2018; Smith et al., 2020b). However, only a few models consider crop
protein content and other quality factors (Nuttall et al., 2017; Asseng
et al., 2019). Some models take account of the impacts of climate on
the timing of key biological events (phenology) in the target species;
however, incorporating biotic interactions with pests, pathogens and
pollinators remains a challenge (Table 5.2; Sections 5.4.1, 5.4.3).
In addition to productivity projections, research also draws on climate
suitability estimates (Table 5.2). These compare the known climate
suitability of species and habitats with projected climate conditions
across different locations. Such projections are useful especially for
incorporating movement of pests and pathogens but cannot be applied
in isolation if non-climate constraints are not considered. As different
research groups use different assumptions and data inputs, more
coordination is needed if suitability projections are to be compared
globally (SM5.3).
Increasingly, projections look across different disciplines and across
multiple components of the food system, including livestock, fisheries
and mixed farming systems (Campbell et al., 2016; Mbow et al., 2019).
Major timber species have been modelled, with projected impacts
on productivity, duration of rotation and distribution (i.e., climate
suitability) (Albert et al., 2018). Livestock systems are influenced
by plant productivity projections via their feedstock, for example,
rangeland cattle impacted by changes in net primary production
(NPP) (Boone et al., 2018). Direct climate impacts on animals are also
projected, using indices based on direct observations (Section 5.5.3).
Since AR5, Fisheries and Marine Ecosystem Model Intercomparison
Project (Fish-MIP) has allowed for global intercomparisons and
ensemble projections of marine fisheries, and projections capturing
interactions from multiple food systems (e.g., Inter-Sectoral Impact
Model Intercomparison Project (ISI-MIP); Sections 5.8, 5.10).
Global simulations have uncovered important differences between
regions (Deryng et al., 2016; Blanchard et al., 2017). Efforts to coordinate
and combine regional and global modelling studies allow for greater
insight into regional differences in climate change impacts, such as
the Coordinated Global and Regional Assessments (CGRA) performed
by the Agricultural Model Intercomparison and Improvement Project
(AgMIP) (Blanchard et al., 2017; Müller et al., 2017; Rosenzweig et al.,
2018; Ruane et al., 2018; Lotze et al., 2019). Increasingly, multi-model
intercomparisons are used to evaluate global gridded crop models’
performance and sensitivity to temperature, water, nitrogen and CO
2
within AgMIP, with the focus mostly on major annual crops (Valdivia
et al., 2015; Ruane et al., 2017; Müller et al., 2021a). Differences in
model type, structures and input data can result in large variation in
projections, particularly for the response of crops to elevated CO
2
and
temperature (5.4.3.1); methods for quantifying and minimising this
uncertainty have been developed, but improvement is still needed (
Asseng et al., 2015; Li et al., 2015; Zhao et al., 2017; Folberth et al.,
2019; Tao et al., 2020; Müller et al., 2021a; Ruane et al., 2021). The
use of multi-model intercomparisons has widened the range of
uncertainties but has increased the robustness of impact assessments
(Asseng et al., 2013; Challinor et al., 2014; Zhao et al., 2017). Model
outputs are strongly influenced by decisions over which factors to
include; for example, including drought impacts can result in positive
yield projections switching to neutral or negative values (Gray et al.,
2016; Jin et al., 2018). Models are also limited in their ability to
incorporate socioeconomic drivers and extreme events (Porter et al.,
2014; Campbell et al., 2016; Ruane et al., 2017; Jagermeyr and Frieler,
2018; Webber et al., 2018; Schewe et al., 2019).
For long-term projections and integrated assessments, a large
component of uncertainty remains in the ability to represent
socioeconomic responses to climate change and the degree to which
these will mitigate or exacerbate climatic changes (Valdivia et al., 2015;
Prestele et al., 2016; Arneth et al., 2019). This includes the potential
adaptation responses of food producers. Models that incorporate
alternative socioeconomic responses offer one solution (e.g., AgMIP)
(Nelson et al., 2014; Von Lampe et al., 2014; Wiebe et al., 2015;
Rosenzweig et al., 2018; van Zeist et al., 2020). Another approach is
the use of solution-oriented scenarios to compare the effectiveness
of adaptation options (Le Mouël and Forslund, 2017; Arneth et al.,
2019), or to quantify the time period in which adaptation responses
will become essential (Challinor et al., 2016; Rojas et al., 2019). Others
point to the necessity of managing food systems within the context of
uncertainty (Campbell et al., 2016).
5.3.2
Methodologies for Assessing Vulnerabilities and
Adaptation
Methods for monitoring vulnerability and adaptation are under-
researched but have increased since AR5. Increasingly, projections
move from individual crops to assessing risks across the food systems
and the relative vulnerability of different systems (Campbell et al.,
2016; Gil et al., 2017; Lipper et al., 2017; Richardson et al., 2018).
Adaptation options can be considered as parameters in integrated
models, such as those used in ISI-MIP, while others use systematic
assessments of case studies, such as the application of agent-based
household models to assessments of adaptation in livestock systems
(Section 5.5.4). Quantitative studies are less common than qualitative
assessments, and there is a need to combine modelling and qualitative
approaches more effectively (Beveridge et al., 2018a; Vermeulen et al.,
2018).
The food system is dynamic, with changes in management practices
driven by many factors, including climate adaptation (Iizumi, 2019;
Iizumi et al., 2021a). Adaptation potential, such as expected advances
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in crop breeding, are often not explicitly accounted for in modelling
studies, but more recent studies do quantify the potential for
adaptation (Iizumi et al., 2017; Tao et al., 2017; Aggarwal et al., 2019;
Minoli et al., 2019). To account for this complexity, case studies rely on
data derived from the perception and practices of stakeholders who
are engaged in adaptation (usually autonomous adaptation) (Hussain
et al., 2016; Lipper et al., 2017; Ankrah, 2018; Sousa-Silva et al., 2018).
Case studies use a range of different indicators to monitor climate
response options, making quantitative comparisons more difficult (Gil
et al., 2017; Vermeulen et al., 2018). However, systematic comparisons
have provided valuable insights (Descheemaeker et al., 2018; Shaffril
et al., 2018; Aggarwal et al., 2019; Bene et al., 2019); for example, the
sustainable livelihood framework has been applied widely to diverse
aquatic systems (Bueno and Soto, 2017; Barange and Cochrane, 2018)
and the Livelihood Vulnerability Index is well used across systems
(Section 5.14). Coordinated efforts such as the AgMIP also provide
systematic assessments (Blanchard et al., 2017; Lipper et al., 2017;
Antle et al., 2018). Nonetheless, the full effectiveness of different
adaptation options is difficult to assess given that many impacts
have not yet occurred (due to the cumulative nature of impacts and
the inertia in the climate system) (Stocker et al., 2013; Zickfeld et al.,
2013).
Transformation of the food system that addresses all dimensions
of ecosystem services is discussed in this chapter, including risk
management and the communication of uncertainties (Section 5.14).
The focus is on flexible approaches to risk and uncertainty, assessing
trends, drivers and trade-offs under different future scenarios (Campbell
et al., 2016).
5.4
Crop-Based Systems
Crops such as cereals, vegetables, fruit, roots, tubers, oilseeds and
sugar account for about 80% of the dietary energy supply (FAO,
2019 f). Crops are a significant source of food and income for about
600 million farms in the world, 90% of which are family farms (Lowder
et al., 2019). Previous assessment reports focused on yields of staple
crops such as maize, wheat and rice, but studies are emerging on
climate change impacts on other crops.
5.4.1
Observed Impacts
5.4.1.1 Observed impacts on major crops
AR5 Chapter 7 (Porter et al., 2014) stated with confidence that warmer
temperatures have benefited agriculture in the high latitudes, and
more evidence has been published to support this statement. Typical
examples include pole-ward expansion of growing areas and reduction
of cold stress in East Asia and North America (Table SM5.1).
Recent warming trends have generally shortened the life cycle of major
crops (
high confidence
) (Zhang et al., 2014; Shen and Liu, 2015; Ahmed
et al., 2018; Liu et al., 2018c; Tan et al., 2021). Some studies, however,
observed prolonged crop growth duration despite the warming trends
(Mueller et al., 2015; Tao et al., 2016; Butler et al., 2018; Zhu et al., 2018b)
because of shifts in planting dates and/or adoption of longer-duration
cultivars in mid-to-high latitudes. Conversely, in mid-to-low latitudes in
Asia, a review study found that farmers favoured early maturing cultivars
to reduce risks of damages due to drought, flood and/or heat (Shaffril
et al., 2018), suggesting that region-specific adaptations are already
occurring in different parts of the world (
high confidence
).
Global yields of major crops per unit land area have increased 2.5- to
3-fold since 1960. Plant breeding, fertilisation, irrigation and integrated
pest management have been the major drivers, but many studies have
found significant impacts from recent climate trends on crop yield (
high
confidence
) (Figure 5.3; see Section 5.2.1 for the change attributable to
anthropogenic climate change).
Climate impacts for the past 20–50 years differ by crops and regions.
Positive effects have been identified for rice and wheat in Eastern Asia,
and for wheat in Northern Europe. The effects are mostly negative
in Sub-Saharan Africa, South America and Caribbean, Southern Asia,
and Western and Southern Europe. Climate factors that affected long-
term yield trends also differ between regions. For example, in Western
Africa, 1°C warming above preindustrial climate has increased heat
and rainfall extremes, and reduced yields by 10–20% for millet and
5–15% for sorghum (Sultan et al., 2019). In Australia, declined rainfall
and increased temperatures reduced yield potential of wheat by
27%, accounting for the low yield growth between 1990 and 2015
(Hochman et al., 2017). In Southern Europe, climate warming has
negatively impacted yields of almost all major crops, leading to recent
yield stagnation (Moore and Lobell, 2015; Agnolucci and De Lipsis,
2020; Brás et al., 2021).
Ortiz-Bobea et al. (2021) analysed agricultural total factor productivity
(TFP), defined as the ratio of all agricultural outputs to all agricultural
inputs, and found that, while TFP has increased between 1961 and 2015,
the climate change trends reduced global TFP growth by a cumulative
21% over a 55-year period relative to TFP growth under counterfactual
non-climate change conditions. Greater effects (30–33%) were
observed in Africa, Latin America and the Caribbean (Figure 5.3).
Climate variability is a major source of variation in crop production
(Ray et al., 2015; Iizumi and Ramankutty, 2016; Frieler et al., 2017;
Cottrell et al., 2019)(Table SM5.1). Weather signals in yield variability
are generally stronger in productive regions than in the less productive
regions (Frieler et al., 2017), where other yield constraints exist such
as pests, diseases and poor soil fertility (Mills et al., 2018; 5.2.2).
Nevertheless, yield variability in less productive regions has severe
impacts on local food availability and livelihood (
high confidence
)
(FAO, 2021).
Climate-related hazards that cause crop losses are increasing (
medium
evidence
,
high agreement
) (Cottrell et al., 2019; Mbow et al., 2019;
Brás et al., 2021; FAO, 2021; Ranasinghe et al., 2021). Drought-related
yield losses have occurred in about 75% of the global harvested area
(Kim et al., 2019b) and increased in recent years (Lesk et al., 2016).
Heatwaves have reduced yields of wheat (Zampieri et al., 2017) and
rice (Liu et al., 2019b)
.
The combined effects of heat and drought
decreased global average yields of maize, soybeans and wheat by
11.6%, 12.4% and 9.2%, respectively (Matiu et al., 2017). In Europe,
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Chapter 5
crop losses due to drought and heat have tripled over the last five
decades (Brás et al., 2021), pointing to the importance of assessing
multiple stresses. Globally, floods also increased in the past 50 years,
causing direct damages to crops and indirectly reduced yields by
delaying planting, which cost 4.5 billion USD in the 2010 flood in
Pakistan and 572 million USD in the 2015 flood in Myanmar (FAO,
2021).
5.4.1.2 Observed impacts on other crops (vegetables, fruit, nut
and fibre)
The impact of climate change on these diverse crop types is under-
researched and uncertain (Manners and van Etten, 2018; Alae-Carew
et al., 2020); there are reports of positive impacts in some cases, but
overall the observed impacts are negative across all crop categories
(Figure 5.3).
Above-ground annual crops consumed as vegetables, fruits or salad are
essential for food security and nutrition (5.12). In temperate regions,
climate change can result in higher yields (Potopová et al., 2017; Bisbis
et al., 2018), while in subtropical/tropical regions, negative impacts
from heat and drought take precedence (Scheelbeek et al., 2018).
Different species have different sensitivities to heat and drought
(Prasad et al., 2017; Scheelbeek et al., 2018) and to combinations
of stresses (Zandalinas et al., 2018). Above-ground vegetables are
especially vulnerable to heat and drought stress during pollination and
fruit set, resulting in negitive impacts on yield (Daryanto et al., 2017;
Sita et al., 2017; Brás et al., 2021) and harvest quality (Mattos et al.,
2014; Bisbis et al., 2018). Growers have already seen negative impacts
from the expansion of pest and disease agents due to warming
(Section 5.4.1.3; Figure 5.3).
Below-ground vegetables include starchy roots and tubers that form a
regular diet in many parts of the tropics and subtropics. Warming and
climate variability has altered the rate of tuber development, with yield
impacts varying by location, including yield increases in some cases
(Shimoda et al., 2018; Ray et al., 2019). These crops are considered
stress tolerant but are more sensitive to drought than cereals (Daryanto
et al., 2017). Impacts on water supply are critical as root crops are
water-demanding for long periods, and highly sensitive to drought and
heat events during tuber initiation (Dua et al., 2013; Potopová et al.,
2017; Brás et al., 2021).
Among perennial tree crops, only grapevine, olive, almond, apple,
coffee and cocoa have received significant research attention. Concerns
about climate impacts on harvest quality are widespread (Figure 5.3)
(Barnuud et al., 2014; Bonada et al., 2015). In higher-latitude regions,
the primary concern is the effect of temperature variability on harvest
stability, pests and diseases and phenology (including fulfilment of
winter chill requirements and risks due to early emergence in spring),
(El Yaacoubi et al., 2014; Ramírez and Kallarackal, 2015; Santos et al.,
2017; Gitea et al., 2019). In lower-latitude regions, information is
Synthesis of observed impacts
on crop yields and productivity
Impact level:
Mixed
Positive
Negative
= not assessed
na
Confidence level:
High
Medium
Low
Northern Africa
Sub-Saharan Africa
Western Asia
Southern Asia
South-eastern Asia
Central Asia
Eastern Asia
Eastern Europe
Western Europe
Northern Europe
Southern Europe
Northern America
Australia and New Zealand
Global (average of regional data)
Agricultural
total factor
productivity
All
crops
Major crop species
Rice
Wheat
Soybean
Maiz
e
na na
Crop categories
Cereals
Vegetable
s
na
na
na
na
na
na
Leafy crops
Soft fruit
Root crops
Tree fruit
s
and nut
s
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
Legumes
Latin America and the Caribbean
na
na
na
na
na
Figure 5.3 | Synthesis of literature on observed impacts of climate change on productivity by crop type and region.
The figure draws on >150 articles categorized
by: agriculture total factor productivity including literature estimating all agricultural outputs in a region; major crop species including literature assessing yield changes in the
four major crops; crop categories including productivity changes (yield, quality and other perceived changes) in a range of crops with different growth habits. The assessment uses
literature published since AR5, although the timespan often extends prior to 2014. The direction of the effect and the confidence are based on the reported impacts and attribution,
and on the number of articles. See SM5.1 and SM5.2 for details.
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limited, but studies are focused on increased tree mortality and yield
loss due to drought, heat and impacts from variability in the timing of
the wet and dry seasons (Glenn et al., 2013; Ramírez and Kallarackal,
2015); see Box 5.7). In fruit trees, warming and climate variability have
already affected fruit quality, such as acidity and texture in apples, or
skin colour in grape berries (Sugiura et al., 2013; Sugiura et al., 2018).
The reliability and stability of harvests has been impacted by climate
variability, changes in the distribution of pests and pathogens (Seidel,
2014; Bois et al., 2017), and the mismatch of important phenological
events (such as bud emergence and flowering) (Guo and Shen, 2015;
Legave et al., 2015; Ito et al., 2018; Vitasse et al., 2018). Perennial
crops are particularly vulnerable to these impacts as they are exposed
throughout the year, with little potential for growers to adjust planting
date or location. Negative impacts via disruption to phenology and
pest dynamics are best studied in grapevine (see Box 5.2).
Among the fibre crops, cotton is particularly well studied. As cotton
is heat tolerant and yield increases with extra plant growth, positive
effects of increasing temperature are expected, but observed impacts
have been mixed due to negative impacts on phenology and plant
water status (Traore et al., 2013; Chen et al., 2015a; Cho and McCarl,
2017). Negative impacts of climate change due to proliferation of the
pest cotton bollworm are widely reported (Ouyang et al., 2014; Huang
and Hao, 2020).
The impacts of climate change on water availability (rainfall and
irrigation supply) are an emerging issue. Increased occurrence of
drought combined with limited access to irrigation water is already
a key constraint; for example, Californian almonds are predicted to
increase their potential geographical range under climate warming
(Parker, 2018), yet a trend of increasing drought has already resulted in
trees being removed due to lack of access to irrigation water (Keppen
and Dutcher, 2015; Kerr et al., 2018; Reisman, 2019).
5.4.1.3 Observed impacts on pests, diseases and weeds
AR5 and SRCCL (IPCC, 2019) indicated that more frequent outbreaks
and area expansion of pests and diseases are serious concerns under
climate change but are under-researched because of the difficulties in
assessing multi-species interactions (Porter et al., 2014; Mbow et al.,
2019). High-quality historical and current observational data to detect
changes in pests and diseases attributable to recent trends in climate
are still limited.
Bebber (2013) found significant poleward expansions of many
important groups of crop pests and pathogens since 1960, with an
average shift of 2.7 km yr
−1
. Different pest species populations respond
differently to ongoing climate change, with some shifting, contracting
or expanding their current distribution range and others persisting or
disappearing in their current range (
high confidence
). These asymmetric
distribution changes can create novel species combinations or
decouple existing ones (Pecl et al., 2017; Hobbs et al., 2018), but their
consequences on future crop production and food security are hard to
predict. Multi-species climate change experiments are rare (Bonebrake
et al., 2018), but one study shows that under future climates different
pest assemblages of interacting species may alter levels of damage
to crops compared with that by only one species (Crespo-Perez et al.,
2015). Some studies highlight the importance of location-specific
species interactions for more realistic projections of pest distribution,
performance and damage to crops, which in turn would allow more
effective prevention and pest control strategies (Wilson et al., 2015;
Carrasco et al., 2018).
Weeds are recognised as a primary constraint on crop production
(Oerke, 2006), rangelands (DiTomaso et al., 2017) and forests (Webster
et al., 2006). Climate change could favour the growth and development
of weeds over crops with negative consequences for desired plants in
managed systems (
medium evidence
,
high agreement
) (Peters et al.,
2014; Ziska and McConnell, 2016). First, changes in temperature
and precipitation alter the range, composition and competitiveness
of native and invasive weeds (Bradley et al., 2010). Second, rising
concentrations of CO
2
enhance growth of C
3
species (~85% of plant
species, including many weeds) (Ogren and Chollet, 1982; Ziska, 2003),
and increase plant water use efficiency with potentially strong effects
on invasive plant species establishment (Smith et al., 2000; Belote
et al., 2004; Blumenthal et al., 2013).
Some invasive species within unmanaged areas will expand further,
proliferate and be more competitive under climate change as they may
benefit from increased resource ability (e.g., additional CO
2
, enhanced
precipitation) (Bradley et al., 2010; Kathiresan and Gualbert, 2016;
Merow et al., 2017; Ramesh et al., 2017; Waryszak et al., 2018), which
will make chemical weed control more problematic (
medium evidence
,
high agreement
) (Waryszak et al., 2018; Ziska, 2020). The range of
other invasive weeds may become static, or even decline (Bradley
et al., 2016; Buckley and Csergo, 2017). A recent meta-analysis also
supports that invasive plants respond more favourably to elevated CO
2
concentrations and elevated temperatures than native plants (Korres
et al., 2016; Liu et al., 2017). Movement of invasive species into low-
fertility areas, however, could provide resource opportunities, especially
if agriculture in those areas is limited (Randriambanona et al., 2019).
Rising CO
2
concentrations and climate change could reduce herbicide
efficacy (
medium evidence
,
high agreement
). These reductions may
be associated with physical environmental changes (precipitation,
wind speed) that influence herbicide coverage (Ziska, 2016) as well
as direct effects of CO
2
on plant biochemistry and herbicide resistance
(Refatti et al., 2019). Increasing CO
2
levels and altered temperature
and precipitation are therefore projected to affect all aspects of weed
biology (Peters et al., 2014; Ziska and McConnell, 2016), including
establishment (Bradley et al., 2016), competition (Fernando et al.,
2019), distribution, (Castellanos-Frías et al., 2016) and management
(Waryszak et al., 2018).
A warmer climate increases the need for pesticides (Shakhramanyan
et al., 2013; Ziska, 2014; Delcour et al., 2015; Zhang et al., 2018).
Increases in temperature and CO
2
concentration may reduce pesticide
efficiency by altering its metabolism, or accelerating detoxification
(Matzrafi et al., 2016; Matzrafi, 2019). Intense rainfall also reduces
persistence (Delcour et al., 2015). Invasive pests and pathogens
impose an additional cost for the society (Bradshaw et al., 2016). Rapid
and large-scale dispersal of pests is already a major threat to food
security, as exemplified by the recent outbreak of desert locusts (see
Box 5.8), indicating the importance of international cooperation. Taken
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Box 5.1: Evidence for Simultaneous Crop Failures Due to Climate Change
Simultaneous yield losses across major producing regions can be a threat to food security but had not been quantified by the time of AR5.
Large-scale sea surface temperature (SST) oscillations greatly influence global yield of major crops (
high confidence
) (Anderson et al.,
2019b; Najafi et al., 2019; Ubilava and Abdolrahimi, 2019; Heino et al., 2020; Iizumi et al., 2021b) and food prices (Ubilava, 2018). Some
studies showed that crop yields in different regions covaried with SST oscillations, suggesting occurrences of tele-connected yield failures
(crop losses caused by related factors in distant regions; Table Box 5.1.1) (
medium confidence
). Evidence of synchronised crop failures
increasing with ongoing climate change is still limited.
Table Box 5.1.1 |
A summary of peer-review papers detecting synchronised yield losses.
Regions/
commodities
Period
studied
Observed impacts
Climate driver
Evidence
for multiple
breadbasket
failures
Evidence for
increasing
risks due
to multiple
breadbasket
failures
Reference
Global
breadbaskets
for maize, rice,
sorghum and
soybean
1961–2013
Not only yields of each crop covaried in many countries, but
also those of different crops, maize in particular, covaried
with other crops.
SST anomalies,
atmospheric and
oceanic in- dices,
air temperature
anomalies and
Palmer Drought
Severity Index
High
NA
Najafi et al.
(2019)
Global
breadbaskets for
wheat, soybean
and maize
1980–2010
Climate modes (El Niño-Southern Oscillation (ENSO), the
Indian Ocean Dipole (IOD), tropical Atlantic variability
(TAV) and the North Atlantic Oscillation (NAO)) account
for 18%, 7% and 6% of global maize, wheat and soybean
production variability, respectively. ENSO events sometimes
offset yield reductions in some places by increases in other
places (e.g., soybean yields in the USA and southeast South
America).
Since 1961, ENSO in 1983 was the only climate mode that
showed global synchronous crop failures.
Climate modes
Medium (1983)
NA
Anderson
et al. (2019b)
Global
breadbaskets for
wheat, soybean
and maize
Climate modes induce yield variability in major
breadbaskets, e.g., ENSO affects about half of maize and
wheat areas. IOD and ENSO influence wheat in Australia.
ENSO affects soybean in northern South America.
Climate modes
Medium
NA
Heino et al.
(2020)
67 maize
producing
countries
1961–2017
SST anomalies from the 1980–2010 base period in
the Niño3.4 region, a rectangular area bounded by
120°W–170°W and 5°S–5° is used as a driver. Maize
yields are tele-connected among the southeastern tier of
Sub-Saharan Africa, as well as Central America, South Asia
and Australia. A 1° increase in SST reduced maize yield by
up to 20% in these countries.
Climate
modes (SST),
precipitation
Medium
NA
Ubilava and
Abdolrahimi
(2019)
Global
breadbasket (the
USA, Argentina,
Europe, Russia/
Ukraine, China,
India, Australia,
Indonesia and
Brazil)
1967–2012
Likelihood of simultaneous climate risks increased from
1967–1990 to 1991–2012 in the global breadbasket (lower
25
th
yield deviation percentile events at province level) for
wheat, soybean and maize, but not rice.
Likelihood of simultaneous climate risks increased from
1967–1990 to 1991–2012 in China (lower 25
th
yield
deviation percentile events at province level).
Unspecified
Medium
Medium
Gaupp et al.
(2020)
Global
1961–2008
Synchronous yield losses among major breadbaskets within
each commodity, such as maize and soybean, decreased
between 1961 and 2008. In contrast, synchronous yield
variation between crops has increased. Under a scenario
of synchronisation of all four crops, the global maximum
production losses for rice, wheat, soybean and maize are
estimated to reach between −17% and −34%.
Unspecified
Medium
Medium
Mehrabi and
Ramankutty
(2019)
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together, the need for control of pests, disease and weeds will increase
under climate change (
medium evidence
,
high agreement
). The use of
toxic agricultural chemicals also has human health and environmental
risks (Whitmee et al., 2015; IPBES, 2019). Surveillance for monitoring
pest distribution and damages, climate-relevant pest risk analysis, and
climate-smart strategies for controlling pests with minimal impacts on
human and environmental health are important tools in the face of
climate change (IPPC Secretariat, 2021).
5.4.1.4 Observed impacts of ozone on crops
Tropospheric (i.e., the lowest 6–10 km of the atmosphere) ozone
exacerbates negative impacts of climate change (
high confidence
)
(Mattos et al., 2014; Chuwah et al., 2015; McGrath et al., 2015; Bisbis
et al., 2018; Mills et al., 2018; Scheelbeek et al., 2018). Ozone is an
air pollutant and short-lived GHG that affects air quality and global
climate. It is a strong oxidant that reduces physiological functions,
yield and quality of crops and animals. Surface ozone concentration
has increased substantially since the late 19
th
century (Cooper et al.,
2014; Forster et al., 2021; Gulev et al., 2021; Szopa et al., 2021) and in
some locations and times reaches levels that harm plants, animals and
human (
high confidence
) (Fleming et al., 2018).
Mills (2018) estimated global distributions of current yield losses
of major crops due to ozone, pest and diseases, heat, and aridity
(Figure 5.4). Ozone-induced yield losses in 2010–2012 averaged
12.4%, 7.1%, 4.4% and 6.1% for soybean, wheat, rice and maize,
respectively. Spatial variation in yield losses is similar among different
stresses; areas with a large loss due to ozone are also at high risk
of yield losses due to pest and diseases and heat. Many vegetable
crops are also susceptible to ozone, which will adversely impact quality
and quantity (Mattos et al., 2014; Bisbis et al., 2018; Scheelbeek et al.,
2018).
The estimated yield loss does not account for interactions with other
climatic factors. Temperatures enhance not only ozone production but
also ozone uptake by plants, exacerbating yield and quality damage.
Burney (2014) estimated current yield losses due to the combined
effects of ozone and heat in India at 36% for wheat and 20% for rice.
Schauberger et al. (2019a) found global yield losses, ranging from
2% to 10% for soybean and 0% to 39% for wheat with a model that
Yield Constraint Score for the effect of five crop stresses on global production of soybean and wheat
The yield constraint score integrates the five stress depicted below which provide an indication of where each stress is predicted to be
affecting crop yield globally and the magnitude of the effect.
(a) Soybean (
Glycine max
)
Yield
constraint
score
Yield
constraint
score
Pests &
diseases
Soil
nutrients
Heat
stress
Aridity
Pests &
diseases
Soil
nutrients
Heat
stress
Aridity
Ozone
Higher stress
Lower stress
Ozone
(b) Wheat (
Triticum aestivum
)
Figure 5.4 | The global effects of five biotic and abiotic stresses on soybean and wheat.
All data are presented for the 1 × 1° (latitude and longitude) grid squares
where the mean production of soybean or wheat was >500 tonnes (0.0005 Tg). The effect of each stress on yield is presented as a Yield Constraint Score (YCS) on a scale of 1–5,
where 5 is the highest level of stress from ozone, pests and diseases, heat stress and aridity (Mills et al., 2018). Data are available at Sharps et al. (2020). See Annex I: Global to
Regional Atlas for all four crops.
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accounts for temperature, water and CO
2
concentration on ozone
uptake.
5.4.2
Assessing Vulnerabilities within Production
Systems
Since AR5, vulnerability assessment has become a pivotal component
of risk analysis associated with climate hazards, climate change and
climate variability (UNDRR, 2019)
.
Vulnerability assessment can be
sectoral or regional but involves social and ecological indicators. This
section presents examples of vulnerability assessment to climatic
hazards and social vulnerabilities.
5.4.2.1 Vulnerability to climatic hazards
Drought is a major risk component in cropping systems globally,
with substantial economic loss (Kim et al., 2019b), livelihood impacts
(Shiferaw et al., 2014; Miyan, 2015) and ultimately health risks such as
malnutrition (Phalkey et al., 2015; Cooper et al., 2019). Vulnerability to
drought can be estimated with a range of indicators (Hagenlocher et al.,
2019). Meza (2020) showed that drought risks could be exacerbated
or moderated by regional differences in vulnerability (Figure 5.5). For
instance, high-level risks observed in southern Africa, western Asia
and central Asia result from high vulnerability (low coping capacity),
whereas risk levels are relatively low despite the high exposure by
relatively high adaptive capacity to drought in other regions.
Regional-scale assessment also highlights the importance of adaptive
capacity. For instance, rice and maize production in Viet Nam Mekong
Delta has high exposure to multiple climate hazards such as flooding,
sea level rise, salinity intrusion and drought (Parker et al., 2019). Risks
can be moderated by a relatively high adaptive capacity because of
infrastructure, resources and high education levels (Parker et al.,
2019). Another regional study demonstrated that erratic rains and
high temperatures in southern and southeastern Africa increased
the vulnerability of agricultural soils, thereby exacerbating impacts
of prolonged and frequent droughts (Sonwa et al., 2017a; See also
Box 5.4).
Farm-scale assessment exemplifies context-sensitive vulnerability
to climate hazards. Studies of coffee growers in Central America
demonstrated that key vulnerability indicators varied greatly between
regions and between farms, ranging from a lack of labour, postharvest
infrastructure, conservation practices and transport that limits access
to market, technical and financial assistance (Baca et al., 2014;
Bouroncle et al., 2017). These region- and scale-specific vulnerability
Rainfed agriculture: Drought risks, hazards, exposure and vulnerability indicators
Observed period 1986–2015
Low
High
Areas with no crops
Areas with no data
Data averaged over 1.5° hexagons
Indicator scores for rainfed agriculture
(c) Drought risk index
(a) Hazard and exposure indicator score
(b) Vulnerability index
Figure 5.5 | Hazard and exposure indicator score (a), vulnerability index (b) and drought risk index (c), for rainfed agricultural systems between 1986 and
2015.
Drought hazard indicator is defined as the ratio of actual crop evapotranspiration to potential crop evapotranspiration, calculated for 24 crops. Vulnerability index is the
country-scale weighted average of a total of 64 indicators including social and ecological susceptibility indicators, and coping capacity. Risk index is calculated by multiplying hazard/
exposure indicator score and vulnerability index (Meza et al., 2020).
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indicators assist in identifying ways to enhance resilience to climate
hazards (
high confidence
).
5.4.2.2 Inequities in cropping systems—other crops and
regional disparities
While those working with major crops have benefited from the release
of new cultivars, those growing other crops are typically reliant
on a heritage cultivars or landraces. While Indigenous knowledge
and local smallholder knowledge and practices play an important
role in supporting agrobiodiversity which provides genetic diversity
resistant to climate-related stresses, a global and national focus in
international research, subsidies and support for a few crop species
has contributed to an overall decline in agrobiodiversity (FAO, 2019e;
Song et al., 2019) Similarly, there is a lack of agronomic innovation and
research to service ‘minor’ crops (Moriondo et al., 2015; Manners and
van Etten, 2018). Even some high-value commodities grown outside
high-income countries suffer from imbalances in the focus of available
credit, research and innovation (Section 5.4.4.3; Glover, 2014; Fischer,
2016; Farrell et al., 2018). There is a possibility that a lack of adaptive
capacity and policy support will drive these growers to move away
from these diverse crops, further reducing the resilience of food
systems by increasing risk of crop loss from pests, disease and drought
and potential loss of Indigenous or local knowledge (Section 5.13.5,
Table Box 5.1.1). In the Andean Altiplano of Bolivia, for example,
Indigenous farmers have traditionally managed a diverse set of native
crops which are drought and frost-tolerant, using cultural practices
of seed selection and exchange, but have faced an increase in pests
and diseases and a decline of traditional crops due to climate-change-
related stresses, out-migration and intensification drivers (Meldrum
et al., 2018).
5.4.2.3 Gender and other social inequities
Social inequities such as gender, ethnicity and income level, which
vary by time and place and may overlap, can compound vulnerability
to climate change for producers within cropping systems (
high
confidence
) (Table 5.3, Arora-Jonsson, 2011; Djoudi et al., 2013; Carr
and Thompson, 2014; Mbow et al., 2019; Rao et al., 2019a; Nyantakyi-
Frimpong, 2020a). Rather than binary and static categories (i.e., men
versus women), social vulnerabilities are dynamic and intersect; to
understand vulnerability, the specific socio-cultural identities and
political and environmental context need to be studied in relation to
climate stress (Thompson-Hall et al., 2016; Rao et al., 2019a; Nyantakyi-
Frimpong, 2020a).
5.4.3
Projected Impacts
5.4.3.1 Advances in the characterisation of the effects of
elevated atmospheric CO
2
Elevated CO
2
concentrations stimulate photosynthesis rates and
biomass accumulation of C
3
crops, and enhance crop water use
efficiency of various crop species, including C
4
crops (
high confidence
)
(Kimball, 2016; Toreti et al., 2020). Perennial crops and root crops may
Table 5.3 |
Examples of social inequities in cropping systems that compound climate change vulnerability.
Social inequity
How social inequity increases vulnerability to climate change in cropping systems
Gender inequity
can create and worsen social
vulnerability to climate change impacts within cropping
systems (
high confidence
) (Carr and Thompson,
2014; Sugden et al., 2014; Nyantakyi-Frimpong and
Bezner-Kerr, 2015; Rao et al., 2019a; Ebhuoma et al.,
2020; Nyantakyi-Frimpong, 2020a; see Cross-Chapter
Box GENDER in Chapter 18).
– Men and women have different access to and decision-making control over resources such as seeds, systemic differences in
land tenure and agricultural employment, and their responsibilities, workloads and response to climate stresses differ due
to systemic gender inequities and socio-cultural norms, which intersect with other inequities (e.g., income level, ethnicity) to
compound vulnerability (Rao et al., 2019a; Ebhuoma et al., 2020; Nyantakyi-Frimpong, 2020a).
– In a study in northern Ghana, for example, poor widows with poor health had fewer resources to rely on during droughts
than married women, particularly those married to local leaders; in contrast, due to gendered expectations, during floods
low-income men suffered greater consequences (Nyantakyi-Frimpong, 2020a).
– Adaptation strategies such as migration can compound that vulnerability, but importantly, the specific gendered
vulnerability intersects with other inequities which are context specific (Sugden et al., 2014; Nyantakyi-Frimpong, 2020a;
Cross-Chapter Box MIGRATE in Chapter 7).
Globally,
smallholder food producers
are more
vulnerable than large-scale producers to climate change
impacts (
high confidence
).
– Smallholder food producers are more vulnerable in part because of limited policy, infrastructure and institutional support,
low credit access, viable markets and limited political voice in policy debates (HLPE, 2013; Karttunen et al., 2017; Mbow
et al., 2019; Nyantakyi-Frimpong, 2020a).
– Smallholder producers’ vulnerability may be increased by heavy reliance on one crop for income, particularly if the crop
requires significant capital investments (
medium confidence
) (Toufique and Belton, 2014; Craparo et al., 2015; Ovalle-Rivera
et al., 2015).
– For example, smallholder coffee producers in southern Mexico and Central America are more vulnerable due to a range of
factors, including unstable and low coffee prices, limited institutional support for small-scale producers, low negotiation
capacity and access to markets, and heavy reliance on one crop for income (Economic Commission for Latin America and
the Caribbean and System, 2014; Ovalle-Rivera et al., 2015; Ruiz Meza, 2015; Hannah et al., 2017; Bacon et al., 2021). Pest
and disease outbreaks such as coffee leaf rust, extreme climatic events, ongoing conflict, poor governance and low viability
of livelihoods increased migration and high levels of food insecurity for this group (Robalino et al., 2015; Hannah et al.,
2017; Donatti et al., 2019) which also varied by institutional- and farm-level responses, land size and income level (Quiroga
et al., 2020; Bacon et al., 2021).
Farmworkers
are another social group with heightened
vulnerability to climate change (
medium confidence
).
– Farmworkers often experience job insecurity, food insecurity, poor working conditions, poverty and social marginalisation.
Climate change impacts can compound their vulnerability, for example by worsening working conditions through increased
temperatures and humidity (Section 5.12.3.1), or increase unreliability of work due to rainfall irregularity, flooding or
drought, and can put them more at risk during climatic extreme events such as wildfires (Turhan et al., 2015; Greene, 2018;
Mendez et al., 2020; Tigchelaar et al., 2020).
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have a greater capacity for enhanced biomass under elevated CO
2
concentrations, although this does not always result in higher yields
(Glenn et al., 2013; Kimball, 2016).
Recent FACE studies found that the effects of elevated CO
2
are greater
under water-limited conditions (
medium confidence
) (Manderscheid
et al., 2014; Fitzgerald et al., 2016; Kimball, 2016), which was generally
reproduced by crop models (Deryng et al., 2016). However, drought
sometimes negates the CO
2
effects (Jin et al., 2018).
There are significant interactions between CO
2
, temperature, cultivars,
nitrogen and phosphorous nutrients (Kimball, 2016; Toreti et al., 2020):
positive effects of rising CO
2
on yield are significantly reduced by higher
temperatures for soybean, wheat and rice (
medium confidence
) (Ruiz-
Vera et al., 2013; Cai et al., 2016; Gray et al., 2016; Hasegawa et al.,
2016; Obermeier et al., 2016; Purcell et al., 2018; Wang et al., 2018). In
above-ground vegetables, elevated CO
2
can in some cases reduce the
impact of other climate stressors, while in others the negative impacts
of other abiotic factors negate the potential benefit of elevated CO
2
(Bourgault et al., 2017; Bourgault et al., 2018; Parvin et al., 2018;
Parvin et al., 2019). Significant variation exists among cultivars in yield
response to elevated CO
2
, which is positively correlated with yield
potential in rice and soybean, suggesting the potential to develop
cultivars for enhanced productivity under future elevated [CO
2
]
(Ainsworth and Long, 2021).
Elevated CO
2
reduces some important nutrients such as protein, iron,
zinc and some grains, fruit or vegetables to varying degrees depending
on crop species and cultivars (
high confidence
) (Mattos et al., 2014;
Myers et al., 2014; Dong et al., 2018; Scheelbeek et al., 2018; Zhu et al.,
2018a; Jin et al., 2019; Ujiie et al., 2019). This is of particular relevance
for fruit and vegetable crops given their importance in human
nutrition (
high confidence
) (see Section 5.12.4 for potential impacts
on nutrition; Nelson et al., 2018; Springmann et al., 2018). Recent
experimental studies (Section 5.3.2), however, show some complex and
counteracting interactions between CO
2
and temperature in wheat,
soybean and rice; heat stress negates the adverse effect of elevated
CO
2
on some nutrient elements (Macabuhay et al., 2018; Kohler et al.,
2019; Wang et al., 2019b). The CO
2
by temperature interaction for grain
quality needs to be better understood quantitatively to predict food
nutritional security in the future.
5.4.3.2 Projected impacts on major crop production
AR5 Chapter 7 estimated global crop yield reduction due to climate
change to be about 1% per decade (Porter et al., 2014), similar to the
previous assessment reports (Porter et al., 2019). Additional research
confirms that climate change will disproportionately affect crop
yields among regions, with more negative than positive effects being
expected in most areas, especially in currently warm regions, including
Africa and Central and South America (
high confidence
).
A systematic literature search between 2014 and 2020 resulted in
about 100 peer-reviewed papers that simulated crop yields of four
major crops (maize, rice, soybean and wheat) using Coupled Model
Intercomparison Project Phase 5 (CMIP5) data (Hasegawa et al.,
2021b). Most studies focus on the relative change in crop yields
due to climate change but do not consider technological advances.
Nevertheless, they provide useful insights into time-, scenario- and
warming-degree-dependent impacts of climate change.
The impact of climate change on crop yield without adaptation projected
in the 21st century is generally negative even with the CO
2
fertilisation
effects, with the overall median per-decade effect being −2.3% for
maize, −3.3% for soybean, −0.7% for rice and −1.3% for wheat, which
is consistent with previous IPCC assessments (Porter et al., 2014). The
effects vary greatly within each crop, timeframe and RCP, but show a
few common features across crops (Figure 5.6a
)
. Differences in the
projected impacts between RCPs are not pronounced by mid-century.
From then onward, the negative effect becomes more pronounced
under RCP8.5, notably in maize. Rice yields show less variation across
models than other crops presumably because simulations are mostly
under irrigated conditions. A part of the uncertainty in the projection is
due to regional differences (Figure 5. 6b). Negative impacts on cereals
are projected in Africa and Central and South America at the end of the
century, which agrees with the previous studies (Aggarwal et al., 2019;
Porter et al., 2019).
The differences due to regions, RCPs and timeframes are related to
the current temperature level and degree of warming (Figure 5.7). The
projected effects of climate change are positive where current annual
mean temperatures (
T
ave
) are below 10°C, but they become negative
with
T
ave
above around 15°C. At
T
ave
> 20°C, even a small degree of
warming could result in adverse effects. In maize, negative effects
are apparent at almost all temperature zones. A new study using
the latest climate scenarios (Coupled Model Intercomparison Project
Phase 6, CMIP6) and global gridded crop model ensemble projected
that climate change impacts on major crop yields appear sooner than
previously anticipated, mainly because of warmer climate projections
and improved crop model sensitivities (Jägermeyr et al., 2021).
As noted in Section 5.3.1, most simulations do not fully account for
responses to pests, diseases, long-term change in soil, and some climate
extremes (Rosenzweig et al., 2014), but studies are emerging to include
some of these effects. For example, based on the temperature response
of insect pest population and metabolic process, global yield losses of
rice, maize and wheat are projected to increase by 10–25% per degree
Celsius of warming (Deutsch et al., 2018). Rising temperatures reduce
soil carbon and nitrogen, which in turn exacerbate the negative effects
of +3°C warming on yield from 9% to 13% in wheat and from 14% to
19% in maize (Basso et al., 2018).
A few studies have examined possible occurrences of tele-connected
yield losses (5.4.1.2) using future climate scenarios. Tigchelaar (2018)
estimated that, for the top four maize-exporting countries, the
probability that simultaneous production losses greater than 10%
occur in any given year increases from 0% to 7% under 2°C warming
and to 86% under 4°C warming. Gaupp (2019) estimated that risks of
simultaneous failure in maize would increase from 6% to 40% at 1.5°C
and to 54% at 2°C warming, relative to the historical baseline climate.
Large-scale changes in SST are the major factors causing simultaneous
variation in climate extremes, which are projected to intensify under
global warming (Cai et al., 2014; Perry et al., 2017). Consequently, risks
of simultaneous yield losses in major food-producing regions will also
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increase with global warming levels above 1.5°C (
medium confidence
).
Further examination is needed for the effects of spatial patterns of
these extremes on breadbaskets in relation to SST anomalies under
more extreme climate scenarios.
Future surface ozone concentration is highly uncertain (Fiore et al.,
2012; Turnock et al., 2018); it is projected to increase under RCP8.5 and
decrease under other RCPs depending largely on different methane
emission trajectories because methane is an important precursor
of ozone. Methane, therefore, reduces crop yield both from climate
warming and ozone increase (Avnery et al., 2013). Shindell (2016)
estimated yield losses of four major crops (to be 25±11% by 2100
under RCP8.5, as a net balance of the positive effect of CO
2
(15±2%)
and negative effects of warming (35±10%) and ozone (4.0±1.3%),
and that 62% of the yield loss was attributable to methane. This
points to the importance of reducing methane and other precursors
of ozone as an effective adaptation strategy (
medium evidence
,
high
agreement
).
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
Near future
Mid centur
y
End of centur
y
Near future
Mid centur
y
End of centur
y
Near future
Mid centur
y
End of centur
y
Projected yield changes relative to the baseline period (2001–2010)
without adaptation and with CO
2
fertilization effects
Numbers are the number of simulations
RCP4.5
RCP4.5
50
55 85 55
61 123 91
58 77 56
65 118 92
43 47 48
45
51
-100
-50
0
77
44 52 50
-100
-50
0
50
10
10
9
9
7
-100
-50
0
50
-100
-50
0
50
10 17
6 13
2
6 22
1
3 16
3
13 17
6 14
6
6 35
3 18 13
14 17
6 14
4
7
17
3 19 12
3 39
1
6
1
3
1
2
1
31
1
6
1
3
3
1
3
4
4
4
Maize
Wheat
Soybean
Rice
Yield
change
(%)
(a)
At different time periods
(b)
At different regions at end of century
49
49
68
68
104
104
73
73 92
92 84
84
18
18 15
15
19
19 14
14
17
17
33
33
77
77
65
65
77
7
49
68
104
73 92 84
18 15
19 14
17
33
77
65
7
Figure 5.6 | Projected yield changes relative to the baseline period (2001–2010) without adaptation and with CO
2
fertilisation effects (Hasegawa et al.
,
2021b).
The box is the interquartile range (IQR), and the middle line in the box represents the median. The upper and lower end of whiskers are median 1.5 × IQR ± median. Open
circles are values outside the 1.5 × IQR.
(a)
At different time periods (near future, NF, baseline to 2039; mid-century, MC, 2040–2069; end-century, EC, 2070–2100) under three
RCPs, and
(b)
at different regions at EC.
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Chapter 5
5.4.3.3 Projected impacts on other crops
Yield projections for crops other than cereals indicate mostly
negative impacts on production due to a range of climate drivers
(
high confidence
), with yield reductions similar to that of cereals
expected in tropical, subtropical and semi-arid areas (Mbow et al.,
2019). Springmann et al. (2016), compared the projected global food
availability for different food groups under the SSP2 2050 scenario
and found reductions in availability were similar in cereals, fruit and
vegetables, and root and tubers (with legumes and oilseed crops
showing a smaller reduction).
Fruit and vegetables have not been subject to extensive or coordinated
yield projections (Figure 5.8). Yield projections have been performed for
individual crops and locations (Ruane, 2014; Adhikari et al., 2015; Awoye
et al., 2017; Ramachandran et al., 2017), but more often crop suitability
Projected yield changes relative to the baseline period (2001–2010)
without adaptation and with CO
2
fertilization effects
Numbers are the number of simulations
Maize
Wheat
Soybean
Rice
Yi
eld change (%) at mid centur
y
-100
-50
0
50
-100
-50
0
50
-100
-50
0
50
Yi
eld change (%) at end of centur
y
Yi
eld change
(%
)
(a) As a function of current annual temperature (T
ave
)
(b) As a function of global temperature rise from the baseline period by three current annual temperature (T
ave
) levels
Current annual temperature (T
ave
°C)
Temperature rise (°C)
T
ave
20<
T
ave
10<20
T
ave
<10
RCP2.6
RCP4.5
RCP8.5
3 4 18 34 51 24 54 21
3 3 10 32 36 25 33 17
1 6 20 53 20
53
53
68
6 19 60 33
56
56
64
9 2 9 1 8 14
9
7
8 12
3 5 36 51 94 56 34 11
3 5 17 52 76 53 19 9
-10 0 5 10 15 20 25 30 -10 0 5 10 15 20 25 30 -10 0 5 10 15 20 25 30 -10 0 5 10 15 20 25 30
53
56
45
322
105
52
≤ 1.5 ≤ 2.5 ≤ 3.5
3.5<
89
342
137
76
≤ 1.5 ≤ 2.5 ≤ 3.5
3.5<
7
59
24
15
≤ 1.5 ≤ 2.5 ≤ 3.5
3.5<
53
53
435
115
92
≤ 1.5 ≤ 2.5 ≤ 3.5
3.5<
53
Maize
Wheat
Soybean
Rice
Figure 5.7 | Projected yield changes relative to the baseline period (2001–2010) without adaptation and with CO
2
fertilisation effects (Hasegawa et al.,
2021b).
(a)
Mid-century (MC, 2040–2069) and end-century (EC, 2070–2100) projections under three RCP scenarios as a function of current annual temperature (
T
ave
),
(b)
as a
function of global temperature rise from the baseline period by three
T
ave
levels. See Figure. 5.6 for legends.
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models have been used (SM5.3). Zhao (2019) introduced a modelling
approach that could be used to generate yield projections for a wider
range of annual crops. The discussion here also draws on reviews of more
restricted experimental studies. Negative impacts of climate change on
crop production are expected across many cropping systems (Figure 5.8).
Apart from the direct effects of elevated carbon dioxide, most changes
are expected to have negative effects on crop production. Changes in
temperature and rainfall are most often mentioned as drivers of climate
impacts, but expected changes in phenology, pests and diseases are
also raising concerns. Scheelbeek et al. (2018) synthesised projections
for vegetables and legumes, based on their response to climate factors
under experimental conditions; in most cases, the magnitude of the
changes is comparable to the RCP8.5 2100 forecasts. Scheelbeek et al.
(2018) projected yield changes of: +22.0% (+11.6% to +32.5%) for a
250 ppm increase in CO
2
concentration; −34.7% (−44.6% to −24.9%)
for a 50% reduction in water availability; −8.9% (−15.6% to −2.2%)
for a 25% increase in ozone concentration; −31.5% for a 4°C increase
in temperature (in papers with a baseline temperature of >20°C).
Overall, impacts are expected to be largely negative in regions where
the temperature is currently above 20°C, while some yield gains are
expected in cooler regions (provided that water availability and other
conditions are maintained). Scheelbeek et al. (2018) did not consider
changes in pest and disease pressure, which are projected to increase
with warming (see SM5.3).
Systematic assessments of climate response for root crops as a group
are lacking (Raymundo et al., 2014; Knox et al., 2016; Manners and
van Etten, 2018). Climate suitability is projected to increase for tropical
root crops (SM5.3), and some studies have found that root crops will
be less negatively impacted than cereals, but there is no consensus on
this (Brassard and Singh, 2008; Adhikari et al., 2015; Schafleitner, 2016;
Manners et al., 2021). For potato, Raymundo et al. (2018) projected
global yield reductions of 2–6% by 2055 under different RCPs, but
with important differences among regions; tuber dry weight may
experience reductions of 50–100% in marginal growing areas such
as central Asia, while increases of up to 25% are expected in many
high-yielding environments. Projections show yield increases of 6%
per 100 ppm elevation in CO
2
but declines of 4.6% per degree Celsius
and 2% per 10% decrease in rainfall (Fleisher et al., 2017). Jennings
et al. (2020) projected an overall increase in global potato production,
but only if widespread adoption of adaptation measures is achieved.
Although increases in CO
2
could produce positive yield responses,
the effects of temperature may offset these potential benefits (Dua
et al., 2013; Raymundo et al., 2014). Warming offers the potential of
longer growing seasons but can also have negative impacts through
disrupted phenology and interactions with pests (Figure 5.8, Bebber,
2015; Pulatov et al., 2015).
Global yield modelling is lacking for woody perennial crops.
Experimental studies suggest negative impacts on yields due to reduced
water supply and increased soil salinity, as well as from warming and
ozone (although evidence was limited for these) (Alae-Carew et al.,
2020). Increasing CO
2
is expected to increase yields, but only where
other factors, such as warming, do not become yield-limiting (Alae-
Carew et al., 2020). Many local projections include large uncertainty
because of a lack of observational data and reliable parametrisation
(Moriondo et al., 2015; Mosedale et al., 2016; Kerr et al., 2018;
Mayer et al., 2019b). Most perennial crop models have found large
negative impacts on yield and suitability, although CO
2
fertilisation
and phenology are not always considered (Lobell and Field, 2011;
Glenn et al., 2013). Perennial crops are often grown in dryland areas
where rainfall or irrigation water can be critical (Mrabet et al., 2020).
Valverde (2015) found that yield losses in the Mediterranean region
were largely driven by reduced rainfall, with maximum estimated
yield losses of 5.4% for grape, 14.9% for olive and 27.2% for almond
under a relatively hot and dry scenario (by 2041–2070). Moriondo
(2015) highlight the need for perennial crop models to incorporate
phenology and extreme climate events. Equally challenging is the need
to estimate the impact of biotic changes, particularly climate-driven
movement of pests and diseases (Ponti et al., 2014; Bosso et al., 2016;
Schulze-Sylvester and Reineke, 2019).
Synthesis of literature on the projected impacts of climate change on different cropping systems
Vegetable
Legumes
Leafy crops
Soft fruit
Root crops
Tree fruits
and nuts
Annual
(above ground)
Annual (below ground)
Perennial
Average confidence in attribution
= not assessed
na
Average direction of impact
Low
Medium
High
Climate
change
(general)
Temperature
(incl. heat
stress)
Precipitation
(Incl.
drought,
flood)
Ecosystem
services
Combined
(sum of
all drivers)
Crop type
Life history strategy
Phenology
& seasons
Carbon
dioxide
Pests &
diseases
na
na
na
na
na
na
na
na
na
na
na
na
na
na
na
All
na
Mixed
Positive
Negative
Figure 5.8 | Synthesis of literature on the projected impacts of climate change on different cropping systems.
The assessment includes projections of impacts on
crop productivity over a range of emission scenarios and time periods. The projected impacts are disaggregated by the different climate and climate-related drivers. Impacts are
reported as positive, negative or mixed. The assessment draws on >60 articles published since AR5. The confidence is based on the evidence given in individual articles and on the
number of articles. See
SM5.2
information for details.
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Box 5.2: Case Study: Wine
Wine-growing regions cover 7.4 million ha, with a value of 35 billion USD in 2018 (OIV, 2019). Important regions (Italy, France, Spain,
USA, Argentina, Australia, South Africa, Chile, Germany, China, Argentina) are located in areas where mean annual temperature roughly
varies between 10°C and 20°C (Schultz and Jones, 2010; Mosedale et al., 2016).
Temperature is the primary determinant for vine development. Recent warming trends have advanced flowering, maturity and harvest
(
high confidence
) (Koufos et al., 2014; Cook and Wolkovich, 2016; Hall et al., 2016; Ruml et al., 2016; van Leeuwen and Destrac-Irvine,
2017; Koufos et al., 2020; Wang et al., 2020b; Wang and Li, 2020), and wine-growing regions have expanded outside the normal
temperature bounds of locally grown varieties (
limited evidence
,
high agreement
) (Kryza et al., 2015; Irimia et al., 2018). Milder winters
have affected harvest in ice-wine growing regions (Pickering et al., 2015). Higher temperatures have mixed effects depending on site, but
generally decrease grape quality (Barnuud et al., 2014; Morales et al., 2014; Sweetman et al., 2014; Kizildeniz et al., 2015; Kizildeniz et al.,
2018). Warming increases sugar accumulation and decreases acidity (Leolini et al., 2019). Secondary metabolites are negatively affected
(Biasi et al., 2019; Teslić et al., 2019). Developmental phases are projected to proceed faster in response to warming (
high confidence
)
(Fraga et al., 2016a; Fraga et al., 2016b; García de Cortázar-Atauri et al., 2017; Costa et al., 2019; Molitor and Junk, 2019; Sánchez, 2019).
However extreme high temperatures may have inhibitory effects on development (Cuccia et al., 2014).
In some cases, irrigation is required, and more frequent droughts are a key concern for yield and fruit quality (Morales et al., 2014;
Bonada et al., 2015; Kizildeniz et al., 2015; Salazar-Parra, 2015; Kizildeniz et al., 2018; Funes et al., 2020). Water stress reduces shoot
growth and berry size, and increases tannin and anthocyanin content (van Leeuwen and Darriet, 2016). However, controlled water stress
produces positive impacts on wine quality, increasing skin phenolic compounds (van Leeuwen and Destrac-Irvine, 2017). The level of
stress will depend on soil type, texture and organic matter content (Fraga et al., 2016a; Fraga et al., 2016b; Bonfante, 2017; García de
Cortázar-Atauri et al., 2017; Leibar et al., 2017; Costa et al., 2019; Molitor and Junk, 2019; Sánchez, 2019). Increases in water demands
with potential negative effects from increased soil salinity are among the most common effects of climate change in irrigated regions
(
medium evidence
,
high agreement
) (Mirás-Avalos et al., 2018; Phogat et al., 2018).
Rising CO
2
will have mixed effects on vine growth and quality (
medium evidence, high agreement
)
(Martínez-Lüscher et al., 2016;
Edwards et al., 2017; van Leeuwen and Destrac-Irvine, 2017). Rising CO
2
concentrations will negatively affect wine quality by reducing
anthocyanin concentration and colour intensity (Leibar et al., 2017).
Suitability responses to warming are region-specific. In regions where low temperature is a limiting factor, warming will enable growers
to grow a wider range of varieties and obtain better-quality wines (
high confidence
) (Fuhrer et al., 2014; Mosedale et al., 2015; Mosedale
et al., 2016; Meier et al., 2018; Jobin Poirier et al., 2019; Maciejczak and Mikiciuk, 2019). Subtropical and Mediterranean regions will
experience major declines in fruit quality for high-quality wines (
high confidence
) (Resco et al., 2016; Lazoglou et al., 2018; Cardell et al.,
2019; Fraga et al., 2019a; Fraga et al., 2019b; Teslić et al., 2019). These changes will also affect wine tourism (Nunes and Loureiro, 2016).
Impacts on suitability may reshape the geographical distribution of wine regions. Viability of the wine-growing regions will depend on the
knowledge of local climatic variability (Neethling et al., 2019; Rességuier et al., 2020) and the implementation of adaptation strategies
such as use of adapted plant material rootstocks, cultivars and clones, viticultural techniques (e.g., changing trunk height, leaf area to
fruit weight ratio, timing of pruning), irrigation, enological interventions to control alcohol and acidity, and policy incentives and support
(Callen et al., 2016; Ollat and Leeuwen, 2016; van Leeuwen and Destrac-Irvine, 2017; Merloni et al., 2018; Alikadic et al., 2019; del Pozo
et al., 2019; Fraga et al., 2019b; Santillan et al., 2019; Morales-Castilla et al., 2020; Marín et al., 2021).
Box 5.3: Pollinators
Climate change will reduce the effectiveness of pollinator agents as species are lost from certain areas, or the coordination of pollinator
activity and flower receptiveness is disrupted in some regions (
high confidence
) (Potts et al., 2010; Gonzalez-Varo et al., 2013; Polce
et al., 2014; Kerr et al., 2015; Potts et al., 2016; Settele et al., 2016; Giannini et al., 2017; Mbow et al., 2019). A modelling study estimates
that complete removal of pollinators could reduce global fruit supply by 23%, vegetables by 16%, and nuts and seeds by 22%, leading
to significant increases in nutrient-deficient population and malnutrition-related diseases (Smith and Haddad, 2015), highlighting the
importance of this ecosystem service for human health.
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Bees are an essential agricultural pollinator, widely recognised for their role in the fertilisation of many domesticated plants. The observed
widespread decline in native bees and honeybee colony numbers, particularly in the USA and Europe, has been associated with a number
of environmental stressors in addition to climate change, such as neonicotinoids and varroa mites, and has raised concerns regarding
plant–pollinator networks, the stability of pollination services, global food production and the prevalence of malnutrition (Williams and
Osborne, 2009; Potts et al., 2010; Chaplin-Kramer et al., 2014).
Any climatic influence on floral phenology or physiology could, potentially, alter bee biology. At present, there is evidence that climate-
change-induced asynchrony in pollen and pollinators can occur (Stemkovski et al., 2020). In addition, the nutritional composition of floral
pollen may also affect bees’ health at the global level (
low evidence
). For example, goldenrod (
Solidago
spp.), a ubiquitous pollen source
for bees just prior to winter, has experienced a ~30% drop in protein since the onset of CO
2
emissions from the industrial revolution
(Ziska et al., 2016).
Climate extremes could pose risks to pollinators when species tolerance is exceeded, with subsequent reduction in populations and
potential extirpation (Nicholson and Egan, 2020; Soroye et al., 2020). The rate of climate change may induce potential mismatches in
the timing of flowering and pollinator activity depending on the species (Bartomeus et al., 2011). For instance, Miller-Struttmann (2015)
showed that long-tongued bumblebees may be at a disadvantage as warming temperatures are reducing their floral hosts, making
generalist bumblebees more successful.
Overall, there is
medium confidence
that long-term mutualisms may be impacted directly by CO
2
increases in terms of nutrition, or by
temperature and other climatic shifts that may alter floral emergence relative to pollinator life cycles. Additional research is needed to
further our understanding of the biological basis for these effects, and their consequence for pollination services.
Box 5.3 (continued)
Table 5.4 |
Projected impacts on CES from climate change.
Region
CES
Climate change scenario
Projected impacts from climate change
References
Central Chile, South America
Aesthetic experience of scenic
beauty in vine-growing region.
RCP2.6 and 8.5.
Increased temperature, reduced precipitation and
increased fires will damage scenic beauty of vineyards.
Participatory scenario analysis estimated reduction in
aesthetic experience from scenic beauty by 18–28% by
2050 for RCP2.6, with greater impacts under RCP8.5.
Martinez-Harms
et al. (2017)
Mountainous regions of
Austria
Cultural and aesthetic
experiences in alpine pastures
and diverse agricultural
landscapes.
Temperature +1.5°C from 2008
to 2040 and four precipitation
scenarios (high, similar
,
seasonal shift and
low).
Some decline in CES, with trade-offs between diversity
and CES and provisioning services depending upon the
scenario.
Kirchner et al. (2015)
Forest and agricultural
landscapes in southern
Saxony-Anhalt in Germany
Recreation, scenic landscape
beauty and spiritual value of
agricultural landscapes and
forests.
Regional scenarios, do not
specify RCPs.
Not anticipated to be significantly changed by climate
change under most scenarios, except for intensification
scenario, which would lead to a decline in the forest
cultural services as they provide important historical and
cultural ties.
Gorn et al. (2018)
Northeast Austria floodplains
(grasslands and wetlands)
Tourism, recreation, cultural
heritage.
Increased temperature by 2050
and 2100 and seasonal shifts in
precipitation.
Increased agricultural intensification due to shifts in
climate and decline in CES is predicted, based on farmer
interviews.
Probstl-Haider et al.
(2016)
Mount Kenya, Kenya
Tourism, recreation, spiritual
and cultural values.
Not specified.
Glacier disappearance may lead to reduced mountain
trekking and other tourism and recreational activities.
Evaristus (2014)
Philippines
Nature-based tourism in
agri-tourism.
Not specified.
Risk of typhoon, drought and strong wind, grass fire,
heavy rains. Anticipated to increase vulnerability in terms
of human health services and energy use in tourism.
Hidalgo (2015)
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For cotton, experimental studies suggest positive impacts from rising
CO
2
and temperature (Zhang et al., 2017a; Jans et al., 2021), but
projections show mixed impacts on yield, including large negative
impacts in warmer regions due to heat, drought and the interaction of
temperature with phenology (Yang et al., 2014; Williams et al., 2015;
Adhikari et al., 2016; Rahman et al., 2018). Climate change is also
expected to increase the demand for irrigation water, which will likely
limit production (Jans et al., 2021). There are also concerns that fibre
quality may deteriorate (e.g., air permeability of compressed cotton
fibers) (Luo et al., 2016).
Higher temperatures and altered moisture levels are expected to
present a food safety risk, particularly for above-ground harvested
vegetables (Figures 5.8; 5.10). Warmer and wetter weather is
anticipated to increase fungal and microbial growth on leaves and fruit,
while altered flooding regimes increase the risk of crop contamination
(Liu et al., 2013; Uyttendaele et al., 2015). This is also true for perennial
crops; for example, warming and climate variability can increase fungal
contamination of grapes, including that associated with mycotoxins
(Battilani, 2016; Paterson, 2018).
5.4.3.4 Observed and projected impacts on cultural ecosystem
service
Cultural ecosystem services (CES) are those non-material benefits,
such as aesthetic experiences, recreation, spiritual enrichment, social
relations, cultural identity, knowledge and other values (Millennium
Ecosystem Assessment, 2005), which support physical and mental health
Box 5.4: Soil Health
Soil health, defined as an integrative property that reflects the capacity of soil to respond to land management, continues to support
provisioning ecosystem services (Kibblewhite et al., 2008). Climate change will have significant impacts on soil health indicators such
as soil organic matter (SOM). For example, precipitation extremes can reduce soil biological functions, and increase surface flooding,
waterlogging, soil erosion and susceptibility to salinisation (Herbert et al., 2015; Chen and Mueller, 2018; Akter et al., 2019; Sánchez-
Rodríguez et al., 2019).
The most significant threat to soil health is the loss of SOM (FAO and ITPS, 2015). SOM holds a great proportion of the nutrients, and
regulates important soil physical, chemical and biological processes, such as cation exchange capacity, pH buffering, soil structure,
water-holding capacity and microbial activity (FAO and ITPS, 2015). Soils also hold the largest terrestrial organic carbon stock, three to
four times greater than the atmosphere (Stoorvogel et al., 2017). At the global scale, climate and vegetation are the main drivers of soil
organic carbon (SOC) storage (Wiesmeier et al., 2019). While organic matter input is the primary driver of SOC stocks (Fujisaki et al.,
2018), temperature and soil moisture play a key role in SOC storage at the local scale (Carvalhais et al., 2014; Doetterl et al., 2015). Soil
type, land use and management practices also play important roles at the local scale.
Increase in soil temperature will negatively impact SOC, but primarily in higher latitudes (
medium confidence
) (Carey et al., 2016; Qi et al.,
2016; Feng et al., 2017; Gregorich et al., 2017; Hicks Pries et al., 2017; Melillo et al., 2017; Hicks Pries et al., 2018). Experiments have
shown that warming can accelerate litter mass loss and soil respiration (Lu et al., 2013) and reduces the soil recalcitrant C pool (Chen
et al., 2020). SOC losses may speed up soil structural degradation, changes in soil stoichiometry and function (Hakkenberg et al., 2008;
Tamene et al., 2019), with downstream effects on aquatic ecosystems. The rate and extent of SOC losses vary greatly depending on the
scale of measurement (local to global), soil properties, climate, land use and management practices (Sanderman et al., 2017; Wiesmeier
et al., 2019).
Adoption of practices that build SOC can improve crop resilience to climate-change-related stresses such as agricultural drought. Iizumi
and Wagai (2019) found that a relatively small increase in topsoil (0–30 cm) SOC could reduce drought damages to crops over 70% of
the global harvested area. The effects of increasing SOC are more positive in drylands owing to more efficient use of rainwater, which
can increase drought tolerance (Iizumi and Wagai, 2019). Similarly, Sun et al. (2020) found that, relative to local conventional tillage,
conservation agriculture has a win-win outcome of enhanced C sequestration and increased crop yield in arid regions. However, the
impact of no-till may be minimal if not supplemented with residue cover and cover crops. As such, this is a highly debated area where
some authors argue that no-till has limited effect and the evidence outside drylands is weak. Furthermore, the use of crop residues is
constrained by its alternative uses (e.g., fuel, livestock feed, etc.) in much of the developing world. Practices that build up SOC may
encourage soil microbial populations, which in turn can increase yield stability under drought conditions (Prudent et al., 2020).
Soil C sequestration is an important strategy to improve crop and livestock production sustainably that could be applied at large scales
and at a low cost, if there was adequate institutional support and labour, using agroforestry, conservation agriculture, mixed cropping
and targeted application of fertilizer and compost (
high confidence
) (Paustian et al., 2016; Kongsager, 2018; Nath et al., 2018; Woolf et al.,
2018; Corbeels et al., 2019; Kuyah et al., 2019; Corbeels et al., 2020; Muchane et al., 2020; Sun et al., 2020; Nath et al., 2021). For example,
a widespread adoption of agroforestry, conservation agriculture, mixed cropping and balanced application of fertilizer and compost by
India’s small landholders could increase annual C sequestration by 70–130 Tg CO
2
e (Nath et al., 2018; Nath et al., 2021).
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and human well-being (Chan et al., 2012; Triguero-Mas et al., 2015).
CES in agricultural and wild landscapes include recreational activities,
access to wild or cultivated products, and cultural foods, spiritual rituals,
heritage and memory dimensions, and aesthetic experiences (Daugstad
et al., 2006; Calvet-Mir et al., 2012; Ruoso et al., 2015). Relative to
other ecosystem services, CES in agricultural landscapes have been less
researched (Merlín-Uribe et al., 2012; Milcu et al., 2013; Bernues et al.,
2014; Plieninger et al., 2014; van Berkel and Verburg, 2014; Ruoso et al.,
2015; Quintas-Soriano et al., 2016). Agricultural heritage is a key aspect
of CES and plays an important role in maintaining agrobiodiversity
(Hanaček and Rodríguez-Labajos, 2018).
Climate change is projected to have negative impacts on CES (
medium
confidence
) (Table 5.4). There is limited evidence that climate change has
been the main driver affecting CES of agroecosystems confounded by
other drivers such as migration and changing farming patterns (Hanaček
and Rodríguez-Labajos, 2018; Dhakal and Kattel, 2019). Recent studies
observed declines in CES in alpine pastures and floodplains in Europe in
part due to climate change impacts (Probstl-Haider et al., 2016; Schirpke
et al., 2019). Another study estimated that the scenic beauty enjoyed by
those who visit the vineyards in central Chile will decline by 18–28%
by 2050 owing to a combination of reduced precipitation, increased
temperatures and natural fire cycles (Martinez-Harms et al., 2017).
More research is needed, however, particularly on cultural heritage and
spiritually significant places and in low-income countries.
5.4.4
Adaptation Options
Adaptation strategies in crop production range from field and farm-
level technical options such as crop management and cultivar/crop
options to livelihood diversification and income protection such
as index-based insurance. This section assesses crop management
options for different crop types. Feasibility of adaptation options in
various systems is addressed in Section 5.14.
5.4.4.1 Adaptation options for major crops
Crop management practices are the most commonly studied adaptation
measures (Shaffril et al., 2018; Hansen et al., 2019a; Muchuru and
Nhamo, 2019), but quantitative assessments are mostly limited to
existing agronomic options such as changes in planting schedules,
cultivars and irrigation (Beveridge et al., 2018a; Aggarwal et al., 2019).
This section draws on the global data set used in Section 5.4.3.2
(Hasegawa et al., 2021b) to estimate adaptation potential, defined
as the difference in simulated yields with and without adaptations. A
caveat to the analysis is that the data set includes management options
if the literature treats them as adaptation. They include intensification
measures such as fertilizer and water management, not allowing for
physical and economic feasibility.
The overall adaptation potential of existing farm management
practices to reduce yield losses averaged 8% in mid-century and
11% in end-century (Figure 5.9), which is insufficient to offset the
negative impacts from climate change, particularly in currently warmer
regions (Section 5.4.3.2). Emission scenarios, crop species, regions and
adaptation options do not show discernible differences. Combinations
of two or more options do not necessarily have greater adaptation
potential than a single option, though a fair comparison is difficult
in the data set from independent studies. One regional study in West
Africa found that currently promising management would no longer
be effective under future climate, suggesting the need to evaluate
effectiveness under projected climate change.
A global-scale meta-analysis estimated a 3–7% yield loss per degree
Celsius increase in temperature (Zhao et al., 2017). Two global-scale
studies using multiple global gridded crop models found that growing-
season adaptation through cultivar changes offsets global production
losses up to 2°C of temperature increase (Minoli et al., 2019; Zabel et al.,
2021). While these studies do not account for CO
2
fertilisation effects,
another global-scale study with the CO
2
fertilisation effects (Iizumi
et al., 2020) showed that residual damage (climate change impacts
after adaptation) would start to increase almost exponentially from
2040 towards the end of the century under RCP8.5. The cost required
for adaptation and due to residual damage is projected to rise from
USD 63 billion at 1.5°C to USD 80 billion at 2°C and to USD 128 billion
at 3°C (Iizumi et al., 2020). All these global studies project that risks
and damages are greater in tropical and arid regions, where crops are
exposed to heat and drought stresses more often than in temperate
regions (Sun et al., 2019; Kummu et al., 2021; SM5.4). There are still
large uncertainties in the crop model projections (Müller et al., 2021a),
but these multiple lines of evidence suggest that warming beyond
+2°C (projected to be reached by mid-century under high-emission
scenarios) will substantially increase the cost of adaptation and the
residual damage to major crops (
high confidence
). The residual damage
will prevail much sooner in currently warmer regions, where the effect
of even a modest temperature increase is greater (Section 5.4.3.2).
Most crop modelling studies on adaptation are still limited to a handful
of options for each crop type (Beveridge et al., 2018a). A range of other
options are possible not just to reduce yield losses but to diversify
risks to livelihoods, which are partially assessed in Sections 5.4.4.4 and
5.14.1. Current modelling approaches are not suited for the assessment
of multiple dimensions of adaptation options. New studies are
emerging that evaluate multiple options for productivity, sustainability
and GHG emission (Xin and Tao, 2019; Smith et al., 2020b), but local-
and household-scale assessment, taking account of future climatic
variability, needs to be enhanced (Beveridge et al., 2018a).
5.4.4.2 Adaptation options for other crops
Across this diverse group of cropping systems, distinct adaptation
options and adaptation limits have emerged (Figure 5.10; Acevedo
et al., 2020; Berrang-Ford et al., 2021b). Some crop types have
already seen widescale implementation of climate adaptation (e.g.,
grapevines), while others show little evidence of preparation for
climate change (e.g., leafy salad crops). Many adaptation responses
are shared with the major crops, but prominent options such as plant
breeding are underutilised and there is a lack of evidence for assessing
adaptation for many crops (Bisbis et al., 2018; Gunathilaka et al.,
2018; Manners and van Etten, 2018). Figure 5.10 assesses several
adaptation options based on the perceived importance of each in
the literature. Fruit and vegetable crops tend to be more reliant on
ecosystem services in the form of pollination, biocontrol and other
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resources (water, nutrients, microbes, etc.), and ecosystem-based
adaptation options are prominent. The range of crops means that
there is great potential for crop switching, but cultural and economic
barriers will make such options difficult to implement, with barriers
to entry for production and marketing (Waha et al., 2013; Magrini
et al., 2016; Kongsager, 2017; Rhiney et al., 2018). Perennial crops
are exposed to a wide range of climate factors throughout the year
and have significant barriers to implementing some of the common
adaptation options, such as relocation or replacing tree species/
cultivar; agronomic interventions on-farm are well used in high-
value tree crops and provide some climate resilience, but longer-term
options will be needed (Glenn et al., 2013; Mosedale et al., 2016;
Gunathilaka et al., 2018; Sugiura, 2019).
Many fruit and vegetable crops are water demanding, and adaptation
responses relating to water management and access to irrigation
water are crucial. Rainwater storage and deficit irrigation techniques
are frequently mentioned as adaptation options and can minimise the
burden on off-farm water supplies (Bisbis et al., 2018; Acevedo et al.,
2020).
5.4.4.3 Cultivar improvements
As stated in AR5, cultivar improvements are one effective counter-
measure against climate change (Porter et al., 2014; Challinor et al.,
2016; Atlin et al., 2017). Plant breeding biotechnology for climate
change adaptation draws upon modern biotechnology and con-
ventional breeding, with the latter often assisted by genomics and
molecular markers. Plant breeding biotechnology will contribute to
adaptation for large-scale producers (
high confidence
). However, in
addition to inconsistencies in meeting farmer expectations, a variety
of socioeconomic and political variables strongly influence, and limit,
Adaptation potential
defined as the difference between yield impacts with and without adaptation in projected impacts
(a)
Mid-century (2040–2069)
End-century (2070–2100)
334 97 33 12 22 51
1
346 134 29
8 12 62 18
3
Soil organi
c
matter managemen
t
Combined
Cultivar
Fertiliser
Irrigation
Planting date
Soil organic
matter management
Tillag
e
Other
s
Combined
Cultiva
r
Fertiliser
Irrigatio
n
Planting date
Tillage
Other
s
-25
0
25
50
75
Adaptation potentia
l (%
)
RCP2.6
RCP4.5
RCP8.5
Maize
32 31
15 39 19
30 39
15 39 23
Africa
Asia
Australasia
Central and
South
Americ
a
Europe
North
Americ
a
-25
0
25
50
75
-25
0
25
50
75
Adaptation potential
(%)
Rice
9 124
3
3
37 125
3 24
3
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
Soybean
9
9
5
9
9
3
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
Mid-century
(2040–2069)
End-century
(2070–2100)
Wheat
23 72
3
9 48 97
23 75
3
9 48 95
Africa
Asia
Australasia
Europe
North
Americ
a
Central and
South
Americ
a
(b)
Adaptation options
Numbers are the number of simulations
Regions
Figure 5.9 | Adaptation potential, defined as the difference between yield impacts with and without adaptation in projected impacts (Hasegawa et al.,
2021b).
(a)
Projections under three RCP scenarios by regions and
(b)
by options at mid-century (MC, 2040–2069) and end-century (EC, 2070–2100).
n
is the number of
simulations. See Figure 5.6 for legends.
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uptake of climate-resilient crops (Acevedo et al., 2020; Rhoné et al.,
2020).
Genome sequencing significantly increases the rate and accuracy
for identifying genes of agronomic traits that are relevant to climate
change, including adaptation to stress from pests and disease,
temperature and water extremes (
high confidence
) (Brozynska et al.,
2016; Scheben et al., 2016; Voss-Fels and Snowdon, 2016). Access to
this information where it is needed and in practical timeframes, as well
as the expertise to use it, will limit the sharing of benefits by the most
vulnerable groups and countries (
high agreement
,
limited evidence
)
(Heinemann et al., 2018).
Genetic improvements for climate change adaptation using modern
biotechnology have not reliably translated into the field (Hu and Xiong,
2014; Nuccio et al., 2018; Napier et al., 2019), but good progress has
been made by conventional breeding. Desirable traits that adapt plants
to environmental stress are inherited as a complex of genes, each of
which makes a small contribution to the trait (Negin and Moshelion,
2017). Adaptation by conventional breeding requires making rapid
incremental changes in the best germplasm to keep pace with the
environment (Millet et al., 2016; Atlin et al., 2017; Cobb et al., 2019).
Further improvements would be difficult without
in situ
and
ex situ
conservation of plant genetic resources to maintain critical germplasm
for breeding (Dempewolf et al., 2014; Castañeda-Álvarez et al., 2016).
Despite the advances in sequencing, phenotyping remains a significant
bottleneck (Ghanem et al., 2015; Negin and Moshelion, 2017; Araus
and Kefauver, 2018); the emergence of high-throughput phenotyping
platforms may reduce this bottleneck in future. Emerging modern
biotechnology such as gene/genome editing may in the future increase
the ability to better translate genetic improvements into the field
(medium agreement
,
limited evidence)
(Puchta, 2017; Yamamoto
et al., 2018; Friedrichs et al., 2019; Kawall, 2019; Zhang et al., 2019b).
Other breeding approaches assisted by genomics have been making
steady gains in introducing traits that adapt crops to climate
change (
high confidence
). DNA sequence information is used to
identify markers of desirable traits that can be enriched in breeding
programmes, as well as to quantify the genetic variability in species
(Gepts, 2014; Brozynska et al., 2016; Voss-Fels and Snowdon, 2016).
However, breeding for smallholder farmers and the stresses caused by
climate change are unlikely to be addressed by the private sector and
will require more public investment and adjusting to the local social-
ecological system (Glover, 2014; Heinemann et al., 2014; Acevedo
et al., 2020). Modern biotechnology has not demonstrated the scale
neutrality needed to serve smallholder-dominated agroecosystems,
due to a combination of the kinds of traits and restrictions that come
from the predominant intellectual property rights instruments used in
their commercialisation, as well as the focus on a small number of
major crop species (
medium confidence)
(Fischer, 2016; Montenegro
de Wit et al., 2020).
Globally, there is a notable lack of programmes aimed specifically at
breeding for climate resilience in fruits and vegetables, although there
have been calls to begin this process (Kole et al., 2015). Breeding for
climate resilience in vegetables has great potential given the range
of crop species available. Tolerance to abiotic stress is reasonably
advanced in pulses (Araújo et al., 2015; Varshney et al., 2018), but
examples of translation to commercial cultivars are still limited
(Varshney et al., 2018; Varshney et al., 2019). The infrastructure for
germplasm collection, maintenance, testing and breeding lags behind
that of major crops (partly because of the large number of species
involved) (Keatinge et al., 2016; Atlin et al., 2017).
Synthesis of literature on the implementation of on-farm adaptation options across different cropping systems
Vegetable
Legumes
Leafy crops
Soft fruit
Root crops
Tree fruits & nuts
Annual
(above ground)
Annual (below ground)
Perennial
Crop type
Life history strategy
All
= not assessed
na
Adaptation option’s implementation status
Untested
Tested
Plant
breeding/
bio-
technology
Climate
services
Shift
planting
area
Shift
planting
date
Shift
crop/
cultivar
Conservation
agriculture
Agro-
ecology/
agroforestry Agronomy
Water
manegement
On-farm
diversity
Combined
sum of
listed
options
na
na
na
na
na
na
na
na
Confidence level
High
Medium
Low
High
Medium
Low
Figure 5.10 | Synthesis of literature on the implementation of on-farm adaptation options across different cropping systems.
Adaptation options that have
been implemented by growers are considered ‘tested’, while those that have not are considered ‘untested’. Untested options are those that appear in studies as suggestions by
stakeholder or experts but were not implemented within the study. The assessment draws on >200 articles published since AR5. The confidence is based on the evidence given in
individual articles and on the number of articles. See SM5.2 for details.
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Table 5.5 |
PPB as cultivar improvement adaptation method.
Region
Crop(s) used for
breeding
Results
West Africa
Sorghum and pearl
millet
– Released sorghum and millet varieties which were selected for climate variability (e.g., drought), low soil fertility, pest and disease
resistance, gendered preferences for processing, and nutrition (Camacho-Henriquez et al., 2015; Weltzien et al., 2019).
– Farmers who adopted these varieties increased yield, income and food security, alongside increased technical knowledge of plant
breeding, and increased breeders’ understanding of local farmers’ varietal requirements (Trouche et al., 2016).
– Joint learning with scientists led to increased genetic gain both in terms of operational scale and focused breeding for diverse
farmer priorities (Weltzien et al., 2019).
South America (Andes)
Potato
– PPB with Indigenous Quechua and Aymara farmers resulted in potato varieties with traits from wild relatives, with yield stability,
higher yields under low input use and disease resistance under climate change impacts such as increased hail or frost events and
upward expansion of pests and diseases (Camacho-Henriquez et al., 2015; Scurrah et al., 2019).
Asia (southwest China)
Maize
– PPB done primarily with women farmers, led to 1500 landraces safeguarded, 12 farmer-preferred varieties released and 30 landraces
released, bred for improved yield (15–20% increases), drought resistance, taste, market potential and other priority traits (Song
et al., 2019).
– Studies suggest PPB improved farmer knowledge, income and access to resilient seeds, and strengthened institutions such as
women-led farmer cooperatives and Farmers’ Seed Network of China (Song et al., 2019).
Table 5.6 |
Agroecosystem diversification practices, climate change adaptation mechanisms, trade-offs, co-benefits and constraints to implementation.
Agroecosystem diversification practice and
mechanism for climate change adaptation
Benefits, trade-offs and constraints to implementation with examples
Crop diversification
– Diversifying revenue streams and food supply (portfolio
effect).
– Can impact multiple plant and soil biological and
physicochemical properties associated with building
SOM, improving soil structure and water conservation.
– Crop diversification reduces cereal crop sensitivity to
precipitation variability
, yield losses and crop insurance payouts
under
drought
(
high confidence
) (McDaniel et al., 2014; Williams et al., 2016; Iizumi and Wagai, 2019; Renwick et al., 2020;
Huang et al., 2021; Kane et al., 2021).
– For example, a study in Canada comparing diversified rotations and monoculture corn found significant positive yield
impacts, yield stability and increased SOC under both RCP4.5 and RCP8.5 by 2100 (Jarecki et al., 2018).
– Diverse agroecosystems with a range of native, neglected and introduced species, often maintained through Indigenous
knowledge and farmer seed systems, offer adaptation opportunities in some regions (
medium evidence
,
high agreement
)
(Bezner Kerr, 2014; Westengen and Brysting, 2014; Camacho-Henriquez et al., 2015; Ghosh-Jerath et al., 2015; Adhikari
et al., 2017; Li and Siddique, 2018; Scurrah et al., 2019).
– Diversified landscapes can also enhance CES, by supporting cultural heritage crops, recreational and aesthetic experiences
(
medium confidence
) (Novikova et al., 2017; Martínez-Paz et al., 2019; Alcon et al., 2020).
– Diversified cropping systems often require new knowledge, equipment access to inputs and viable markets for new
products (van Zonneveld et al., 2020). Barriers to diversification, or those which support agroecosystem simplification,
include environmental constraints such as elevation or soil type, along with institutional constraints such as low research
investment, limited policy support, subsidies that encourage monocrops, poor market access, market instability and limited
access to seeds (Kaushal and Muchomba, 2015; DeLonge et al., 2016; Burchfield and de la Poterie, 2018).
Legume diversification
can be effective for both
mitigation and adaptation, by reducing
use of nitrogen
derived from fossil fuels
, and meat consumption, and
providing ecosystem services through
nutrient cycling,
increasing soil biological activity and erosion control
(Snapp et al., 2019).
– Can increase food security and nutrition by increasing cereal productivity and stability in intercropped systems, diversify
diets and increase income in crop sales (
high agreement, medium evidence
) (Snapp et al., 2019; Steward et al., 2019;
Renwick et al., 2020), but legume production may be constrained by pest, disease, limited access to genetic material,
market access and food preferences (Anders et al., 2020).
Organic amendments, no/low tillage or crop residue
retention
may increase diversity in soil biological
organisms, which might be important in building resilience
to multiple stresses such as
drought and pest pressure
(Furze et al., 2017; Blundell et al., 2020; de Vries et al.,
2020; Stefan et al., 2021; Yang et al., 2021).
– Higher organic matter does not consistently improve soil hydraulic properties (Minasny and McBratney, 2018; Basche and
DeLonge, 2019).
– Can decrease
yield variability under dry conditions
and increase rainfed annual crop yield productivity (
high
agreement
) (Pittelkow et al., 2014; Williams et al., 2016; Williams et al., 2018; Degani et al., 2019; Steward et al., 2019;
Bowles et al., 2020; Marini et al., 2020; Sanford et al., 2021).
Livestock integration
. Inclusion of legumes and other
forage into crop rotation allows mixed crop and livestock
operations to
mitigate farm-level risk and ecosystem
buffering
.
– Benefits to productivity and stability of annual crop yields in some contexts (see Section 5.10.3,
high agreement
,
medium
evidence
) (Stark et al., 2018; Peterson et al., 2020; de Albuquerque Nunes et al., 2021).
Traditional and locally adapted
mixed cropping and
agroforestry practices
which include leguminous trees
can improve soil fertility and microclimate (Sida et al.,
2018; Amadu et al., 2020).
Benefits: resilience to extreme events such as hurricanes can be promoted by supporting ecosystem functions to mitigate
impacts and accelerate recovery (
high agreement
,
medium evidence
) (Altieri et al., 2015; Simelton et al., 2015; Sida et al.,
2018; Perfecto et al., 2019).
– Can increase food security, livelihoods and productivity, but local context and resource availability must be considered to
optimise species arrangement and benefits and can have considerable implementation barriers and costs (
high confidence
)
(see Sections 5.10.3, 5.14 and Cross-Chapter Box NATURAL in Chapter 2). (Altieri et al., 2015; Simelton et al., 2015; Sida
et al., 2018; Perfecto et al., 2019).
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Participatory plant breeding (PPB) facilitates interaction between
Indigenous and local knowledge systems and scientific research and
can be an effective adaptation strategy in generating varieties well
adapted to the socio-ecological context and climate hazards (
high
confidence
) (Table 5.5, Westengen and Brysting, 2014; Humphries
et al., 2015; Anderson et al., 2016; Migliorini et al., 2016; Leitão et al.,
2019; Ceccarelli and Grando, 2020; Singh et al., 2020).
5.4.4.4 Integrated approach to enhance agroecosystem
resilience
Diversifying agricultural systems is an adaptation strategy that can
strengthen resilience to climate change, with socioeconomic and
environmental co-benefits, but trade-offs and benefits vary by socio-
ecological context (
high confidence
) (Table 5.6, M’Kaibi et al., 2015;
Bellon et al., 2016; Jones, 2017b; Schulte et al., 2017; Jarecki et al.,
2018; Jones et al., 2018; Luna-Gonzalez and Sorensen, 2018; Sibhatu
and Qaim, 2018; Renard and Tilman, 2019; Rosa-Schleich et al., 2019;
Bozzola and Smale, 2020; Mulwa and Visser, 2020). Crop diversification
alongside livestock, fish and other species can be applied at various
scales in a range of systems, from rainfed or irrigated to urban and home
gardens in multiple spatial and temporal arrangements such as mixed
planting, intercrops, crop rotation, diversified management of field
margins, agroforestry (Section 5.10.1.3) and integrated crop livestock
systems (Section 5.10.1.1, Isbell et al., 2017; Kremen and Merenlender,
2018; Dainese et al., 2019; Rosa-Schleich et al., 2019; Hussain et al.,
2020; Renwick et al., 2020; Tamburini et al., 2020; Snapp et al., 2021;
see Section 5.14 and Cross-Chapter Box NATURAL in Chapter 2).
Diversification improves regulating and supporting ecosystem services
such as pest control, soil fertility and health, pollination, nutrient
cycling, water regulation and buffering of temperature extremes (
high
confidence
) (Barral et al., 2015; Prieto et al., 2015; Tiemann et al., 2015;
Schulte et al., 2017; Beillouin et al., 2019a; Dainese et al., 2019; Kuyah
et al., 2019; Tamburini et al., 2020), which can in turn mediate yield
stability and reduced risk of crop loss according to socio-ecological
contexts and time since adoption (
high confidence
) (Prieto et al., 2015;
Roesch-McNally et al., 2018; Sida et al., 2018; Williams et al., 2018;
Birthal and Hazrana, 2019; Degani et al., 2019; Amadu et al., 2020;
Bowles et al., 2020; Li et al., 2020; Sanford et al., 2021).
Agroecosystem diversification often has variable impacts depending
on crop combination, agro-ecological zone and soil types, and rigorous
assessments of adaptive gains with traditional and locally diversified
systems and potential trade-offs still need to be conducted across
socio-ecological contexts. The quantitative upstanding will assist in
enhancing multiple benefits of diversification tailored for each condition
(Table 5.6). Progress is also needed via breeding and/or agronomy
to adapt underutilised as well as major food crops to diversified
agroecosystems and optimise management of nutrients, pest and
disease pressure and other socio-ecological constraints (Araújo et al.,
2015; Foyer et al., 2016; Adams et al., 2018; Pang et al., 2018).
Managing for diversity and flexibility at multiple scales is central to
developing adaptive capacity. Policies to support diversification include
shifting subsidies towards diversified systems, public procurement for
diverse foods for schools and other public institutions, investment
in shorter value chains, lower insurance premiums and payments
for ecosystem services that include diversification (Sorensen et al.,
2015; Guerra et al., 2017; Nehring et al., 2017; Valencia et al., 2019).
Integrated landscape approaches involving multiple stakeholders
(Reed et al., 2016) including urban governments can support
diversification at a regional scale through public and private sector
investment in extension services, regional supply chains, agritourism
and other incentives for diversified landscapes (Milder et al., 2014;
Münke et al., 2015; Sorensen et al., 2015; Pérez-Marin et al., 2017;
Caron et al., 2018; 5.14.1.5).
5.5
Livestock-Based Systems
Livestock systems may be classified as industrial (monogastric,
ruminant), grassland-based in which crop-based agriculture is absent
or minimal (pastoralism, agro-pastoralism), mixed rainfed combining
mostly rainfed cropping with livestock, and mixed irrigated systems
with a significant proportion of irrigated cropping interspersed with
livestock. Livestock systems are located widely across all regions of the
world, and animal-sourced food provides humans with 39% of their
protein and 18% of their calorie intake (FAO, 2019 f). Some 400 million
people depend on livestock for a substantial part of their livelihood
(Robinson et al., 2011).
5.5.1
Observed Impacts
Climate change affects livestock productivity and production in many
ways (Porter et al., 2014; Rojas-Downing et al., 2017). Evidence is
accumulating that rising temperatures are increasing heat stress in
domestic species and affecting productivity (
high confidence
) (Das
et al., 2016b; Godde et al., 2021).
5.5.1.1 Pastoral systems
Many grassland-based livestock systems are vulnerable to climate
change and increases in climate variability (
high confidence
) (Dasgupta
et al., 2014; Sloat et al., 2018; Stanimirova et al., 2019). Decadal
vegetation changes from warming and drying trends have been
detected in North American grasslands, with implications for species
composition, rangeland quality and economic viability of grazing
livestock (Rondeau et al., 2018; Reeves et al., 2020). Feed quality
in South Asian grasslands has been negatively affected, reducing
food security (Rasul et al., 2019). Increased grassland degradation
has been observed in parts of Inner Mongolia (Nandintsetseg et al.,
2021). Changing seasonality, increasing frequency of drought and
rising temperatures are affecting pastoral systems globally (
high
confidence
). These and other drivers are reducing herd mobility,
decreasing productivity, increasing incidence of vector borne diseases
and parasites, and reducing access to water and feed (
high agreement
,
medium evidence
) (López-i-Gelats et al., 2016; Vidal-González and
Nahhass, 2018; de Leeuw et al., 2020).
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5.5.1.2 Livestock distribution and climate variability
There is
limited evidence
of observed distributional changes in
livestock species due to climate changes. Asian buffalo and yak breeds
in China over the past 50 years have shifted distribution partly because
of increases in heat stress (Wu, 2015; Wu, 2016). Nepalese cattle
numbers have declined, attributed to increases in the number of hot
days (Koirala and Shrestha, 2017).
Climate variability has been identified as the primary cause of
vegetation cover changes on the Tibetan Plateau since 2000 (Lehnert
et al., 2016). Increasing inter-annual variability is a driver of farm
extensification in Mediterranean dairy systems (Dono et al., 2016). In
Australian rangelands (Godde et al., 2019) and dairy systems (Harrison
et al., 2016; Harrison et al., 2017), increasing rainfall variability
contributes more to stocking rate and profitability variability than
changes in mean rainfall.
5.5.1.3 Diseases and disease vectors
Climate change is affecting the transmission of vector-borne diseases
(Hutter et al., 2018; Semenza and Suk, 2018) and parasites (Rinaldi
et al., 2015) in high latitudes (
high confidence
). Different processes link
climate change and infectious diseases in domesticated livestock. Some
show a positive association between temperature and range expansion
of arthropod vectors that spread the bluetongue virus. Others show a
contraction, such as tsetse flies that transmit trypanosome parasites
of several livestock species. Positive associations have been found
between temperature and the spread of pathogens such as anthrax,
and droughts and ENSO weather patterns and Rift Valley fever
outbreaks in East Africa (Bett et al., 2017). Observed range expansion
of economically important tick disease vectors in North America
(Sonenshine, 2018) and Africa (Nyangiwe et al., 2018) are presenting
new public health threats to humans and livestock.
5.5.2
Assessing Vulnerabilities
5.5.2.1 Rising temperature and heat stress
Most domestic livestock have comfort zones in the range 10–30°C,
depending on species and breed (Nardone et al., 2006). At higher
temperatures, animals eat 3–5% less per additional degree of
temperature, reducing their productivity and fertility. Heat stress
suppresses the immune and endocrine system, enhancing susceptibility
of the animal to disease (Das et al., 2016b). Recent stagnation in
dairy production in West Africa and China may be associated with
increased periods of high daily temperatures (
low confidence
)
(Rahimi et al., 2020; Ranjitkar et al., 2020). Increases in the productive
capacity of domestic animals can compromise thermal acclimation
and plasticity, creating further loss. Escalating demand for livestock
products in low-to-middle-income countries (LMICs) may necessitate
considerable adaptation in the face of new thermal environments
(
medium confidence
) (Collier and Gebremedhin, 2015; Theusme et al.,
2021). Heat effects on productivity have been summarised for pigs
(da Fonseca de Oliveira et al., 2019), sheep and goats (Sejian et al.,
2018), and cattle (Herbut et al., 2019). The direct effects of higher
temperatures on the smaller ruminants (sheep and goats) are relatively
muted, compared with large ruminants; goats are better able to cope
with multiple stressors than sheep (Sejian et al., 2018). Under SSP5-8.5
to mid-century, land suitability for livestock production will decrease
because of increased heat stress prevalence in mid and lower latitudes
(
high confidence
) (Thornton et al., 2021).
5.5.2.2 Livestock water needs
Livestock production may account for 30% of all water (blue, green
and grey) used in agriculture (Mekonnen and Hoekstra, 2010) and can
negatively affect water quality. Cropland feed production accounts
for 38% of crop water consumption (Weindl et al., 2017). High-input
livestock systems may consume more water than grazing or mixed
systems, though water used per kg beef produced, for example, depends
on country, context and system (Noya et al., 2019). In systems where
feed production is rainfed, livestock and crop water productivity may
be comparable (Haileslassie et al., 2009). Direct water consumption by
livestock is <1–2% of global water consumption (Hejazi et al., 2014).
Rising temperatures increase animal water needs, potentially affecting
access of herders and livestock to drinking water sources (Flörke et al.,
2018).
5.5.2.3 Rising temperatures and livestock disease
Climate change will have effects on future distribution, incidence
and severity of climate-sensitive infectious diseases of livestock (
high
confidence
) (Bett et al., 2017). In an assessment of climate sensitivity
of European human and domestic animal infectious pathogens, 63%
were sensitive to rainfall and temperature, and zoonotic pathogens
were more climate-sensitive than human- or animal-only pathogens
(McIntyre et al., 2017). Over the last 75 years, >220 emerging zoonotic
diseases, some associated with domesticated livestock, have been
identified, several of which may be affected by climate change,
particularly vector-borne diseases (Vaillancourt and Ogden, 2016;
see Cross-Chapter Box ILLNESS in Chapter 2). Walsh et al. (2018)
identified both temperature and rainfall as influential factors in
predicting increasing anthrax outbreaks in northern latitudes. Growing
infectious disease burdens in domesticated animals may have wide-
ranging impacts on the vulnerability of rural livestock producers in the
future, particularly related to human health and projected increases
in zoonoses (
high confidence
) (Bett et al., 2017; Heffernan, 2018;
Rushton et al., 2018; Meade et al., 2019).
5.5.2.4 Livestock and socioeconomic vulnerability to climate
change
There is
limited evidence
about the role of livestock in addressing
socioeconomic vulnerability. Although agriculture in parts of North
America has become more sensitive to climate over the last 50 years,
livestock have helped to moderate this effect, being less sensitive to
increasing temperatures than some specialised crop systems (Ortiz-
Bobea et al., 2018). Increasing frequency and severity of droughts
will affect the future economic viability of grassland-based livestock
production in the North American Great Plains (Briske et al., 2021).
Purchasing more forage and selling more livestock have reduced
household vulnerability in semi-arid parts of China over the last
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35 years (Bai et al., 2019). A greater focus on sheep production
away from cropping has increased the resilience of farming systems
in Western Australia in low-rainfall years, although with mixed
environmental effects (Ghahramani and Bowran, 2018). More insights
are needed as to where and how livestock can affect the vulnerability
of farmers and pastoralists.
5.5.2.5 Effects of climate on the health and vulnerability of
livestock keepers
Vulnerability to the health impacts of climate change will be shaped
by existing burdens of ill health and is expected to be highest in poor
and socioeconomically marginalised populations (
high agreement
,
limited evidence
) (Labbé et al., 2016). In addition to projected changes
in infectious disease burdens, labour capacity in a warming climate is
anticipated to decrease further, beyond the >5% drop estimated since
2000 (Watts et al., 2018). Loss of labour capacity may greatly increase
the vulnerability of subsistence livestock keepers (
high agreement
,
limited evidence
).
5.5.2.6 Gender and other social inequities
Vulnerability to climate change depends on demography and social
roles (Mbow et al., 2019). Gender inequities can act as a risk multiplier,
with women being more vulnerable than men to climate-change-
induced food insecurity and related risks (
high confidence
) (Cross-
Chapter Box GENDER in Chapter 18). Women and men often have
differential and unequal control over different productive assets and
the benefits they provide, such as income from livestock (Ngigi et al.,
2017; Musinguzi et al., 2018). Indigenous livestock keepers can be
more vulnerable to climate change, partly due to ongoing processes of
land fragmentation (Hobbs et al., 2008), historical land dispossession,
discrimination and colonialisation, creating greater levels of poverty
and marginalisation (Stephen, 2018). Adaptation actions may also be
affected by gender and other social inequities (Balehey et al., 2018;
Dressler et al., 2019). Men and women heads of household may access
institutional support for adaptation in different ways (Assan et al.,
2018). Further research is warranted to evaluate alternative gendered
and equity-based approaches that can address differences in adaptive
capacity within communities.
5.5.3
Projected Impacts
There is
limited evidence
on future impact of climate change on
livestock production, particularly in LMICs (Rivera-Ferre et al., 2016).
5.5.3.1 Impacts on rangelands, feeds and forages
Uncertainties persist regarding estimates of net primary productivity
(NPP) in grazing lands (Fetzel et al., 2017; Chen et al., 2018b), so
estimation of climate change impacts on grasslands is challenging.
Mean global annual NPP is projected to decline 10 gC m
−2
yr
−1
in
2050 under RCP8.5, although herbaceous NPP is projected to increase
slightly (Boone et al., 2018; see Figure 5.11). Similar estimates were
made by Havlik et al. (2014): large increases in projected NPP in
higher northern latitudes (21% increase in the USA and Canada)
and large declines in western Africa (−46%) and Australia (−17%).
The cumulative effects of impacts on forage productivity globally are
projected to result in 7–10% declines in livestock numbers by 2050 for
warming of ~2°C, representing a loss of livestock assets ranging from
USD 10 to 13 billion (Boone et al., 2018). Changes to African grassland
productivity will have substantial, negative impacts on the livelihoods
of >180 million people.
Increases in above-ground NPP, and woody cover at the expense
of grassland, are projected in some of the tropical and subtropical
drylands (Doherty et al., 2010; Ravi et al., 2010; Saki et al., 2018), in
Mediterranean wood pastures (Rolo and Moreno, 2019) and in the
northern Great Plains of North America (Klemm et al., 2020). Godde
et al. (2021) projected that woody encroachment would occur on 51%
of global rangeland area by 2050 under RCP8.5. The future makeup of
grasslands under climate change is uncertain, given the variation in
responses of the component species, though this variation may provide
a climate buffer (Jones, 2019) (
low confidence
). C4 grass species are
regarded as less responsive to elevated carbon dioxide than C3 species,
though this is not always the case (Reich et al., 2018).
There are other interactions between climate change and grazing
effects on grasslands. Li (2018a) reported strong negative responses
of NPP and species richness to 4°C warming, a 50% precipitation
decrease, and high grazing intensity. Changes in grassland composition
will inevitably change their suitability for different grazing animal
species, with switches from herbaceous grazers such as cattle to goats
and camels to take advantage of increases in shrubland (Kagunyu
and Wanjohi, 2014). Rangeland feed quality may also be reduced via
invasive species of lower quality than native species (Blumenthal et al.,
2016).
Warming and water deficits impair the quality and digestibility of a
C4 tropical forage grass,
Panicum maximum
,
because of increases in
leaf lignin (Habermann et al., 2019). A metanalysis by Dellar (2018)
of climate change impacts on European pasture yield and quality
found an increase in above-ground dry weight under increased
CO
2
concentrations for forbs, legumes, graminoids and shrubs
with reductions in N concentrations in all plant functional groups.
Temperature increases will increase yields in alpine and northern areas
(+82.6%) but reduce N concentrations for shrubs (−13.6%) and forbs
(−18.5%).
Increased temperatures and CO
2
concentrations may increase
herbaceous growth and favour legumes over grasses in mixed pastures
(He et al., 2019). These effects may be modified by changes in rainfall
patterns, plant competition, perennial growth habits and plant–animal
interactions. The cumulative effect of these factors is uncertain. Large,
persistent declines in forage quality are projected, irrespective of
warming, under elevated CO
2
conditions (600 ppm and +1.5°C day/3°C
night temperature increases) in North American grasslands (Augustine
et al., 2018). Rising CO
2
concentrations may result in losses of iron, zinc
and protein in plants by up to 8% by 2050 (Smith and Myers, 2018).
Little information is available on possible impacts on carbon-based
micronutrients, such as vitamins. About 57% of grasses globally are C3
plants and thus susceptible to CO
2
effects on their nutritional quality
(Osborne et al., 2014). These impacts will result in greater nutritional
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stress in grazing animals as well as reduced meat and milk production
(quality and quantity) (
high confidence
,
medium evidence
).
5.5.3.2 Impacts of increased temperature on livestock
Recent research confirms the seriousness of the heat stress issue
(
medium evidence
,
high agreement
). Considerable increases are
projected during this century in the number of ‘extreme stress’ days per
year for cattle, chicken, goat, pig and sheep populations with SSP5-8.5
but many fewer with SSP1-2.6 (Thornton et al., 2021: Figure 5.12; see
Cross-Chapter Box MOVING PLATE in this chapter). Resulting impacts
on livestock production and productivity may be large, particularly for
cattle throughout the tropics and subtropics and for goats in parts
of Latin America and much of Africa and Asia. Pigs are projected to
be particularly affected in the mid-latitudes of Europe, East Asia and
Projected plant responses in the rangelands to enhanced CO
2
fertilization
Changes in 2050 under RCP8.5 relative to 1971–2000
(k) Central
Americ
a
(f) Central
Asia
(a) Eastern
Africa
(g) Eastern
Asia
(m) Eastern Europe
(b) Middle
Africa
(n) North americ
a
(c) Northern
Africa
(l) South
Americ
a
(d) Southern
Africa
(h) Southern
Asia
(e)
We
stern
Africa
(i)
We
stern
Asia
(j)
Australia & New Zealand
(k) Central
Americ
a
(f) Central
Asia
(a) Eastern
Africa
(g) Eastern
Asia
(m) Eastern Europe
(b) Middle
Africa
(n) North americ
a
(c) Northern
Africa
(l) South
Americ
a
(d) Southern
Africa
(h) Southern
Asia
(e)
We
stern
Africa
(i)
We
stern
Asia
(j)
Australia & New Zealand
(k) Central
Americ
a
(f) Central
Asia
(a) Eastern
Africa
(g) Eastern
Asia
(m) Eastern Europe
(b) Middle
Africa
(n) North americ
a
(c) Northern
Africa
(l) South
Americ
a
(d) Southern
Africa
(h) Southern
Asia
(e)
We
stern
Africa
(i)
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stern
Asia
(j)
Australia & New Zealand
-40
-20
0
20
40
60
-40
-20
0
20
40
60
-40
-20
0
20
40
60
-60
-60
-60
Annual
net primary
productivity
% change
% change
% change
Mean change
across regions
Above ground
live biomass
Bare ground
Shrub cover
Below ground
live biomass
Tree cover
Herbaceous
net primary
productivity
Soil carbon
Herb cover
*
*
Truncated bar reaches 82%
a
b
c
d
e
f
g
h
i
j
k
l
m
n
Figure 5.11 | Regional percent changes in land cover and soil carbon from ensemble simulation results in 2050 under emissions scenario RCP8.5 compared
with 1971–2000.
Plant responses were enhanced by CO
2
fertilisation. The larger chart (lower left) shows mean changes for all rangelands, and all charts are scaled to −60% to
+60% change. Shown are annual net primary productivity (ANPP), herbaceous net primary productivity (HNPP), bare ground, herbaceous (herb), shrub, and tree cover, SOC (soil
carbon), above-ground live biomass and below-ground live biomass. Regions as defined by the United Nations Statistics Division. The bar for above-ground live biomass in Western
Asia (*) is truncated and is 82% (Boone et al., 2018).
North America. Lallo et al. (2018) estimated that global warming of
1.5°C and 2°C may exceed limits for normal thermo-regulation of
livestock animals and result in persistent heat stress for animals in the
Caribbean. Breed differences in heat stress resistance in dairy animals
are now being quantified (Gantner et al., 2017), as are effects on sow
reproductive performance in temperate climates (Wegner et al., 2016).
Estimates of losses in milk production due to heat stress in parts of
the USA, UK and West Africa to the end of the century range from
1% to 17% (Hristov et al., 2018; Fodor et al., 2018; Wreford and
Topp, 2020; Rahimi et al., 2020). Much larger losses in dairy and beef
production due to heat stress are projected for many parts of the
tropics and subtropics: these could amount to USD 9 billion per year
for dairy and USD 31 billion per for beef to end-century under SSP5-
8.5, approximately 5% and 14% of the global value of production of
these commodities in constant 2005 dollars.
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In many LMICs, poultry contribute significantly to rural livelihoods,
including via modest improvements in nutritional outcomes of house-
hold children (de Bruyn et al., 2018). Rural poultry are generally as-
sumed to be hardy and well adapted to stressful environments, but
little information exists regarding their performance under warmer
climates or interactions with other production challenges (Nyoni et al.,
2019).
5.5.3.3 Impacts on livestock diseases
The impacts of climate change on livestock diseases remain highly un-
certain (
medium evidence
,
high agreement
). Bett et al. (2017) showed
positive associations between rising temperature and expansion of the
geographical ranges of arthropod vectors such as
Culicoides imicola
,
which transmits the bluetongue virus. A 1-in-20-year bluetongue out-
break at present-day temperatures is projected to increase in frequen-
cy to 1-in-5 to 1-in-7 years by the 2050s, under RCP4.5 and RCP8.5,
although animal movement restrictions can prevent devastating out-
breaks (Jones et al., 2019).
The prevalence and occurrence of some livestock diseases are positively
associated with extreme weather events (
high confidence
). There are
high risks of future Rift Valley fever (RVF) outbreaks under both RCP4.5
and RCP8.5 this century in East Africa and beyond (Taylor et al., 2016;
Mweya et al., 2017).
Early 21st Century
Cattle
Goats
Chicken
Days per year when livestock is under extreme stress
Sheep
Pigs
1
366 days
0
(No days)
No
livestock
SSP5-8.5, End 21st Century
SSP1-2.6, End 21st Century
Temperature and humidity driven “extreme stress” for livestock
Figure 5.12 | Change in the number of days per year above ‘extreme stress’ values from the early 21st century (1991–2010) to end of century (2081–2100),
estimated under SSP1-2.6 and SSP5-8.5 using the Temperature Humidity Index (THI).
Mapped for species current global distribution (Gilbert et al., 2018) (grey areas,
no change). (Thornton et al., 2021), Also see Annex I: Global to Regional Atlas.
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Few studies explicitly consider the biotic and abiotic factors that
interact additively, multiplicatively or antagonistically to influence
host–pathogen dynamics (Cable et al., 2017). Integrative concepts that
aim to improve the health of people, animals and the environment such
as One Health may offer a framework for enhancing understanding
of these complex interactions (Zinsstag et al., 2018). Much remains
unknown concerning disease transmission dynamics under a warming
climate (Heffernan, 2018), highlighting the need for effective
monitoring of livestock disease (Brito et al., 2017; Hristov et al., 2018).
5.5.3.4 Impacts on livestock and water resources
Water resources for livestock may decrease in places because of
increased runoff and reduced groundwater resources, as well as
decreased groundwater availability in some environments (AR5).
Increased temperatures will cause changes in river flow and the amount
of water stored in basins, potentially leading to increased water stress
in dry areas such as parts of the Volta River Basin (Mul et al., 2015).
Toure (2017) estimated decreases in groundwater recharge rates of
49% and of stored groundwater by 24% to the 2030s in the Klela
Basin in Mali under both RCP4.5 and RCP8.5, with potentially serious
consequences for water availability for livestock and irrigation.
Water intake by livestock is related to species, breed, animal size, age,
diet, animal activity, temperature and physiological status of animals
(Henry et al., 2018). Direct water use by cattle may increase by 13% for
a temperature increase of 2.7°C in a subtropical region (Harle et al.,
2007). Changes in water availability may arise because of decreased
supply or increased competition from other sectors. Availability
changes may be accompanied by shifts in water quality, such as
increased levels of microorganisms and algae, that can negatively
affect livestock health (Naqvi et al., 2015). In arid lands, projected
decreases in water availability will severely compromise reproductive
performance and productivity in sheep (Naqvi et al., 2017). In higher-
input livestock systems, water costs may increase substantially owing
to increased competition for water (Rivera-Ferre et al., 2016).
5.5.3.5 Livestock and climate variability
Information on future climate variability changes on livestock system
productivity does not exist yet. Increases in climate variability may
increase food insecurity in the future, mediated through increased
crop and livestock production variability (Thornton and Herrero, 2014)
in LMICs. Rainfall variability increases in pastoral lands have been
linked to declining cattle numbers (Megersa et al., 2014). Changes in
future climate variability may have large negative impacts on livestock
system outcomes (Sloat et al., 2018; Stanimirova et al., 2019); these
effects can be larger than those associated with gradual climate
change (
limited evidence
,
medium agreement
) (Godde et al., 2019).
In grasslands, Chang et al. (2017) (Europe) and Godde et al. (2020)
(globally) projected increases in biomass inter-annual variability,
the worst effects occurring in rangeland communities that are
already vulnerable. Ways in which climate variability impacts have
been addressed in the past, such as via herd mobility, may become
increasingly unviable in the future (Hobbs et al., 2008).
5.5.3.6 Societal impacts within the production system
Livestock play important social (Kitalyi et al., 2005) and cultural
(Gandini and Villa, 2003) roles in many societies. Climate change will
negatively affect the provisioning of social benefits in many of the
world’s grasslands (
medium confidence
). Examples include moving to
semi-private land ownership models, driven in part by climate change,
that are changing social networks and limiting socio-ecological
resilience in pastoral systems in East Africa (Kibet et al., 2016; Bruyere
et al., 2018) and Asia (Cao et al., 2018a); altering traditional food,
resource and medicine sharing mechanisms in West Africa (Boafo
et al., 2016); and the limited ability of current livestock systems to
satisfy societies’ demand for CES in Northwest Europe (Bengtsson
et al., 2019). The societal impacts of climate change on livestock
systems may interact with drivers of change and increase herders’
vulnerability via processes of sedentarisation and land fragmentation,
both of which may result in decreased animal access to rangelands
(Adhikari et al., 2015; Cross-Chapter Box MOVING PLATE this chapter).
Stronger linkages are needed between ecosystem service and food
security research and policy to address these challenges (Gentle and
Thwaites, 2016; Bengtsson et al., 2019).
5.5.4
Adaptation in Livestock-Based Systems
Livestock adaptation options are increasingly being studied with
methods such as agent-based household models (Hailegiorgis et al.,
2018), household models that disaggregate climate scenarios as
well as differentiate farms of varying types and farmer attributes
(Descheemaeker et al., 2018), new meso-scale grassland models (Boone
et al., 2018) and modelling approaches that capture decision making at
the farm level for sample populations (Henderson et al., 2018).
Many grassland-based livestock systems have been highly resilient
to past climate risk, providing a sound starting point for current
and future climate change adaptation (Hobbs et al., 2008). These
adaptations include more effective matching of stocking rates with
pasture or other feed production; adjusting herd and watering point
management to altered seasonal and spatial patterns of forage
production; managing diet quality, which also helps reduce enteric
fermentation in ruminants and thus GHG emissions (using diet
supplements, legumes, choice of introduced pasture species and
pasture fertility management); more effective use of silage, rotational
grazing or other forms of pasture spelling; fire management to control
woody thickening; using better-adapted livestock breeds and species;
restoration of degraded pastureland; migratory pastoralist activities;
and a wide range of biosecurity activities to monitor and manage the
spread of pests, weeds and diseases (Herrero et al., 2015; Godde et al.,
2020). Combining adaptations can result in increases in benefits in
terms of production and livelihoods over and above those attainable
from single adaptations (
high confidence
) (Bonaudo et al., 2014;
Thornton and Herrero, 2015; ul Haq et al., 2021).
The adaptations that livestock keepers have been undertaking in Asia
(Hussain et al., 2016; Li et al., 2017) and Africa (Belay et al., 2017;
Ouédraogo et al., 2017) are largely driven by their perceptions of climate
change. Keeping two or more species of livestock simultaneously on
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the same farm can confer economic and sustainability benefits to
European farmers (Martin et al., 2020). Some livestock producers are
changing and diversifying management practices, improving access to
water sources, increasing uptake of off-farm activities, trading short-
term profits for longer-term resilience benefits and migrating out of
the area (Hussain et al., 2016; Berhe et al., 2017; Merrey et al., 2018;
Thornton et al., 2018; Espeland et al., 2020). Others are adopting more
climate-resilient livestock species such as camels (Watson et al., 2016a),
using climate forecasts at differing time scales, and benefitting from
innovative livestock insurance schemes, though challenges remain in
their use at scale (Dayamba et al., 2018; Hansen et al., 2019a; Johnson
et al., 2019).
In West Africa, cattle and small ruminant producers and traders are
changing strategies in response to emerging market opportunities as
well as to multiple challenges including climate change (Gautier et al.,
2016; Ouédraogo et al., 2017). Niles (2017) found that reduced food
insecurity in 12 countries was associated with livestock ownership,
providing cash for food purchases. Livestock ownership or switching
to smaller, local breeds does not automatically translate into positive
nutrition outcomes for women and children, although it may if
communities see such animals as suitable for husbandry by women
(Chanamuto and Hall, 2015); the relationship is complex (Nyantakyi-
Frimpong and Bezner-Kerr, 2015; Dumas et al., 2018).
Options for adapting domestic livestock systems to increased exposure
to heat stress (Table 5.7) include breeding and crossbreeding strategies,
species switching, low-cost shading alternatives and ventilation and
building-design options (Chang-Fung-Martel et al., 2017; Godde et al.,
2021).
In utero
exposure to heat stress may increase adaptive capacity
in later life, though the underlying mechanisms are incompletely
understood (Skibiel et al., 2018). For confined livestock systems in
temperate regions, the economic consequences of adapting to heat
stress are still being quantified.
New research is investigating the prospects for accelerating traditional
and novel breeding processes for animal traits that may be effective in
improving livestock adaptation as well as production (Stranden et al.,
2019; Barbato et al., 2020). Even if the technical challenges of using
new tools such as CRISPR-Cas9 for genome editing in livestock are
overcome, the granting of societal approval to operate in this research
space may be elusive (Herrero et al., 2020; Menchaca et al., 2020).
5.5.4.1 Contributions of Indigenous knowledge and local
knowledge
Indigenous knowledge has a role to play in helping livestock
keepers adapt (
medium confidence
), though the transferability of
this knowledge is often unclear. Pastoralists’ local knowledge of
climate and ecological change can complement scientific research
(Klein et al., 2014), and local knowledge can be mobilised to inform
adaptation decision making (Klenk et al., 2017). While Indigenous
weather forecasting systems among pastoralists in Ethiopia (Balehegn
et al., 2019; Iticha and Husen, 2019) and Uganda (Nkuba et al., 2020)
are effective, synergies can be gained by combining traditional
and modern knowledge to help pastoralists adapt. Sophisticated
Table 5.7 |
Selected adaptations to heat stress in livestock systems.
Adaptation
Example
Reference
Breeding for heat stress
tolerance
Sheep and cattle farming systems in southern Australia under IPCC Special Report on Emissions Scenarios (SRES) A2.
Projected not to improve livestock productivity by 2070, even in drier locations.
Moore and Ghahramani (2014)
‘Slick hair’ breeding
In the Caribbean, introduction of a ‘slick hair’ gene into Holstein cows by crossbreeding with Senepols to increase
thermo-tolerance and productivity. An integrated approach to heat stress adaptation will still be needed, including
shading strategies, for example.
(Ortiz-Colón et al. (2018)
Crossbreeding
Crossbreeding with Indigenous sheep breeds as an adaptation option in Mongolia produced some benefits in
productivity and improved adaptation to winter cold. Best combined with other improved management interventions. In
general, effectiveness of crossbreeding as an adaptation strategy will be dependent on context.
Wilkes et al. (2017)
Species switching
Switching from large ruminants to more heat-resilient goats for dairy production in Mediterranean systems to adapt to
increasing heat stress.
Switching from cattle to more heat- and drought-resilient camels in pastoral systems of southern Ethiopia as an
adaptation to increasing drought.
Silanikove and Koluman (2015)
Wako et al. (2017)
Shading, fanning, bathing
Low-capital relief strategies (shading with trees or different types of shed; bathing animals several times each day;
installing electric fans in sheds) are effective at reducing heat stress impacts on household income in smallholder dairy
systems in India.
Different tree arrangements in silvopastoral systems in Brazil were effective in reducing thermal loads by up to 22% for
animals compared with full-sun pasture.
York et al. (2017)
Pezzopane et al. (2019)
Ventilation and cooling
systems
A wide range of different ventilation systems, cooling systems and building designs for confined and seasonally confined
intensive livestock systems (pigs, poultry, beef, dairy) in temperate regions. Economic consequences and profitability of
different options under different RCPs are still being assessed.
Vitt et al. (2017)
Derner et al. (2018),
Hempel and Menz (2019),
Mikovits et al. (2019),
Schauberger et al. (2019b)
In utero
exposure to heat
stress
Potential as an adaption option is uncertain, as there are different effects of
in utero
heat stress exposure and the
mechanisms are not completely understood:
– Cows may be better adapted to heat stress conditions at maturity via improved regulation of core body temperature
– Cow milk yield at first lactation was reduced
– Nutrient partitioning and carcass composition were altered in pigs
Ahmed et al. (2017)
Monteiro et al. (2016),
Boddicker et al. (2014)
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knowledge of feed resources among agro-pastoralists in West Africa
is being used to increase system resilience (Naah and Braun, 2019).
Understanding local knowledge for adaptation can present research
challenges, for which new multi-disciplinary research methods may be
needed (Reyes-Garcia et al., 2016; Roncoli et al., 2016). In particular,
the complexities of knowledge, practice, power, local governance and
politics need to be addressed (Hopping et al., 2016; Scoville-Simonds
et al., 2020).
5.6
Forestry Systems
Forests play a vital role in the ecology of the planet, including
climate regulation, and provide a range of important ecosystem
services within their local landscape. Moreover, they are essential
to the well-being of millions of people around the world. Forests are
sources of food contributing about 0.6% of global food consumption
and provide important products, such as timber and non-timber
forest products (NTFPs) (FAO, 2014). Indigenous Peoples and local
communities are estimated to manage at least 17% of total carbon
(or 293 × 10
9
Mg) stored in forest in 64 assessed countries (RRI,
2018a). While small in number, numerous local communities around
the world are highly or entirely dependent on forests for their food
supply (Karttunen et al., 2017). An estimated 9% of the world’s
rural population is lifted above the extreme poverty line because
of income from forest resources (World Bank, 2016). Additionally,
forest income plays a particularly important role in diversifying the
income sources of poor households, reducing their vulnerability to
loss from one source of income. This section covers an assessment
of the impacts of climate change on forestry production systems and
the adaptation options available. Non-timber forest products will be
covered in the next section.
5.6.1
Observed Impacts
The IPCC AR5 stated that there is high confidence that numerous
plants and animal species have already migrated, changed their
abundance, and shifted their seasonal activities as a result of climate
change (Settele et al., 2014). The report highlighted the widespread
deaths of trees in many forested areas of the world. Forest die back
could significantly affect wood production among other impacts.
The SRCCL (Barbosa et al., 2019) concluded that climate change will
have positive and negative effects on forests, with varying regional
and temporal patterns. For example, the SRCCL noted the increasing
productivity in high-latitude forests such as those in Siberia. In contrast,
negative impacts are already being observed in other regions such as
increasing tree mortality due to wildfires.
In the past years, tree mortality continued to increase in many parts
of the world. Large pulses of tree mortality were consistently linked
to warmer and drier than average conditions for forests throughout
the temperate and boreal biomes (
high confidence
) (Sommerfeld
et al., 2018; Seidl et al., 2020). Long-term monitoring of tropical forests
indicates that climate change has begun to increase tree mortality and
alter regeneration (Hubau et al., 2020; Sullivan et al., 2020). Climate-
related die back has also been observed due to novel interactions
between the life cycles of trees and pest species (Kurz et al., 2008;
Lesk et al., 2017; Sambaraju et al., 2019). A recent example of the
impacts of climatic extremes is the European drought of 2018 (Buras
et al., 2020), which led to a significant browning of the vegetation and
resulted in widespread tree mortality (
high confidence
) (Brun et al.,
2020; Schuldt et al., 2020). This brought markets for conifer timber
close to collapse in parts of Europe, posing considerable challenges
for timber-based forestry and leading to cascading impacts on society
(Hlásny et al., 2021). Overall, there is
robust evidence
and
medium
agreement
that provisioning services of boreal and temperate forests
are affected negatively by forest disturbances, while for cultural
Box 5.5: Alternative Sources of Protein for Food and Feed
Alternative protein sources for human food and livestock feed are receiving considerable attention. Laboratory or ‘clean meat’ is one
potential contributor to the human demand for protein in the future (SRCLL). Such technology may be highly disruptive to existing value
chains but could lead to significant reduction in land use for pastures and crop-based animal feeds (Burton, 2019; Rosenzweig et al.,
2020). The impacts on GHG emissions depend on the meat being substituted and the trade-off between industrial energy consumption
and agricultural land requirements (Mattick et al., 2015; Alexander et al., 2017; Rubio et al., 2020b; Santo et al., 2020). Livestock feeds
can make use of other protein sources: insects are generally rich in protein and can be a significant source of vitamins and minerals. Black
soldier fly, yellow mealworm and the common housefly have been identified for potential use in feed products in the EU, for example
(Henchion et al., 2017). Replacing land-based crops in livestock diets with some proportion of insect-derived protein may reduce the
GHG emissions associated with livestock production, though these and other potential effects have not yet been quantified (Parodi
et al., 2018; Section 5.13.2). Other sources are high-protein woody plants such as paper mulberry (Du et al., 2021) and algae, including
seaweed. While microalgae and cyanobacteria are mainly sold as a dietary supplement for human consumption, they are also used as a
feed additive for livestock and aquaculture, being nutritionally comparable to vegetable proteins. The potential for cultivated seaweed as
a feed supplement may be even greater: some red and green seaweeds are rich in highly digestible protein.
Asparagopsis taxiformis
, for
example, also decreases methane production in both cattle and sheep when used as a feed supplement (Machado et al., 2016; Li et al.,
2018b). Novel protein sources may have considerable potential for sustainably delivering protein for food and feed alike, though their
nutritional, environmental, technological and socioeconomic impacts at scale need to be researched and evaluated further.
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services only
limited evidence
with
medium agreement
exists (Thom
and Seidl, 2016).
Increasingly, climate impacts on the recovery of forests after disturbance
are observed: using data from the past 20 years and 33 wildfires, it
has been shown that post-fire regeneration of
Pinus ponderosa
and
Pseudotsuga menziesii
in the western USA has declined because of
climate change and increased severity of fires (Davis et al., 2019).
However, the observed patterns of post-disturbance recovery vary with
region, with reduced tree regeneration reported for the western USA
(Stevens-Rumann and Morgan, 2019; Turner et al., 2019) but robust
recovery observed in Canada (White et al., 2017) and Central Europe
(
medium confidence
) (Senf et al., 2019).
Also, the distribution and traits of trees are increasingly influenced by
climate change, with impacts for local ecosystem service supply. In the
USA, a study of 86 tree species/groups over the past three decades
showed that more tree species have shifted westward (73%) than
poleward (62%) in their abundance (Fei et al., 2017). This was due more
to changes in moisture availability than to changes in temperature.
As climate has warmed, trees are growing faster with longer growing
seasons. However, a study of forests in Central Europe revealed that
wood density has decreased since the 1870s (Pretzsch et al., 2018).
This means that increasing tree growth might not directly translate to
increased total biomass and carbon sequestration.
5.6.2
Projected Impacts
AR5 stated that other stressors such as human-driven land use change
and pollution will continue to be the main causes of forest cover change
in the next three decades (Settele et al., 2014). In the second half of
this century, it was projected that climate change will be a strong
stressor of change in forest ecosystems. Many forest species may not
be able to move fast enough to adjust to new climate conditions. In
some cases, a warmer climate could lead to extinction of species.
The SR15 concluded that limiting warming to 1.5°C will be more
favourable to terrestrial ecosystems, including forests, relative to a 2°C
warming (Hoegh-Guldberg et al., 2018). In general, a 2°C warming could
lead to two times more area of biome shifts compared with a 1.5°C
warming. As a result, keeping a cooler average global temperature
will lead to lower extinction risks. The special report supports the AR5
conclusion that a warmer planet will impact wide swaths of forests
adversely. For example, higher temperatures will promote fire, drought
and insect disturbances. Consistent with AR5, SRCCL projected that
tree mortality will increase with climate change (Barbosa et al., 2019).
In addition, forests will be more exposed to extreme events such as
extreme heat, droughts and storms. The incidence of forest fires will
likewise increase.
Additional evidence since the above reports were published supports
their overall conclusions. For example, at the global scale, modelling the
vulnerability of 387 forest ecoregions under future climate change (to
2080 using the average of five Global Circulation Models (GCMs) and
RCP4.5 and 8.5) across different biomes, biogeographical realms and
conservation statuses showed that 8.8% of global forest ecoregions
are highly vulnerable in a low-greenhouse-gas-concentration scenario,
and 32.6% of the global forest ecoregions are highly vulnerable in
a high-greenhouse-gas-concentration scenario (Wang et al., 2019a).
Furthermore, a recent synthesis of the literature suggests that climate
change will result in younger and shorter forests globally (McDowell
et al., 2020). In Asia, a systematic review of climate change impacts
on tropical forests revealed that future climate may lead to changes
in species distribution and forest structure and composition as well as
phenology (Deb et al., 2018).
Overall, studies indicate both negative and positive climate change
impacts on forest production systems. Some forests in the USA
could benefit slightly from CO
2
fertilisation (using IGSM-CAM and
MIROC3.2 till 2100) resulting in increased productivity especially for
hardwoods (Beach et al., 2015). A study across Europe showed that
both productivity gains (mostly in Northern and Central Europe, up to
+33%) and losses (predominately in Southern Europe, up to −37%)
are possible until the end of the 21st century (Reyer et al., 2017). The
study further indicated that disturbances would reduce gains and
exacerbate losses of productivity throughout Europe under climate
change (Reyer et al., 2017). For Central and Eastern Canada, decreasing
biomass production is projected as a result of increasing disturbance
from wildfire and drought (Brecka et al., 2020). Climate-induced
disturbances could also reduce the temporal stability of ecosystem
service supply (Albrich et al., 2018), increasing the volatility of timber
markets (
medium confidence
). More broadly, climate change could
lead to abrupt changes and the crossing of tipping points, resulting
in profoundly altered future forest development trajectories (Turner
et al., 2020). Some studies suggest that such threshold could already
be crossed at relatively low warming levels of +2°C (Elkin et al., 2013;
Albrich et al., 2020), with substantial implications for ecosystem
service supply (
limited evidence
,
high agreement
).
Regional studies on the potential future effects of climate change
on forest production systems indicate diverse impacts. In Germany,
drier conditions in 2070 (RCP8.5; GCMs INM-CM4, ECHAM6 and
ACCESS1.0) are expected to benefit the mean annual increment at
biological rotation age of Scots pine and oak, while beech might
suffer losses of up to 3 m
3
ha
–1
yr
–1
depending on climate scenario
and region (Albert et al., 2018). In India, 46% of the forest grid points
were found to have high, very high or extremely high vulnerability
under future climate in the short term (2030s) under both RCP4.5
and 8.5, increasing to 49% and 54%, respectively, in the long term
(2080s) (Sharma et al., 2017). In addition, forests in the higher rainfall
zones show lower vulnerability as compared with drier forests under
future climate, which is in contrast to dry forests in Central and South
America cited above. Warming and drying trends are projected to
reduce timber production in the neotropics in some cases (Hiltner
et al., 2021). Also in India, a study using CMIP5 (RCP4.5 and 8.5 with
two time slices 2021–2050 and 2070–2099) shows how forests in
five districts in Himachal Pradesh in Western Himalayan region are
vulnerable to global warming (Upgupta et al., 2015). In the Guiana
Shield, climate projections under RCP2.5 and 8.5 led to decreasing
the basal area, above-ground fresh biomass, quadratic diameter, tree
growth and mortality rates of tropical forests (Aubry-Kientz et al.,
2019). In Central Africa, projections under RCP4.5 and 8.5 showed
a general increase in growth, mortality and recruitment leading to
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a strong natural thinning effect, with different magnitudes across
species (Claeys et al., 2019).
On a global and regional scale, there is
limited evidence
and
high
agreement
(
medium confidence
) that climate change will increase
global and regional supply of timber and other forest products. To date,
there are eight studies assessing the total economic impacts of climate
change on the forestry sector at the global level. Some of them have
assumed only flow effects of climate change by using the projected
changes in yields of forest types from integrated economic models
(Perez-Garcia et al., 1997; Perez-Garcia et al., 2002; Buongiorno,
2015), while other studies have assumed both flow and stock effects
by accounting for changes in forest yields, die back effects and biome
migration (Sohngen et al., 2001; Lee and Lyon, 2004; Tian et al., 2016;
Favero et al., 2018; Favero et al., 2021).
According to these studies, global timber supply will increase as the
result of an increase in global forest growth under climate change
scenarios (
medium confidence
). Some studies indicate that timber
supply is projected to increase more in tropical and subtropical areas
because of the assumed availability of short-rotation species which
might could adaptation easier for forest owners in these regions
relative to others (Sohngen et al., 2001; Perez-Garcia et al., 2002; Tian
et al., 2016), while others indicate that temperate areas will experience
the largest increase in supply (Favero et al., 2018; Favero et al., 2021).
The results are very sensitive to the climate change scenarios tested,
the climate and vegetation models used and the climate drivers that
are considered. For example, Tian et al. (2016) and Favero et al. (2018;
2021) used the same economic model (the global timber model) but
different climate scenarios and vegetation models, obtaining different
results.
The increasing supply induces lower global timber prices (
medium
confidence
). Studies estimate that the prices will decline between
1% and 38% in 2100 with respect to a no climate change scenario
depending on the model and the climate change scenario assumed
(climate change is represented as a change in GHG concentration,
global average temperature or radiative forcing) (Favero et al., 2018;
Favero et al., 2021). Clearly, further studies are needed considering
a wider set of vegetation and climate models and incorporating the
impacts of extreme events (such as droughts and wildfires).
There are a number of national and regional scale studies exploring
the impact of climate change on yields and markets of wood products,
with mixed results. In Finland, it is projected that timber yield in the
north will increase in Scots pine and birch stands by 33–145% and
42–123%, compared with the current climate, depending on the
GCM and thinning regime using a 90-year rotation (10 individual
GCM projections under the RCP4.5 and RCP8.5 forcing scenarios)
(ALRahahleh et al., 2018). However, in Norway spruce stands, yield
could decline by up to 35%, under GFDL-CM3 RCP8.5 and increase
by up to 39%, under CNRM-CM5 RCP8.5, compared with the current
climate.
In Germany, timber harvest was projected to increase slightly (<10%)
in 2045 using the process-based forestry model (4C) driven by three
management strategies (nature protection, biomass production and a
baseline management) and an ensemble of regional climate scenarios
(RCP2.6, RCP4.5, RCP8.5) (Gutsch et al., 2018). Similarly, average
production of pulpwood in slash pine stands in the southeastern USA
are projected to increase by 7.5 m
3
ha
−1
for all climatic scenarios using
the Physiological Processes Predicting Growth (3-PG) forest growth
model by 2100 (RCP4.5 and RCP8.5; CanESM2) (Susaeta and Lal, 2018).
Box 5.6: Contributions of Indigenous and Local Knowledge: An Example
Indigenous and local people have long histories of adaptation to climate hazards in forests (see Eriksen and Hankins, 2014; Neale et al.,
2019; Bourke et al., 2020; Long et al., 2020; Williamson, 2021 for notable examples in Australia and North America). In this section, we
present a North American example of an indigenous adaptation practice developed by the Karuk Tribe in northern California. The Karuk
Climate Adaptation Plan focuses on the use of cultural fire as climate adaptation, places a central importance on restoring human
ecological caretaking responsibilities, and emphasises the need for collaboration, public education and policy advocacy to achieve these
outcomes.
The Karuk Climate Adaptation Plan utilises a combination of Western science and Karuk traditional ecological knowledge. The plan
centres on 22 focal species as
cultural indicators
as cues for human responsibilities and the particular techniques of fire application
across seven habitat management zones (e.g., multiple forest types as well as riverine, riparian and montane systems). These adaptations
range from specific prescriptions for the use of fire to lower river temperatures in acute scenarios (David et al., 2018), to protocols for
treatment of grasslands and the use of high elevation meadows as fuel breaks. The plan also includes chapters on adaptations for tribal
sovereignty, the mental and physical health effects of the changing climate and the protection of critical tribal infrastructure.
One aspect of Indigenous fire knowledge featured in the Karuk Climate Adaptation Plan is the culture-centric perspective on vegetation
zones which are organised in relation to the elevation band in which smoke inversions occur (Figure Box 5.6.1). Within this system,
burn timing follows a gradient that tracks the reproductive life cycles of season and elevational migrant species, the calving of elk and
the nesting of birds. Within this system, elevational migrants are indicators of when to stop burning at one location and move upslope,
following receding snows.
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5.6.3 Adaptation
AR5 notes that natural ecosystems have built-in adaptation ability
(Settele et al., 2014). However, this capacity will not be enough to
prevent loss of forest ecosystem services because of projected climate
change in this century under RCP6.0 and 8.5. Management actions
could reduce the risks of impacts to forest ecosystems but only up to
a certain point.
A systematic review of literature revealed that successful adaptation in
forest management can be achieved if there are partnerships between
key stakeholders such as researchers, forest managers and local actors
(Keenan, 2015). Such partnerships will lead to a shared understanding
of climate-related challenges and more effective decisions. Forest
managers in some countries of the world seem to have high awareness
of climate change (van Gameren and Zaccai, 2015; Seidl et al., 2016;
Sousa-Silva et al., 2016). However, they need more information on
how they can adjust their practices in response to climate change.
Institutional and policy context needs to be considered to facilitate
adaptation by forest managers (Sousa-Silva et al., 2016; Andersson
et al., 2017).
The plan also calls for the restoration of Indigenous fire science in emergency scenarios such as when rivers become too hot for salmon.
With such fires localised, smoke inversions cool water temperatures through a variety of mechanisms, including shading river systems and
reducing evapo-transpiration, thereby increasing stream flow (David et al., 2018).
Seasonality and elevation dynamics of cultural indicators in Karuk Cultural Management Zones
Figure Box 5.6.1 | Seasonality and elevation dynamics of cultural indicators in Karuk Cultural Management Zones based in Karuk traditional
ecological knowledge.
Box 5.6 (continued)
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5.6.3.1 Adaptation measures in sustainable forest management
A wide range of measures exist to adapt sustainably managed
forests of the boreal and temperate zone to climate change (Kolström
et al., 2011; Gauthier et al., 2014; Keenan, 2015). Evidence emerging
since the last assessment report further bolstered the notion that
adapting the tree species composition to more warm-tolerant and less
disturbance-prone species can significantly mitigate climate change
impacts (
high confidence
) (Duveneck and Scheller, 2015; Seidl et al.,
2018). Assisting the establishment of species in suitable habitats is
one option to achieve climate-adapted tree species compositions
(Benito-Garzón and Fernández-Manjarrés, 2015; Iverson et al., 2019).
Furthermore, increasing the diversity of tree species within stands can
have positive effects on tree growth and reduce disturbance impacts
(
high confidence
) (Neuner et al., 2015; Jactel et al., 2018; Ammer, 2019).
Some studies also suggest a positive effect of increased structural
diversity, such as on forest resilience (
moderate confidence
) (Lafond
et al., 2013; Koontz et al., 2020). Managing for continuous forest cover
can also help to maintain the forest microclimate and buffer tree
regeneration and the forest floor community against climate change
(
high confidence
) (De Frenne et al., 2013; Zellweger et al., 2020).
Reducing stocking levels, such as through thinning, has been found
to effectively mitigate drought stress (Gebhardt et al., 2014; Elkin
et al., 2015; Bottero et al., 2017), yet effects vary with species and
ecological context (
robust evidence
,
medium agreement
) (Sohn et al.,
2016; Castagneri et al., 2021). Also shortened rotation periods have
been suggested in response to climate-induced increases in growth
and disturbance (Jönsson et al., 2015; Schelhaas et al., 2015). However,
recent evidence suggests that these measures diminish in efficiency
under climate change and can have corollary effects on other important
forest functions such as carbon storage and habitat quality (
medium
confidence
) (Zimová et al., 2020). Also, measures targeting landscape
structure and composition have proven effective for increasing the
climate resilience of forest systems (
medium confidence
) (Aquilue
et al., 2020; Honkaniemi et al., 2020). While an increasing number
of adaptation measures exist for sustainably managed forests, many
studies highlight that the lead times for adaptation in forestry are
long and that some vulnerabilities might remain also after adaptation
measures have been implemented. Furthermore, the costs and benefits
of adaptation measures relative to other goals of sustainable forest
management, such as the conservation of biological diversity, have
to be considered (Felton et al., 2016; Zimová et al., 2020; see Cross-
Chapter Paper 7.5 Adaptation Response Options).
5.6.3.2 Linking adaptation and mitigation through Reducing
Deforestation and Forest Degradation plus
Reducing Deforestation and Forest Degradation plus (REDD+) is
a climate mitigation strategy which could also provide important
climate change adaptation co-benefits; for example, sustainable forest
management could provide long term livelihoods to local communities
and enhance resilience to climate risks (Turnhout et al., 2017). However,
major challenges related to REDD+ implementation and forest use
remain such that it has not been implemented successfully at scale
(Table 5.8).
5.7
Other Natural Products
Natural products such as medicinal plants, wild food (plants, animals,
mushrooms) and resins (e.g., gum arabic and frankincense) have high
commercial value and contribute an important source of livelihood
in some regions. One in six persons globally live in or near forests,
and many depend on forest resources for some of their livelihood and
needs, particularly in low- and middle-income countries (Vira et al.,
2016; Newton et al., 2020). The FAO has estimated that in 2011 non-
wood forest products, including medicinal plants, contributed over
88 billion USD to the global economy (FAO, 2014). Greater diversity
in local knowledge and Indigenous knowledge of natural resources
supports resilience in the face of hazards, especially in environments
with high levels of uncertainty (Berkes et al., 2003; Blanco and Carriere,
2016).
Table 5.8 |
Challenges and solutions for REDD+
Challenges with REDD+ implementation
Solutions for successful forest management
Legal
: lack of carbon rights in national legislations (Sunderlin et al., 2018; RRI, 2018b);
unclear forestland tenure systems (Resosudarmo et al., 2014).
There is
high confidence
that implementing social safeguards such as a
Free Prior and
Informed Consent (FPIC) is vital to adequately involving Indigenous Peoples and local
communities in REDD+ (White, 2014; Raftopoulos and Short, 2019). Indigenous Peoples,
consisting of at least 370 million people, manage or have tenure rights over a quarter of
the world’s land surface (around 38 million km
2
) encompassing about 40% of the world’s
protected areas (Garnett et al., 2018; RRI, 2018a).
Food security and livelihoods
: negative impacts of REDD+ on food security, agroforestry and
swidden agriculture (Fox et al., 2014; Holmes et al., 2017).
There is
high agreement
that REDD+ and other green adaptation and mitigation efforts need
to cooperate with Indigenous Peoples and other local communities who depend on forest
resources for their livelihoods and food security (Wallbott, 2014; Mccall, 2016; Brugnach
et al., 2017; Vanclay, 2017; Garnett et al., 2018; Paneque-Galvez et al., 2018; Sunderlin et al.,
2018; Schroeder and Gonzalez, 2019).
Political and socio-cultural
:
land acquisition or ‘green grabbing’ (Asiyanbi, 2016; Corbera
et al., 2017); (mis)communicating the concept of carbon (Kent and Hannay, 2020); and
lack of influence of Indigenous and local communities’ representation in global and
national REDD+ negotiations (Wallbott, 2014; Dehm, 2016). In the absence of social and
environmental safeguards, REDD+ could drive large-scale land acquisitions by states and
corporations, resulting in global land grabs (or green grabbing), negatively affecting the food
security, livelihoods and tenure rights of Indigenous and local communities (
limited evidence,
high agreement
) (Carter et al., 2017; Lund et al., 2017; Borras et al., 2020).
There is
low confidence
as to whether community forestry is compatible with REDD+ (Hajjar
et al., 2021). This is mainly due to lack of carbon payments and the variety of approaches to
REDD+. There is
high confidence
that restoring land access and rights via transfer of formal
land titles to Indigenous and local communities improves biodiversity conservation and
carbon sequestration.
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5.7.1
Medicinal Plants
The World Health Organization lists traditional medicine as an essential
component of culturally appropriate healthcare (WHO, 2013). Medicinal
plants make up the primary source of medicine for 70–95% of people
in low- and middle-income countries and are used widely in wealthier
countries (Applequist et al., 2020). Continued use of medicinal plants
ensures millions of rural people have access to effective treatments
for day-to-day illness and infection and thus improves their health and
resilience to climate change.
Indigenous Peoples largely depend on medicinal plants for their
healthcare need in different parts of the world (de Boer and Cotingting,
2014; Silva et al., 2020). Medicinal and aromatic plants can support
the economy and generate livelihood options for rural people through
preparing and selling traditional medicine; collecting from wild;
and trade for income generation (Fajinmi et al., 2017; Zahra et al.,
2020). Income from medicinal plant collection increases livelihood
diversification, which is widely accepted to improve resilience.
5.7.2
Resin and Gum
Resin and gum are economically important natural products,
contributing 14–23% total household income in parts of Ethiopia and
Sudan (Abtew et al., 2014; Fikir et al., 2016), Cambodia (Sakkhamduang
et al.) and India (Tewari et al., 2017). They are an important source of
raw material for many industries. For instance, in Africa, the genera
Boswellia
and
Commiphora
,
which provide frankincense and myrrh
resins, provide significant income generation and export value (Tilahun
et al., 2015). Populations of many species that provide gums and
resins are declining under pressure from unsustainable harvesting and
deforestation, and climate change may threaten them further.
In Sri Lanka,
Boswellia serrata
Roxb. is critically endangered or
possibly extinct (Weerakoon and Wijesundara 2012). In India,
B.
serrata
populations are ‘vulnerable’ (Chaubey et al., 2015; Brendler
et al., 2018), and declining in the Western Ghats (Soumya et al., 2019).
Invasion of
Lantana camara
and
Prosopis juliflora
has resulted in
poor regeneration of
Commiphorawightii
in central India (Jain and
Nadgauda, 2013). Other resin-producing species under threat include:
Daemonoropsdraco
(dragon’s blood resin) in Indonesia (Yetty et al.,
2013; Widianingsih et al., 2019),
Pinus merkusii
(tusam) in Sumatra
(Indonesia) (Hartiningtias et al., 2020),
Pinus pinaster
in Spain,
Pinus
massoniana
in China
(Génova et al., 2014; Chen et al., 2015b) and
Pistacia atlantica
in Iran (Yousefi et al., 2020).
5.7.3
Wild Foods
Wild foods can include both native and introduced species that are not
cultivated or reared but may be under various degrees of management
by humans and may include escapees of species that are cultivated
in some contexts (Powell et al., 2015). Information on the use and
importance of wild foods for nutrition is growing but remains limited
(FAO, 2019e). The AR4 covered wild food briefly in the polar regions
and noted the inter-related nature of climate change and Indigenous
knowledge loss in reducing access to wild food (Anisimov et al., 2001).
AR5 did not address wild foods and other natural products. There is
large variation in the importance of wild foods (Powell et al., 2015;
Rowland et al., 2017; Dop et al., 2020). A recent survey of 91 countries
found that 15 reported regular use of wild foods by most of the
population, and 26 reported regular use of wild foods by a subsection
of the population (FAO, 2019e). While they contribute little to food
energy intake, their contribution to nutrition can be significant because
most wild and forest foods (vegetables, fruits, mushrooms, insects and
meat) are rich in proteins and micronutrients (Powell et al., 2015). The
impacts of climate change on wild foods will vary in time and space
and among species.
5.7.4
Observed and Projected Impacts
5.7.4.1 Medicinal plants
Research is limited on the effects of climate change on the distribution,
productivity or availability of medicinal plants (Applequist et al., 2020),
but some are facing threats due to climate change (Phanxay et al., 2015;
Chirwa et al., 2017; Chitale et al., 2018). Climate change is projected to
impact some medicinal plant species through changes in temperature,
precipitation, pests and pathogens; unsustainable harvest of high-value
species will significantly exacerbate these impacts (
medium evidence
,
high agreement
) (Applequist et al., 2020). Table 5.9 highlights that
climate change impacts on medicinal plant species will vary greatly
by species. Medicinal plants that grow in arid environments are also
highly susceptible to climate-induced change (Applequist et al., 2020).
Arctic medicinal species may also be particularly at risk due to climate
change (Cavaliere, 2009).
Changes in range distribution will interact with detailed local
knowledge and Indigenous knowledge needed to harvest and use
medicinal plants. Northward range shifts, for example, may mean
certain plants still exist, but not where they have traditionally been
important as medicine, and possibly moving suitable ranges outside of
areas where plants species have sufficient protection (Kaky and Gilbert,
2017). Climate-induced phenological changes are already observed as
a threat to some species (Gaira et al., 2014; Maikhuri et al., 2018).
Other major climate-induced impacts on medicinal plants will be via
the phytochemical content and pharmacological properties of medical
plants (Gairola et al., 2010; Das et al., 2016a). Experimental trials have
shown that drought stresses increase phytochemical content, either
by decreasing biomass or increasing metabolites production (
high
confidence
) (Selmar and Kleinwachter, 2013; Al-Gabbiesh et al., 2015).
5.7.4.2 Wild food
5.7.4.2.1 Wild food in the Arctic, North America and Europe
Changes to the availability, abundance, access and storage of wild
foods associated with changing climate are exacerbating high rates of
food insecurity (
high confidence
) (Ford, 2009; Beaumier and Ford, 2010;
Herman-Mercer et al., 2019). Wild foods are central to the food systems
of communities throughout the Arctic and sub-Arctic (Kuhnlein et al.,
1996; Ballew et al., 2006; Kuhnlein and Receveur, 2007; Johnson et al.,
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Table 5.9 |
Observed and predicted impacts of climate change on selected medicinal plant species.
Region
Species
Observed and projected impacts of climate change
Assessment of
evidence and level
of agreement
Egypt, Sub-Saharan
Africa, Spain,
Central Himalaya,
China, Nepal
General assessment of
medicinal plants
Habitat suitability and/or range distribution will shift or may be lost (Munt et al., 2016; Yan et al.,
2017; Brunette et al., 2018; Chitale et al., 2018; Zhao et al., 2018; Applequist et al., 2020), including
in high-elevation meadows which are home to some of the most threatened plant populations
and contain a high number of and higher proportion of species used as medicine compared with
lower-elevation habitats (Salick et al., 2009; Brandt et al., 2013).
Medium confidence
Hindukush
Himalaya
Gynostemmapentaphyllum
The elevated CO
2
and temperature can increase biomass, but the health-promoting properties such as
total antioxidants, phenols and flavonoids are expected to decrease (Chang et al., 2016).
Medium confidence
Arctic
Golden root (
Rhodiola rosea)
Population decline has been associated with drying of stream beds and alpine meadows, which are
predicted to become more severe under climate change
(Cavaliere, 2009; Brinkman et al., 2016).
Medium confidence
North America
American ginseng
(
Panax quinquefolius
)
Modelling of the combined impact of climate change (warming) and harvesting pressure indicates a
nonlinear increase in extinction risk (Souther and McGraw, 2014).
Medium confidence
Asia
Gentiana rigescens
A model evaluating future climate impacts shows a westward range shift and major loss of highly
suitable habitats. Modelling also shows a potential decline in quality (chemical concentration of iridoid
glycoside, which is highest in highly suitable habitats) due to climate change (Shen et al., 2021).
Medium confidence
Africa
Alstoniaboonei
Modelling indicates that the range for this species remains relatively stable, with a possible modest
expansion at the northern and southern margins of the range (Asase and Peterson, 2019).
Medium confidence
Asia
Homonoia riparia
Modelling of future climate scenarios in Yunnan Province, China projects that habitat suitability
improves (Yi et al., 2016). Modelling of future climate scenarios across the whole species range in
China shows that both the suitable area and suitability of the habitat increase (Yi et al., 2018).
Medium confidence
Asia
Notopterygiumincisum
Modelling for future climate change shows areas of suitable habitat will significantly decrease;
however, the area of marginally suitable habitat will remain relatively stable (Zhao et al., 2020).
Medium confidence
Himalayas
Himalayan yew
Taxus
wallichiana
Modelling shows projected shrink in climatic niche of the species by 28% (RCP4.5) and 31% (RCP8.5),
highlighting the vulnerability to climate change impacts (Rathore et al., 2019).
Medium confidence
Iran
Daphne mucronata
Modelling of future climate change projects disappearance of the species below 2000 m, significant
change in distribution between 2000 and 3000 m and no change above 3000 m (Abolmaali et al., 2018).
Medium confidence
Central America
Pericón or Mexican Mint
Marigold
Tagetes lucida
Models predict range to contract somewhat and shift northward (Kurpis et al., 2019).
Medium confidence
Africa
Rooibos tea
Aspalathus linearis
Modelling of future climate scenarios shows substantial range contraction of both wild and cultivated
tea, with range shifts southeastwards and upslope (Lotter and Maitre, 2014).
Medium confidence
Himalayas
Lilium polyphyllum
Habitats of this species will shrink by 38–81% under future climate scenarios and shift towards the
southeast region in Western Himalaya, India (Dhyani et al., 2021).
Medium confidence
Iran
Fritillaria imperialis
Modelling shows 18% and 16.5% of the habitats may be lost due to climate change by 2070 under RCP4.5
and RCP8.5, respectively. Further, it is observed that, under the current climatic conditions, the suitable
habitat may become unsuitable in the future, resulting in local extinction (Naghipour Borj et al., 2019).
Medium confidence
Himalayas/ China
Snow lotus
(
Saussurea spp.
)
Climate change is a significant threat to this species (Law and Salick, 2005). Laboratory and field trials
show considerable plasticity and a wide thermal range for germination, which may help compensate
for range reductions under climate change (Peng et al., 2019).
Medium confidence
North Africa
Atlas cedar
Cedrus atlantica
Modelling shows a significant and rapid contraction of distribution range, upward elevational range
shift, increased fragmentation, and possible disappearance in many North African localities (Bouahmed
et al., 2019).
Medium confidence
Asia/South Korea
Paeonia obovata
Modelling of climate change scenarios shows significant loss of suitable habitat and possible
disappearance of
P. obovatain
in South Korea after 2080 (Jeon et al., 2020).
Medium confidence
Iran
Salvia hydrangea
A projected loss of habitat in the southeast of the range will not be compensated by the northward or
upward elevational range migration (Ardestani and Ghahfarrokhi, 2021).
Medium confidence
Patagonian,
Argentina
Valeriana carnosa
Modelling for future climate scenarios projects a 22% loss of the suitable habitat (Nagahama and
Bonino, 2020).
Medium confidence
Western Ghats,
India
Kokum
Garcinia indica
Predictions of climate change impact on habitat suitability indicate drastic reduction in the suitability
by over 10% under RCP8.5 for the years 2050 and 2070 (Pramanik et al., 2018).
Medium confidence
Himalaya
Ophiocordyceps sinensis
A decline of the species is largely due to over harvesting, but ecological modelling indicates that
climate warming is also contributing to this decline (Hopping et al., 2018).
High confidence
Pacific islands
Noni (
Morindacitrifoli
),
naupaka (
Scaevola spp
.), kukui
(
Aleurites moluccana
) and milo
(
Thespesia populnea
)
May be less susceptible to climate change as they are fast growing, have high reproduction rates, grow
at sea level (and are often salt-tolerant) and have significant room for range shifts (Cavaliere, 2009).
Low confidence
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2009) and play an essential role in people’s physical and emotional
health (Section CCP6.2.5; 2.8) (
high confidence
) (Loring and Gerlach,
2009; Cunsolo Willox et al., 2012). Wild foods consumed in the Arctic
and northern regions include animals and a wide variety of plant
foods (Wein et al., 1996; Ballew et al., 2006; Kuhnlein and Receveur,
2007). Wild foods contribute most of important nutrients in the diets
of northern and Arctic people (Johnson et al., 2009; Wesche and Chan,
2010; Kenny et al., 2018). However, the use of traditional wild foods is
declining across the region, lowering diet quality (Rosol et al., 2016).
Indigenous communities in the Arctic perceive climate change related
impacts on traditional wild foods, and availability and access to wild
foods are forecast to continue to decline (Brinkman et al., 2016). Some
communities hold positive views of the new opportunities a warmer
climate will bring, seeing them as a favourable trade-off relative to
the loss of some forms of subsistence hunting (Nuttall, 2009). Climate
change is causing ecological changes that impact Arctic wild food
availability and abundance in many different ways, including changes
to breeding success, migration patterns and food webs (Table 5.10,
Markon et al., 2018).
Climate-change-induced impacts of access to wild foods are also
of concern in Arctic regions (
high confidence
). Coastal and inland
communities of Alaska found that 60% of climate impacts on food
security listed by hunters were related to access (Brinkman et al.,
2016). Reduced duration, thickness and quality of sea ice are some of
the most cited impacts of climate change on wild food consumption
(Ford, 2009; Laidler et al., 2009; Downing and Cuerrier, 2011;
Huntington et al., 2017; Nuttall, 2017; Fawcett et al., 2018; Ford et al.,
2018; Markon et al., 2018). Lack of snowfall reduces and delays the
ability to travel on land using snowmobiles (Downing and Cuerrier,
2011), impacting safety of travel, time needed and costs of accessing
wild foods (Cold et al., 2020).
Rising temperatures and humidity are also impacting wild food storage
and increasing the risk of food-borne diseases (Cozzetto et al., 2013;
Nuttall, 2017; Markon et al., 2018). Changes in AT and humidity can
mean that whale and fish meat no longer dry properly, or meat may
spoil before hunters can get it home (Downing and Cuerrier, 2011;
Nuttall, 2017). Traditional permafrost ice cellars are no longer reliable
(Downing and Cuerrier, 2011; Nyland et al., 2017; Herman-Mercer et al.,
2019). Climate-related environmental change compounded with social,
economic, cultural and political change have had complex but overall
negative impacts on wild foods (Section CCP6.4, Lujan et al., 2018) .
Communities across other (non-Arctic) parts of North America and
Europe also report declining availability of wild foods, with climate
change among the perceived drivers for decline (
medium confidence
)
(Table 5.10, Serrasolses et al., 2016; Smith et al., 2019a). Even when
climate change may not always be the primary driver of loss of these
wild food resources, climate may interact with other stressors to
exacerbate loss of wild foods (Lynn et al., 2013; Reo and Parker, 2013).
5.7.4.2.2 Wild food in the arid and semi-arid environments
Wild foods are also impacted by climate change in arid and semi-arid
landscapes around the world (
medium evidence
,
high agreement
)
(Table 5.10). A number of wild species are important traditional foods
of Indigenous Peoples or local communities across arid regions of
North America (Messer, 1972; Kuhnlein and Calloway, 1977; Santos-
Fita et al., 2012; Vinyeta et al., 2016), South America (e.g., Argentina;
Ladio and Lozada, 2004; Altrichter, 2006; Eyssartier et al., 2011),
Australia (Scelza et al., 2014), the Mediterranean Basin (Hadjichambis
et al., 2008; Powell et al., 2014), India and the Himalayas (Pingle, 1975;
Gupta and Sen, 1980; Delang, 2006; Bhatt et al., 2017).
Wild foods such as baobab, shea and nere from plants and animals
make an important contribution to diets and nutrition in arid and semi-
arid regions of Africa (Boedecker et al., 2014; Leßmeister et al., 2015;
Bélanger and Pilling, 2019) and are being impacted by climate change
(Moseley et al., 2015; Sango and Godwell, 2015; Hitchcock, 2016) (see
Chapter 9). There has been little published research on the impacts
of climate change on wild food in arid regions of Australia, although
Aboriginal elders in one report suggested that climate-related changes
are impacting wild food (Memmott et al., 2013).
5.7.4.2.3 Wild food in tropical humid environments
Wild foods are important to many communities that live in and
adjacent to humid tropical forests, but climate change impacts are
mixed (Table 5.10, Dounias et al., 2007; Colfer, 2008; Powell et al.,
2015; Rowland et al., 2017; Reyes-García et al., 2019). In some
humid tropical forest regions, bushmeat is particularly important
(Golden et al., 2011; Nasi et al., 2011; Fa et al., 2015; Powell et al.,
2015; Rowland et al., 2017). In humid tropical regions, the impact of
climate change on wild food availability, access and consumption is
currently unclear and research is limited. There are, however, important
interrelationships between climate change and wild food use in
humid forests. For example, the loss of large mammals to bushmeat
consumption and global trade will likely slow the regeneration of
tropical forests in which a large number of tree species are dependent
on large mammals for seed dispersal (Brodie and Gibbs, 2009).
Conversely, others argue that bushmeat provides local communities
with an important incentive to support local maintenance of forest
cover and, thus, carbon sequestration (Bennett et al., 2007).
5.8
Ocean-Based and Inland Fisheries Systems
The livelihoods of 10–12% of the world’s population depend on
fisheries and aquaculture (FAO, 2020c). Globally, fish provide more
than 3.3 billion people with 20% of their average per capita intake of
animal proteins, reaching 50% or more in countries such as Bangladesh,
Cambodia, The Gambia, Ghana, Indonesia, Sierra Leone, Sri Lanka and
several Small Island Developing States (FAO, 2020c). Between 1961
and 2017, the average annual apparent global food fish consumption
increased (3.1% per year; from 9.0 kg per person in 1961 to 20.5 kg in
2018), exceeding the rate of increase in consumption of meat from all
terrestrial animals combined (2.1% annually, currently around 40 kg
per person) (FAO, 2020d). Fish are a rich source of protein and specific
vitamins and minerals (Khalili Tilami and Sampels, 2018), and are an
essential food source in regions in need of nutritious, affordable food
(Thilsted et al., 2016; FAO et al., 2018; Hicks et al., 2019; Cross-Chapter
Box MOVING PLATE this chapter).
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Table 5.10 |
Observed and predicted impacts of climate change on selected wild food species.
Region
Species
Observed and projected impacts of climate change
Assessment of
evidence and level
of agreement
Arctic region
Ringed seals
(
Pusahispida
)
Drastic declines in population size and major changes in population structure (Hammill, 2009; Reimer
et al., 2019); habitat (dependent on snow cover or ice breathing holes for lairs) will decline by
approximately 70%, and significantly reduce survival rates of pups (Freitas et al., 2008).
High confidence
Arctic region
Bearded seal (
Erignathus
barbatus
)
Climate change affects the availability and stability of at least 11 ice-associated species, including
bearded seal. Potential impacts due to climate change will reduce available habitat for birthing (Moore
and Huntington, 2008; Fink, 2017).
Medium evidence
,
high agreement
Arctic region
Walrus
(
Odobenus rosmarus
)
Declines in the climate-vulnerable Pacific walrus populations, induced by overharvesting (Taylor et al.,
2018); however, the species is considered highly vulnerable to loss of sea ice (Lydersen, 2018). Possible
diet changes (related to climate-induced changes in food web) raise concerns about the health of the
population (Clark et al., 2019).
High confidence
Arctic region
Narwhal
(
Monodon monoceros
)
The impacts of climate change on other sea ice-associated marine mammals are somewhat less clear
(Moor et al., 2017). Climate change may threaten narwhal given their vulnerability to ice entrapment
(Laidre and Heide-Jorgensen, 2005) and the narrow range of prey in their diet (Heide-Jørgensen, 2018).
In Greenland, hunters report that narwhal now frequent fjords and other areas where manoeuvring a
boat is difficult (Nuttall, 2017).
Low evidence
,
medium agreement
Arctic region
Beluga
(
Delphinapterus leucas
)
Belugas are thought to be less sensitive to climate change than some other sea mammals but can
perish in large groups from ice entrapment. Climate impacts likely increased human activity (noise)
(O’Corry-Crowe, 2009). Changes in migrating timing have been documented (Hsiang et al., 2017).
Low evidence
,
low
agreement
Arctic region
Bowhead
(
Balaena mysticetus
)
The movements of some whale species are linked to SSTs (Moore and Huntington, 2008; Chambault
et al., 2018). Some whale hunting communities are now reporting that whales pass by at a time of year
when launching boats is impaired by rough weather and poor sea ice conditions (Noongwook et al.,
2007; Huntington et al., 2017).
Medium confidence
Arctic region
Other sea ice associated marine
mammals (harp seal, hooded
seal)
The impacts of climate change on other sea ice associated marine mammals are somewhat less clear
(Moor et al., 2017).
Low confidence
Arctic and
northern regions
Reindeer and caribou
(
Rangifer tarandus
)
Large herbivores are highly dependent on their food sources such as mosses, lichens and grasses which
are sensitive to climate change (Istomin and Habeck, 2016).
Combined impacts of climate change and other inter-related factors suggest significant declines in
caribou and reindeer populations, although to varying extents from one population to another (Kenny
et al., 2018; Mallory and Boyce, 2018).
Warming has led to increased plant productivity and associated increases in body mass of some
reindeer populations (Albon et al., 2017; Mallory and Boyce, 2018).
Increasing primary production, warming will also change the plant composition, leading to increases in
woody/shrubby vegetation which will have negative nutritional consequences for caribou and reindeer
(Elmendorf et al., 2012; Mallory and Boyce, 2018). The loss of lichens, a key winter food source, due
to increased wildfire or replacement by grasses and herbs that die back in the winter, may also be
detrimental to caribou and reindeer, although there is currently no consensus on this among experts
(Mallory and Boyce, 2018).
Rain on snow and icing events during winter, which are predicted to become more frequent, have been
documented to lead to large increases in arctic herbivore mortality because they create an ice barrier
making access to food more difficult (Putkonen and Roe, 2003; Tyler, 2010; Stien et al., 2012; Hansen
et al., 2013; Forbes et al., 2016). Rain-on-snow events may also impact reproductive success, although
recent research suggests this relationship in not straightforward (Douhard et al., 2016).
Increased summer insect harassment is also predicted to increase and further stress large herbivores
both by the additional parasitic load and by decreasing the amount of time spent grazing as animals
seek to outrun pests (Mallory and Boyce, 2018).
Finally, many caribou and reindeer populations rely on sea and freshwater ice to facilitate their movement
and migration; loss of ice may make some populations no longer viable (Mallory and Boyce, 2018).
Medium confidence
Arctic and
northern regions
Moose (
Alces alces
)
The distributional changes of
Rangifer
populations might be affected by the range expansions and
the northward expansion of moose (Mallory and Boyce, 2018). This is due to increases in productivity
on the tundra and more frequent wildfire activity resulting in improved habitat quality for moose
northward.
Medium confidence
North America
Geese (
Branta canadensis
,
Answer spp.
,
Branta spp.
)
Phenological mismatch developing between the berries and migration timing may mean that Canadian
geese no longer stop near some communities (Downing and Cuerrier, 2011).
Medium confidence
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Region
Species
Observed and projected impacts of climate change
Assessment of
evidence and level
of agreement
Arctic and
northern regions
Berries
(
Vaccinium spp.
,
Rubus spp.
and others)
Berries are among the most important and widely consumed wild foods of plant origins in Arctic and
northern regions (Vaara et al., 2013; Hupp et al., 2015; Boulanger-Lapointe et al., 2019).
Berry production will be impacted by climate change, including snow cover, rainfall, soil moisture, air
temperature and availability of insect pollinators (Herman-Mercer et al., 2020) and possible risk from
sea-level-rise-associated soil salinisation (Cozzetto et al., 2013).
Increased growth of woody shrub vegetation, driven by increased temperatures, can also make moving
across the land difficult, impairing access to berry patches (Boulanger-Lapointe et al., 2019). Conversely,
a recent modelling experiment suggested that the >2°C warming experienced by Arctic communities
over the past three decades has had minimal impact on overall trail access (Ford et al., 2019).
In Alaska, communities perceive berry abundance as declining and/or becoming more variable (Kellogg
et al., 2010; Hupp et al., 2015). In a Gwich’in community in Canada, Parlee and Berkes (2005) recorded
that local women perceived climate change, especially extreme weather events, as the greatest risk to
traditional berry patches (cranberry, blueberry and cloudberry).
The expansion of trees and shrubs may cause shading and negatively impact the productivity of berry
plants (Downing and Cuerrier, 2011; Lévesque et al., 2012).
Berries are predicted to be increasingly susceptible to negative impacts of invasive species (which
compete for pollinators) (Spellman and Swenson, 2012) and infections (Turner and Clifton, 2009) as
climate change progresses. Suitable area of huckleberry (
Vaccinium membranaceum
) would shrink by
5–40% by the end of the 21st century (Prevéy et al., 2020).
Phenological shifts are also important. Many communities report changes in phenology including failed
ripening or ‘all of the berries are ripening at the same time’ (Turner and Clifton, 2009; Herman-Mercer
et al., 2020). Competition with growing populations of geese is viewed by many communities to be an
important threat to berry harvesting. (Boulanger-Lapointe et al., 2019). In Labrador, Canada, changes in
permafrost, vegetation, water and weather have had an impact on cloudberry (bakeapple) productivity,
phenology and patch fragmentation. Moreover, changes in summer settlement patterns (which are now
farther from berry patches) are making it more difficult for people to respond to variations in growth
and timing (Anderson et al., 2018).
In Montana, USA, Crow Nation elders have noted that many of their important berry resources have
been impacted by climate change, either because they bud earlier and are then vulnerable to cold
snaps, or the timing of fruit production has changed (with many now ripening at the same time) (Doyle
et al., 2013). Similarly, the Wabanaki Nations in Maine and Eastern Canada worry that climate change
will impact berry resources already under pressure from dwindling territory and pollution (Lynn et al.,
2013).
High confidence
North America
(Washington State,
USA)
Salmon (
Salmonidae
)
Indigenous communities in Washington State, USA report devastation of their salmon fishery due to
loss of glacial run off and associated warming river and stream temperatures; potential damage to
shellfish resources due to sea level rise and ocean acidification (Lynn et al., 2013). The Karuk people in
California have also experienced losses in salmon (Lynn et al., 2013; Vinyeta et al., 2016).
Medium confidence
North America
(California)
Acorns from oak trees (
Querus)
In the arid southwest of the USA, wild foods are less widely consumed today, but their revitalisation
is important to identity and well-being of many Indigenous People. The Karuk people of the Klamath
River in California have experienced an almost complete loss of two key traditional wild foods: salmon
and acorns, foods which once made up 50% of a traditional Karuk diet (Lynn et al., 2013; Vinyeta et al.,
2016), as well as huckleberry (Vinyeta et al., 2016). Using regional climate models, Kueppers (2005)
showed a major reduction in the range of two species of oak in California that are used in traditional
diets. Increasing frequency of severe fires in the western USA threaten a number of traditional wild
food resources, especially acorns (Vinyeta et al., 2016).
Medium confidence
North America
Wild rice
(
Zizania spp
.)
Significant reductions in wild rice area in Great Lakes have been associated with mining, dams and
other activities, but climate change may lead to further reductions (Cozzetto et al., 2013; Lynn et al.,
2013).
High confidence
North America
Camas tuber
(
Camassia quamash
)
Historic changes in fire regimes, linked to changes in climate, are believed to have altered availability of
the important camas tuber (
Camassia quamash
) (Lepofsky et al., 2005).
Medium confidence
North America
Wapato tuber
(
Sagittaria latifolia
)
The aquatic
Sagittaria latifolia
(the roots of which are consumed by Indigenous groups across North
America) is vulnerable to both water salinity and temperature (Delesalle and Blum, 1994).
Medium confidence
North America
Springbeauty
(
Claytonia
lanceolate
)
Claytonia lanceolata
is particularly vulnerable to changes in snow melt and other climatic changes
owing to advancement in the flowering (Renner and Zohner, 2018).
Medium confidence
North America
Seaweed (
Porphyra abbottiae
,
among others)
In British Columbia, Canada, Indigenous People Gitga’at elders noted that the ripening of an important
edible seaweed (
Porphyra abbottiae
) had rarely synchronised with weather patterns that enabled
them to process it in the traditional way (drying on rocks and then ripening and re-drying) (Turner and
Clifton, 2009).
Low confidence
Africa
Baobab (
Adansonia digitata
)
Baobab is thought to be vulnerable to climate change because it is long-lived, it can take up to 23 years
to start fruiting and leaf harvesting is often so intensive that it depresses fruit production. Modelling
study using different records model shows that the percentage of present distribution predicted to be
suitable in the future ranged from 5% to 91% (Sanchez et al., 2011).
Low confidence
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Overall capture fishery production has remained relatively static since
the 1990s, reaching 96.4 million tonnes in 2018, with over 87% of
the production coming from marine environments and the rest from
inland fisheries (FAO, 2020c). Finfish represent 85% of global marine
seafood production, with small pelagic fishes (anchovies, sardines
and herrings) as the major contributor. Almost 60% of the total
global marine catches come from China, Peru, Indonesia, the Russian
Federation, the USA, India, Viet Nam, Japan, Norway and Chile (FAO,
2020c). Inland fisheries are found on every continent other than
Antarctica and provide 158 million people the equivalent of all dietary
animal protein (McIntyre et al., 2016). Inland production accounted
for 12 million tonnes in 2018, with nearly 70% of capture from low-
income Asian and African countries (Harrod et al., 2018a).
The aquaculture and fisheries’ share of gross domestic product
(GDP) varies mostly from 0.01% to 10% (Cai et al., 2019), but the
relative importance in countries’ economies and welfare is greater in
several low-income countries, especially in many African and Pacific
Island states. Approximately 60 million people are directly employed
in fisheries value chains, from harvesting to distribution (Vannuccini
et al., 2018); around 95% of them are in small-scale fisheries of low-
and middle-income countries, and almost half are women.
Region
Species
Observed and projected impacts of climate change
Assessment of
evidence and level
of agreement
Africa
Shea (
Vitellaria paradoxa
)
Shea (
Vitellaria paradoxa
) was expanded through human intervention and is linked to human
migration; fruit traits such as fruit size and shape, pulp sweetness and kernel fat content are
determined both by temperature and rainfall, as well as human selection for preferred traits (Maranz
and Wiesman, 2003). There is limited and conflicting evidence of the impacts of climatic conditions
and future projected climate variations on
V. paradoxa
(Tom-Dery et al., 2018). Mixed evidence of the
impact of climate and rainfall on fruit production and timing is reported (Tom-Dery et al., 2018). Fruit
production was negatively correlated with mean annual temperature and positively correlated with
annual rainfall (Bondé et al., 2019).
Limited evidence
,
medium agreement
North Africa
(Morocco)
Argan (
Argania spinosa
)
Climate change projections suggest a 32% decrease in habitat suitable for
Argania spinosa
under some
scenarios (Alba-Sánchez et al., 2015; Moukrim et al., 2019).
Medium confidence
Asia (Nepal)
Fruit species and vegetables
(e.g.,
Asparagus racemosus
,
Urticadioica
)
In Nepal, Thapa (2015) reports phenological changes in semi-domesticated fruit species, as well as
decreased availability of a number of wild plants that can be consumed as vegetables.
Limited evidence
,
medium agreement
Worldwide, most
important in
Europe and Asia
Mushrooms
Wild mushrooms production (including truffles) is closely linked to climate factors including temperature
and precipitation as well as tree growth and carbohydrate production (Tahvanainen et al., 2016). Some
species are sensitive to high temperatures (Büntgen et al., 2012; Le Tacon et al., 2014; Ágreda et al.,
2015; Bradai et al., 2015; Taye et al., 2016; Alday et al., 2017; Karavani et al., 2018; Büntgen et al., 2019;
Thomas and Buntgen, 2019). Models for some varieties suggest ‘declines of 78–100% in European
truffle production are likely for 2071–2100’ (Thomas and Buntgen, 2019). For some species in northern
Europe, the season is expanding (starting earlier and/or ending later), likely linked to warming (Büntgen
et al., 2012; Le Tacon et al., 2014; Ágreda et al., 2015; Bradai et al., 2015; Taye et al., 2016; Alday et al.,
2017; Karavani et al., 2018; Büntgen et al., 2019; Thomas and Buntgen, 2019).
Matsutake mushroom (
Tricholoma matsutake
), highly prized in China, is sensitive to timing and amount
of precipitation and temperature (Yang et al., 2012), and suitable habitat for this species is predicted
to significantly decrease and highly suitable habitat to nearly disappear under various climate change
scenarios (Guo et al., 2017).
High confidence
North America
(California)
Acorns, nuts and berries and
other fire-dependent wild foods
Low-intensity traditional burning practices increased pyro-diversity (Vinyeta et al., 2016). Climate
change will exacerbate the risks posed by exotic pathogens that attack oak species and further reduce
access to acorns as well as other foods founds in oak ecosystems (Voggesser et al., 2013).
High confidence
South America
(Amazon region)
Aguaje, (
Mauritia
felxuosa
)
,
Brazilian nut
(
Bertholletiaexcelsa
), fishing
and hunting in general
Local communities perceived a lower yield of aguaje due to drought (Hofmeijer et al., 2013). In another
study from the Colombian Amazon, wild food use was reported to be vulnerable to extreme climate
events which impact species migration patterns or restrict access to fishing and hunting rounds
(Torres-Vitolas et al., 2019). In some humid regions, the range of some wild food species may be
extended by climate change, such as the Brazilian nut (
Bertholletiaexcelsa
) (Thomas et al., 2014).
Medium confidence
Small islands
(Papua New
Guinea)
Sweet potato
Increases in the ENSO were associated with drought which increased sweet potato losses (Jacka, 2016)
in highlands humid forest.
Limited evidence
,
medium agreement
Australasia
(Australia)
General wild foods
Aboriginal communities in North Queensland, a humid tropical region of northern Australia, reported
some climate impacts on wild foods, although primarily for marine resources and those found in dry
forest ecosystems (McIntyre-Tamwoy et al., 2013).
Limited evidence
,
medium agreement
Asia (Indonesia)
Sago (
Metroxylon sagu
)
People in a sago-dependent community in Papua Indonesia viewed climate variation as less important
than other factors (logging, mining, infrastructure), but still expressed concerns about salinity of water
supplies, floods and reduced hunting success (Boissière et al., 2013).
Limited evidence
,
medium agreement
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5.8.1
Observed Impacts
Ocean systems are already facing significant impacts of climate
change. At the ocean surface, temperature has on average increased
by 0.88 [0.68–1.01] °C from 1850–1900 to 2011–2020 (Fox-Kemper
et al., 2021; Gulev et al., 2021). Marine heatwaves have increased
in frequency over the 20th century, with an approximate doubling
since the 1980s (
high confidence
), and their intensity and duration
have also increased (
medium confidence
) (IPCC, 2021, Box 9.2). In
the Northeast Pacific, for example, an intense and long-lasting marine
heatwave during 2013–2015 bridged to the strong 2015–2016 El Niño
(Tseng et al., 2017) resulted in over 5 years of warmer-than-normal
temperatures affecting the migration, distribution and abundance
of several marine species, including fisheries resources (Cornwall,
2019; Jiménez-Quiroz et al., 2019). The surface open ocean pH has
declined globally over the last 40 years by 0.003–0.026 pH per decade
(
virtually certain
), and a decline in the ocean interior pH has been
observed in all ocean basins over the past two to three decades (
high
confidence
) (Gulev et al., 2021). The ocean is losing dissolved oxygen
(
very likely
) in the range of 0.5–3.3% between 1970 and 2010 for the
0–1000 m depth stratum (Bindoff et al., 2019; Canadell et al., 2021),
salt content is being redistributed (
very likely
) (Liu et al., 2019a; Gulev
et al., 2021) and vertical stratification is increasing (
virtually certain
)
(HLPE, 2017a; Fox-Kemper et al., 2021; Ranasinghe et al., 2021). There
is
high confidence
that all these new physical, chemical and biological
conditions affect marine organisms’ physiology, distribution and
ecology, with an overall shift in biomass and species composition
affecting ecosystem structure and function (Chapter 3). Under climate
change, freshwater ecosystems are highly exposed to eutrophication,
species invasion and rising temperatures (Lynch et al., 2016; Hassan
et al., 2020). Major threats to wetland fisheries include water stress,
sedimentation, weed proliferation, sea level rise and loss of wetland
connectivity (Naskar et al., 2018).
Changes in aquatic ecosystems directly affect humans by altering
livelihood, cultural identity and sense of self, and seafood provision,
quality and safety. The state of marine fishery resources has
continued to decline, with the proportion of fish stocks at biologically
unsustainable levels of exploitation increasing from 10% in 1974 to
34.2% in 2017 (FAO, 2020d). There is
medium confidence
that fisheries
production declines in different world regions can be partly attributed
to climate change, along with overfishing and other socioeconomic
factors. It has been estimated that, from 1930 to 2010, the amount
of fish that can be sustainably harvested from several marine fish
populations has decreased by 4.1% globally due to ocean warming,
with some regions (East Asian Marginal Seas, the North Sea, the Iberian
Coast and the Celtic-Biscay Shelf), experiencing losses of 15–35%
(Free et al., 2019). There is regional variation such as redistribution of
fishing grounds, due to climate-induced fish species migrations (Cross-
Chapter Box MOVING PLATE this chapter). In Tanzania, for example,
most small-scale fishers (75%) have reported shifting fishing grounds
from nearshore to offshore areas during the last decade, due to
perceived combined effects of overfishing and environmental impacts
(Silas et al., 2020). Observed impacts in some inland aquatic systems
indicate substantial productivity reductions (
medium confidence
).
For example, sustained warming in Lake Tanganyika during the last
∼
150 years has affected the biological productivity by strengthening
and shallowing stratification of the water column (Cohen et al., 2016).
Still, over 60% of the published reports on directly observed impacts
of climate change on freshwater biota are on salmonids in North
America and Europe, highlighting significant literature gaps for other
fish species and regions (Myers et al., 2017a).
There is
low confidence
in climate change affecting the nutritious value
of seafood. Contrasting evidence suggests that ocean warming and
acidification could be altering the nutritional quality of commercial
mollusks, primarily by reducing healthy fatty acids content (Tate
et al., 2017; Ab Lah et al., 2018; Lemasson et al., 2019), but Coleman
(2019) found no significant changes in a widely distributed coastal
fish species.
In terms of food safety, there is
high confidence
that climate change
increases the trends in seafood consumption related illnesses due to
biological agents such as algae-produced toxins, ciguatera and
Vibrio
(Cross-Chapter Box ILLNESS in Chapter 2, Sections 5.11 and 5.12).
Increased surface water warming changes the occurrence, intensity,
species composition and toxicity of marine and freshwater algae and
bacteria, and expansion to areas where they had not been reported
before (Botana, 2016; McCabe et al., 2016; Griffith et al., 2019). There
is
limited evidence
suggesting that risks linked to the bioaccumulation
of chemicals are also of concern, such as neurotoxic methylmercury
(MeHg) and heavy metals, due to water quality and trophic changes
induced by climate change (Shi et al., 2016; Schartup et al., 2019).
5.8.2
Assessing Vulnerabilities
In the absence of adaptive measures, climate-induced changes in
the abundances and distributions of fish will impact the provision,
nutrition and livelihood security of many people (
high confidence
) as
well as regional and global trade patterns (
medium confidence
).
5.8.2.1 Food security: provision and nutrition
The importance of seafood in food security and nutrition is
increasing, largely due to its contribution as high-quality food (
high
confidence
) (Hicks et al., 2019), as seafood contains unique long-
chain polyunsaturated fatty acids (LC-PUFAs) and highly bioavailable
essential micronutrients—vitamins (A, B and D) and minerals (calcium,
phosphorus, iodine, zinc, iron and selenium). These compounds, often
not readily available elsewhere in diets, have beneficial effects for
adult health and child cognitive development (HLPE, 2014). Changes
in marine and freshwater fish production can have significant
consequences for human nutrition (Colombo et al., 2020). These
changes are of particular concern in regions with few nutrition
alternatives, such as low-income countries in Africa, Asia, Australasia,
and Central and South America (
high confidence
) (Ding et al., 2017;
Kibria et al., 2017).
Freshwater ecosystems that support most inland fisheries are under
continuing threat from changes in land use, water availability and
pollution and other pressures that will be exacerbated by climate
change (
high confidence
) (Section 4.3.5). Declines in dissolved oxygen
in freshwater are 2.75–9.3 times greater than observed in the world’s
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oceans (Jane et al., 2021). These systems have a relatively low buffering
capacity and are therefore more sensitive to climate-related shocks
and variability (Harrod et al., 2018b). Freshwater faunae are projected
to be highly vulnerable; in the tropics because organisms are closer
to approaching their thermal physiological limits and in the northern
hemisphere (30–50°N) because the rate of temperature change is
faster (Comte and Olden, 2017). The worldwide spatial confluence of
productive freshwater fisheries and low food security highlights the
critical role of rivers and lakes in providing locally sourced, low-cost,
nutritious food sources (McIntyre et al., 2016).
Deltas and other wetland fisheries are extremely vulnerable to climate
change and home to a large and growing proportion of the world’s
population. In India, Ghana and Bangladesh, where three of the most
populated Deltaic systems are located, subsistence fisheries provide
12–60% of the animal protein in people’s diets (Lauria et al., 2018).
The concern over aquatic food products’ safety due to climate change
is increasing (
high confidence
). A strong positive relationship exists
between specific bacterial growth rates and temperature, including
pathogenic species of the genera
Vibrio
,
Listeria
,
Clostridium
,
Aeromonas
,
Salmonella
,
Escherichia
and others, whose distributional
area is expanding with changing climate conditions (Cross-Chapter
Box ILLNESS in Chapter 2, Section 5.12.1).
5.8.2.2 Social vulnerabilities, including gender and
marginalised groups and cultural services
There is
high confidence
that climate change is and will continue
to be a threat to the livelihood of millions of fishers, with the most
vulnerable being those with fewer opportunities and less income
(Barange and Cochrane, 2018; Section 3.4.3). The social vulnerability
can differ largely between locations, even between relatively close
coastal or inland communities (Bennett et al., 2014; Maina et al., 2016;
Ndhlovu et al., 2017; Martins et al., 2019) and among inhabitants
within a location, depending on factors such as access to other
economic activities, education, health, adults in the household, and
political connections (
high confidence
) (Senapati and Gupta, 2017;
Abu Samah et al., 2019; Lowe et al., 2019).
Indigenous coastal communities consume 1.5–2.8 million metric
tonnes of fish per year (about 2% of global yearly commercial
marine catch), and reach a per capita consumption estimated to be
15 times greater than that of non-Indigenous country populations
(Cisneros-Montemayor et al., 2016). There is
high confidence
that
some Indigenous fishing communities are particularly vulnerable to
climate change through a reduced capacity to conduct traditional
harvests because of limited access to, or availability of, fish resources
(Weatherdon et al., 2016), with consequences that include dietary
shifts with significant nutritional and health implications (Marushka
et al., 2019), displacement and loss of cultural identity (Sullivan and
Rosenberg, 2018) and loss of social, economic and cultural rights
(Finkbeiner et al., 2018). Areas of high risk for Indigenous Peoples
include the Arctic, coastal communities with a high dependency
on marine and freshwater fisheries, and Small Island States and
Territories (Finkbeiner et al., 2018; Hanich et al., 2018, Section
CCP6.2.5.1).
Women play a crucial role along the entire fisheries value chain,
providing labour force in industrialised and small-scale fisheries all
around the world (FAO, 2020d). For small-scale fisheries alone, women
represent about 11% of the labour force, and their activity is generally
in subsistence fisheries, highlighting their role in household food
security (Harper et al., 2020). In general, gendered division of labour
tends to cause lower salaries for women and different perception and
experience of risk to climate change impacts (
high confidence
) (Lokuge
and Hilhorst, 2017).
5.8.2.3 Management, economic and geopolitical vulnerabilities
Local, national, regional and international fisheries are mostly
underprepared for geographic shifts in marine animals driven by
climate change over the coming decades (
high confidence
) (Pinsky
et al., 2018; Oremus et al., 2020; Pinsky et al., 2020). With fisheries
distribution changes, sometimes into areas dedicated to different
historical uses or new ventures, the current management regimes
will face constraining legal frameworks (Farady and Bigford, 2019;
Pinsky et al., 2020), which will demand interventions in the form of
policies, programmes and actions, at multiple scales (Cross-Chapter
Box MOVING PLATE this chapter). Coordinated fisheries management
can substantially expand capacity to respond to a changing climate
(Pinsky et al., 2020), but a great deal of political will, capacity building
and collective action will be necessary (
high confidence
) (Teslić et al.,
2017; Burden and Fujita, 2019; Section 5.8.4).
Today, approximately half the world’s population (~4 billion out of
7.8 billion people) are assessed as being currently subject to severe
water scarcity for at least 1 month per year (
medium confidence
)
(Box 4.1), and freshwater inland fisheries are particularly vulnerable
as they are given lower priority for water resources than other sectors
(
high confidence
). In some cases, this situation results in the total
loss of freshwater fisheries. Examples include diversion of water
for agriculture, shifts from food provision to recreational fisheries,
conserving biodiversity, and the requirement for high-quality water for
drinking water supply (Section 5.13, Harrod et al., 2018a).
There is
high confidence
that climate change increases the risk of
conflicts due to the redistribution of stocks and their abundance
fluctuations, with subsequent impacts on resource sharing (Spijkers and
Boonstra, 2017; Pinsky et al., 2018; Spijkers et al., 2018; Mendenhall
et al., 2020; Pinsky et al., 2020). High vulnerability and lack of adaptive
capacity to climate change impacts (including fisheries-dependent
livelihoods, attachment to place, and pre-existing tensions) increase
the risk of conflicts, including among fishery area users and authorities
(Ndhlovu et al., 2017; Shaffril et al., 2017; Spijkers and Boonstra,
2017; Mendenhall et al., 2020). Similarly, shifts in the distribution
of transboundary fish stocks under climate change alter the current
sharing of resources between countries and create conflicts as well
as new opportunities (Cross-Chapter Box MOVING PLATE this chapter,
Spijkers and Boonstra, 2017; Pinsky et al., 2018).
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5.8.3
Projected Impacts
There is
medium confidence
that climate change will reduce global
fisheries’ productivity (Section 3.4.4.2.3), with more significant
reductions in tropical and subtropical regions and gains in the poleward
areas (Bindoff et al., 2019; Oremus et al., 2020). Through an ensemble
of marine ecosystem models and Earth System Models, mean global
animal biomass in the ocean has been estimated to decrease by 5%
under the RCP2.6 emissions scenario and 17% under RCP8.5 by 2100,
with an average decline of 5% for every 1°C of warming (Lotze et al.,
2019), affecting food provision, revenue distribution, and potentially
hindering the rebuilding of depleted fish stocks (Britten et al., 2017). The
projected declining rates result in a 5.3–7% estimated global decrease
in marine fish catch potential by 2050 (Cheung et al., 2019), particularly
accentuated in tropical marine ecosystems and affecting many low-
income countries (Barange and Cochrane, 2018; Bindoff et al., 2019;
Cross-Chapter Box MOVING PLATE this chapter). Projections indicate
that by 2060 the number of exclusive economic zones (EEZs) with
new transboundary stocks will increase to 46 under strong mitigation
RCP2.6, and up to 60 EEZs under the RCP8.5 GHG emissions scenario
(Pinsky et al., 2018). Similarly, by combining six intercompared marine
ecosystem models, Bryndum-Buchholz et al. (2019) projected that
under the RCP8.5 scenario a total marine animal biomass decline
of 15–30% would occur in the North and South Atlantic and Pacific
and the Indian Ocean by 2100. In contrast, polar ocean basins would
experience a 20–80% increase. In the eastern Bering Sea, simulations
based on RCP8.5 predict declines of pollock (>70%) and cod (>35%)
stocks by the end of the century (Holsman et al., 2020). Temperate tunas
(albacore, Atlantic bluefin and southern bluefin) and the tropical bigeye
tuna are expected to decline in the tropics and shift poleward by the
end of the century under RCP8.5, while skipjack and yellowfin tunas are
projected to increase abundance in tropical areas of the eastern Pacific
but decrease in the equatorial western Pacific (
medium confidence
)
(Erauskin-Extramiana et al., 2019). In the western and central Pacific,
redistribution of tropical tuna due to climate change is projected to
affect license revenues from purse seine fishing and shift more fishing
into high seas areas (Bell et al., 2018; Table 15.5). For the east Atlantic,
observational evidence indicates that not only will tuna distribution
change with temperature anomalies, but also fishing effort distribution
(Rubio et al., 2020a). There is
medium confidence
that climate change
will create new fishing opportunities when exploited fish stocks shift
their distribution into new fishing regions in enclosed seas, such as the
Mediterranean and the Black Sea (Hidalgo et al., 2018; Pinsky et al.,
2018). However, in general, where land barriers constrain the latitudinal
shifts, the expected impacts of climate change are population declines
and reduced productivity (
high confidence
) (Oxenford and Monnereau,
2018). Besides direct impacts on the abundance of fisheries-targeted
species, climate-change-induced proliferation of invasive species could
also affect fisheries’ productivity (
low confidence
) (Mellin et al., 2016;
Goldsmith et al., 2019).
Shifting marine fisheries will affect national economies (
high
confidence
) (Bindoff et al., 2019). It has been suggested that, without
government subsides, fishing is already non-profitable in 54% of the
international waters (Sala et al., 2018). Projections are that fishing
maximum revenue potential from landed catches will decrease further
by 10.4% (±4.2%) by 2050 relative to 2000 under RCP8.5, close to
35% greater than the decrease projected for the global maximum catch
potential (7.7±4.4%); (Lam et al., 2016). The global revenue potential
loss for that period ranges from USD 6 to 15 billion (depending on the
model), but impacts may be amplified at the regional scale for fisheries-
dependent and low-income countries. The maximum revenue potential
percentage decrease in the EEZ under RCP8.5 is estimated to be over
2.3 times larger than that of the high seas (Lam et al., 2016). Ocean
acidification is also expected to drive large global economic impacts
(
medium confidence
) (Cooley et al., 2015; Fernandes et al., 2017;
Macko et al., 2017; Hansel et al., 2020), and there is
high confidence
that the integrated economic consequences of all interacting climate
change-related factors would result in even larger losses. Changes in
the frequency and intensity of extreme events will also alter marine
ecosystems and productivity. Marine heatwaves can lead to severe
and persistent impacts, from mass mortality of benthic communities
to decline in fisheries catch (IPCC, 2021, Box 9.2). These events have
very likely
doubled in frequency between 1982 and 2016 and have also
become more intense and longer (Smale et al., 2019; Laufkotter et al.,
2020); for all future scenarios Earth System Models project even more
frequent, intense and longer-lasting marine heatwaves (Eyring et al.,
2021; IPCC, 2021, Box 9.2).
In addition to temperature and water availability stress, climate
change will bring new water quality challenges in freshwater systems,
including increased dissolved organic carbon and toxic metal loads
(
high confidence
) (Chen et al., 2016). Harrod et al. (2018a) found that
the two major inland fishery producers (China and India) will face
significant stress in the future, a large group of countries that produce
around 60% of total yield is projected to face medium stress, and a
small group of 17 countries has the least severe repercussions (
medium
confidence
). Climate warming may enhance northward colonisation of
water bodies of commercial freshwater species in the Arctic, where
there are few ecological competitors (
medium confidence
) (Campana
et al., 2020) but at the same time may also accentuate the age-
truncation effect of harvesting, elevating the population’s vulnerability
to environmental perturbations (Smalås et al., 2019). Detailed
information on many of the most important inland fisheries is limited.
In terms of food safety, major concerns linked to climate change
include the continued trend of increasing HABs, and the quantity of
pollutants reaching aquatic systems (Box 3.3; Section 5.11).
5.8.4 Adaptation
Adaptation options in land- and aquatic-based culturing food
production systems include both governance actions and changes
in the factors of production (Section 5.4.4, 5.5.4, Reverter et al.,
2020). In contrast, adaptation options in fisheries are primarily
concentrated in the socioeconomic dimension, especially governance
and management (Brander et al., 2018; Holsman et al., 2019), and
given the scale of the problem, there are relatively few intentional,
well-documented examples of implemented tactical responses (Bell
et al., 2020).
The proportion of fisheries operating at levels that are considered
biologically unsustainable by the FAO has increased from 10% in 1974
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to 34.2% in 2017 (FAO, 2020d). There is
high confidence
that reducing
stresses on marine ecosystems reduces vulnerability to climate
change and augments resilience (Barange, 2019; Woodworth-Jefcoats
et al., 2019; Ogier et al., 2020). Specifically, overfishing is the most
critical non-climatic driver affecting the sustainability of fisheries,
and therefore improving management could help rebuild fish stocks,
reduce ecosystem impacts and increase the adaptive capacity of
fishing (
high confidence
); (Barange, 2019; Das et al., 2020). Pursuing
sustainable fisheries practices under a low-emissions scenario would
decrease risk by 63%; in contrast, under the most extreme RCP8.5,
both profit and harvest decline relative to today even under the most
optimistic assumptions about global fisheries management reforms
(Gaines et al., 2018; Sumaila et al., 2019; Free et al., 2020).
One adaptation strategy in the fishing sector is developing the capacity
to recognise and respond to new opportunities that might arise from
climate change by establishing a policy and planning setting that
augments the fishers’ flexibility to change target species of fisheries or
even engage in different productive activities. A key element would be
the design and implementation of management schemes that consider
flexible permits, sharing quotas, rethinking boundaries and reference
points in response to system changes (Brander et al., 2018; Cross-
Chapter Box MOVING PLATE this chapter). Large-scale distribution and
productivity changes of commercial fish species will demand the ability
to implement cooperative fishing strategies (Cisneros-Montemayor
et al., 2020; Østhagen et al., 2020), and adjust multi-lateral treaties
and other legal instruments used for managing shared transboundary
ecosystems (Butler et al., 2019; Cross-Chapter Box MOVING PLATE this
chapter).
There is
high confidence
that making climate change and adaptive
capacity a mainstream consideration in global, regional, environmental
and fisheries governance structures can improve the response capacity
to ocean change (Gaines et al., 2018; Bindoff et al., 2019; Holsman
et al., 2020; Ojea et al., 2020). For example, spatial management that
includes strategies such as Territorial Use Rights for Fishing (TURFs),
locally managed marine areas (LMMAs) and customary tenure is an
approach that has climate change adaptation potential in small-scale
fisheries but will require adjustments in governing and managing
institutions that allow them to be more dynamic and flexible (Le Cornu
et al., 2018). In regions where some of these measures have already
been tested, institutional, legal, financial and logistical barriers to
successful adaptation have been encountered, such as market failures
stemming from uncertainty around new or emerging species, or policy
barriers derived from the fact that the creation of scientific information
needed to change regulations is likely slower than the pace of changes
in stocks (Peck and Pinnegar, 2018).
Adaptation capacity is limited by the financial capacity of some
countries (Bindoff et al., 2019). For example, in West African fisheries,
adaptation costs associated with replacing the loss of coastal
ecosystems and productivity is estimated to require 5–10% of
countries’ GDP (Zougmoré et al., 2016). For Pacific Islands and Coastal
Territories, fisheries adaptation will require significant investment from
local governments and the private sector (Rosegrant et al., 2016), and
reducing dependence on or finding alternatives to vulnerable marine
resources (Johnson et al., 2020; Mabe and Asase, 2020).
Adaptive capacity is strongly associated with social capital (i.e., the
networks, shared norms, values and understandings that facilitate
cooperation within or among groups) (
high confidence
) (Stoeckl
et al., 2017; D’agata et al., 2020) and depends on to what extent
stakeholders are aware of climate change and their perception of risk
(Ankrah, 2018; Martins and Gasalla, 2018; Chen, 2020). Improving
information flows allows for a more efficient co-management
implementation (
medium confidence
) (Vasconcelos et al., 2020).
Utilisation of local and Indigenous knowledge has the potential
to facilitate adaptation (Bindoff et al., 2019), not only because it
represents actual experiences and autonomous adaptations, but
also because it facilitates reaching shared understanding among
stakeholders and adoption of solutions. Challenges to hybridising local
ecological knowledge and scientific knowledge include differences
in stakeholder or governance perceptions about the validity of each
knowledge set and issues of expertise and trust (Harrison et al.,
2018). Engaging Indigenous Peoples and local communities as
partners across climate research ensures this knowledge is utilised,
enhancing the usefulness of assessments (Bindoff et al., 2019) and
facilitating the co-construction and implementation of sustainable
solutions (
medium confidence
) (Braga et al., 2020; Bulengela et al.,
2020). Building climate resilience in the fishing sector also involves
recognising gender and other social inequities (Call and Sellers,
2019), and ensuring that all stakeholders are equally involved in the
adaptation plans, including their design and the capacity-building
training programmes.
There is
high confidence
that, for the freshwater fisheries systems, the
most immediate adaptation option is the effective linkage of fisheries
management to the adaptation plans of other sectors, especially
water management (hydropower, irrigation and the commitment to
maintaining environmental flows) (Harrod et al., 2018a; Kao et al.,
2020). In some regions, organisations are already addressing this issue;
for example, The Office of Water (OW) in the USA is aimed at ensuring
that drinking water is safe while ecosystem is conserved to provide
healthy habitat for fish, plants and wildlife; however, success strongly
depends on the possibility of integrating the jurisdictional framework
of different agencies (Poesch et al., 2016), the implementation of
effective monitoring programmes (Paukert et al., 2016) and finding
ways to incentivise the early restoration of degraded systems (Ranjan,
2020).
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Cross-Chapter Box: MOVING PLATE: Sourcing Food When Species Distributions Change
Authors: H. Gurney-Smith (Canada/UK), W. Cheung (Canada), S. Lluch Cota (Mexico), E. Ojea (Spain), C. Parmesan (France/UK/USA), J.
Pinnegar (UK) P. Thornton (Kenya/UK), M-F. Racault (UK/France), G. Pecl (Australia), E.A. Nyboer (Canada), K. Holsman (USA), K. Miller
(USA), J. Birkmann (Germany), G. Nelson (USA) and C. Möllmann (Germany)
This Cross-Chapter Box, the ‘moving plate’, addresses climate-induced shifts and domesticated production suitability of food species
consumed by people. Marine, freshwater and terrestrial systems are already experiencing species shifts in response to climate change
(
very high confidence
) (see also Sections 2.4.2.1. and 3.4.3., Figure MOVING PLATE.1 this chapter), with subsequent impacts on food
provisioning services, pests and diseases (
high confidence
) (see Box 5.8 and Cross-Chapter Box ILLNESS in Chapter 2). This Box highlights
food insecurity and malnutrition of vulnerable peoples under climate change for both wild and domesticated aquatic and terrestrial
species, and discusses challenges for adaptation and the roles that management (transboundary and ecosystem-based) can play to
enable food security, reduce conflicts and prevent resource over-extraction.
Range contractions, shifts or extirpations are projected for terrestrial and aquatic species under warming, with greater warming leading
to larger shifts and losses, where mitigation would therefore benefit climate refugia and reduce projected biodiversity declines (Smith
et al., 2018; Warren et al., 2018). Marine species are moving poleward faster than terrestrial and freshwater species, despite faster
warming on land (Pecl et al., 2017; Lenoir et al., 2019; Woolway and Maberly, 2020), leading to new or exacerbated socioeconomic
conflicts within and between countries (see Figure MOVING PLATE.1 this chapter, see Sections 13.5.2.2., 15.3.4.4., FAQ 15.3., Mendenhall
et al., 2020). There is large variation in the magnitude and pattern of species shifts, even among similar species within a region, leading
to changes in communities in a given region (Brown et al., 2016; Pecl et al., 2017). The number of extreme heat stress days are projected
to increase for domesticated species like cattle (see Figure MOVING PLATE.1 this chapter), leading to shifts in suitable habitat for raising
livestock in the open with associated impacts in animal productivity and the costs of adapting in Africa, Asia, and Central and South
America (Thornton et al., 2021).
Nutritional dependency, cultural importance, livelihood, or economic reliance on shifting species will increase impacts of climate change,
especially for small-scale fishers (marine and freshwater), farmers, women and communities highly dependent on local sources of food
and nutrition (
high confidence
) (see Figures MOVING PLATE.1 and MOVING PLATE.3 this chapter, Sections 3.5.3., 8.2.1.2. and 15.3.4.4,
McIntyre et al., 2016; Blasiak et al., 2017; Kifani et al., 2018; Bindoff et al., 2019; Atindana et al., 2020; Hasselberg et al., 2020; Farmery et al.,
2021). Micronutrient concentrations from marine fisheries vary with species, providing higher concentrations of calcium, iron and zinc in
tropical regions and higher concentrations of omega-3 fatty acids in polar regions (Hicks et al., 2019). While consumption of smaller species
rich in micronutrients may provide significant benefits against deficiencies in Asia and Africa, local dietary changes in fish consumption may
be linked to food preferences, fish availability due to international trade or illegal fishing and competing usage of fish (see Figure MOVING
PLATE.3 this chapter, Hicks et al., 2019; Sumaila et al., 2020; Vianna et al., 2020). Industrial fleets are likely to switch target species
(Belhabib et al., 2016) and inhibit small-scale fishers via illegal, unreported or unregulated fishing in EEZs (Belhabib et al., 2019; Belhabib
et al., 2020). Extreme events can exacerbate issues, as fisheries are frequently increasingly exploited as a coping mechanism under times
of crisis, increasing illegal fishing activities and conflict among maritime users (Pomeroy et al., 2016; Mazaris and Germond, 2018). Spatial
conflicts between artisanal and commercial foreign fishing fleets are already occurring in Ghana (Penney et al., 2017), and from climate-
induced tropical tuna shifts in the Western and Central Pacific Ocean Islands (see Section 15.3.4.4., (Bell et al., 2018a)). Properly managed
small-scale fisheries can reduce poverty and improve localised food security and nutrition in low-income countries but will likely require
restriction in the number of fishers, boat size or fishing days (Purcell and Pomeroy, 2015; Hicks et al., 2019).
Shifting species have negative implications for the equitable distribution of food provisioning services, increasing the complexity of
resolving sovereignty claims and climate justice (
high confidence
) (Allison and Bassett, 2015; Ayers et al., 2018; Baudron et al.; Ojea
et al., 2020; Palacios-Abrantes et al., 2020). Higher-latitude countries generally have higher GHG emissions and will benefit from
poleward-migrating resources from tropical poorer and lower-emitting GHG countries (Free et al., 2020). In this context, climate justice
supporting fishing arrangements could offset socioeconomic impacts from exiting species (Mills, 2018; Lam et al., 2020) and have
negative implications particularly for small-scale operators (Farmery et al., 2021), However, considerations of climate justice have not
been used by Regional Fisheries Management Organizations (RFMOs) allocation shares to date (Engler, 2020). Species shifting from one
historical jurisdiction to another may result in an incentivised depletion of the resource by the country the stock is shifting away from;
reforming management to allocate resource sharing of quotas and permits or stock-unrelated side payments in bilateral or multilateral
cooperative agreements may compensate or prevent loss (Diekert and Nieminen, 2017; Free et al., 2020; Ojea et al., 2020; Østhagen et al.,
2020; Cross-Chapter Paper Polar 6.2.).
Strong governance, ecosystem-based and transboundary management are considered fundamental to ameliorate the impacts of climate
change (
high confidence
) but may be limited in effectiveness by the magnitude of change projected under low or no mitigation scenarios
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(see Sections 2.6.2., 14.4.2.2. and 15.3.4.4., Harrod et al., 2018c; Pinsky et al., 2018; Holsman et al., 2020; Ojea et al., 2020). Flexible and
rapid policy reform and management adaptation will help to meet sustainability targets (Nguyen et al., 2016; Pentz and Klenk, 2020), and
may only be available for countries with the scientific, technical and institutional capacity to implement these (
high confidence
) (Peck and
Pinnegar, 2018; Figures MOVING PLATE.2 and 3 this chapter). Other adaptation options include ‘follow the food’ thereby migrating
further (Belhabib et al., 2016), provision of alternative livelihoods (Thiault et al., 2019; Cross-Chapter Box MIGRATE in Chapter 7, Free
et al., 2020), increasing ecosystem resilience by rebuilding coastal mangroves (Tanner et al., 2014; and Box 1.3) and riparian areas of
freshwater ecosystems (Mantyka-Pringle et al., 2016) and autonomous adaptations, such as harvesting gear modifications to access new
target species (Harrod et al., 2018c; Kifani et al., 2018), practice change, and early-warning systems (see Section 11.3.2.3; Pecl et al., 2019;
Melbourne-Thomas et al., 2021). Adaptive capacity will change with country, region, scale (commercial, recreational, Indigenous) of
fishery, jurisdiction, and resource dependence (see Figure MOVING PLATE.2 this chapter for adaptation options for marine, freshwater
and terrestrial systems). While shifting fishing fleets or herding may be an adaptation option to follow resources, limits to feasibility
include institutional, legal, financial and logistical barriers such as costs of sourcing food and operational economic viability (Belhabib
et al., 2016); this could potentially lead to maladaptation through increased GHG emissions from fuel usage and cultural displacement
from traditional fishing and herding lands. Overall, decreases in GHG emissions under future scenarios would reduce increases in global
temperatures and limit species shifts, thereby lowering the likelihood of conflicts and food insecurity (
high confidence
).
Coastal Regions of the Gulf of Guinea: Ghanian Fisheries
Marine fisheries in Ghana are dominated by artisanal fishers with overfished stocks, high nutritional fish dependency, high illegal fishing,
low governance capacity (−0.21 2018, (World Bank, 2019)) and low climate awareness in regional fisheries management (Figure MOVING
PLATE.3 this chapter; see Chapter 9; Nunoo et al., 2014; Belhabib et al., 2015; Belhabib et al., 2016; Kifani et al., 2018; Belhabib et al.,
2019). Artisanal fishing plays a pivotal role in reducing poverty and food insecurity, and the impacts of climate change will risk developing
poverty traps (see Section 8.4.5.6., (Kifani et al., 2018)). Climate change induced species redistribution is a large risk to Ghanian fisheries,
with projections of over 20 commercial fish species exiting the region with no new species entering under RCP4.5 by 2100 (Oremus et al.,
2020), and has already seen increases in warmer-water species with declining stocks. Adaptation options being applied are extending
fishing ranges, increasing fishing effort (and cost) to access declining fish (with government fuel incentives) (Kifani et al., 2018; Muringai
et al., 2021), developing aquaculture for alternative livelihoods, implementing fleet monitoring to reduce illegal fishing, and developing
a robust Fisheries Information and Management System that accounts for environmental and climate drivers (Johnson et al., 2014; FAO,
2016; Kassi et al., 2018). However, fisheries remain insufficiently regulated, there is a lack of a skilled workforce, and there is low access
to credit; collectively, these factors limit options for artisanal fishers to find alternative sustainable employment (FAO, 2016).
Shifting Distributions of Freshwater Fishery Resources: Knowledge Gaps
Freshwater fisheries provide the primary source of animal protein and essential micronutrients for an estimated 200 million people
globally and are especially important in tropical developing nations (see Section 9.8, Lynch et al., 2017; Funge-Smith and Bennett,
2019.). There is evidence that freshwater fishes have undergone climate-induced distribution shifts (Comte and Grenouillet, 2015; see
Section 9.8.5.1.), and further shifts are projected as water temperatures rise and hydrological regimes change, with the largest effects
predicted for equatorial, subtropical and semi-arid regions (Barbarossa et al., 2021). Currently, the effects of distribution shifts on local
fishery catch potential, food security and/or nutrition have not been quantified for any major inland fishery, representing a key knowledge
gap for anticipating future adaptation needs for freshwater fishing societies. However, studies on fishers’ perceptions of climate-induced
changes in fishery catch rates have revealed that using local knowledge to adjust management practices (see Chapter 12 Central and
South America this volume; Oviedo et al., 2016) and shifting gears, fishing grounds and target species (see Section 9.8.5.3.; Musinguzi
et al., 2016) can be effective adaptation options.
Terrestrial Species Shifts
There is
robust evidence
of shifts that terrestrial species have shifted poleward in high latitudes, with general declines of sea-ice dependent
as well as some extreme-polar-adapted species (
high confidence
) (Arctic and Siberian Tundra, see Section 2.4.2.2., Cross-Chapter Paper
6), with often deleterious effects on the food security and traditional knowledge systems of Indigenous societies (Horstkotte et al., 2017;
Pecl et al., 2017; Mallory and Boyce, 2018; Forbes et al., 2020). Recent decades have seen declines in Arctic reindeer and caribou (see
Section 2.5.1., Cross-Chapter Paper 6), and adaptation responses include utilisation of Indigenous knowledge with scientific sampling to
maintain traditional management practices (Pecl et al., 2017; Barber et al.; Forbes et al., 2020). Preserving herder livelihoods will
necessitate novel solutions (supplementary feeding, seasonal movements), where governance, ecological and socioeconomic trade-offs
will be balanced at the local level (Horstkotte et al., 2017; Pecl et al., 2017; Mallory and Boyce, 2018; Forbes et al., 2020). Wild meat
consumption plays a critical, though not well understood, role in the diets and food security of several hundred million people (
medium
evidence
), for example in lower latitudes such as Central Africa and the Amazon basin (Bharucha and Pretty, 2010; Godfray et al., 2010;
Nasi et al., 2011; Friant et al., 2020). Although illegal in many countries, wild meat hunting occurs either in places where there is no or
Cross-Chapter Box: MOVING PLATE (continued)
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limited domesticated livestock production, or in places where shock events such as droughts and floods threaten food supply, forcing
increased reliance on wild foods including bush meat (Mosberg and Eriksen, 2015; Bodmer et al., 2018). Appropriate management of wild
meat for reliant peoples under projected climate change will necessitate incorporating social justice elements into conservation and
public health strategies (see Cross-Chapter Box ILLNESS in Chapter 2, Cross-Chapter Box COVID in Chapter 7, Friant et al., 2020; Ingram,
2020; Pelling et al., 2021).
(a) Ocean sensitivity within FAO regions and projected average fishing resource shifts in location
(b) Projected changes in the number of extreme heat stress days for cattle from early to end of century
Potential movement of cattle
from areas of high heat stress risk
to areas of lower heat stress risk
Global vulnerabilities to current and projected climate change for living marine resources and cattle
Current cattle distribution
Small-scale
fisheries
Projected shifts by 2100
Industrial
fisheries
0.9
0.5
0.0
Ocean
sensitivity
0.1
0.2
0.3
0.4
0.6
0.7
0.8
1.0
Examples of vulnerabilities,
conflicts and opportunities
for marine resource usage
New Arctic fisheries opportunities with poleward fish migrations
Climate regime shift triggers reform of cooperative management
under Pacific Salmon Treaty
Species exits and increased competition between small-scale and
large-scale fisheries
i
ii
iii
Conflicts over climate-induced migrations of commercial stocks
and food sovereignty
High regional dependency on tuna for economy and food security
New opportunities for migrating species of commercial interest
iv
v
vi
RCP2.6
RCP8.5
Catch
proportion
<40%
40–70%
>70%
i
ii
iii
i
ii
iii
IPCC climate regions
Additional days per year
of extreme heat stress
10–50 days
50–100 days
>100 days
SSP1-2.6
SSP5-8.5
Figure Cross-Chapter Box MOVING PLATE.1 | Global vulnerabilities to current and projected climate change for living marine resources and cattle.
Cross-Chapter Box: MOVING PLATE (continued)
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Chapter 5
(a)
Ocean areas are delineated into FAO (Food and Agricultural Organization of the United Nations) regions. Ocean sensitivity is calculated from aggregated sensitivities
from Blasiak et al. (2017) S1 country data based on number of fishers, fisheries exports, proportions of economically active population working as fishers, total fisheries
landings and nutritional dependence, which was subsequently re-analysed for each FAO region depicted here. Arrows denote projected average commercial and
artisanal fishing resource shifts in location under RCP2.6 and under RCP8.5 (dark-blue and red arrows, respectively) scenarios by 2100. Text boxes highlight examples
of vulnerabilities (Bell et al., 2018a), conflicts (Miller et al., 2013; Blasiak et al., 2017; Østhagen et al., 2020) or opportunities for marine resource usage (Robinson et al.,
2015; Stuart-Smith et al., 2018; Meredith et al., 2019).
(b)
Projected changes in the number of extreme heat stress days for cattle from early (1991–2010) to end of century (2081–2100) under SSP1-2.6 and SSP5-8.5, shown
as arrows rooted in the most affected area in each IPCC sub-region pointing to the nearest area of reduced or no extreme heat stress. Arrows are shown only for sub-
regions where >1 million additional animals are affected. Areas in green are those with >5000 animals per 0.5° grid cell in the eary 21st century (Thornton et al., 2021).
Common adaptation options, limitations and potential for adaptation in aquatic and terrestrial species with climate-induced movement
of food species and reliant peoples
Adapting food livelihoods to species shifts
Adaptation
options
Transboundary
management
Monitoring
shifts
Ecosystem-based
management
Economic
incentives
Technology
& knowledge
Mobility
Alternative
species
Alternative
livelihoods
International
Limits to
adaptation
Insufficient member
state involvement,
consensus & enforcement
Insufficient
scientific capacity
& consensus
Power dynamics
(sovereignty rights),
inequalities
Low acces
to credit &
financial capacity
Low access
to new & existing
technology
Restricted right
to roam, fisheries tenure
& access, especially for
vulnerable groups
Lack of training,
education,
income
alternatives
Marine
RMFOs
- EEZ fisheries
TB agreements
Adaptive
fisheries
management
Shared quotas,
establish fishing
rights, use of IK & LK
Gear/vessel
modification
Ecosystem-based &
multi-species management
Shifting
fleets
New markets
for incoming
species
Aquaculture
/ tourism
Terrestria
l
TB protected
areas &
management
Climate data
tracking &
CITES
Access rights,
tenure &
licenses
Herding,
utilization of
IK & LK
Sufficient
capacity &
enforcement
Shifting
herding
New markets
for incoming
species
Agro-ecological
livestock &
farming
Freshwater
Fisheries
agreements &
TB management
Fisheries
considered
in freshwater
usage
(e.g., hydroelectric)
Adaptive/
ecosystem-based
fisheries
management
Access rights,
tenure
licenses
Sufficient
capacity &
enforcement
New markets
for emerging
fisheries
Reduction of
post-harvest
losses
Aquaculture
/ tourism
Maladaptation
International
conflicts,
unbalanced
negotiations,
sovereignty &
climate justice
issues
leading to
overharvest
Illegal &
unreported
harvest,
species
trafficking &
poaching
Power
dynamics,
top-down
policy
making &
agreement,
failure to
adapt policies
Perverse
subsidies,
increased
inequities
Data poor
assessments,
uninformed
decision-making
Regional /
community
conflicts,
increased
inequities
due to access
Overexploitation,
industry
re-location,
human relocation
necessitated by
food/livelihood
insecurity
Resource
detachment,
loss of cultural
identity,
knowledge &
social pride
Adaptation outcome
s
Individual
Figure Cross-Chapter Box MOVING PLATE.2 | Common adaptation options, limitations and potential for adaptation and maladaptation in aquatic
and terrestrial species with climate-induced movement of food species and reliant peoples.
Cross-Chapter Box: MOVING PLATE (continued)
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(a) Documented fisheries adaptive capacity to climate change
(b) Regional seafood-relevant micronutrient deficiency risk (Calcium, Iron, Zinc, Vitamin A)
Current fisheries adaptive capacity and regional micronutrient deficiency risks related to seafood-
relevant micronutrients in human diets
0.9
0.5
0.0
0.1
0.2
0.3
0.4
0.6
0.7
0.8
1.0
Adaptive
Capacity Index
90
50
0
10
20
30
40
60
70
80
100
Nutritional
dependence
No data
Figure Cross-Chapter Box MOVING PLATE.3 | Global documented fisheries adaptive capacity to climate change and regional seafood micronutrient
deficiency risk.
Ocean areas are delineated into FAO (Food and Agricultural Organization of the United Nations) regions. Fisheries management adaptive capacity is a
function of: averaged GDP World Development Indicators for 2018 (World Bank, 2020); climate awareness assessments of 30 of the FAO recognised most recent RFMOs
with direct fisheries linkages (see Supplementary Material SM5.5); governance effectiveness index based on six aggregate indicators (voice and accountability, political
stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law, control of corruption) from 2018 World Governance Indicator (World
Bank, 2019) data; and heterogeneity of countries within each FAO zone (highly heterogeneous regions are less likely to establish sustainable and efficient fisheries
management for the entire FAO zone). Land area represents the percentage regional averaged seafood micronutrient deficiency risk of calcium, iron, zinc and vitamin A
from 2011 data (Beal et al., 2017).
In terrestrial, marine and freshwater systems, human populations already impacted by poverty and hunger experience greater risk under
climate change. Future food security will depend on access to other sustainable sources either via transnational agreements or resource/
livelihood diversification. Sudden shocks across food production systems (Cottrell et al., 2019) can lead to increases in fisheries harvest
Cross-Chapter Box: MOVING PLATE (continued)
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and wild meat consumption, and following food species may result in community relocations or disruption and loss of access to historical
places of attachment (
high confidence
) (Pecl et al., 2017; Lenoir et al., 2019; Meredith et al., 2019; Melbourne-Thomas et al., 2021; see
Cross-Chapter Box MIGRATE in Chapter 7). Ecosystem-based management approaches exist for terrestrial, marine and freshwater
systems, but have proved successful only with early engagement of local small-scale, subsistence fishers/harvesters, utilising Indigenous
knowledge and local knowledge and needs, in addition to those of larger-scale operators (
high confidence
) (Huntington et al., 2015;
McGrath and Costello, 2015; Huq and Stubbings, 2016; Huq et al., 2017; Raymond-Yakoubian et al., 2017; Nalau et al., 2018; Raymond-
Yakoubian and Daniel, 2018; Pecl et al., 2019; Planque et al., 2019). Currently, there are large regional differences in climate literacy in
RFMOs (Sumby et al., 2021) which, when combined with low governance and GDP per capita, will limit adaptation capacity and increase
vulnerabilities, particularly for tropical and subtropical regions already at increased risk due to poleward species migrations (see
Figure MOVING PLATE.3 this chapter). Trade will be an alternative to compensate for the moving plate but has specific risks that can
amplify inequities and maladaptation (Asche et al., 2015; Vianna et al., 2020).
Cross-Chapter Box: MOVING PLATE (continued)
5.9
Ocean-Based and Inland Aquaculture
Systems
Global aquaculture provides more fish for human consumption
than wild capture fisheries, with projected provisioning of 60% by
2030 (FAO, 2018c). Aquaculture can contribute to SDGs by reducing
poverty and food insecurity, filling increasing aquatic food demand
shortages from declining capture fisheries production (
medium
confidence
) (Figure 5.13a and c, World Bank, 2013; Béné et al.,
2016; Hambrey, 2017; Beveridge et al., 2018b; Kalikoski et al.,
2018; Belton et al., 2020) and improving social inequities for poor
rural communities (Béné et al., 2016; FAO, 2018c; Vannuccini et al.,
2018; Pongthanapanic et al., 2019). Global aquaculture production
reached 82 million tonnes (Mt) of food fish, crustaceans, molluscs
and other aquatic animals from inland (51 Mt) and marine (31 Mt)
systems, and 32 Mt of aquatic plants in 2018 (FAO, 2020d). China,
India, Indonesia, Vietnam, Bangladesh, Egypt, Norway and Chile are
major production regions (FAO, 2020d). The range of species, farming
methods and environments makes aquaculture the most diverse,
long-standing farming practice in the world, with an estimated global
sectoral value of USD 250 billion in 2018 (Figure 5.13b and 5.14d,
Bell et al., 2019; Harland, 2019; FAO, 2020d; Houston et al., 2020;
Metian et al., 2020), but it is dominated by 20 finfish, 9 mollusc and 6
crustacean species (FAO, 2020). Inland aquaculture in freshwater and
coastal ponds accounts for 85–90% of farmed production (Beveridge
et al., 2018b; Naylor et al., 2021). Globally, 20.5 million people are
engaged in aquaculture (FAO, 2020d), where marine finfish farming is
primarily conducted by high-income countries and inland production
is dominated by small-scale producers in lower-middle-income
countries (Vannuccini et al., 2018).
5.9.1
Observed Impacts
Marine aquaculture food production is being impacted directly
and indirectly by climate change (
high confidence
) (Bindoff et al.,
2019). Ocean pH and oxygen levels are declining, whereas global
warming, sea level rise and extreme events are increasing (Cross-
Chapter Box SLR in Chapter 3, Canadell et al., 2021; Eyring et al.,
2021; Fox-Kemper et al., 2021; Lee et al., 2021;). Marine heatwaves
have been increasing in both incidence and longevity over the past
century (Frolicher and Laufkotter, 2018; Oliver et al., 2018; Bricknell
et al., 2021), with productivity consequences for marine aquaculture
(mariculture), carbon sequestration and local species extinctions (
high
confidence
) (Weatherdon et al., 2016; Smale et al., 2019). Temperature
increases related to El Niño climatic oscillations have caused mass fish
mortalities either through warming waters (e.g., Pacific threadfin in
Hawaii (McCoy et al., 2017)) or associated HABs (e.g., 12% loss of
Atlantic salmon as well as other fish and shellfish in Chile in 2016,
with estimated USD 800 million in losses (
high confidence
) (Clement
et al., 2016; Apablaza et al., 2017; Leon-Munoz et al., 2018; Trainer
et al., 2020)). Increases in sea lice parasite infestations on salmon are
related to higher salinity and warmer waters (
medium confidence
)
(Groner et al., 2016; Soto et al., 2019). Ocean acidification is having
negative impacts on the sustainability of mariculture production (
high
confidence
) (Bindoff et al., 2019), with observed impacts on shellfish
causing significant production and economic losses for regions,
estimated at losses of nearly USD 110 million by 2015 in the Pacific
Northwest (Barton et al., 2015; Ekstrom et al., 2015; Waldbusser et al.,
2015; Zhang et al., 2017b; Doney et al., 2020). Ocean oxygen levels are
declining due to climate change (Hoegh-Guldberg et al., 2018; IPCC,
2021), and decreased oxygen (hypoxia) has negative impacts on fish
physiology (Cadiz et al., 2018; Hvas and Oppedal, 2019; Martos-Sitcha
et al., 2019; Perera et al., 2021), fish growth, behaviour and sensitivity
to concurrent stressors (
high confidence
) (Stehfest et al., 2017; Abdel-
Tawwab et al., 2019).
Observed impacts on inland systems have generally been site and
region specific (
high confidence
) (Hoegh-Guldberg et al., 2018; Sainz
et al., 2019; Lebel et al., 2020). Salinity intrusions into freshwater
aquaculture systems have changed oxygen and water quality of inland
ponds, resulting in mortalities in areas such as India and Bangladesh
(
medium confidence
) (Dubey et al., 2017; Dabbadie et al., 2018). Rapid
changes in temperature, precipitation, droughts, floods and erosion
have created significant production losses for aquatic farmers in
Cambodia, Laos, Myanmar, Thailand, Viet Nam and Ghana (
medium
confidence
) (Asiedu et al., 2017; Pongthanapanic et al., 2019; Lebel
et al., 2020). Algal blooming and inland lake browning related to
warming was found to negatively affect fish biomass (van Dorst et al.,
2018). Observed indirect effects of climate change on aquaculture
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include extreme weather events that damage coastal aquaculture
infrastructure or enable flooding, both leading to animal escapees
(e.g., fish, shrimp), damaged livelihoods and interactions with wild
species (
high agreement
,
medium evidence
) (Beveridge et al., 2018b;
Dabbadie et al., 2018; Kais and Islam, 2018; Pongthanapanic et al.,
2019; Ju et al., 2020).
Global and regional aquaculture production
(b) Diversity of aquaculture groups cultured in 2016
62
%
Fish
12
%
Crustacea
1% Amphibians and reptiles
2% Aquatic invertebrates
11
%
Molluscs
7
%
Aquatic
plants
Africa
America
s
Europe
Oceania
(c) Aquaculture share of total
fisheries production
18% 18%
18% 18%
(a) World aquaculture and capture fisheries production
250,000
200,000
150,000
100,000
50,000
0
1950 1954 1958 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018
Capture
fisheries
Aquaculture
production
Marine
Inland
Marine
Inland
Tonnes
Tonnes of
production
(Log scale)
1
100
10,000
1,000,000
100,000,000
Fish
Crustacea
Molluscs
Aquatic plants
Freshwater
Brackish
Marine
(d) Global aquaculture species production in 2018
Africa
Asia
America
s
Europe
Oceani
a
Africa
Asia
America
s
Europe
Oceani
a
Africa
Asia
America
s
Europe
Oceani
a
Africa
Asia
America
s
Europe
Oceani
a
Asia
China alone
75%
China
excluded
42%
Figure 5.13 | Global and regional aquaculture production.
(a)
World wild capture fisheries and aquaculture inland (freshwater and brackish) and marine production from
1950 to 2018;
(b)
diversity of aquaculture groups cultured in 2016;
(c)
regional aquaculture share of total fisheries production; and
(d)
global aquaculture species production in
2018 by region and type (freshwater, brackish or marine) on a logged scale (FAO, 2018c; FAO, 2020c; FAO, 2020d).
5.9.2
Assessing Vulnerabilities
Aquaculture vulnerability assessments have shown that countries from
both high and low latitudes are highly vulnerable to climate change,
where vulnerability is driven by particular exposures, economic reliance,
type of production sector (freshwater, brackish, marine) and adaptive
capacity (
high confidence
) (Handisyde et al., 2017; Soto et al., 2018).
Regional aquaculture vulnerabilities and risk mitigation potentials
for the major FAO reporting regions are shown in Figure 5.14. Best
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practice guidelines for assessments exist (Brugère et al., 2019; FAO,
2020d), but in practice most only cover some climatic drivers (
medium
agreement
,
limited evidence
) (Soto et al., 2018). Holistic vulnerability
assessments include ecosystem services (Custódio et al., 2020; Gentry
et al., 2020) and farming practices which can exacerbate production
pressures (stocking densities, eutrophication, fish stress) (Soto et al.,
2018; Sainz et al., 2019). Common vulnerabilities to inland and marine
aquaculture include increasing incidence and toxicity of HABs related
to warming waters, causing fish kills and product consumption risks,
negatively impacting the productivity and stability of production
sectors and reliant communities (
high confidence
) (Soto et al., 2018;
Aoki et al., 2019; Bannister et al., 2019).
There is
high confidence
that inland aquaculture in Southeast Asia
is highly vulnerable to climate change, due to fluctuations in water
resources either through climatic variability in precipitation, flooding
or salinity inundation or through competition (Handisyde et al., 2017;
Nguyen et al., 2018; Soto et al., 2018; Islam et al., 2019; Nguyen et al.,
2019b; Prakoso et al., 2020). Studies in Bangladesh and Indonesia
highlighted regional and species-specific vulnerabilities (Prakoso et al.,
2020) and roles of governance in vulnerability reduction (Islam et al.,
2019).
In the marine sector, vulnerability models (Brugère and De Young,
2015; Handisyde et al., 2017) have been adapted and applied to
semi-quantitative spatial risk assessments for Chilean Atlantic
salmon, where analysis of exposure threat coupled with mortality
and temperature farm data could enhance salmon production (Soto
et al., 2019). Vulnerability assessments in Korea (RCP8.5 temperature
increase of 4–5°C by 2100) (Kim et al., 2019a) and the USA (ocean
acidification, Barton et al., 2015; Ekstrom et al., 2015) found major
exposure-related vulnerabilities for seaweeds and shellfish, with
reduced vulnerabilities under higher production control and adaptive
capacity. Global bivalve vulnerability assessments (RCP8.5 by 2100)
show high vulnerabilities for major producing countries related to
cyclones (China, Japan, South Korea, Thailand, Viet Nam and North
Korea), regional risk of high sensitivity and low adaptive capacity
(Chile, Peru, Spain, Italy), with few major producers (France, the
Netherlands and USA) anticipated to remain moderately vulnerable
by 2100 (Stewart-Sinclair et al., 2020).
Climate uncertainty and data limitations hinder vulnerability assess-
ments (
high confidence
), so broader vulnerabilities and qualitative as-
sessments can be used (Brugère and De Young, 2015; Soto et al., 2018;
Brugère et al., 2019; Cochrane et al., 2019). Filling data gaps with mon-
itoring (
high confidence
), increasing governmental support to assist
particularly vulnerable small- and medium-scale farmers with increased
costs associated with risk management and uncertainty (
medium con-
fidence
) and the early inclusion of community stakeholders (
high agree-
ment
,
medium evidence
) can reduce vulnerabilities (Handisyde et al.,
2017; Dabbadie et al., 2018; Soto et al., 2018; Bindoff et al., 2019; Co-
chrane et al., 2019).
5.9.2.1 Gender and other social vulnerability and roles in
aquaculture
There are regional differences in women’s roles, responsibilities
and involvement in adaptation strategies in the aquaculture sector.
Women comprise 14% of the 2018 global aquaculture workforce
of 20.5 million (FAO, 2020c), representing up to 42% of the salmon
workforce in Chile (Chávez et al., 2019), predominantly in processing
roles (Gopal et al., 2020). In the majority of lower-middle-income
countries, seaweed culture is dominated by women in family-owned
businesses as in Zanzibar and the Philippines (Brugere et al., 2020;
Ramirez et al., 2020), where women are not always paid directly
but contribute to family incomes (
high confidence
) (Msuya and
Hurtado, 2017; Brugere et al., 2020; Ramirez et al., 2020). In India,
women collect stocking juveniles and assist in pond construction; in
Bangladesh, women do the same tasks as men; and in Ghana, women
undertake post-harvest fishing activities (Lauria et al., 2018). Women
employed in aquaculture cooperatives gained adaptive capacity, which
reduced gender inequities (
medium confidence
) (Farquhar et al., 2018;
Gonzal et al., 2019), but lack of financial access for women can create
gender inequity at larger commercial scales (Gurung et al., 2016; Call
and Sellers, 2019). Women in aquaculture experience competing roles
between employment, childcare and home duties (
high confidence
)
(Morgan et al., 2015; Lauria et al., 2018; Chávez et al., 2019; see Cross-
Chapter Box GENDER in Chapter 18) and differ from men in terms
of perceptions of environmental risk, climate change and adaptation
behaviour, with limited contributions to decision making (
medium
confidence
) (Barange and Cochrane, 2018). Therefore, effective
climate aquaculture adaptation options need to address gender
inequity, such as suitable technology designs that fit with social
norms and access to credit to facilitate independent uptake (
medium
evidence
,
high agreement
) (Morgan et al., 2015; Oppenheimer et al.,
2019). Generalised best practices for gender-sensitive approaches to
adaptation are relevant for aquaculture (UNFCCC, 2013).
5.9.3
Projected Impacts
Projected impacts on regional inland and marine aquaculture production
are summarised in Figure 5.15.
5.9.3.1 Inland freshwater and brackish aquaculture
Predicted sea level and temperature rise will result in coastal
inundation into brackish and inland aquaculture systems (
high
confidence
) (Mehvar et al., 2019; Nhung et al., 2019; Oppenheimer
et al., 2019; Fox-Kemper et al., 2021), with negative impacts on
aquaculture production in Viet Nam, East Africa and Jamaica (
medium
confidence
) (Lebel et al., 2018; Nguyen et al., 2018; Bornemann
et al., 2019). Precipitation and temperature changes will cause
drought and flooding, negatively affecting near-shore fishpond
productivity (
limited evidence
) (Canevari-Luzardo et al., 2019), but
provide competitive advantages to non-native shrimp in Australia
(
limited evidence
) (Cerato et al., 2019). Warming and acidification
will increase HAB toxicity in freshwater systems, but responses may
be strain-specific (Griffith and Gobler, 2020; Hennon and Dyhrman,
2020). As for molluscs in marine systems, projected climate change
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Assessment of inland freshwater and brackish aquaculture, and marine aquaculture
vulnerabilities and mitigation potential
Mitigation confidence level
Vulnerability level
Vulnerability confidence level
Medium
Low
Mitigation potential
High
Medium
Low
Vulnerability
Food security at local level
Livelihood
Land use conflict
Social inequality
Feed conversion efficency
Governance
Low greenhouse gas emission species
Water use conflict
Alternative energies
Mitigation
(a) Inland aquaculture (freshwater and brackish)
Vulnerability
Food security at local level
Livelihood
Coastal and marine use conflict
Food conversion efficiency
Governance
Low greenhouse gas emission species
Mitigation
(b) Marine aquaculture
Africa
(Sub-Saharan)
Tilapia,
Catfish,
Carp
Seaweed,
Prawn,
Mussels
Northern
America
Catfish,
Crawfish,
Trout
Oysters,
Salmon,
Clams
Latin America
and the
Caribbean
Tilapia, Pacu,
Salmonids,
Carp
Shrimp,
Salmon,
Mussels,
Seaweed
Europe
Carp,
Salmonids
Salmon,
Sea Bream,
Seabass,
Mussels,
Oysters
Asia-
Pacific
Tilapia, Catfish,
Prawn, Crayfish,
Carp, Crab
Molluscs, Shrimp,
Seaweed,
Milkfish, Crab,
Grouper,
Sea Bream
Africa
(Near East and
Northern)
Tilapia,
Trout,
Carp
Mullet,
Shrimp,
Sea Bream
Source of feeds
Social inequality
Alternative energies
Source of feeds
High
Figure 5.14 | Assessment of inland freshwater and brackish aquaculture
(salinities of <10 ppm and/or no connection to the marine environment)
(a)
and marine
aquaculture vulnerabilities and mitigation potential per major FAO production zones
(b).
See SM5.6 (Tables SM5.5, 5.6, 5.9, 5.10) for assessment methodologies.
in freshwater and brackish systems may limit the availability of wild-
sourced juveniles from fisheries (Beveridge et al., 2018). Projected
impact studies for the inland and small-scale aquatic sectors are very
limited (Halpern et al., 2019; Galappaththi et al., 2020b); therefore,
this is a noted knowledge gap.
5.9.3.2 Marine Aquaculture
5.9.3.2.1 Finfish culture
Global projections of ocean warming, primary productivity and ocean
acidification predict suitable habitat expansions and short-term growth
benefits for finfish aquaculture for some regions (
medium confidence
)
(see Figure 5.15) until thermal tolerances or productivity constraints
are exceeded by 2090 (Beveridge et al., 2018b; Dabbadie et al.,
2018; Froehlich et al., 2018a; Catalán et al., 2019; Thiault et al., 2019;
Falconer et al., 2020a). Sensitivities for marine finfish may be high
even under +1.5–2.0°C (
medium confidence
) (Gattuso et al., 2018),
resulting in finfish farms moving northward to maintain productivity
(e.g., Arctic (Troell et al., 2017)). Downscaled projections of regionally
specific tolerances (Klinger et al., 2017) may be particularly useful for
management and planning; a 0.5°C rise is predicted for Chilean salmon
aquaculture (Soto et al., 2019), and potential negative impacts on
productivity in Norway by 2029 have been projected (
limited evidence
)
(Falconer et al., 2020a). Marine heatwaves are predicted to increase in
occurrence, intensity and persistence under RCP4.5 or RCP8.5 by 2100
(Oliver et al., 2019; Bricknell et al., 2021), with risk partly mitigated
by husbandry (
medium confidence
) (McCoy et al., 2017). Generally,
negative impacts are predicted for marine species, with residual risk
increasing with level of exposure (Sara et al., 2018; Smale et al.,
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2019), where warming will affect oxygen solubility and reduce salmon
culture capacity (
limited evidence
) (Aksnes et al., 2019, Chapter 3)
and combine with increasing incidence of HABs (
high confidence
)
resulting in negative impacts for food security and nutrition and health
(Oppenheimer et al., 2019; Colombo et al., 2020; Glibert, 2020; Raven
et al., 2020). Climate change is predicted to affect the incidence,
magnitude and virulence of finfish disease such as
Vibriosis
(Barber
et al., 2016; Mohamad et al., 2019a; Mohamad et al., 2019b), but
specific host–pathogen–climate relationships are not yet established
(
high confidence
) (Slenning, 2010; Marcogliese, 2016; Montanchez
et al., 2019; Bandin and Souto, 2020; Behringer et al., 2020; Filipe et al.,
2020; Montanchez and Kaberdin, 2020). Projected climate change will
Confidence level
Assessment of projected impacts of climate change
on inland freshwater and brackish aquaculture, and marine aquaculture
Direction of impact
Negative
Very
negative
Neutral
or mixed
effects
Very
positive
Positive
(a) Inland aquaculture (freshwater and brackish)
(b) Marine aquaculture
Africa
(Sub-Saharan)
Tilapia,
Catfish,
Carp
Seaweed,
Prawn,
Mussels
Northern
America
Catfish,
Crawfish,
Trout
Oysters,
Salmon,
Clams
Latin America
and the
Caribbean
Tilapia, Pacu,
Salmonids,
Carp
Shrimp,
Salmon,
Mussels,
Seaweed
Europe
Carp,
Salmonids
Salmon,
Sea Bream,
Seabass,
Mussels,
Oysters
Asia-
Pacific
Tilapia, Catfish,
Prawn, Crayfish,
Carp, Crab
Molluscs, Shrimp,
Seaweed,
Milkfish, Crab,
Grouper,
Sea Bream
Africa
(East and
Northern)
Tilapia,
Trout,
Carp
Mullet,
Shrimp,
Sea Bream
Global warming
Deoxygenation
Freshwater availablility
Precipitation changes (including droughts)
Eutrophication
Harmful algal blooms
Food safety
Sea level rise
Floods
Cyclones/hurricanes/extreme events
Pathogens and parasites
Juvenile availability
Aquaculture feed
Global warming
Deoxygenation
Precipitation changes (including droughts and freshwater discharge)
Acidification
Eutrophication
Harmful algal blooms
Food safety
Sea level rise
Extreme wave heights
Cyclones/hurricanes/severe storms
Circulation patterns and strength
Pathogens and parasites
Juvenile availability
Aquaculture feed
Primary productivity
Low
Medium
High
Figure 5.15 | Assessment of projected impacts of climate change on inland freshwater and brackish aquaculture
(salinities of <10 ppm and/or no connection to
the marine environment)
(a)
and marine aquaculture
(b)
per major FAO production zones. See SM5.6 (Tables SM5.7, 5.11) for assessment methodologies.
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Table 5.11 |
Projected impacts of climate on specific inland, brackish and marine culture systems and species.
Exposure
Scenario
Region
Production
system
Species
Impact
Reference
Temperature increase
RCP4.5 and RCP8.5 by
2050
Northern
Thailand
Inland
Nile tilapia
Reduced productivity
Lebel et al. (2018)
Precipitation change
(drought, hurricane,
heavy rainfall)
–
Jamaica
Inland
Tilapia
Reduced productivity, infrastructure
damage
Canevari-Luzardo et al.
(2019)
Temperature increase
4°C increase, B2, A1B
by 2100
Australia
Inland
Freshwater
shrimp
Increased production in non-native
zones
Cerato et al. (2019)
Temperature increase,
ocean acidification,
primary productivity
declines
CMIP5 RCP8.5 in 20-year
increments to 2090
Global
Marine
Finfish species
Increased suitable habitat
expansion for regions (Russia,
Norway, USA Alaska, Denmark,
Canada). By 2100, reduction in
productivity for major producers
(Norway, China)
Froehlich et al. (2018a),
Thiault et al. (2019)
Temperature increase
2–5°C increase under
RCP8.5
Europe
Marine
Atlantic salmon
Increased growth
Catalán et al. (2019)
Temperature increase
RCP4.5 to 2029
Norway
Marine
Atlantic salmon
Growth threshold reached by 2029
Falconer et al. (2020a)
Temperature increase
Downscaled CM2.6 by
2050
Global
Marine
Atlantic salmon,
cobia and sea
bream
Increased or decreased growth
rates depending on region
Klinger et al. (2017)
Temperature increase,
ocean acidification,
primary productivity
declines
CMIP5 RCP8.5 in 20-year
increments to 2090
Global
Marine
Shellfish
Overall declines in suitable habitat
globally, up to 50–100% reductions
in regions in China, Thailand and
Canada
Froehlich et al. (2018a)
Temperature increase
CMIP5 RCP8.5 by 2050,
2100
Italy
Marine
Clams
Negative impacts for juvenile
timing, spatial distribution, and
quality
Ghezzo et al. (2018)
Temperature increase
CMIP5 RCP2.6 and
RCP8.5 by 2035, 2070
France
Marine
Oysters
Increase incidence of oyster
mortality; increase by 2035 to
annual occurrence by 2070
Thomas et al. (2018)
Temperature increase
RCP2.6 and RCP8.5 by
2050
Global
Marine
Shellfish
Species reduction (10–40%) in
tropical and subtropical regions,
with increase (40%) in higher
latitudes
Oyinlola et al. (2020)
Temperature increase,
ocean acidification
Ecopath with RCP8.5 by
2100 (2.8°C warming
and pH 7.89)
USA
Marine
Shellfish
Reduction primary productivity
and subsequent bivalve carrying
capacity
Chapman et al. (2020)
Temperature increase,
stratification change
RCP8.5 by 2088–2099
Spain
Marine
Mussels
Decline in mussel optimal culture
conditions of 60% in upper and
30% in deeper waters by 2099
Des et al. (2020)
Temperature increase,
ocean acidification
RCP2.6 and 8.5 by
2070–2090
Global
Marine
Shellfish
Under RCP8.5, a decline in
shellfish production due to primary
productivity reduction in tropical
regions and gains in high latitudes.
Under RCP2.6, marine production
will have net gain
Thiault et al. (2019)
Temperature increase
4°C increase
Global
Marine
Vibrio
spp.
(mortality
causative agent)
Increased virulence
Montanchez et al. (2019)
Temperature increase
(marine heatwave)
5°C increase
Global
Marine
Oysters
Increased oyster mortality
Green et al. (2019)
Ocean acidification
~2000 ppm CO
2
Global
Marine
Oysters
Impaired immune function
Cao et al. (2018b)
Ocean acidification
RCP8.5 in 20-year
increments to after 2099
USA
Marine
Shellfish
Regional projected vulnerabilities;
southern Alaska and Pacific
Northwest at more immediate risk
Ekstrom et al. (2015)
Ocean acidification
A1B and RCP8.5 by 2100
UK
Marine
Shellfish
Regional projected vulnerabilities;
Wales and England at more
immediate risk
Mangi et al. (2018)
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also increase competition for feed ingredients between aquatic and
terrestrial animal production systems (see Section 5.13.2.).
5.9.3.2.2 Shellfish culture
Globally, there is overall
high confidence
that suitable shellfish
aquaculture habitat will decline by 2100 under projected warming,
ocean acidification and primary productivity changes, with
significant negative impacts for some regions and species before
2100 (Table 5.9, Froehlich et al., 2018a; Ghezzo et al., 2018). Shellfish
growth will increase with warming waters until tolerances are
reached, such as through extreme El Niño events (
high confidence
)
(Beveridge et al., 2018b; Dabbadie et al., 2018; Liu et al., 2018b; Liu
et al., 2020). Rising temperatures and ocean acidification will result
in losses of primary productivity and farmed species from tropical and
subtropical regions, and gains in higher latitudes (
high confidence
)
(Froehlich et al., 2018a; Aveytua-Alcazar et al., 2020; Chapman
et al., 2020; Des et al., 2020; Oyinlola et al., 2020), but net marine
production gains could be achieved under strong mitigation (Thiault
et al., 2019). Shellfish
Vibrio
infections will increase with warming
waters and extreme events, increasing shellfish mortalities (
medium
confidence
) (Green et al., 2019; Montanchez et al., 2019), with ocean
acidification impairing immune responses (
limited evidence
) (Cao
et al., 2018b). Bivalve larvae are known to be highly vulnerable to
ocean acidification (
high confidence
) (see Section 3.3, Bindoff et al.,
2019), with projected regional and species-specific levels of impact
(
high confidence
) (Ekstrom et al., 2015; Zhang et al., 2017b; Mangi
et al., 2018) (Greenhill et al., 2020). Ocean acidification is also
projected to weaken shells, affecting productivity and processing
(
high confidence
) (Martinez et al., 2018; Cummings et al., 2019) and
dependent livelihoods (Doney et al., 2020).
5.9.3.2.3 Aquatic plant culture
There is
medium confidence
that cultivated seaweeds are predicted
to suffer habitat loss resulting in population declines and northward
shifts (Table 5.11).
5.9.3.2.4 Societal impacts within the production system
Marine aquaculture provides distinct ecosystem services through
provisioning (augmenting wild fishery catches), regulating (coastal
protection, carbon sequestration, nutrient removal, improved water
clarity), habitat and supporting (artificial habitat) and cultural (livelihoods
and tourism) services (Gentry et al., 2020), which vary with species,
location and husbandry (Alleway et al., 2019). Projected thermal increases
of 1.5°C will reduce ecosystem services, further reduced under 2°C
warming, with associated increases in acidification, hypoxia, dead zones,
flooding and water restrictions (
medium confidence
) (Hoegh-Guldberg
et al., 2018). Sudden production losses from extreme climate events can
exacerbate food security challenges across production sectors, including
aquaculture, increasing global hunger (
high confidence
) (Cottrell et al.,
2019; Food Security Information Network, 2020). While aquaculture
provides positive influences such as food security and livelihoods, there
are negative concerns over environmental impacts (including high
nutrient loads from sites) and socioeconomic conflicts (Alleway et al.,
2019; Soto et al., 2019), and adoption of ecosystem approaches is
dependent on particular user groups and regions (Gentry et al., 2017;
Brugère et al., 2019; Gentry et al., 2020). In coastal Bangladesh, projected
saline inundation to wetland ecosystem services will result in ecosystem
services losses of raw materials and food provisioning, ranging from
USD 0 to 20.0 million under RCP2.6 to RCP8.5 scenarios (Mehvar et al.,
2019). Mangrove deforestation for shrimp farming in Asia negatively
impacts ecosystem services and reduces climate resilience (
medium
confidence
) (Mehvar et al., 2019; Nguyen and Parnell, 2019; Reid et al.,
2019; Custódio et al., 2020), while mangrove reforestation efforts may
have some effectiveness in re-creating important nursery grounds for
aquatic species (
low confidence)
(Gentry et al., 2017; Chiayarak et al.,
2019; Hai et al., 2020). Families are highly vulnerable to climate change
where nutritional needs are being met by self-production, such as in
Mozambique, Namibia (Villasante et al., 2015), Zambia (Kaminski et al.,
2018) and Bangladesh (
high confidence
) (Pant et al., 2014). Climate
change will therefore affect multiple ecosystem services where ultimately
decisions on balance or trade-offs will vary with regional perceptions of
service value (
high confidence
).
5.9.4
Aquaculture Adaptation
5.9.4.1 Adaptation planning
Aquaculture is often viewed as an adaptation option for fisheries
declines, thereby alleviating food security from losses of other climate
change impacts (Sowman and Raemaekers, 2018; Johnson et al.,
2020) such as Pacific Islands freshwater aquaculture, Bangladesh crop-
aquaculture systems or Viet Nam rice–fish cultivations (Soto et al.,
Exposure
Scenario
Region
Production
system
Species
Impact
Reference
Ocean acidification
RCP2.6 and RCP8.5 by
2300
East China
Marine
Shellfish
Carbonate saturation projected to
decrease by 13% and 72% under
RCP2.6 and RCP8.5 respectively,
projecting decreased shellfish
productivity
RCP2.6 and RCP8.5
by 2300 (Zhang et al.,
2017b)
Increased temperature
RCP2.6 and RCP8.5 by
2100
North Sea
Marine
Seaweed
Northward population shift by 110–
163 km and 450–635 km under
RCP2.6 and RCP8.5, respectively
Westmeijer et al. (2019)
Increased temperature
RCP4.5 and RCP8.5 by
2090
Japan
Marine
Kelp
Habitat decline to 30–51% and
0–25% under RCP4.5 and RCP8.5,
respectively
Sudo et al. (2020)
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2018). Many adaptations are specific to regions, countries or sectors,
implemented on a regional to national scale (FAO, 2018c; Galappaththi
et al., 2020b). Adaptation likelihood (potential), effectiveness and risk
of maladaptation was assessed per major FAO production region for
inland, brackish and marine aquaculture (Figure 5.16) production
systems. Potential adaptation measures to reduce production loss can
be built upon existing adaptation planning and guidelines, to reduce
the risk of maladaptation including feedback loops (e.g., FAO, 2015;
Bueno and Soto, 2017; Dabbadie et al., 2018; FAO, 2018c; Poulain
et al., 2018; Brugère et al., 2019; Pham et al., 2021; Soto et al., 2021).
Large climate change adaptation strategies for the aquaculture sector
exist, such as in the USA (Link et al., 2015), Australia (Hobday et al.,
2017) and South Africa (Department of Environmental Affairs, 2016).
Lower-income countries often lack financial, technical or institutional
capacity for adaptation planning (Galappaththi et al., 2020b), but
examples include Bangladesh and Myanmar (FAO, 2018c), with
programmes offering adaptation funding (Dabbadie et al., 2018).
Early participation of stakeholders in adaptive planning has promoted
action and ownership of results (
high confidence
), such as in India
and the USA (Link et al., 2015; FAO, 2018c; Soto et al., 2018) Early
outreach, education and knowledge gap assessments raise awareness,
where utilisation of local knowledge and Indigenous knowledge
and scientific involvement support informed adaptive planning and
uptake for all stakeholders (
high confidence
) (Cooley et al., 2016; FAO,
2018c; Rybråten et al., 2018; Soto et al., 2018; McDonald et al., 2019;
Galappaththi et al., 2020b), as perceptions of climate risk and capacity
will vary (Tiller and Richards, 2018). Supporting the active involvement
of women helps address gender inequity and perceived risk,
particularly for smallholder farmers (
high confidence
) (Morgan et al.,
2015; Barange and Cochrane, 2018; FAO, 2018c; Avila-Forcada et al.,
2020). However, regional and national political influences, financial
and technical capacity, governance planning and policy development
will ultimately support or hinder adaptation for aquaculture (
high
confidence
) (Cooley et al., 2016; FAO, 2018c; Galappaththi et al.,
2020b; Greenhill et al., 2020).
5.9.4.2 Species selections and selective breeding
Adaptation options at the operational level include species selections,
such as cultivation of brackish species (shrimp, crabs) during dry seasons,
and rice-finfish in wetter seasons in Thailand (Chiayarak et al., 2019),
use of salt-tolerant plants in Viet Nam (Nhung et al., 2019; Paik et al.,
2020), converting inundated rice paddies into aquaculture, rotating
shrimp, and rice culture (
high confidence
) (Chiayarak et al., 2019).
Species diversification through co-culture, integrated aquaculture–
agriculture (e.g., rice–fish) or integrated multi-trophic culture (e.g.,
shrimp–tilapia–seaweed or finfish–bivalve–seaweed) may maintain
farm long-term performance and viability by: creating new aquaculture
opportunities; promoting societal and environmental stability; reducing
GHG emissions through reduced feed usage and waste; and carbon
sequestration (
medium confidence
) (see Section 5.10, Ahmed et al.,
2017; Bunting et al., 2017; Gasco et al., 2018, Soto et al., 2018; Ahmed
et al., 2019; Dubois et al., 2019; FAO, 2019c; Li et al., 2019; Freed et al.,
2020; Galappaththi et al., 2020b; Prasko et al., 2020; Tran et al., 2020).
In practice, most aquaculture operations concentrate on single-species
systems (Metian et al., 2020), and barriers such as land availability,
freshwater resources and lack of credit access may limit the uptake
and success of integrated adaptation approaches to climate change
(Ahmed et al., 2019; Tran et al., 2020; Kais and Islam, 2021).
Selective breeding can promote climate resilience (
medium
confidence
) (Klinger et al., 2017; Fitzer et al., 2019), and operations
have already intentionally, or unintentionally, selected for production
traits for changing conditions (de Melo et al., 2016; Tan and Zheng,
2020). Exposure of broodstock to future climate conditions may or
may not confer advantages to offspring (
moderate evidence
,
low
agreement
) (Parker et al., 2015; Griffith and Gobler, 2017; Thomsen
et al., 2017; Durland et al., 2019). Traditional pedigree developments
require extensive phenotypic data, but genomic selections can rapidly
select for robust climate-associated traits (Sae-Lim et al., 2017;
Gutierrez et al., 2018; Zenger et al., 2018; Houston et al., 2020; Tan and
Zheng, 2020). Genomic resources are available for salmon, rainbow
trout, coho, carp, tilapia, seabass, bream, turbot, flounder, catfish,
yellow drum, scallops, oysters and shrimp, but have been developed
for disease and growth selections rather than climate resistance
(Dégremont et al., 2015a; Dégremont et al., 2015b; Abdelrahman
et al., 2017; Gjedrem and Rye, 2018; Gutierrez et al., 2018; Guo et al.,
2018; Liu et al., 2018a; FAO, 2019d; Houston et al., 2020), although
bivalve selections for ocean acidification and warming resiliency are
underway (Tan and Zheng, 2020). Targeted genome editing could
modify phenotypes of major aquaculture species (Li et al., 2014a;
Elaswad et al., 2018; Yu et al., 2019; Houston et al., 2020), but uptake
is dependent upon national regulatory and public approvals. Local
adaptations within species with higher climate resiliencies may assist
in selections (Thomsen et al., 2017; Falkenberg et al., 2019; Scanes
et al., 2020; Toomey et al., 2020), but highlight the need to consider
specific farming environments for selective processes (Houston et al.,
2020). Projections of climate on aquaculture production traits are not
well understood (Lhorente et al., 2019); therefore, genetic diversity
needs to be maintained to ensure population fitness (
high confidence
)
(Bitter et al., 2019; Lhorente et al., 2019; Visch et al., 2019; Houston
et al., 2020; Mantri et al., 2020).
5.9.4.3 Farm site selection, infrastructure and husbandry
Land-based aquaculture systems including hatcheries may reduce
exposure to climatic extremes (due to better control of the culture
environment), limit water usage, reduce juvenile reliance and buffer
climate effects using optimal diets (
high confidence
) (Barton et al.,
2015; Reid et al., 2019; Cominassi et al., 2020). However, land-based
aquaculture requires large capital and operational costs and use of
land, increasing conflicts between land and water use, have increased
energy demands (increasing GHG if fossil fuels are the primary energy
source), require necessary expertise and will not reduce outgrowing
exposures (
high confidence
) (see Section 5.13, Beveridge et al., 2018b;
Soto et al., 2018; Tillotson et al., 2019; Costello et al., 2020; Prakoso
et al., 2020).
Geographical selection of marine farm sites may prevent climate
productivity declines (
medium confidence
) (Froehlich et al., 2018a;
Sainz et al., 2019; Oyinlola et al., 2020), particularly for temperature-
related mortality hotspots (Garrabou et al., 2019), HAB occurrences
(Dabbadie et al., 2018) or extreme events (Liu et al., 2020; Wu
et al., 2020). However, while downscaled climate forecasts facilitate
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localised adaptation planning (Falconer et al., 2020a), such projections
are rare (Whitney et al., 2020). GIS can be used for climate adaptive
planning along with routine site assessments (Falconer et al., 2020b;
Galappaththi et al., 2020b; Jayanthi et al., 2020). Building coastal
protection, stronger cages and mooring systems, and deeper ponds
and using sheltered bays can reduce escapees and mortalities related
to flooding, increased storms and extreme events (
medium confidence
)
(Dabbadie et al., 2018; Bricknell et al., 2021; Kais and Islam, 2021).
Inshore aquaculture in low-lying areas prone to sea level salinity
intrusion (e.g., Mekong delta and Viet Nam) have already implemented
Assessment of the likelihood and effectiveness of a range of adaptation options
for potential implementation in the near-term for inland freshwater and brackish aquaculture, and marine aquaculture systems
Maladapation confidence level
Adaptation (likelihood of
implementation and effectiveness)
Adaptation confidence level
High
Medium
High
Medium
Maladaptation (risk of)
High
Medium
Low
Combined food production
Biotechnology
Tolerant species/strain selections
Governance - national
Insurance and financial support
Early warning systems
Aquaculture feeds
Gender equity
Governance - local
(a) Inland aquaculture (freshwater and brackish)
(b) Marine aquaculture
Africa
(Sub-Saharan)
Tilapia,
Catfish,
Carp
Seaweed,
Prawn,
Mussels
Northern
America
Catfish,
Crawfish,
Trout
Oysters,
Salmon,
Clams
Latin America
and the
Caribbean
Tilapia, Pacu,
Salmonids,
Carp
Shrimp,
Salmon,
Mussels,
Seaweed
Europe
Carp,
Salmonids
Salmon,
Sea Bream,
Seabass,
Mussels,
Oysters
Asia-
Pacific
Tilapia, Catfish,
Prawn, Crayfish,
Carp, Crab
Molluscs, Shrimp,
Seaweed,
Milkfish, Crab,
Grouper,
Sea Bream
Africa
(East and
Northern)
Tilapia,
Trout,
Carp
Mullet,
Shrimp,
Sea Bream
Optimizing fisheries - aquaculture interactions
Best practice implementation
On-farm adaptation approaches
Spatial planning
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Combined food production
Biotechnology
Tolerant species/strain selections
Governance - national
Insurance and financial support
Early warning systems
Aquaculture feeds
Gender equity
Governance - local
Optimizing fisheries - aquaculture interactions
Best practice implementation
On-farm adaptation approaches
Spatial planning
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Adap.
Malad.
Low
Low
Figure 5.16 | Assessment of the likelihood and effectiveness of a range of adaptation options for potential implementation in the near term (next decade)
for inland freshwater and brackish aquaculture
(salinities of <10 ppm and/or no connection to the marine environment)
(a)
and marine aquaculture systems
(b)
per major
FAO production zone. See SM5.6 (Tables SM5.8, 5.12) for assessment methodologies.
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adaptation measures, such as conversion of land to mixed plant–
animal systems (Nguyen et al., 2019a), conversion of freshwater ponds
to brackish or saline aquaculture (Galappaththi et al., 2020b), building
of dams and dykes (Renaud et al., 2015) and intensification of shrimp
or fish pond culture to reduce water and land usage (Nguyen et al.,
2019b; Johnson et al., 2020). Other adaptation options for limited
water supply are government equitable water allocations and water
storage (
high confidence
) (Bunting et al., 2017; Galappaththi et al.,
2020b).
Feed formulations and improved feed conversion can reduce climate-
associated stress for freshwater species, significantly reducing waste
and increase sustainability (
medium confidence
) (FAO, 2018c; Gasco
et al., 2018; Chen and Villoria, 2019). Projected decreases in fish meal
and global targets of limiting warming to under 2°C may increase
the ratio of plant-based diets but reduce fish nutritional content
(see Sections 5.10 and 5.13, Hasan and Soto, 2017; Johnson et al.,
2020). Companies provide insurance in major production areas, but
aquaculture is considered high risk with large levels of small claims
(Secretan et al., 2007). Insurance covers natural disasters and disease,
helping to reduce and cope with climate-induced risk, enabling faster
livelihood recoveries and preventing poverty (
high agreement
,
limited
evidence
) (Xinhua et al., 2017; Kalikoski et al., 2018; Soto et al., 2018).
For example, small-scale shrimp farmers were willing to pay higher
premiums to manage risk, after participation in government pilot
insurance schemes, ensuring greater pay-outs if a mortality event
occurred (Nyguyen and Pongthanapanic, 2016; Pongthanapanic et al.,
2019). Technological innovations are more widely implemented in
larger operations, with Internet access promoting adoption at the
farm site (Joffre et al., 2017; Salazar et al., 2018). Improved farm
management is a key opportunity (
high confidence
) to reduce climate
risks on aquaculture, where Best Management Practices can increase
resiliency (Soto et al., 2018) and lower additional risk from non-
climatic stressors (Gattuso et al., 2018; Smith and Bernard, 2020), and
decision-tree frameworks can provide adaptation choices when events
occur (Nguyen et al., 2016).
5.9.4.4 Early-warning and monitoring systems
Globally, monitoring is increasing to fill scientific uncertainties
(Goldsmith et al., 2019) but is not often at spatial scales which
facilitate farm or regional adaptation management (Whitney et al.,
2020) or data complexities prevent direct uptake by operators,
resource managers and policymakers (
medium confidence
) (Soto
et al., 2018; Gallo et al., 2019). Specialised industry portals (Pacific
shellfish) and government-established monitoring programmes
(Chilean salmon) and other observational networks (e.g., Global
Ocean Acidification Observing Network (GOA-ON)) can provide
real-time monitoring and early-warning event alerts and facilitate
aquaculture decision making (
medium confidence
) (Cross et al., 2019;
Farcy et al., 2019; Soto et al., 2019; Tilbrook et al., 2019; Bresnahan
et al., 2020; Peck et al., 2020). Seasonal forecasting, downscaled
models and early-warning systems provide valuable regional or
farm site risk information (Hobday et al., 2018; Galappaththi et al.,
2020b; Whitney et al., 2020), but monitoring will need to be useful
for farmers, involve farmers, and be accurate, timely, cost-effective,
reviewed and maintained in order to ensure uptake (
high confidence
)
(Soto et al., 2018). Early-warning systems for HABs enable rapid
decision making and risk mitigation (
medium confidence
), such
as ocean colour monitoring in South Africa (Smith and Bernard,
2020), where early harvesting and additional husbandry were used
to minimise production and economic losses (Pitcher et al., 2019).
New tools, strategies and observations are needed to predict HAB
occurrences and range shifts with changing climate (
high confidence
)
(Schaefer et al., 2019; Tester et al., 2020), as there is uncertainty on
drivers of incidence and toxicity (Wells et al., 2020).
5.9.5
Contributions of Indigenous, Traditional and Local
Knowledge
Indigenous mariculture practices, such as intertidal clam gardens,
have been occurring for thousands of years, providing knowledge of
traditional practices still applicable to mariculture (Deur et al., 2015;
Jackley et al., 2016; Poulain et al., 2018; Bell et al., 2019; Toniello
et al., 2019). Indigenous groups differ in opinions on aquaculture
acceptability, implications for coastal management and territorial rights
(
high confidence
) (Young et al., 2019). Such perceptions may determine
culturally appropriate types and benefits of aquaculture (employment,
food diversification, income, building autonomy and skillsets), such as
in Australia (Petheram et al., 2013) and Canada (Young and Liston,
2010). Marginalised people, like small-scale aquaculture farmers in
lower-income and lower-middle-income countries, are often overlooked
and are not represented at a governance level (Barange et al., 2014;
Kalikoski et al., 2018). Therefore policy, economic, knowledge and
other support must ensure representation with traditional and other
stakeholder ecological knowledge at national, regional and local levels
to facilitate climate change adaptation and safeguard human rights for
poor and vulnerable groups (
high confidence
) (Kalikoski et al., 2018;
Poulain et al., 2018).
5.10
Mixed Systems
The food and livelihoods of many rural people depend on combinations
of crops, livestock, forestry and fisheries, and still information on these
mixed systems is scarce. Rural households in low- and middle-income
countries earn almost 70% of their income through mixed production
systems (Angelsen et al., 2014). These systems produce about half of
the world’s cereals, most of the fruits, vegetables, pulses, roots and
tubers, and most of the staple crops and livestock products consumed
by poor people in lower-income countries (Herrero et al., 2017). They
can help in adapting to climatic risks and reducing GHG emissions
by improving nutrient flows and improving the recycling of nutrients
within the production system and by increasing food production and
diet quality per unit of land and diversifying income sources (Smith
et al., 2019c). Indigenous groups often practice mixed production,
integrating crops, animals, fisheries, forestry and agroforestry through
traditional ecological knowledge.
Some evidence exists of the buffering capacity that integrated
systems can provide in the face of climate change (Gil et al., 2017).
This buffering, often affecting the farming system as a whole rather
than the individual agricultural enterprises involved, applies to some
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aquaculture–agriculture systems as well as to crop–livestock systems
(Bunting et al., 2017; Stewart-Koster et al., 2017). In some situations,
there may be trade-offs and constraints at the household level that
affect this resilience-conferring ability: for instance, mixed systems
often need relatively high levels of management skill, and extra labour
may be required (van Keulen and Schiere, 2004; Thornton and Herrero,
2015). The diversification of food production systems offers promise
for enhanced resilience at the global level (Kremen and Merenlender,
2018; Dainese et al., 2019; Section 5.4.4.4), though policies need
to provide adequate incentives for resource efficiency, equity and
environmental protection (Havet et al., 2014; Thornton and Herrero,
2014; Troell et al., 2014).
5.10.1 Observed Impacts
5.10.1.1 Mixed crop–livestock systems
Overall, there is
high confidence
that farm strategies that integrate
mixed crop–livestock systems can improve farm productivity and
have positive sustainability outcomes (Havet et al., 2014; Thornton
and Herrero, 2014; Herrero et al., 2015; Thornton and Herrero, 2015;
HLPE, 2019). The scale of the improvement varies between regions and
systems and is moderated by overall demand in specific food products
and the policy context. Integrated crop–livestock systems present
opportunities for the control of weeds, pests and diseases. They can
also provide a range of environmental benefits, such as increased soil
carbon and soil water retention, increased biodiversity and reduced
need for inorganic fertilizers (Havet et al., 2014; Thornton and Herrero,
2014; Herrero et al., 2015; Thornton and Herrero, 2015; HLPE, 2019).
Research indicates that mixed crop–livestock systems are often more
resilient to climate change
(medium confidence
). In the southern Afar
region of Ethiopia, crop–livestock households were more resilient than
livestock-only households to climate-induced shock (Mekuyie et al.,
2018). However, the
benefits of managing crop–livestock interactions
in response to climate change depend on local context. For example,
in higher-rainfall zones in Australia, Nie et al. (2016) found some yield
reductions and difficulty in maintaining groundcover. The systematic
review of Gil et al. (2017) concluded that the integration of crop and
livestock enterprises as an adaptation measure can enhance resilience
(FAQ 5.1).
Reconfiguration of mixed farming systems is occurring. In semi-
arid eastern Senegal, Brottem and Brooks (2018) found increasing
reliance on livestock production mostly because of changing climate
conditions. Many poorer households are having to rely on migration to
compensate for shortfalls in crop production arising from a changing
climate. Some farmers have successfully shifted to crop–livestock
systems in Australia, where they have allocated land and forage
resources in response to climate and price trends (Bell et al., 2014).
Mixed livestock–crop systems may increase burdens on women,
require managing competing uses of crop residues, and have higher
requirements of capital and management skills. These factors can
be challenging in many lower-income countries (Rufino et al., 2013;
Thornton and Herrero, 2015; Jost et al., 2016; Thornton, 2018). The
policy actions needed for the successful operation of mixed crop–
livestock systems may be similar across widely different situations:
good access to credit inputs and capacity building needed to facilitate
uptake (Hassen et al., 2017; Marcos-Martinez et al., 2017), and good
levels of market infrastructure (Ouédraogo et al., 2017; Iiyama et al.,
2018).
5.10.1.2 Mixed crop–aquatic systems
Households may have a mix of aquatic and land-based food
production, contributing to food security and nutrition and income
generation (Freed et al., 2020; see also discussion of aquaponics and
hydroponics in Section 5.10.4.3. and combined rice–aquatic species
production in Section 5.9.4). Failures in agricultural outputs due to
climate-associated factors may result in diversification to fisheries
as a way of alleviating food production shortfalls; for example,
fisheries landings may dramatically increase after agricultural failures
following hurricanes, which can subsequently create overfishing
collapses (Cottrell et al., 2019). Where climatic impact drivers affect
multiple sectors, adaptation may become more difficult because of the
interacting challenges (Cottrell et al., 2019). One study of 12 countries
with high food insecurity levels found that fish-reliant households
utilised as much land as those not reliant on fish (Fisher et al., 2017).
To meet food security requirements, most of these households needed
to both farm and fish, illustrating the interdependence of aquatic–
terrestrial food systems.
5.10.1.3 Agroforestry systems
Agroforestry is frequently mentioned as a strategy to adapt to and
mitigate climate change and address food security (de Coninck et al.,
2018; Smith et al., 2019c). There is strong evidence of net positive
biophysical and socioeconomic effects of agroforestry systems under
both smallholder and large-scale mechanised production systems
(Quandt et al., 2017; Hoegh-Guldberg et al., 2018; Sida et al., 2018;
Wood and Baudron, 2018; Table 5.10; Cross-Chapter Box NATURAL in
Chapter 2; Quandt et al., 2019). Many of these effects also reduce climate
risk. At the same time, agroforestry systems are subject to impacts from
climate change, potentially reducing the benefits they provide. Still, there
is limited evidence of observed climate impacts on agroforestry systems,
and modelling climate impacts is more complex for agroforestry than for
single cropping systems (Luedeling et al., 2014).
5.10.2 Assessing Vulnerabilities
5.10.2.1 Assessing vulnerability in mixed systems
Important information gaps exist concerning the costs and benefits
of many adaptation options in mixed systems, where the interactions
between farming enterprises may be complex. Among communal
crop–livestock farmers in Eastern Cape Province of South Africa, Bahta
(2016) reported high levels of vulnerability to drought and highlighted
the need for more coordination between monitoring agencies in terms
of reliable early-warning information that can be communicated
appropriately, between farmers’ organisations and the private sector
to facilitate adaptation options that can overcome feed shortages such
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as fodder purchases in times of drought, and between government
departments at the national and provincial level that address the
concerns and needs of affected communities. Nyamushamba (2017)
reviewed the use of indigenous beef cattle breeds in smallholder
mixed production systems in southern Africa. Some of these breeds
exhibit adaptive traits such as drought and heat tolerance and
resistance to tick-borne diseases. However, their adaptation potential
in crossbreeding programmes is essentially unknown, as most African
cattle populations are still largely uncharacterised.
5.10.2.2 Social vulnerabilities
As in other production systems, Indigenous groups, gender, race and
other social categories can result in heightened vulnerability to climate
change in mixed production systems owing to historical and current
marginalisation and discrimination (
high confidence
) (Parraguez-
Vergara et al., 2016; Baptiste and Devonish, 2019; Moulton and
Machado, 2019; Popke and Rhiney, 2019; Fagundes et al., 2020). A study
of the Mapuche Indigenous group in Chile found that marginalisation
and discrimination worsened their vulnerability and observed impacts
of climate change because they had less access to services and lower
incomes and were not as high a priority as other groups (Parraguez-
Vergara et al., 2016). Among fisherfolk on Lake Wamala, Uganda,
Musinguzi (2018) found evidence of considerable diversification to crop
and livestock production as a means of increasing households’ food
security and income, but women had greater workloads and less control
over new income sources than men. Ngigi (2017) evaluated adaptation
actions within households in rural Kenya and found that women tended
to adopt adaptation strategies related to crops, and men to livestock
and agroforestry activities. Chingala (2017) found substantial gender-
and age-related differences in control of access to animal feed, animal
health and water resources in beef producers in mixed crop–livestock
systems in Malawi. In a review of agriculture–aquaculture systems in
coastal Bangladesh, Hossain et al. (2018) showed that existing policies
and adaptation mechanisms are not adequately addressing gender
power imbalances, and women continue to be marginalised, leading
to increasing feminisation of food insecurity. Such studies highlight the
need to consider gender and other social inequities when examining
adaptation in mixed production systems, particularly in situations in
which men and women have different levels of control over productive
assets (Cross-Chapter Box GENDER in Chapter 18).
5.10.3 Projected Impacts
The impacts of climate change on risk in mixed farming systems are
projected to be dependent on market, ecosystem and policy context
(
medium evidence
,
low agreement
). In mixed crop–livestock farms in
a semi-arid region of Zimbabwe, Descheemaeker (2018) found that
feeding forages and grain could alleviate dry-season feed gaps to the
2050s, but their effectiveness depended on the household’s livestock
stocking density. In comparing different commercial production
systems, Tibesigwa (2017) found that, under South African conditions,
climate change to the 2050s will reduce productivity across the
agricultural sector, with the largest impacts occurring in specialised
commercial crop farms owing to their relative lack of diversity. Mixed
farming systems were the least vulnerable in terms of relative effects
on farm output; this applied to commercial and subsistence sectors
(Tibesigwa et al., 2017). Other studies suggest increased risk in mixed
systems in semi-arid conditions. In northern Burkina Faso, Rigolot (2017)
examined different crop fertilisation and animal supplementation
levels under RCP8.5 to the 2050s. They found that, although aggregate
profits could be increased via moderate levels of inputs, the use of
external inputs may increase risk because of marginal costs exceeding
marginal benefits in lower rainfall years. In the Western Australian
wheat belt, Thamo (2017) assessed climate-change-induced shifts in
farm profitability to the 2050s. For most options, the adverse effects
on profitability were greater than the advantageous effects, profit
margins being much more sensitive to climate change than production
levels. However, in the same system, Ghahramani (2018) evaluated
adaptation options to 2030 and found that a shift to a greater reliance
on livestock could be profitable, even in years with low rainfall.
Risk management in integrated production systems may constitute a
barrier to uptake of adaptation options (Rigolot et al., 2017). Watson
(2018) highlighted the current lack of financial risk management tools
that could be used in smallholder coastal communities. Alongside other
risk management tools such as weather-based index insurance, risk
pooling may find wide application in different farming systems as an
effective adaptation measure (
medium agreement
,
limited evidence
)
(Hansen et al., 2019a).
Climate change impacts on productivity of agroforestry systems are
similar to individual perennial crops, although there is limited research on
tree crops (see Section 5.4.1.2). Impacts include increased temperature
or water stress, an increase in pathogens affecting crops, changes to
pollinator abundance, and changes in the nutrient content of one or
more of the agroforestry components. Many tree products such as fruits
and nuts are grown in agroforestry settings. The quality and nutrition of
these products and other specialty crops are often negatively affected
by rising temperatures, ambient CO
2
concentrations and tropospheric
ozone (Ahmed and Stepp, 2016). There is also evidence that the fungus
coffee rust will be positively affected by climate change (Avelino et al.,
2015; Bebber et al., 2016), with adverse effects on coffee agroforestry
systems.
While shade trees can ameliorate increasing stand temperatures that
will significantly impact arabica coffee (Ovalle-Rivera et al., 2015;
Schroth et al., 2015), the opposite can also be true. Comparing shade
and full-sun coffee systems in Ghana, Abdulai (2018) concluded
that the leguminous tree species providing shade and additional
nitrogen led to soil water competition with the coffee trees during
severe drought, resulting in enhanced coffee mortality. On the other
hand, experimentally induced drought in a soybean-intercropping
agroforestry system in eastern Canada led to crop losses in the
monocropping system only, whereas N-fixation declined in both
systems (Nasielski et al., 2015). Thus, balancing the synergies and
trade-offs of multiple component systems is necessary based on local
context. While species diversification can enhance resilience to climate
shocks, lack of water can constrain the implementation of agroforestry
practices in arid locations (Apuri et al., 2018).
For people reliant on both agriculture and fisheries for food production,
regional differences in productivity effects of climate change are
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expected; populations in LMICs that are already vulnerable will be
most affected by simultaneous reductions in fisheries and agricultural
productivity (Blanchard et al., 2017). Twelve out of 17 high-income
countries in Europe showed projected increases in agricultural
production where adaptive capacity is higher, and agricultural and
food fisheries’ dependence was lower. Some LMIC countries (Nigeria,
Cameroon, Ghana and Gabon) showed relative reductions in both
fisheries and agricultural production, where food insecurity, human
population growth and fisheries overexploitation rates are high
(Blanchard et al., 2017). Model projections under the RCP6.0 scenario
show decrease in marine and terrestrial production to 2050 in 87 out
of the 119 coastal countries studied, even though there is a wide
variance in adaptive capacity and relative and combined dependencies
on fisheries and agriculture (Blanchard et al., 2017). A projected 2050
move towards greater consumption of cultured seafood and less meat
showed that aquaculture requires less feed crops and land, but was
regionally dependent upon differing patterns of production, trade and
feed composition (Froehlich et al., 2018b).
Box 5.7: Perspectives of Crop and Livestock Farmers on Observed Changes in Climate in the Sahel
The Sahel region of West Africa has experienced some of the most severe multi-decadal rainfall variations in the world: excessive rainfall
in the 1950s–1960s followed by two decades of deficient rainfall, leading to a large negative trend until the mid-to-late 1980s with
a decrease in annual rainfall of between 20% and 30%. Recently, there has been a partial recovery of annual rainfall amounts, more
significant over the central than the western Sahel. This recovery is characterised by new rainfall features, including false starts and early
cessation of rainy seasons, increased frequency of rainy days, increased precipitation intensity and more frequent and longer dry spells
(Salack et al., 2015; Sanogo et al., 2015; Salack et al., 2016; Biasutti, 2019). The Sahel is experiencing a new era of rainfall extremes
(Bichet and Diedhiou, 2018; Panthou et al., 2018), suggesting an intensification of the hydrological cycle (Doblas-Reyes et al., 2021).
The ways in which crop and livestock farmers in the Sahel have responded to climatic variability have been studied widely (Sissoko, 2011;
Gonzalez et al., 2012; Jalloh et al., 2013; Gautier et al., 2016; Sultan and Gaetani, 2016; Zougmoré et al., 2016; Segnon, 2019). Local
communities have developed an extensive Indigenous ecological knowledge system, enabling them to make use of ecosystem services to
support their livelihoods and to survive environmental change (Nyong et al., 2007; Mertz et al., 2009; Lahmar et al., 2012; Segnon et al.,
2015). These knowledge systems have been crucial in people’s resilience to and recovery from major environmental change, such as the
severe drought period experienced in the region in the 1970s and 1980s (Nyong et al., 2007; Lahmar et al., 2012; Segnon et al., 2015;
Gautier et al., 2016; Zouré et al., 2019). As climate change became evident and a primary concern on the global agenda, interest in local
people’s knowledge and understanding of climate change has also increased (Mertz et al., 2009; Tambo and Abdoulaye, 2013; Traore
et al., 2015; Kosmowski et al., 2016; Sanogo et al., 2017; Segnon, 2019).
There is no simple understanding of crop and livestock farmers’ response in the Sahel to rainfall variability. Nielsen and Reenberg (2010)
developed human–environment timelines for the period 1950–2008 for a small village in northern Burkina Faso, relating livelihood
diversification and crop–livestock management changes that map closely to local rainfall variability, such as fields abandoned in dry
years and intense animal manure use in wet years. Although they found a significant correlation between crop–livestock management
practice changes and major climatic events, the climate is only one of many interacting factors that influence local adaptation strategies
(Mortimore, 2010; Nielsen and Reenberg, 2010; Sendzimir et al., 2011). Robust attribution of observed changes to specific change drivers
remains a challenge.
Crop and livestock farmers’ knowledge and perceptions of increases in temperature and temperature-related stressors (heatwaves,
number of extreme hot or cold days) are consistent with the observed meteorological data (Mertz et al., 2009; Mertz, 2012; Tambo and
Abdoulaye, 2013; Traore et al., 2015; Sanogo et al., 2017; Segnon, 2019). Their perceptions of changes in rainfall amounts have not
always been consistent with the observational record (Mertz, 2012; Segnon, 2019). Nevertheless, their perception of increases in dry spell
occurrence during the rainy season and changes in rainfall pattern (onset, cessation, intensity and distribution) were consistent with the
recent observations (Barbier et al., 2009; Ouédraogo et al., 2010; Tambo and Abdoulaye, 2013; Salack et al., 2015; Traore et al., 2015;
Kosmowski et al., 2016; Salack et al., 2016; Segnon, 2019). Rainfall patterns within the season, rather than the total amounts of rainfall,
matter more for crop and livestock farmers in the Sahel (Segnon, 2019).
Crop and livestock farmers in the Sahel have a sophisticated understanding of the local climate. There is considerable potential to
harness this knowledge, coupled with an enabling institutional environment, in developing policies and adaptation plans (Rasmussen
et al., 2018); the Sahel is a region where meteorological stations and observed data are scarce (Buytaert et al., 2012; Nkiaka et al., 2017).
A deeper understanding of the resilience of local ecological knowledge systems, in light of the hydro-climatic intensification currently
experienced in the region and future changes, may well provide further insights into their long-term effectiveness.
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5.10.4 Adaptation Strategies
5.10.4.1 Increasing integration and diversity within mixed systems
There is
medium confidence
in the effectiveness of changing
the nature of the integration between crops and livestock as an
adaptation: moving from crops to livestock, moving from livestock to
crops, and moving from one species of livestock to others, for example
(Roy et al., 2018). Such transitions that increase integration between
farm enterprises may contribute to risk reduction and increased food
security. In areas with adequate rainfall and relatively limited rainfall
variability under climate change, where agricultural diversity is the
greatest, transitions towards more diverse and integrated systems may
bring substantial adaptation benefits (Waha et al., 2018).
Barriers to increasing integration and diversification include policies
which support cereals and crop specialisation, lack of markets, limited
post-harvest processing, limited technical or biophysical research on
implementation and poor market infrastructure (Keatinge et al., 2015;
Bodin et al., 2016; Garibaldi et al., 2016; Bassett and Koné, 2017;
Kongsager, 2017; Rhiney et al., 2018; Roesch-McNally et al., 2018;
Clay and King, 2019; Ickowitz et al., 2019). Proactive policy and market
development are needed to reduce these barriers (Clay and King, 2019;
Ickowitz et al., 2019; See 5.14.3.8 for Insurance).
5.10.4.2 Agroforestry as an adaptation–mitigation strategy for
mixed systems
Agroforestry, the purposeful integration of trees or shrubs with crop
or livestock systems, increases resilience against climate risks through
a range of biophysical and economic effects (
high confidence
).
Traditional agroforestry has been practiced for millennia and provides
prime examples of sustainable agroecological production systems
meeting the production, income and socio-cultural needs of farming
communities within their ecological niches, but market forces have
often led to their demise (McNeely and Schroth, 2006; Plieninger and
Schaar, 2008; García-Martínez et al., 2016; Krčmářová and Jeleček,
2016; Coq-Huelva et al., 2017; Paudel et al., 2017; Doddabasawa et al.,
2018; Maezumi et al., 2018; Lincoln, 2020). The wide range of options
to associate different trees with crops, livestock and aquaculture
allows agroforestry to be practiced in most regions, including those
with precipitation regimes ranging from semi-arid to humid. While
most agroforestry systems occur in smallholder settings, there are
examples of successful industrial-scale mechanised agroforestry
systems (Feliciano et al., 2018; Lovell et al., 2018). Agroforestry delivers
medium to large benefits to all five land challenges described in the
SRCCL—climate change mitigation, adaptation, desertification, land
degradation and food security—and is considered to have broad
adaptation and moderate mitigation potential compared with other
land challenges (Smith et al., 2019c). Agroforestry is also able to
deliver multiple biophysical and socioeconomic benefits (Table 5.12).
The adoption and maintenance of agroforestry practices require
appropriate incentives or the removal of barriers (
high confidence
).
Agroforestry adoption has been limited to date in both higher-income
and lower-income countries. Several constraints need to be carefully
addressed for successful scaling-up of agroforestry systems, including
costs of establishment, limited short-term benefits, lack of reliable
financial support to incentivise longer-term returns on investments, land
tenure, knowledge of and experience with trees and the management of
multiple component systems, and inadequate market access, (Coulibaly
et al., 2017; Iiyama et al., 2017; Jacobi et al., 2017; Kongsager, 2017;
Hernández-Morcillo et al., 2018; Iiyama et al., 2018; Lincoln, 2019).
Kongsager (2017) and Roupsard et al. (2020) also highlight the need
for vertical integration of measures from local to national scales to
successfully address local barriers to adoption. Although there are few
studies evaluating the long-term performance of agroforestry systems
(Coe et al., 2014; Meijer et al., 2015; Brockington et al., 2016; Kongsager,
2017; Toth et al., 2017), the available results suggest that successful
adoption of agroforestry practices depends strongly on the local
Table 5.12 |
Some of the biophysical and socioeconomic benefits of agroforestry.
Contribution
Pathway
References
Increased food security and household
income
Diversification of production, avoiding trade-offs between crop and
tree products
Nath et al. (2016), Coulibaly et al. (2017), Montagnini and Metzel
(2017), Waldron et al. (2017), Blaser et al. (2018), Sida et al. (2018),
Quandt et al. (2019), Amadou et al. (2020)
Increased productivity per unit of land
Introduction of multiple species leading to higher land equivalency ratios
van Noordwijk et al. (2018), Reppin et al. (2019)
Improved biophysical site properties
Via limiting soil erosion, facilitating water infiltration, increasing
nutrient use efficiency, improving soil physical properties, improving
crop nutritional quality, modifying the site micro-climate, and helping
to buffer against extreme events
Nguyen et al. (2013); Carsan et al. (2014), Rosenstock et al. (2014),
Quandt et al. (2017), Hoegh-Guldberg et al. (2018), Sida et al. (2018),
Wood and Baudron (2018), de Leeuw et al. (2020), Muchane et al.
(2020), Nyberg et al. (2020)
Enhanced biodiversity and supporting
ecosystem services
Via integrating different perennial and annual species in different
spatial or temporal associations, thereby providing greater habitat
diversity for other species, including pollinators and predators
McNeely and Schroth (2006), Imbach et al. (2017), Isbell et al. (2017),
Sonwa et al. (2017b), Tran and Brown (2019)
Enhanced CES
Enhanced recreational, cultural and spiritual uses
Nyberg et al. (2020)
Carbon dioxide removal
Via enhanced above-ground carbon sequestration compared with
most cropping or livestock systems, ranging from 2.6 to 10 Mg C ha
−1
yr
−1
depending on regional and climatic conditions (>0.7 Gt CO
2
e yr
−1
globally between 2000 and 2010)
Ramachandran Nair et al. (2009), Zomer et al. (2016), Rochedo et al.
(2018), Wolz et al. (2018), Crous-Duran et al. (2019), Platis et al. (2019)
Enhanced gender balance
Via providing women with more diversified income sources
Kiptot et al. (2014), Ngigi et al. (2017), Benjamin et al. (2018)
Strengthened urban and peri-urban
agricultural systems
Via provision of regulating and provisioning ecosystem services such as
shade, water infiltration, new food and livelihood opportunities
Borelli et al. (2017)
See Section 5.12
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enabling environment, including appropriate markets, technologies and
delivery systems (
medium evidence
,
high agreement
).
5.10.4.3 Links between crops and aquaponics–hydroponics as
adaptation
Hydroponic systems produce plants in a soilless environment requiring
mineral fertilizers to meet plant nutritional needs, whereas aquaponics
combines an aquaculture production system with hydroponics, where
fish waste provides nitrogen, phosphorous and potassium for plant
growth and nitrifying and mineralising bacteria act as filters (Goddek
et al., 2015; Pérez-Urrestarazu et al., 2019; Ghamkhar et al., 2020). The
relative environmental impact of hydroponic systems is lower com-
pared with conventional systems owing to the significant reductions
in land use and fertilizer usage (
high confidence
) (Goddek et al., 2015;
Datta et al., 2018; Pantanella, 2018; Suhl et al., 2018; El-Essawy et al.,
2019; Jaeger et al., 2019; Monsees et al., 2019; Mupambwa et al., 2019;
Pérez-Urrestarazu et al., 2019; Ghamkhar et al., 2020). While studies
indicate that aquaponics and hydroponics have higher yields and a
lower environmental footprint than conventional agriculture (
medium
confidence
), aquaculture and heated greenhouse production (Panta-
nella, 2018; Romeo et al., 2018), aquaponic production may need to
be coupled or decoupled or have double-recirculation systems to meet
the different requirements of farmed fish and crop species (Pantanella,
2018; Suhl et al., 2018; Mupambwa et al., 2019). Aquaponics and hy-
droponics are a promising adaptation option for urban agriculture, with
benefits including a protected growing environment from climate ex-
tremes, reduced GHG emissions related to food transportation, reduced
food waste, rainwater harvesting and use of food waste (
medium agree-
ment
,
limited evidence
) (Goddek et al., 2015; Al-Kodmany, 2018; Clin-
ton et al., 2018; Weidner and Yang, 2020). Such systems show promise
for reducing food production environmental footprints and increasing
food security, particularly in arid or water-stressed environments (Doyle
et al., 2018; Mupambwa et al., 2019). Barriers to aquaponics and hydro-
ponics adoption include market acceptance of cultured fish species and
desirability of plant crops, lack of expertise, legal constraints or high
investment costs and financial feasibility (Bosma et al., 2017; Al-Kod-
many, 2018; Datta et al., 2018; Pantanella, 2018; El-Essawy et al., 2019;
Martin and Molin, 2019; Pérez-Urrestarazu et al., 2019; Specht et al.,
2019). There is
high confidence
(
high agreement
,
medium evidence
)
that a major barrier to hydroponic and aquaponics adoption is the re-
quirement for skilled operators (Goddek et al., 2015; Bosma et al., 2017;
Datta et al., 2018; McHunu et al., 2018; Pantanella, 2018), which could
be mitigated by decoupling systems and disciplines (Pantanella, 2018).
As yet, these systems are not widely implemented and information on
their climate change impacts is limited.
5.10.4.4 Transitions in and between mixed systems as
adaptation strategy
Transitions in and between the different elements of integrated
agricultural systems can be an effective adaptation option
(medium
confidence
). Havlik et al. (2014) projected that, by 2030, market-
driven autonomous transitions towards more efficient production
systems would increase ruminant meat and milk productivity by
up to 20% and decrease emissions by 736 MtCO
2
e y
−1
, most of this
arising through avoided emissions from the conversion of 162 Mha of
natural land. Weindl et al. (2015) assessed the implications of several
climate projections on land use change to 2045 and found that shifts
in livestock production towards mixed crop–livestock systems would
represent a resource- and cost-efficient adaptation option, reducing
global agricultural adaptation costs and abating deforestation by
about 76 million ha globally. Both studies suggest that public policy
support for transitioning livestock production systems to increase their
efficiency could be an important lever for reducing adaptation costs and
contributing to emissions reductions. This policy support could include
modified regulatory and certification frameworks that incentivise
livestock producers to adapt and mitigate (Weindl et al., 2015).
Recent reviews have summarised literature on production system
transitions, driven at least partly by a changing climate or changing
climate variability, that sometimes involves substantial shifts in
enterprises and land configurations. These reviews found several cases
of transitions affecting pastoral and mixed systems, with a range of
responses including intensification, diversification and sedentarisation
as well as the abandonment of agriculture (see Section 5.14.3.1,
Vermeulen et al., 2018; Thornton et al., 2019). The consequences of these
system transitions have been mixed; in some cases, the household-level
outcomes have been beneficial, while in others not. Policy environments,
defined in terms of multi-level governance structures and institutions,
are critical enablers of change. The vulnerability of many crop–livestock
keepers to climate change is particularly affected by property and grazing
rights (
high confidence
). Identifying the winners and losers from changes
in land ownership and the use of communal lands in the coming decades
is a key challenge for the research agenda, particularly as climate change
impacts in the marginal lands intensify (Reid et al., 2014).
5.11
The Supply Chain from Post-harvest to
Food
The food system is more than just the production of food. It includes
domestic and international transportation, storage, processing, market
infrastructure and institutions that make up value chains, as well as the
food environment in which consumers make food purchasing decisions
(HLPE, 2017a). Climate change impacts along the value chain alter
availability, access and stability of food security. Nutrition-dense
foods tend to be more perishable and are thus more vulnerable to
limitations of food storage and transportation infrastructure (Ickowitz
et al., 2019). Climate-change-related damage to food in storage
(e.g., electricity failures and loss of cold storage) and transportation
infrastructure (e.g., extreme weather events damaging roads and other
infrastructure) could significantly decrease availability and increase
the cost of highly perishable, nutritious foods such as fruits, vegetables,
fish, meat and dairy.
This discussion of the post-harvest food system (i.e., after production
or catch) focuses on three key elements—food safety, storage, and
domestic and international transactions—that could see significant
climate change impacts, either directly or indirectly. Higher temperatures
and humidity can increase post-harvest loss from pests and diseases,
increase occurrence of food-borne diseases and contamination, and
raise the cost of refrigeration and other forms of preservation. Extreme
weather events can cause disruptions to food transport networks
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and storage infrastructure. Changes in regional weather can cause
production centres to shift locations, potentially requiring changes in
storage and processing locations. Prices to producers and consumers
will change, although directions and magnitudes are determined by
local conditions and policies.
Food
loss
is the harvest not used by industry or for food. Food
waste
is
the subset of food loss that is potentially recoverable for food use. As
a product moves in the post-harvest chain to end users, post-harvest
food loss from climate change can occur from improper handling to
damage from microorganisms, insects, rodents or birds. Post-harvest
losses in quality can be the result of stresses and damage to a plant or
animal before harvest, including from climate change (Hodges et al.,
2011; Medina et al., 2015a). Food
waste
caused by climate change
may occur at both retail units and homes because fresh ingredients
and freshly prepared foods are vulnerable to quality reduction and
Box 5.8: Climate Adaptation and Maladaptation in Cocoa and Coffee Production
Coffee and cocoa are important crops in low-latitude regions where agriculture is projected to be heavily impacted by climate change.
Both crops are at risk from climate change impacts by 2050 (Baca et al., 2014; Ovalle-Rivera et al., 2015; Chemura et al., 2016; Schroth
et al., 2016; Bacon et al., 2017; Schreyer et al., 2018; de Sousa et al., 2019; Lahive et al., 2019; Pham et al., 2019; Cilas and Bastide, 2020).
Chocolate and coffee are notable among foods in that their carbon footprint ranges from negative to high, as these industries include
both low-input agroforestry systems that have many co-benefits, and high-input monoculture systems where crops are grown without
shade, in some cases on sites that have been deforested (Poore and Nemecek, 2019). While the coffee industry in many countries has
already transitioned from agroforestry to full-sun production (Jha et al., 2014), the cocoa industry is at a turning point, with many growers
deciding whether to move to the potentially more productive ‘full-sun system’, despite a general view that the agroforestry system is
more resilient to climate change impacts (Rajab et al., 2016; Schroth et al., 2016; Farrell et al., 2018; Niether et al., 2020).
Shade-grown cocoa and coffee agroforestry systems provide an array of ecosystem services, including regulating pests and diseases,
maintaining soil fertility, maintaining biodiversity and carbon sequestration (
high confidence
) (Jha et al., 2014; Rajab et al., 2016; Cerda
et al., 2017; Pham et al., 2019). For example, a comparison of Indonesian cocoa stands found that total carbon stocks above and below
ground were five times higher in multi-shade agroforestry stands compared with monoculture stands (57 compared with 11 Mg C ha
−1
),
and total NPP was twice as high (18 compared with 9 Mg C ha
−1
yr
−1
). The extra carbon sequestration was achieved without any notable
difference in cocoa yield (Rajab et al., 2016). At higher levels of shade, there can be negative impacts on the yield of the understory crop,
but careful management of shade trees allows for both crops to thrive (Andreotti et al., 2018; Blaser et al., 2018; Niether et al., 2020).
Cocoa grown under shade in some situations may be more resilient to climate change (Schwendenmann et al., 2010; Schroth et al.,
2016). Schwendenmann et al. (2010) implemented drought experimentally in the field and found shade trees increased drought
resilience. Shade trees insulate the understory crop from the warming and drying sun (Schroth et al., 2016). On the other hand, full-sun
cocoa systems may be more climate resilient in some cases (Abdulai et al., 2018), as interactions between understory trees and shade
trees are complex; in addition to shade effects, evapotranspiration and root interactions must be considered (Niether et al., 2017;
Wartenberg et al., 2020). Moving to a full-sun system may also involve additional inputs in irrigation, fertilizer and labour. Neither (2020)
reviewed the literature comparing the two cocoa production systems and concluded that the agroforestry system was superior in terms
of climate adaptation.
The choice of cropping system will have wide-reaching consequences for climate vulnerability and climate justice. Coffee and cocoa
are often a main source of income for small-scale producers who are among the most vulnerable to climate hazards (Bacon et al.,
2014; Schroth et al., 2016). Most of their produce is exported by large corporations and sold to relatively better-off consumers. In the
context of climate justice, underlying structural inequities (socioeconomic, ethnicity, gender, caste), marginality and poverty help to shape
the vulnerabilities of small-scale farmers to climate hazards (Beckford and Rhiney, 2016; Schreyer et al., 2018). Climate change may
compound their vulnerability, if for example the loss of pollination services leads to a reduction in productivity (Avelino et al., 2015).
Adaptation needs to consider the inequities associated with the commodity chain, and the adaptative capacity of producers as they
seek to move into the more advanced processing stages of the commodity chain to realise higher returns from their exports (Ovalle-
Rivera et al., 2015). Blue Mountain Coffee is a ‘specialty’ coffee associated with a protected area forest ecosystem that attracts a high
price premium owing to its distinct flavour and aroma. The livelihoods of coffee farmers in this region are characterised by multiple
socioeconomic, environmental and institutional stressors related to climate change, pests, plant diseases and production costs. Some
coping strategies employed by these coffee farmers have increased their susceptibility to future climate impacts (Guido et al., 2019). Davis
(2017) showed that these coffee farmers’ food security challenges could be alleviated by improved marketing of fruit tree products under
shade coffee farming systems. Adaptation measures in such systems need to consider co-benefits and negative trade-offs, especially
in vulnerable communities, to avoid widening further the inequities, rural livelihood loss, migration and marginalisation, and ensure
progress towards the SDGs (
high confidence
).
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spoilage from exposure to higher temperatures and humidity. Food
waste also contributes to climate change by utilising resources that
emit GHGs (Galford et al., 2020).
5.11.1 Current and Future Climate Change Impacts on
Food Safety
Emerging food safety risks from climate change include those posed
by toxigenic fungi, plant- and marine-based bacterial pathogens, HABs
and increased use of chemicals (plant protection products, veterinary
drugs) potentially leaving residues in food (European Food Safety
Authority Panel on Plant Protection Products and their Residues et al.,
2017; Deeb et al., 2018; Mbow et al., 2019; FAO et al., 2020).
Mycotoxins, produced by toxigenic fungi found on many crops,
contaminate food and feed and cause a wide range of adverse
impacts to human and animal health. Climate change can affect the
growth and geographical expansion of these fungi (
high confidence
)
(Wild et al., 2015; Battilani, 2016; FAO and WHO, 2016; Watson et al.,
2016b; Alshannaq and Yu, 2017; Chen et al., 2018a; Avery et al., 2019;
Milicevic et al., 2019; Van der Fels-Klerx et al., 2019; FAO, 2020a; FAO
et al., 2020).
Aspergillus flavus
is a fungus that infects a range of crops and
can reduce grain quality. Several strains also produce aflatoxin, a
particularly problematic mycotoxin
.
Increasing CO
2
and drought stress
has little effect on growth of
Aspergillus
but significantly increases the
production of aflatoxin (Medina et al., 2015b).
In Europe, one estimate is that the risk of aflatoxin contamination
will increase in maize in a +2°C temperature scenario in Europe, with
nearly 40% of Europe exceeding the current legal limits (Battilani and
Toscano, 2016). In Malawi, maize aflatoxin levels above European
Union (EU) legal thresholds are possible for most of the country by
mid-21st century (Warnatzsch and Reay, 2020). The occurrence of
toxin-producing fungi will increase and expand from tropical and
subtropical areas into new regions and where appropriate capacity
for surveillance and risk management is lacking (
medium confidence
)
(Miller, 2016). The increase in toxigenic fungi in crops, and consequent
contamination of staple foods with mycotoxins, will increase the risks
of human and animal exposure (
high confidence
) (Botana and Sainz,
2015; Rose and Wu, 2015; Battilani, 2016; Avery et al., 2019; Bosch
et al., 2019; Milicevic et al., 2019; Moretti et al., 2019; Van der Fels-
Klerx et al., 2019; FAO, 2020a).
In aquatic systems, toxins produced during HABs also cause food
safety problems (
high confidence
) (Botana, 2016; Estevez et al., 2019;
Section 5.8). Increased poleward expansion of
Vibrio
in coastal mid-
to high-latitude areas has been observed (Baker-Austin et al., 2017).
Vibrio
-related mortalities from finfish consumption are expected to
rise with climate change (water temperature, salinity, oxygen and
pH) (
medium confidence
) (Mohamad et al., 2019a; Mohamad et al.,
2019b). For shellfish species, oxygen deficits (Mohamad et al., 2019b),
sea level rise (Deeb et al., 2018) and temperature (Green et al., 2019)
will be most important for food safety.
Food safety is also anticipated to worsen from increased contaminant
bioaccumulation under climate-induced warming (
high confidence
)
(Sections 3.5.8, 3.5.9, 5.8, 5.9, Bindoff et al., 2019;), with changes in
pathogen, parasite, fungi and virus abundance and virulence (Bondad-
Reantaso et al., 2018). Coastal communities who depend on fisheries
for livelihoods and nutrition are especially vulnerable (Hilmi et al.,
2014; Golden et al., 2016; Bindoff et al., 2019).
Occurrence of bacterial pathogens such as
Salmonella
and
Campylobacter
will increase with rising temperatures (
high
confidence
). Foodborne pathogen risks will increase through multiple
mechanisms, though in general the impacts of climate change on
different pathogens are uncertain (Akil et al., 2014; Hellberg and Chu,
2016; Lake and Barker, 2018). Even species within a genus can be
affected differently. For example, higher CO
2
levels depress the growth
rate of
F. graminearum
, an economically important pathogen on barley
but have little effect on
F. verticillioides
, which is the most reported
fungal species infecting maize.
Increases in rainfall intensity will have some effect on the transport
of heavy metals by enhancing runoff from soil and increasing the
leaching of heavy metals into water systems, with magnitudes
dependent on local conditions (
high confidence
) (Joris et al., 2014;
Wijngaard et al., 2017). Methyl mercury (MeHg) is highly neurotoxic
and nephrotoxic and bioaccumulates and biomagnifies through the
food web via dietary uptake (fish, seafood, mammals) (Fort et al.,
2016). Ocean warming facilitates methylation of mercury, and the
subsequent uptake of
methyl mercury in fish and mammals has been
found to increase by 3–5% for each 1°C rise in water temperature
(Booth and Zeller, 2005; FAO, 2020a). A changing climate will release
mercury from snow and ice, raising the amount of mercury in aquatic
ecosystems, although its importance relative to industrial sources is
unknown (Morrissey et al., 2005).
Increased frequency of inland floods has been associated with
contamination of food with toxic and fat-soluble persistent organic
pollutants (POPs), polychlorinated biphenyls (PCBs) and dioxins (Lake
et al., 2014; Tirado, 2015; Alava et al., 2017). Exposure to POPs can
lead to serious health effects, including certain cancers, birth defects
and impairments to the immune, reproductive and neurological
systems.
Climate change–contaminant interactions may alter the bioaccumulation
and biomagnification of POPs and PCBs as well as MeHg (Alava et al.,
2017). Of particular concern is the pollution risk influenced by climate
change in Arctic ecosystems and the bioamplification of POPs and
MeHg in seafoods resulting in long-term contamination of traditional
foods in Indigenous communities (Tirado, 2015; Alava et al., 2017).
The high risk associated with emerging zoonoses (animal diseases
that can infect humans) and alterations in the distribution, survival
and transmission of vectors and associated pathogens and parasites
could lead to an increased use of veterinary drugs and more rapid
development of microbial resistance (European Food Safety Authority
et al., 2020; FAO, 2020a) and higher veterinary drug residues in food
of animal origin, potentially posing health issues for humans (Beyene
et al., 2015; FAO et al., 2018; European Food Safety Authority et al.,
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2020). These outcomes will depend, at least in part, on the extent of
changes in current regulatory systems for veterinary drugs. Pre-harvest
stress on animals can increase the contamination of meat products
with zoonoses. Climate change may also increase rodent populations
and rodent-born zoonoses (Naicker, 2011). Extreme weather events
that cause flooding, such as hurricanes or extreme rain events, increase
the chance of inundating areas that contain waste from animal farms
where antibiotics are used for production, increasing the spread of
antibiotic-resistant bacteria into the surrounding environment (FAO,
2020a).
5.11.2 Current and Future Climate Change Impacts on
Food Loss in Storage, Distribution and Processing
The potential for climate-change-based food losses exists in all
parts of the food system—post-harvest storage, distribution and
processing—with the potential for impacts in one part of the system
to be passed on to other elements (Davis et al., 2021). Storing a
product destined for food use makes it available in times other than
immediately after harvest, which is especially important for products
with a pronounced seasonal availability or that are not available
from other regions with different seasons. Storage of fresh products
(meat, fish, fruits and vegetables) even with the best cold storage
technology results in some quality loss relatively quickly. Higher
temperatures increase the cost of maintaining quality. One estimate
is that an increase in outdoor temperature from 17°C to 25°C
increases cold storage power consumption by about 11% (James and
James, 2010). Post-harvest storage of roots and cereals is subject
to physical and quality losses from damage by mice, rats and birds
and by microorganisms such as the toxigenic fungi discussed above,
all of which are expected to increase in warmer and more humid
conditions.
The higher temperatures and humidity will generally raise storage
costs and lower the quantity and quality of stored product, reducing
producer incomes and raising consumer prices (
high agreement
,
medium evidence
)
(Mbow et al., 2019). For example, in the US state of
Michigan, climate change will shorten the period of reliably cold local
storage of potato by 11–17 days and 14–20 days further south by
mid-century and by 15–29 days and 31–35 days, respectively, by late
century. These changes would increase future demand for ventilation
and/or refrigeration immediately after harvest and again in spring and
early summer (Winkler et al., 2018).
Insects are a main source of food loss. Climate change can alter
insect damage in at least two ways: increases in reproductive rate
from temperature increases and changes in pheromone effectiveness
(
high confidence
). Increasing temperature up to about 40°C raises the
rates of insect food digestion and reproduction (Deutsch et al., 2018),
but temperatures above that level are fatal for many insects (Neven,
2000). Most insects rely on pheromones to facilitate reproduction.
Higher temperatures, but also increases in atmospheric CO
2
and O
3
levels, can affect this process. Insect species that rely on long-range
chemical signals (such as ladybirds, aphids, bark beetles and fruit
flies) will be most impacted, because these signals suffer from longer
exposure to processes that reduce pheromone effectiveness (Medina
et al., 2015b; Moses et al., 2015; Boullis et al., 2016; Verheecke-
Vaessen et al., 2019).
There are several potential pathways for climate change impacts on
processing that would negatively affect quality and appearance, but
with limited research to date. For example, some studies have indicated
that recent increases in temperature have decreased the appearance
and milling quality of rice in the USA and East Asia, owing to increased
occurrence of chalky grains (Lyman et al., 2013; Morita et al., 2016;
Masutomi et al., 2019; Ishigooka et al., 2021). Impacts on quality of
perennial crops and annual fruits and vegetables are discussed above
(Section 5.4.3 and Box 5.2).
5.11.3 Current and Projected Impacts on Transportation
and Distribution: Domestic and International Trade
Regional differences in resource availability are a key underlying
driver of domestic and international trade. Climate change can change
resource availability, in terms of both quantity and quality, altering
trade flows, prices and incomes of producers. Climate change can also
affect food access, and its stability can be affected through climate-
change-driven disruption of infrastructure (FAO et al., 2018; Mbow
et al., 2019). Extreme events are expected to become more common
as climate change progresses. Recent examples illustrate the potential
for trade disruptions. In March 2019, Cyclone Idai affected 1.7 million
people in Mozambique and 920,000 in neighbouring Malawi, according
to United Nations (UN) officials. The World Food Program reported that
satellite imagery of flooding in central Mozambique showed an ‘inland
ocean’ the size of Luxembourg with potentially large impacts on
distribution of existing supplies, and uncertain effects on future food
production and availability. The extreme rainfall events in the US state
of Iowa in spring 2019 destroyed large numbers of well-built grain
silos. In addition, major road and bridge damage required rebuilding.
Trade plays a sizeable role in global food supplies. More than 1 billion
people relied on international food trade in the early 21st century
(Fader et al., 2013; Pradhan, 2014). Domestic and international trade
flows can be dramatically affected by climate change impacts
(medium
evidence
,
high confidence)
(Nelson et al., 2014; Pradhan, 2014; Wiebe
et al., 2015)
.
Since the impacts of climate change will not be uniform,
profitable locations for exports production will change. In addition, the
effects of increasing local weather variability caused by climate change
means increasing variability of food availability for domestic use and
international trade. Finally, extreme events driven by climate change
can disrupt transportation along the food value chain. Countries more
at risk of natural hazards that disrupt transportation and distribution,
and with less extensive routes, are more vulnerable to climate change
impacts.
A global multi-hazard risk assessment (Koks et al., 2019)
suggests surface and river flooding, which are projected to increase
in a warmer climate, are the main hazards for road and railway
infrastructure, increasingly disrupting international and domestic
transportation of agricultural commodities.
Climate change impacts will increase most global prices relative to
early 21st century levels, with varying effects on the cost of food
imports (
high confidence
) (Nelson et al., 2014; Wiebe et al., 2015;
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Fujimori et al., 2018; Lee et al., 2018). For example, analysis using
results from one study (using CMIP5 data for RCP8.5 and SSP2) found
that net food importing countries in the early 21st century would
see expenditures on food imports decrease by USD 36 billion in mid-
century in real terms with climate change over a no climate change
scenario. (Table 5.13).
Global economic models with a focus on agriculture provide a
perspective on the range of potential changes in market outcomes
because of climate change. In one study comparing several SSPs to
a future with no climate change to one with impacts from RCP8.5,
2050 yields with climate changes impacts are 17% smaller on average
than those without climate change. Adaptation by farmers reduce
that to an 11% decline. The change in 2050 prices of all crops and
regions after climate change impacts and farm-level adaptation is a
mean 20% increase (Nelson et al., 2014). Substantial differences arise
from both the heterogeneous impacts of climate change over crops
and geography and the diversity of modelling approaches in the GCM
and crop models. A later study with more socioeconomic scenarios and
fewer models got roughly similar results (Wiebe et al., 2015), as did a
modelling study focused on food security in South Asian countries (Cai
et al., 2016).
Most climate scenario modelling to date does not incorporate increasing
variability nor the use of storage, a critical tool to manage variability.
Two recent studies are exceptions. In one, climate change generally
reduces mean yields and increases their variability in the Midwestern
USA and causes modest increases in price volatility (Thompson et al.,
2018). A second study (Chen and Villoria, 2019) focuses on maize net
importers across Africa, Asia and Latin America during 2000–2015.
A 1% increase in the ratio of imports to total consumption reduces
domestic price variability by 0.29%. A 1% increase in stocks at the
beginning of the season is correlated with a 0.22% reduction in the
coefficient of variation.
5.11.4 Adaptation in the Post-harvest Supply Chain
The SRCCL (Mbow et al., 2019) findings on adaptation support
targeting food value chains and intervention types to the needs of
specific locations. Furthermore, adaptation choices will need to be
dynamic as climate change impacts are expected to worsen over time.
As discussed above and in Section 6.2.5, climate change is expected
to cause increasingly severe effects on infrastructure needed for food
security: roads and harbours for transport, water storage facilities
for irrigation and storage facilities able to withstand climate-related
damage. Three categories of adaptation could be considered: adoption
of technologies already in use elsewhere, including Indigenous and
local knowledge, or available or near ready that become profitable as
impacts become more severe; development of new technologies; and
taking advantage of changing comparative advantage across regions.
Specific examples of post-harvest technical adaptation options that
are already available but could be more widely adopted include solar
driers, cold storage facilities and transport and use of ultrasonic
humidification of selected fruits and vegetables, a technology that has
been shown in Europe to reduce losses in each post-harvest stage by
20% or more (Fabbri et al., 2018). Hermetic storage containers using
community-based farmer research networks to scale out (Singano et al.,
2020; Wenndt et al., 2021) also show promise. Another innovation is to
introduce
Aspergillus
fungi that do not produce aflatoxins in biocontrol
formulations, as is being undertaken in the Aflasafe project in Kenya
(Bandyopadhyay et al., 2016).
International trade changes are a potentially important adaptation
mechanism for both the short-term effects of climate variability and
long-term changes in comparative advantage with globally substantial
benefits but that are distributed unevenly (Mosnier et al., 2014; Baldos
and Hertel, 2015; Fuss et al., 2015; Costinot et al., 2016; Hertel and
Baldos, 2016; Gouel and Laborde, 2021). One estimate is that, with a
reduction in tariffs as well as institutional and infrastructural barriers,
the negative impacts of climate change globally would be reduced
by 64%, with hunger-affected import-dependent regions seeing the
greatest benefit. However, in hunger-affected export-oriented regions,
partial trade integration might lead to increased exports at the expense
of domestic food availability (Janssens et al., 2020). It is possible for
policy changes that result in increased trade flows to also increase the
potential for maladaptation, for example by encouraging conversion of
environmentally sensitive areas to agriculture (Fuchs et al., 2020; 5.13.3).
As discussed in Section 5.4, climate change is expected to increase
variability in yields. As long as the variability is not correlated across
regions, trade flows within a year can partially compensate, with
in-period exports from countries less affected to those that are.
Alterations in trade flow patterns to accommodate these impacts will
reduce the negative effects so long as this variability is not correlated
across regions (UK, 2015; Janetos et al., 2017).
In terms of food safety impacts, Lake and Barker (2018) highlight a range
of approaches to enhance preparedness for more serious foodborne
disease effects from climate change: adoption of novel surveillance
methods to speed up detection and improve intervention in foodborne
outbreaks; genotype-based approaches to surveillance of food pathogens
to enhance spatiotemporal resolution in tracing and tracking of illness;
improving integration of plant, animal and human surveillance systems
under the rubric of One Health, increased commitment to cross-border
and global information initiatives; and improved clarity regarding the
governance of complex societal issues such as the conflict between food
safety and food waste and strong user-centric (social) communications
strategies to engage diverse stakeholder groups.
The range of potential adaptation approaches from production to
transportation to reduce food loss and waste is captured in Figure 5.17
(Galford et al., 2020).
Table 5.13 |
Net exports of agricultural products, by net exporting and net importing
countries, 2010 and 2050 (billion constant parity US dollars), based on analysis in
Beach et al. (2019).
2010
2050
Net importers in 2010
No climate change
–301
−838
Climate change
−301
−802
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Food loss and waste (FLW) interrelationships by value change stage
Plan cultivation schedules
to time harvest for
maximum shelf life.
Improve physical handling
to reduce physical
deterioration of products.
Sort freshly harvested
items to separate
damaged.
Production
Harvesting
Processing
Storage
Transportation
P
P
to
o
m
m
Im
m
to
o
de
e
S
So
it
e
e
da
a
H
H
P
P
S
St
T
T
Maintain hygiene during
food handling and storage
through improved
packaging.
Promote climate controlled
facilities and units.
Maintain cold chain from
harvest to retail.
Utilize pest and contamina-
tion reduction practices.
Improve infrastructure for
physical travel.
Develop centralized
distribution facilities.
Schedule transportation for
ideal storage conditions for
products while in transit.
Modify the product's form
or make-up for longer
preservation.
Dry product to achieve
optimal moisture levels for
storage.
Reduce contamination
through use of proper
practices, standards, and
tools.
Select crop varieties that
have longer shelf life, meet
buyer quality requirements,
and have improved drought
or salinity tolerance.
Select crop and livestock
types, species or breeds
that are disease tolerant.
Figure 5.17 | Examples of food loss and waste (FLW) interventions at five stages in the food value change (Galford et al., 2020).
The importance of reducing food loss and waste due to climate change
is widely recognised, but literature on cost-effective reductions is
sparse, particularly in low-income countries (Parfitt et al., 2010). A
list of farm and post-harvest methods to reduce food loss (Sheahan
and Barrett, 2017) includes potential farm interventions such as
varietal choice, education in harvest and post-harvest handling,
hermetic storage technologies (see above), chemical sprays and
integrated pest management techniques in storage. The evidence on
their effectiveness, especially in the face of increased climate change
impacts, is limited.
5.12
Food Security, Consumption and Nutrition
5.12.1 Introduction
Food security and nutrition are key desired outcomes of food systems.
Climate change is already contributing to reduced food security and
nutrition and will continue to do so (
high confidence
)
(Sections 5.4, 5.5,
5.8, 5.9, 5.10). Climate change impacts affect all four dimensions of
food security: availability, access, utilisation and stability (Table 5.14),
through both direct and indirect pathways.
Global food security improved dramatically in the 20th century even
as global population increased from 2 to 6 billion. While some may
assume that global food security is primarily provided by large-scale
producers, research since AR5 has shown the sizeable role of small and
mid-sized food producers in Asia, Africa and Latin America contributing
to global food security and nutrition, while being highly vulnerable to
climate change impacts on food security (Samberg et al., 2016; Herrero
et al., 2017; FAO et al., 2018; Ricciardi et al., 2018). In 2019, more than
750 million people in the world, almost 1 in 10 people, suffered from
severe food insecurity, a figure which has risen since 2014 in every
region except North America and Europe
(FAO et al., 2020). Overnutrition, a result of high-calorie unbalanced
diets, is also rising, with over 2 billion adults overweight or obese (FAO
et al., 2018; Swinburn et al., 2019; FAO et al., 2020; Venkatesh Mannar
et al., 2020; WHO, 2021). Many low- and middle-income countries now
have both high under- and overnutrition rates (FAO et al., 2018).
There are multiple drivers of food security, including changing dietary
patterns, urbanisation and population growth (HLPE, 2017b; FAO et al.,
2018; Swinburn et al., 2019). Vulnerability to climate change impacts
on food insecurity and malnutrition is worsened by other underlying
causes, including poverty, multiple forms of inequity (e.g., gender,
racial, income), low access to water and sanitation, macroeconomic
shocks and conflict (Smith and Haddad, 2015; Clay et al., 2018; FAO
et al., 2018; Cook et al., 2019). Climate change frequently acts to
compound these drivers of food insecurity (Table 5.14).
The coronavirus disease 2019 (COVID-19) pandemic has increased
vulnerability to food insecurity and malnutrition of particular groups
and sectors in the food system, including low-income households,
farmworkers, food service workers, informal food market sellers and
low-income countries dependent on food imports (Cross-Chapter
Box COVID in Chapter 7). Climate change will compound pandemic
vulnerabilities in the food system (
high agreement
,
low evidence
)
(HLPE, 2020; UNDRR (United Nations Office for Disaster Risk
Reduction, Regional Office for Asia and Pacific), 2020; WFP-FSIN,
2020). The pandemic may also increase coordination among sectors
and a willingness to address food system weaknesses made visible
by the impacts of COVID-19 (Blay-Palmer et al., 2020; Cohen, 2020;
Ramos et al., 2020).
Ecosystem services, the provisioning, supporting and regulating
mechanisms we all depend on for food security and nutrition, are
also undermined by climate change impacts (Section 5.4.3). Even in
the absence of climate change, our current food system threatens to
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Table 5.14 |
Impacts from climate change drivers on the four dimensions of food security. Adapted from Table 5.1 in SRCCL.
CIDs and mechanism for food security impacts
Examples of regions and groups most affected
References
Food security dimension: Availability
Increased heat and drought
reduce crop and animal
productivity and soil fertility and increase land degradation for
some regions and crops.
Countries in which a large proportion relies on agriculture for
livelihoods.
Food production systems that rely on rainfed agriculture and
pastoral rangeland. Urban populations and the poor.
FAO et al. (2018), Dury et al. (2019), Mbow et al.
(2019), Section 5.4 and 5.5).
Extreme heat
affects crop productivity. Combined with high
humidity reduces agricultural labour capacity and animal
productivity.
Countries and sectors that rely extensively on outdoor manual
agricultural labour and experience high temperatures and
humidity
Zander et al. (2015), Kjellstrom et al. (2016), Ioannou
et al. (2017), Mitchell et al. (2017), FAO et al. (2018),
Flouris et al. (2018), Kjellstrom et al. (2018), Levi
et al. (2018).
Increasing temperatures and precipitation changes
increase and shift crop and livestock pests and diseases
East African pastoral groups who experienced increased
livestock morbidity and mortality from RVF in El Niño years.
Bebber (2015), FAO et al. (2018), Mbow et al. (2019),
Sections 5.4.1.3 and 5.5.1.3
Increasing temperatures and drought stress
has led to
higher post-harvest losses due to mycotoxins.
Tropical and subtropical regions with limited food safety
surveillance
Miller (2016), FAO et al. (2018), Section 5.11
Rising ocean temperatures, marine heatwaves and ocean
acidity
has reduced availability of fish in coastal communities.
Coastal people and coastal areas of tropical countries with high
dependence on fisheries, e.g., West African coastal communities
Hilmi et al. (2014), Golden et al. (2016), Bindoff et al.
(2019), Section 5.8 and 5.9
Increased number and intensity of extreme events such
as cyclones
lead to reduced food production and distribution
from crop damage, increased pest incidence and transportation
disruption.
Delta regions where there are high populations and are
often important food production regions, e.g., Cyclone Nargis
in Myanmar estimated to reduce crop production by 19%,
production declined for subsequent 3 years.
Omori et al. (2020)
Increased atmospheric CO
2
concentrations
increase total
plant biomass and plant sugar content, which can increase
crops as well as pests and weeds. High CO
2
also reduces
transpiration during drought, which can increase plant drought
resistance.
All regions are anticipated to have increased atmospheric CO
2
concentrations, but due to impacts of other CIDs (e.g., drought,
heat stress, pests), the impacts on crop growth, forage and
subsequent food availability are mixed.
Iizumi et al. (2018); Canadell et al. (2021),
Ranasinghe et al. (2021), Cross-Chapter Box MOVING
PLATE this chapter)
Food security dimension: Access
Increased
drought
and
flood events
and increased pests and
disease from
rising temperatures
lead to loss of agricultural
income due to reduced yields, and higher costs of production
inputs such as water. Reduced ability to purchase food leads to
lower dietary diversity and consumption levels.
Low-income smallholder farmers and pastoralists in Ethiopia,
Mali, Niger, Malawi, Zambia and Tanzania.
Saronga et al. (2016), Giannini et al. (2017), FAO
et al. (2018) Mbow et al. (2019) Omori et al. (2020)
Increase in number and intensity of
extreme weather
events (e.g., droughts, floods
) lead to increased food prices,
which often leads to lower dietary diversity as well as lower
consumption levels.
Low-income consumers.
Women and girls.
FAO et al. (2018), Mbow et al. (2019), Ilboudo Nébié
et al. (2021)
Extreme events
(e.g., floods) disrupt food storage and
transport networks, reducing access and availability of food
supplies.
Countries dependent on food imports, e.g., Small Island
Developing States. Poor households living in flash flood and
saline zones in Bangladesh who rely on monocropped rice.
Women and children may experience greater impacts from
extreme events.
Toufique and Belton (2014), FAO et al. (2018), Hickey
and Unwin (2020), Algur et al. (2021)
Food security dimension: Utilisation (food quality and safety)
I
ncreased temperatures
reduce food safety caused by
microorganisms, including increased mycotoxins in food and
feed.
Countries with limited food safety surveillance systems.
FAO et al. (2018), Mbow et al. (2019), Section 5.11
Climate change
extreme events
make fruits and vegetables
relatively unaffordable compared with less-nutrient-dense
foods.
Urban low-income households and rural households who
purchase the majority of their food. Children in regions such as
West Africa, with lower access to diverse food types as a result
of climate impact drivers, e.g., drought.
An et al. (2018), Algur et al. (2021), Baker and
Anttila-Hughes (2020), Niles et al. (2021)
Rising air temperature
,
ocean warming and high
CO
2
conditions
increase risk of food poisoning and pollutant
contamination of food through increased prevalence of
pathogens, HAB and increased contaminant bioaccumulation
and threaten human health.
Low-income tropical countries where current ability to reduce
and monitor mycotoxin contamination is limited. Coastal
Indigenous Peoples and other poor populations in coastal areas
of tropical countries with high dependence on fisheries, e.g.,
west African coastal communities
Golden et al. (2016), Bindoff et al. (2019),
Sections 5.7, 5.8, 5.9, 5.11
Increased atmospheric CO
2
concentrations
reduce
nutritional quality of grains, some fruits and vegetables.
Low-income households who have limited access to range of
diverse foods.
Mbow et al. (2019), Section 5.4
Rising ocean temperatures, marine heatwaves and ocean
acidity
reduce fish populations, which reduces consumption of
fish high in iron, zinc, omega-3 fatty acids and vitamins in areas
where fish populations decline.
Coastal areas of tropical countries; coastal Indigenous Peoples
and other groups who rely on fisheries.
Golden et al. (2016); Bindoff et al., 2019; Section 5.7,
5.8, 5.9
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exceed planetary, regional or local boundaries of long-term sustainable
development (Campbell et al., 2017). Climate change will make efforts
to reduce this threat more difficult to achieve (
medium confidence
),
though many solutions to enhancing food security are also potential
climate change adaptation responses (Sections 5.4, 5.6, 5.8, 5.10,
5.14).
5.12.2 Mechanisms for Climate Change Impacts on Food
Security
Climate change is increasing the number of people experiencing
food insecurity through greater incidence and severity of climatic
impact drivers (CIDs), (Seneviratne et al., 2021) such as extreme heat,
drought and floods. Increasing CO
2
concentrations have positive
effects on food and forage crops by enhancing photosynthesis and
alleviating drought stresses (5.4.3.1, 5.5.3.1) but have negative
effects on nutrient concentrations in food crops. Ocean acidification
is also caused by increasing CO
2
, causing negative impacts on aquatic
systems. Tropospheric ozone concentrations already hinder crop
production (Section 5.4.1.4). Several CIDs increase the number of
people experiencing food insecurity (
high confidence
) (SROCC 2019,
FAO et al., 2018; Mbow et al., 2019; Baker and Anttila-Hughes, 2020;
Table 5.12).
Vulnerability to climate impacts on food security and nutrition varies
by region and group. Countries that experience CIDs such as extreme
heat, severe drought or floods and have a large proportion of the
population dependent on rainfed agriculture or livestock for their
livelihoods and food supply have experienced rising food insecurity
due to climate change impacts (FAO et al., 2018; Cooper et al., 2019;
Mbow et al., 2019). Children in Sub-Saharan Africa are particularly
at risk of undernutrition and mortality from increasing temperatures
(Belesova et al., 2019; Baker and Anttila-Hughes, 2020). An additional
estimated 5.9 million children became underweight because of rising
temperatures in 51 countries affected by ENSO intensity in 2015–2016
(Anttila-Hughes et al., 2021). Low-income urban households and
marginalised groups such as landless and ethnic minorities are at risk
of increased food insecurity due in part to climate change extreme
events such as extended drought, floods or cyclones that interrupt
supply chains and impact livelihoods (Rodriguez-Llanes et al., 2016;
FAO et al., 2018; Algur et al., 2021). A systematic review in India found
that women often experience greater workloads and stress during
drought events (Algur et al., 2021).
In the subsequent sections, the four dimensions of food security
will be discussed in relation to observed and projected impacts and
vulnerabilities (Table 5.14).
5.12.3 Observed Impacts
5.12.3.1 Impacts on food availability
All food production systems (crops, livestock, marine, fish, mixed,
aquaculture) have been undermined by climate change and are
expected to experience larger impacts in the future as described in
earlier sections (see Sections 5.4.1, 5.5, 5.8, 5.9, 5.10). In addition,
sudden production losses from extreme climate events can reduce food
security (FAO et al., 2018; Cottrell et al., 2019; FAO et al., 2020; Anttila-
Hughes et al., 2021). For example, a 2007 drought-induced crop failure
in southern Africa led to severe food insecurity in Lesotho because
of the land-locked country’s dependence on imports from South
Africa that aggravated food availability and access under conditions
of declining food production and land degradation (Verschuur et al.,
2021). Pest and disease outbreaks in both crops and livestock due
to climate change (Sections 5.4.1, 5.5.1) have also impacted food
availability and access (see Box 5.8 Desert Locust case study). Loss
in labour productivity from climate-change-related heat stress is a
growing problem.
CIDs and mechanism for food security impacts
Examples of regions and groups most affected
References
Food security dimension: Stability
Increased frequency and severity of extreme events
(e.g.,
droughts
and
heatwaves)
lead to greater instability of supply
through production losses and disruption to food transport.
Landlocked countries; low-income countries reliant on imports;
low-income households in areas prone to floods.
Toufique and Belton (2014), FAO et al. (2018), Algur
et al. (2021), Section 5.11
Increased drought
and
flood events
and increased pests and
disease from
rising temperatures
lead to unstable incomes
from agriculture and fisheries.
Small-scale producers (crops and livestock) and fishers
Ruiz Meza, (2015), FAO et al. (2018), Sections 5.8,
5.9
Climate change
extreme events
increase food prices due to
climate shocks.
Low-income countries reliant on imports; urban low-income
households and rural households who purchase the majority
of their food.
Bene et al. (2015), Peri (2017), Mbow et al. (2019),
Section 5.11
Increased drought
and
flood events
and increased pests
and disease from
rising temperatures
cause widespread crop
failure.
Rising ocean temperatures, marine heatwaves and
ocean acidity
lead to dramatic decline in fisheries, contributing
to migration and conflict.
Coastal communities in West Africa, Southeast Asia and other
tropical countries highly dependent on fisheries.
Golden et al. (2016), Bindoff et al. (2019) Mbow
et al. (2019)
Reduced frost days and snow days
will increase stability
of food security in some temperate regions since there will be
less loss of food crops to frost damage and a longer growing
season. However, they also raise pest and disease risks due to
increased range and overwintering.
Australia, most Asian regions, Europe, Central and South
America and North America.
The benefits of yield gains at high latitudes may be tempered by
greater risks of pests and pathogen damages.
Jones and Barbetti (2012), IPPC Secretariat (2021),
Ranasinghe et al. (2021)
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Climate change affects agricultural labour productivity through
increased intensity and frequency of heat stress events, with
those performing physical labour in high humidity and ambient
temperatures most vulnerable to heat stress (
high confidence
) (Hsiang
et al.; FAO et al., 2018; Kjellström et al., 2019; Antonelli et al., 2020;
Shayegh et al., 2020). Labour capacity, supply and productivity loss
in moderate outdoor work due to heat stress is estimated between
2% and 14%, depending on the location and indicator (Ioannou et al.,
2017; Kjellstrom et al., 2018), with an overall estimate of 5.3% loss
in productivity for outdoor work between 2000 and 2015 (
medium
confidence
) (Watts et al., 2018) but as high as 14% in low-income
tropical countries (Antonelli et al., 2020; Shayegh et al., 2020). Highly
vulnerable occupation groups affected by heat stress include farmers,
farmworkers and livestock keepers working outdoors in low-income
tropical countries (
high confidence
) (Zander et al., 2015; Kjellstrom
et al., 2016; Flouris et al., 2018; Kjellstrom et al., 2018; Levi et al.,
2018). Farmworkers and small-scale food producers in high- and
middle-income countries involved in outdoor labour are also affected
by heat stress (Zander et al., 2015; Gosling et al., 2018; Szewczyk et al.,
2018; Watts et al., 2021). There is also evidence that heat stress is
affecting labour supply through variation in nutrition intake (Antonelli
et al., 2020).
5.12.3.2 Impacts on food access (physical, economic and socio-
cultural) and vulnerabilities
Increased extreme events (e.g., droughts, floods and tropical storms;
Seneviratne et al., 2021) due to climate change are key drivers of
recent rises in food insecurity rates and severe food crises in some
regions (
high confidence
) (Section 5.4.1, Yeni and Alpas, 2017; FAO
et al., 2018; Cooper et al., 2019; Baker and Anttila-Hughes, 2020;
Bogdanova et al., 2021; Ilboudo Nébié et al., 2021). Extreme weather
events reduce physical and economic access to food, increase food
prices, and compound underlying conditions of food insecurity and
malnutrition such as low access to diverse healthy foods and safe
water (FAO et al., 2018; Niles et al., 2021). Increased incidence of
severe drought conditions since 2005 is contributing to food insecurity
in affected regions, including Africa, Asia and the Pacific (Chapter 7,
Phalkey et al., 2015; FAO et al., 2018; Cooper et al., 2019; Ilboudo Nébié
et al., 2021; Verschuur et al., 2021;). In Arctic western Siberia, high
temperatures, melting ice and forest and tundra fires have degraded
reindeer pastures; Indigenous Peoples have reduced traditional diets
and increased purchased food with increases in hypertension and
related health impacts (Bogdanova et al., 2021).
There is growing evidence that anthropogenic climate warming has
already intensified climate extreme events induced by large-scale
SST oscillations such as ENSO (Herring et al., 2018; Seneviratne et al.,
2021). For example, the 2015–2016 El Niño, the strongest in the past
145 years, induced severe droughts in Southeast Asia and eastern and
southern Africa, some intensified by anthropogenic warming (Funk
et al., 2018). As a result, 20.5 million people faced acute food insecurity
in 2016 (FSIN, 2017) and an estimated additional 5.9 million children
became underweight (Anttila-Hughes et al., 2021).
Weather extreme events increased food prices and food price volatility
(Peri, 2017), thereby worsening food insecurity (Shiferaw et al., 2014;
Bene et al., 2015; Miyan, 2015; FAO et al., 2018; Ilboudo Nébié et al.,
2021). Rising food prices can affect conflict, political instability and
migration (Bush and Martiniello, 2017), but the relationship between
Box 5.9: Desert Locust Case Study: Climate as Compounding Effect on Food Security
At the end of 2019, desert locust swarms infested Eastern Africa and caused widespread damage to crops and pastures, threatening food
security and livelihoods (Kimathi et al., 2020; Salih et al., 2020). The FAO estimates that over 200,000 ha of crop and pastureland were
damaged, rendering 2 million people in the region acutely food insecure (IGAD, 2020). The desert locust infestation was facilitated by two
tropical cyclones that created desert lakes in a usually dry region of Saudi Arabia. Moist soils, warm temperatures and ample vegetation
provided a suitable environment for desert locust breeding and migration to Yemen and Somalia, where the pest remained uncontrolled
due to conflict and spread to neighbouring countries. A series of political and socioeconomic weaknesses such as armed conflict, limited
financial resources and lack of early actions compounded the impact of the current invasion and made it the most damaging in 70 years
(Meynard et al., 2020; Salih et al., 2020).
Although desert locusts have been here for centuries, this recent outbreak can be linked to a unique feature of the positive IOD event,
in part caused by long-term trends in SSTs (Wang et al., 2020a). The warming of the western Indian Ocean has increased frequency and
intensity of severe weather, including tropical cyclones (Roxy et al., 2014; Murakami H, 2017; Roxy et al., 2017). Under a 1.5°C warmer
climate, extreme positive IODs are anticipated to occur twice as often, which could also increase the occurrence of pest outbreaks (Cai
et al., 2018).
Climate change increases the need for robust adaptation measures, such as transnational early-warning systems, biological control
mechanisms, crop diversification and further technological innovations in areas of sound and light stimulants, remote sensing, and
modelling for tracking and forecasting of movement (Maeno and Ould Babah Ebbe, 2018; Peng et al., 2020). The desert locust outbreak
and the role of the Indian Ocean warming show that the impacts of climate change can increase unpredictable events. Extreme weather
events act as a compounding effect, exacerbated further by weak governance systems, political instability, limited financial resources and
poor early-warning systems (Meynard et al., 2020).
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climate change, political instability and conflict is often mediated by
other underlying factors such as poor governance (Chapter 7.2.7,
Mach et al., 2019; Selby, 2019).
Low-income urban and rural households who are net food buyers
are particularly affected by food price increases, with reduction in
consumption of diverse food groups (
high confidence
) (Green et al.,
2013; Villasante et al., 2015; FAO et al., 2018). Depending on the
context, particular groups, including women, ethnic and religious
minorities, will be more vulnerable to worsening food insecurity from
climate change impacts (Clay et al., 2018; Jantarasami et al., 2018;
Nature climate change Editorials, 2019; Algur et al., 2021 and see
Cross-Chapter Box GENDER in Chapter 18). Indigenous Peoples are
often more vulnerable to climate change, due to conditions of poverty,
limited resources, discrimination and marginalisation (
high confidence
)
(Smith and Rhiney, 2016; Vinyeta et al., 2016; Jantarasami et al., 2018).
Indigenous Peoples may experience loss of culturally significant foods
and declining traditional ecological knowledge (Dounias and Ichikawa,
2017; Ross and Mason, 2020; 5.7).
5.12.3.3 Impacts on food utilisation and vulnerabilities
Food utilisation refers to the way the body most effectively uses food,
and includes food preparation, food quality and intra-household
distribution. Food utilisation is affected by climate change in several
ways: food safety, dietary diversity and food quality (Aberman and
Tirado, 2014).
Climate change have increased food safety risks (
high confidence
),
including foodborne zoonotic animal diseases (5.5), and marine toxins
from HABs (Sections 5.8, 5.9) and mycotoxins (Section 5.11). Other
foodborne and waterborne infectious diseases such as cholera are
further covered in Chapter 7.
Weather variability and extreme events (Seneviratne et al., 2021) have
reduced availability and access to diverse foods to sell and to purchase
in rural markets, thereby reducing access to affordable, diverse foods
for both rural small-scale producers and net consumers, particularly
for landlocked and low-income countries (
high confidence
) (Pant
et al., 2014; Villasante et al., 2015; Alston and Akhter, 2016; FAO et al.,
2018; Park et al., 2019; Niles et al., 2021) and otherwise marginalised
communities (Algur et al., 2021). One study of 87 countries and 150
extreme events estimated that low-income food deficit and landlocked
countries had reduced nutrient supply ranging from −1.6 to −7.6%
of average supply, a significant portion of a healthy child’s average
dietary intake (Park et al., 2019).
Rural children in low-income countries are at particular risk of
undernutrition from climate change impacts, due to a combination
of factors: potential reduction in food quantity and quality from
heat impacts; greater exposure from outdoor play and agricultural
activities; and increased likelihood of heat exhaustion and vector-
borne and diarrheal diseases (Oppenheimer and Anttila-Hughes, 2016).
A study of child growth data in 30 countries in Africa between 1993
and 2012 found that increased temperature was significantly related
to children’s wasting (Baker and Anttila-Hughes, 2020). Another
study examined 30 years of climate data and child dietary diversity
outcomes in 19 countries, and found that higher-than-average annual
temperatures correlated with declines in child diet diversity at levels
equal to or greater than other factors which often are the focus of
policy, such as market access or education (Niles et al., 2021).
5.12.3.4 Impacts on food stability
Climate change has already changed the start and duration of the
growing season and increased variability of rainfall in some places,
with impacts on food intake and nutritional status and income for
low-income and small-scale producers (
medium evidence
,
high
agreement
, (FAO et al., 2018; Cooper et al., 2019). Evidence to date
suggests that climate change has negative impacts on the stability
of food supply over the medium to long term, thereby affecting food
stability (Myers et al., 2017b). Increasing number and intensity of
adverse weather events, driven by climate change (Seneviratne et al.,
2021), are important factors decreasing food stability, through reduced
availability, increased local price volatility, reduced livelihoods for food
producers and disruption to food transport (Toufique and Belton, 2014;
Verma et al., 2014; Ruiz Meza, 2015; Clay et al., 2018; FAO et al., 2018;
Mbow et al., 2019).
5.12.4 Projected Impacts on Food Security
5.12.4.1 Food availability and access
Climate change will have negative effects on food security and nutrition
in 2050 (
high agreement
,
medium evidence
) (Amjath-Babu et al., 2016;
Springmann et al., 2016; Lloyd et al., 2018; Richardson et al., 2018; see
Chapter 7; Hasegawa et al., 2021a). How many people are affected
will depend considerably on non-climatic drivers of food security (van
Dijk et al., 2021), but modelling studies agreed that climate change
would increase the risk of food insecurity. For example, one study
comparing an RCP8.5 scenario with one that has zero climate impacts
estimates 65 million additional people (10% increase) will experience
food insecurity due to climate change impacts in 2050 (modelling
results in Nelson et al., 2018). Another study accounting for climate
extreme events estimates that, by 2050, the number of people at risk
of hunger will increase by 20% and 11% under high- and low-emission
scenarios, respectively, owing to a once-per-100-year extreme climate
event (Hasegawa et al., 2021a). Sub-Saharan Africa and South Asia
in this study were projected to be at the greatest risk, with triple the
amount of South Asia’s current food reserves needed to offset such
an extreme event. Models suggest that food security and malnutrition
impacts will be much more severe from 2050 onwards relative to pre-
2050, but the scale and extent of the impacts will strongly depend on
the GHG emission scenario (FAO, 2018a; Richardson et al., 2018). Due
to CIDs and non-climate drivers of food insecurity, Sub Saharan Africa
is projected to be the hardest hit, followed by South Asia and Central
and South America, but contingent on adaptation level (Richardson
et al., 2018; Hasegawa et al., 2021a).
Without adaptive measures, heat stress impacts on agricultural labour
will increase with climate change (
high confidence
) (Im et al., 2017;
Levy and Roelofs, 2019; Hertel and de Lima, 2020). Climate-change-
related heat stress will reduce outdoor physical work capacity on a
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global scale. Depending on GHG concentrations, some regions will
experience losses of 200–250 outdoor workdays per year at century’s
end. Using results from one study reporting experimental procedures to
assess loss of work capacity (Foster et al., 2021), regions hardest hit in
an SSP5-8.5 scenario include much of South Asia, tropical Sub-Saharan
Africa and parts of Central and South America (Figure 5.18). de Lima
et al. (2021) projected that negative impacts of warming on crop yields
and labour capacity would affect crop production and cost for workers
and labour-saving mechanisation, raising food price by 5% at +3° from
the baseline period (1986–2005) globally, with significant implications
for vulnerable regions (sub-Saharan Africa and Southeast Asia). Large
uncertainties, however, exist around population diversity and adaptive
capacity (Vanos et al., 2019). Agricultural labour productivity impacts
Days per year when outdoor
physical work capacity is
reduced by at least 40%
1 day
366 days
Temperature and humidity-driven reduction in first-hour physical capacity for outdoor work
Upper insets and arrows point to the only locations across the globe where the first hour loss of physical work capacity* is 40% for the
early century and end century SSP1-2.6 scenario. Other locations will have large capacity losses over the course of a work day. End century
impacts will be much greater and more widespread under SSP5-8.5.
Historical (1991–2010)
SSP1 2.6 (2081–2100)
SSP5 8.5 (2081–2100)
No days
* The research for the representation of lost physical work capacity was undertaken in a controlled environment. The worker was on a treadmill operating at a constant speed for
one hour in a room with controlled temperature and humidity. These conditions approximate work in a field with no wind (which would reduce heat effects) and no direct exposure
to solar radiation (which would worsen heat effects). In addition, work capacity declines as hours in the field extend beyond one hour. Research is underway to take these additional
factors into account.
Figure 5.18 | The number of days per year where physical work capacity (PWC) is less than 60% based on average daily air temperature and relative humidity
(Foster et al., 2021).
PWC is defined as the maximum physical work output that can be reasonably expected from an individual performing moderate-to-heavy work in a ‘cool’
reference environment of 15°C. Values plotted are from the early (A) and end of century (B) for SSP5-8.5 using ensemble means from the ISI-MIP CMIP6 data set. See SM5.4 for details.
of heat attributed to climate change are expected to be worse in low-
and middle-income countries (Kjellstrom et al., 2016). Adaptation
options needed to protect agricultural worker productivity outdoors
and reduce occupational heat illnesses and deaths include cooled
working environments, improved surveillance systems and education
on the need to monitor (
high confidence
) (Xiang et al., 2016; Quiller
et al., 2017; Flouris et al., 2018; Day et al., 2019; Vanos et al., 2019).
Currently available options, however, are more difficult to achieve in
lower-income economies (Kjellstrom et al., 2016; Im et al., 2017).
Under higher-emission scenarios, food availability will be further
reduced after 2050, due to the potential for widespread crop failure
and decline in livestock and fisheries stocks (Mbow et al., 2014; Kelley
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et al., 2017; Challinor et al., 2018; Hendrix, 2018; Bindoff et al., 2019).
At +3°C from the preindustrial era, all food production sectors will
experience greater, and pronounced, losses due to climate change
compared with +1.5°C or +2°C (see Sections 5.2, 5.4.3, 5.8.3 and
5.9.3).
Food insecurity from food price spikes due to reduced agricultural
production associated with climate impact drivers such as drought
can lead to both domestic and international conflict, including political
instability (Abbott et al., 2017; Bush and Martiniello, 2017; WEF, 2017;
D’Odorico et al., 2018; de Amorim et al., 2018;Chapter 7.2.7). While
climate change impacts, including drought impacts on food security,
are important risk factors for conflict, other key drivers are often more
influential, including low socioeconomic development, limited state
capacity, weak governance, intergroup inequities and recent histories of
conflict (
medium confidence
) (Mach et al., 2019; Selby, 2019; Chapter
7.2.7). The interaction between extreme weather events, conflict and
human migration may increase vulnerability of particular communities
of low-income countries (WEF, 2017; D’Odorico et al., 2018; de Amorim
et al., 2018; Chapter 7). Further research is needed to better understand
how increased drought risk under future climate change might affect
food prices and water availability (Abbott et al., 2017).
5.12.4.2 Projected Impacts on Food Safety and Quality
Increasing levels of CO
2
directly contribute to reduced food quality
by reducing levels of protein, iron, zinc and some vitamins, varying
by crop species and cultivars (
high confidence
) (Section 5.4.3, Myers
et al., 2014; Smith and Haddad, 2015; Bisbis et al., 2018; Scheelbeek
et al., 2018; Weyant et al., 2018; Zhu et al., 2018a). Higher levels of CO
2
are predicted to lead to 5–10% reductions in a wide range of minerals
and nutrients (Loladze, 2014). Climate warming will also reduce food
quality of seafood, by changing the LC-PUFA content in phytoplankton
(Section 5.8; Hixson and Arts, 2016).
5.12.4.3 Reaching Sustainable Development Goal 2
Current projections indicate that it is
highly likely
that the UN SDG2
(‘Zero Hunger’) by 2030 will not be achieved, with climate impacts on
one of several drivers of food security and nutrition preventing this goal,
including in Africa, Small Island States and South Asia (
high confidence)
(FAO et al., 2018; Otekunrin et al., 2019; Singh et al., 2019; Atukunda
et al., 2021; Kumar et al., 2021; Vogliano et al., 2021). Integrated policy
strategies that consider synergies and trade-offs between different
food system components would strengthen the likelihood of meeting
SDG2 goals (Dyngeland et al., 2020; Lipper et al., 2020; Vogliano et al.,
2021) (Grosso et al., 2020). Adaptation options which address climate
risks for food security and nutrition are discussed below.
5.12.5 Adaptation Options for Food Security and
Nutrition
Since AR5, there has been increased research on adaptation options
that address climate risks for food security and nutrition. In this section,
cultivar improvements, urban and peri-urban agriculture, changing
dietary patterns, integrated multi-sectoral approaches and rights-based
approaches are assessed for their potential as an adaptation option
that addresses food security and nutrition. Feasibility and effectiveness
assessment of several options is in Section 5.14.
5.12.5.1 Potential, barriers and challenges for genetically
modified crops to address food security and nutrition
While biotechnology can be used as an adaptation strategy
(Section 5.4.4.3), there is low confidence that genetically modified
(GM) crops can increase food security and nutrition in smallholder
farming systems relative to alternative agronomic strategies (National
Academies of Sciences Engineering and Medicine, 2016; Qaim, 2016).
Some underline their potential in building resilience to changing
climatic conditions, in the form of enhanced drought/heat tolerance,
pest/disease protection and/or reduced land usage, thus serving to
bolster food security and nutrition (Sainger et al., 2015; Muzhinji and
Box 5.10: Food Safety Interactions with
Food Security and Malnutrition
Climate change significantly increases the future food
safety risks (
high confidence
) (Sections 5.8.2, 5.8.3, 5.11.1,
Box 5.9). Increasing temperatures and drought stress are
expected to lead to greater aflatoxin contamination of food
crops. Aflatoxins, a major foodborne hazard, contaminate
staple crops and are associated with various health risks,
including stunting in children and cancer (Koshiol et al., 2017).
In LICs, children with high exposure to aflatoxins were found to
be more likely to suffer from micronutrient (zinc and vitamin A)
deficiencies (Watson et al., 2016b). Climate change is expected
to cause decreases in micro- and macronutrient content of
foods, leading to an increased burden of infectious diseases,
diarrhea and anaemia, with an estimated 10% increase in
disability-adjusted life years (DALYs) by 2050 associated with
undernutrition and micronutrient deficiencies (Aberman and
Tirado, 2014; Smith and Myers, 2018; Weyant et al., 2018; Zhu
et al., 2018a; Ebi and Loladze, 2019; FAO, 2020a; Sulser et al.,
2021b).
Children in low-income countries will be at greater risk of
undernutrition from these multiple climate change impacts,
including lower food availability, quality and safety and
increased risk of diarrheal disease (
high confidence
) (Aberman
and Tirado, 2014). One study of 30 countries in Africa estimated
that, by 2100, increased temperatures under RCP8.5 could
increase children’s wasting by 37% in western Africa and 25%
in southern Africa (Baker and Anttila-Hughes, 2020).
The combination of climate change and the presence of arsenic
in paddy rice fields is expected to increase the toxic heavy metal
content of rice and reduce production by 2100, threatening
food security and food safety mainly in low-income countries
where rice is the main staple (Neumann et al., 2017; Muehe
et al., 2019; Farhat et al., 2021).
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Ntuli, 2021). Others suggest that the empirical evidence supporting
GM crops as a climate-resilience strategy remains thin (Leonelli, 2018).
Technical and social barriers and potential solutions are summarised
in Table 5.15.
5.12.5.2 Urban and peri-urban agriculture, vertical and
horizontal
Urban areas have more than half of the global population and consume
about 70% of the total food supply (FAO, 2019b). The urban population
is projected to grow further to about 70% of the global population
by 2050 (UN, 2018). Direct evidence supporting climate resilience of
urban and peri-urban agriculture (UPA) is limited and contextual, but
there is
medium confidence
of multi-functional benefits from UPA,
depending on regions and types of UPA (Artmann and Sartison, 2018;
Kareem et al., 2020). UPA takes different forms of production, and
can be broadly classified into four categories, depending on operating
characteristics and capital inputs (Table 5.16) (Goldstein et al., 2016).
Controlled environments can protect crops, livestock and fish from
extreme weather events or pest and disease outbreak (Mohareb
et al., 2017). Innovative indoor farming such as vertical farming can
be highly productive with minimal water and nutrient supply but can
be capital intensive with high energy demand (O’Sullivan et al., 2019),
and those with aquaponics can be water demanding (Love et al.,
2015). Currently, commodities are often limited to crops with short
growing seasons such as leafy vegetables. Vertically grown crops are
more expensive than field-grown produce and, thus, not accessible
for low-income urban dwellers (Al-Kodmany, 2018). Community and
institutional unconditioned (outdoor) farms and gardens are better
positioned to provide increased access to healthy food to those who
need it (Eigenbrod and Gruda, 2015; Goodman and Minner, 2019).
Many UPA farmers are migrant workers or other socially marginalised
racial and ethnic groups and often limited by access to land (Lawanson
et al., 2014; Horst et al., 2017). There is
high agreement
that proactive
policies for urban design accounting for food–energy nexus and social
inclusion including addressing questions of governance and rights to
green urban spaces are necessary to enhance food provisioning and to
gain multiple functions of UPA (Lwasa et al., 2014; Horst et al., 2017;
Mohareb et al., 2017; Siegner et al., 2018; O’Sullivan et al., 2019; Titz
and Chiotha, 2019; Halvey et al., 2020).
5.12.6 Changing Dietary Patterns
Dietary change in regions with excess consumption of calories and
animal-sourced foods to a higher share of plant-based foods with
greater dietary diversity and reduced consumption of animal-sourced
foods and unhealthy foods (as defined by scientific panels such as
EAT-Lancet) has both mitigation and adaptation benefits along with
reduced mortality from diet related non-communicable diseases,
health, biodiversity and other environmental co-benefits (
high
confidence
) (Springmann et al., 2016; Springmann et al., 2018; Branca
et al., 2019; Henry et al., 2019; Searchinger et al., 2019; Swinburn
et al., 2019; Willett et al., 2019; Rosenzweig et al., 2020; Chapter
7.4.2.1.3 and WGIII Chapter 12). Reducing food waste, especially of
environment- and climate-costly foods would further extend these
benefits (Rosenzweig et al., 2020 and see Section 5.11).
Dietary behaviour is complex: shaped by the broader food system
(HLPE, 2017a), the food environment (Herforth and Ahmed, 2015;
Turner et al., 2018) and socio-cultural factors (Fischler, 1988). Since
most food-related decisions are made at a subconscious level
(Marteau et al., 2012), achieving dietary change for personal health
reasons has proven difficult; it seems unlikely that dietary change for
climate will be achieved without careful attention to the factors that
shape dietary choice and behaviour. Food environments, defined as
‘the physical, economic, political and socio-cultural context in which
Table 5.15 |
Barriers, challenges and potential solutions for GM crops.
Barriers and challenges
Examples and potential solutions to barriers
Major challenges as a food security and nutrition adaptation include the introgression of GM
traits into host varieties (Dowd-Uribe, 2014), and confusion around proper growing practices
that can accelerate resistance (Iversen et al., 2014; Fischer et al., 2015). The combination
of the kinds of traits and restrictions that come from the predominant intellectual property
rights instruments used in their commercialisation, and concentration of plant and animal
breeding industry (Bonny, 2017) mean that benefits from released GM crops tend to be
captured disproportionately by farmers with more land, wealth and education (Afidchao
et al., 2014; Ali and Rahut, 2018; Azadi et al., 2018) but also increase debt levels for growers
(Dowd-Uribe, 2014; Leguizamón, 2014).
Underlying gender inequities also play a critical role in shaping food security and nutrition
outcomes associated with the introduction of GM crops, in part due to unequal control
over income and agricultural decision making; in some cases, women reported decreased
workload and enhanced decision-making power (Gouse et al., 2016), while in others the
introduction of GM crops could increase workload and devalue womens’ role as seed savers
(Carro-Ripalda and Astier, 2014; Addison and Schnurr, 2016).
Major hurdles for GM crops include translating promising research results into real-world
farming systems and consumer trust in the food product. Experimental programmes have
been dogged by issues, including complications with the introgression of GM traits into
high-performing varieties (Dowd-Uribe and Schnurr, 2016; Stone and Glover, 2017), strict
management regimes that clash with the realities of smallholder agricultural systems
(Iversen et al., 2014; Whitfield et al., 2015), and a lack of attention to farmer decision making
(Schnurr, 2019).
One case study is the Water Efficient Maize for Africa (WEMA) programme, a public–private
partnership that transplants a cold shock protein B, known as Droughtgard, into maize in
order to mitigate yield losses from drought. Proponents suggest that this GM venture, which
will be distributed free to smallholder farmers, represents the best strategy for ensuring
stable yields in the face of climatic change across Africa (Kyetere et al., 2019). Critics argue
that WEMA maize is not a good fit with the smallholder farming systems it is designed to
benefit, with particular concerns around how farmers will access the extra inputs, credit and
labour that WEMA maize requires to be successful (Schnurr, 2019).
Emergent genome-edited crops are considered a more precise, accessible and accelerated
means of targeting stressors that matter to poor farmers, but evidence is limited (Kole
et al., 2015; Haque et al., 2018; Zaidi et al., 2019). A more iterative and flexible adaptation
approach beyond just genomic improvement to tackle the multiplicity of factors limiting
smallholder production is anticipated to increase the likelihood that these promising
technologies can enhance food security and nutrition (
medium confidence
) (Giller et al.,
2017; Stone, 2017; Montenegro de Wit, 2019).
To address food security and nutrition, future breeding needs to move from just enhancing
agronomic traits of a single crop to improving multiple traits of multiple crops suited to
local conditions that will increase climate resilience of farming systems. To make breeding
technologies scale-neutral, the policy structure needs to support and protect smallholders
(
medium confidence
).
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consumers engage with the food system to make their decisions about
acquiring, preparing and consuming food’ (HLPE, 2017a): 28), include
food availability, accessibility, price/ affordability, food characteristics,
desirability, convenience and marketing.
There are a range of options to change dietary patterns, but more
research is needed in this area, adjusted to the regional, socioeconomic
and cultural context. Studies of policy instruments to change diets
include changes in subsidies, taxes, marketing regulation and efforts
to change the retail physical environment. Subsidies directed at staple
foods and animal sourced foods could be shifted towards diversified
production of plant-based foods in order to change the relative price of
foods and, thus, dietary choice (Franck et al., 2013; Harris et al., 2021).
Taxes on animal-sourced foods that are climate-costly and unhealthy, as
defined by scientific panels such as the EAT-Lancet report, could similarly
impact relative price (Mbow et al., 2019; Willett et al., 2019). Regulation
of marketing could change desirability of climate-unfriendly and
unhealthy foods (Willett et al., 2019). Many of the same strategies used
to increase sales by conventional food marketing efforts hold potential
to change the desirability and people’s preferences for plant foods which
are strongly shaped by social–cultural norms. Studies have shown that
changes to the number, placing or prevalence of vegetarian options on a
Table 5.16 |
Urban agriculture classifications based on operating characteristics and capital inputs (Goldstein et al., 2016; O’Sullivan et al., 2019), and a summary of literature
search on positive and negative aspects.
Summary of urban and peri-urban agriculture and evidence for improved food security and nutrition
Urban agriculture has two components: vertical (e.g., grown on or in buildings) and horizontal (grown on land within urban boundaries, in backyards and marginal spaces). The
horizontal component of urban and peri-urban agriculture (UPA) has gained attention because of multiple functions that could improve food systems and ecosystem services
under climate change (Revi et al., 2014; Artmann and Sartison, 2018; FAO, 2019b; Mbow et al., 2019; Chapter 6).
UPA cannot fully feed urban dwellers within its boundaries but can make an important contribution to local food security and nutrition (medium confidence) (Martellozzo et al.,
2014; Badami and Ramankutty, 2015; Algert et al., 2016; Mohareb et al., 2017; Clinton et al., 2018; Kriewald et al., 2019). UPA is also expected to play important roles in eco-
system functions in addition to alleviating food shocks caused by natural disasters and reducing food mileage.
Categories
and Description
Synergies
Trade-offs
Ground-based Unconditioned
– Multi-species cropping can increase access to diverse healthy
foods and reduce food costs for low-income households (Algert
et al., 2016; Horst et al., 2017).
– Green cover helps to attenuate heat island effects, and reduce
runoff and flood risks (Lwasa et al., 2015; Di Leo et al., 2016;
Gondhalekar and Ramsauer, 2017; Artmann and Sartison, 2018;
Small et al., 2019).
– Green garden spaces can reduce vulnerability to heat stress and
food insecurity for low-income neighbourhoods and address
racial inequities in access to green spaces if UA governance
addresses equity concerns (Horst et al., 2017; Titz and Chiotha,
2019; Halvey et al., 2020; Hoffman et al., 2020).
– Multi-species cropping helps to conserve biodiversity (Lovell,
2010; Goldstein et al., 2016).
– Skill building and job opportunities (Lovell, 2010; Mok et al., 2014;
Horst et al., 2017), sometimes in regions and for groups that have
been socially and economically disadvantaged (Horst et al., 2017).
– CES benefits through cultivation of specific crops, cultural
learning, sharing culinary and garden knowledge and
strengthening social networks for socially marginalised ethnic,
racial groups (Horst et al., 2017; Nadeau et al., 2019).
– UPA provides social and health co-benefits such as increased
social interaction and physical and mental health benefits (Horst
et al., 2017; White and Bunn, 2017).
– Can divert organic waste produced in cities as compost, to reduce
water contamination and input costs (Menyuka et al., 2020).
– Can increase the value of land and thereby push out
lower-income households via gentrification (Horst et al., 2017).
– Unconditioned UPA is under strong pressure from other lucrative
land use demands and can be difficult to maintain without
addressing urban social inequities, (Martellozzo et al., 2014;
Horst et al., 2017; White and Bunn, 2017).
– Yields are lower than conventional, rural production, and water
demand is high (Goldstein et al., 2016; Bisaga et al., 2019).
– Air, soil and water quality in urban areas can disturb crop
production and reduce food safety (Eigenbrod and Gruda,
2015; Titz and Chiotha, 2019), and create health risks from
contamination (Mok et al., 2014), causing mixed or even
negative public perceptions against the produce (Specht et al.,
2019; Menyuka et al., 2020). Trace metal contamination in soils
and plants is an increased risk in outdoor UPA (Eigenbrod and
Gruda, 2015; Titz and Chiotha, 2019).
– May provide limited job and income opportunities in low-income
urban areas (Daftary-Steel et al., 2015; Biewener, 2016).
– Outdoor fields are exposed to rising temperatures and urban
heat islands (Chapman et al., 2017). Low water availability may
be another limit for UPA as a form of adaptation (Kareem et al.,
2020; Tankari, 2020). In coastal cities, sea level rise and flooding
from climate change impacts may make significant portions of
cities unuseable for UPA (Algert et al., 2016; Kareem et al., 2020).
Traditional, peri-urban field farms, market
gardens, community farms, community
gardens, home gardens.
Building-integrated Unconditioned
Rooftop gardens, balcony agriculture, and
green wall, but production quantity is small.
Ground-based Conditioned
– Controlled environments can protect crops, livestock and fish
from extreme weather events or pest and disease outbreak
(Mohareb et al., 2017).
– Some building-integrated conditioned farms can utilise
wastewater and waste heat from buildings or other urban source
(De Zeeuw et al., 2011; Thomaier et al., 2015; Mohareb et al.,
2017).
– Innovative indoor farming such as vertical farming (VF) is highly
productive with minimal water and nutrient supply, but highly
energy-demanding (O’Sullivan et al., 2019).
– Some initiatives combine with social justice goals and use
abandoned buildings in low-income neighbourhoods to grow
diverse food types for addressing food security of low-income
groups (Thomaier et al., 2015; Horst et al., 2017).
– Power outages and/or system failure can easily destroy the
production system (Small et al., 2019).
– Initial costs and energy requirements are substantially higher
than those of unconditioned farms (Goodman and Minner, 2019;
O’Sullivan et al., 2019).
– GHG emissions may be higher than conventional rural
agriculture (Santo et al., 2016) and full mitigation potential only
realised with low-energy systems (WGIII, 12.4).
– Commodities are often limited to short-cycled crops such as leafy
vegetables and herbs, and the produce is more expensive, making
it difficult for the urban poor to access (O’Sullivan et al., 2019).
Horticultural farms using glasshouses or
polyhouses. Often exist on the city fringes.
Aquaponics that grow fish in aquaculture
systems and re-use nutrient-rich wastewater.
One of the few options that provide proteins
in urban farms.
Building integrated Conditioned
Rooftop glasshouses, fully indoor, artificially lit
plant factories. Recent advancements include
production using vertical stacks to produce
more food per land area.
Indoor aquaculture is also included.
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menu (Bacon and Krpan, 2018; Kurz, 2018; Garnett et al., 2019; Gravert
and Kurz, 2019), the relative price of vegetarian options (Garnett et al.,
2021) and the ‘access’ (order and distance) to vegetarian options in
the retail physical environment (Garnett et al., 2020) can all increase
consumption of plant-based foods and decrease meat consumption
(Bianchi et al., 2018). Studies on food environment ‘nudging’ methods
found that making the vegetarian meal option the default during
conference registration or on a meal plan significantly reduced meat
consumption (Campbell-Arvai et al., 2012; Hansen et al., 2019b). Studies
simply educating people about the negative health and environmental/
climate outcomes of meat consumption have been found to have very
little impact (Byerly et al., 2018). More research is needed to understand
the potential for motivational crowding in shaping pro-climate dietary
choice, as has been demonstrated in development (Agrawal et al., 2015)
and conservation interventions (Rode et al., 2015).
5.12.7 Integrated Multisectoral Food Security and
Nutrition Adaptation Options
Integrated multi-sectoral strategies that incorporate social protection
are effective adaptation responses (
high confidence
) (Gros et al.,
2019; Ulrichs et al., 2019; Medina Hidalgo et al., 2020; Daron et al.,
2021; Ilboudo Nébié et al., 2021; Verschuur et al., 2021; 7.4.2, Cross-
Chapter Box-GENDER in Chapter 18). Social protection programmes,
such as cash transfers, weather index insurance and asset-building
activities such as well construction, can support short-term responses to
acute food insecurity in response to extreme events but can also build
adaptive capacity longer term (Table 5.16, Costella et al., 2017; Ulrichs
et al., 2019). An assessment of an adaptive social protection programme
in the Sahel found that tailored seasonal forecasting can improve
responsiveness to climate-related extreme events, but investment in
capacity building and dialogue between forecasters, community groups
and humanitarian organisations is needed (Daron et al., 2021). Forecast-
based financing, which automatically disperses funds when threshold
forecasts are reached for an extreme event (Coughlan de Perez et al.,
2016), used in Bangladesh prior to a 2017 flood event allowed low-
income, flood-prone communities to access better-quality food in the
short term without accruing debt (Gros et al., 2019).
Differentiated responses based on food security level and climate risk
can be effective. A study of drought impacts on food security in Senegal
between 1997 and 2016 recommended different adaptation strategies
based on whether the region was a higher risk of acute short-term food
insecurity and/or faced higher risk of drought (Table 5.16; Ilboudo Nébié
et al., 2021). Given identified linkages between higher temperatures
and extreme events with declines in child dietary diversity, safeguarding
diverse diets is one important adaptation priority (Niles et al., 2021).
Humanitarian responses are appropriate for short-term acute hunger,
while in the medium term, home-grown school feeding programmes
with diverse foods can support child nutrition and learning, and with
local procurement can also increase income and food security of
smallholder farmers (Ilboudo Nébié et al., 2021). Farmer associations
can manage regional staple food storehouses, in which farmers store
their harvest and receive credit, and can sell their harvest later in
the season and pay back the credit with interest, strengthening local
supplies and farmer income (Ilboudo Nébié et al., 2021).
A study in Lesotho examined the extent to which climate change
increased the likelihood of an acute drought in 2007, and a related
food crisis (Verschuur et al., 2021). Given land degradation, reliance on
rainfed agriculture and food imports from neighbouring South Africa,
the study recommended crop diversification, increased use of drought
tolerant crop varieties and expanded trade partners in the medium to
long term, to both strengthen regional food production and reduce
risk of crop failure and the likelihood of climate-induced drought
from trade partners reducing food imports (Verschuur et al., 2021). A
longitudinal study of smallholder coffee farmers in Nicaragua found
that crop diversification, alongside crop management and varietal
improvement, would help farmers strengthen food security long
term in the face of climate hazards such as drought and coffee leaf
rust (Bacon et al., 2021). Another medium- to long-term adaptation
response is to address systemic gender, land tenure and other social
inequities as part of an inclusive approach (Bezner Kerr et al., 2019;
Khatri-Chhetri et al., 2020; Bacon et al., 2021). This long-term strategy
could be part of a human-rights-based approach (HRBA, 5.12.8)
5.12.8 Incorporating Human Rights-Based Approaches
into Food Systems
A human rights-based approach (HRBA), endorsed by the UN, is one
strategy for addressing core inequities that are key drivers for food
insecurity and malnutrition of particular groups such as low-income
consumers, children, women, small-scale producers and different
regions of the world (FAO, 2013; Claeys and Delgado Pugley, 2017;
Caron et al., 2018; Le Mouël et al., 2018; Springmann et al., 2018;
Tramel, 2018; HLPE, 2019; Willett et al., 2019). Climate change impacts,
mitigation and adaptation approaches can also worsen inequities
(Eastin, 2018; Borras et al., 2020). HRBA includes core principles of
participation, accountability, non-discrimination, transparency, human
rights, empowerment and rule of law, which can be integrated into
policymaking and implementation as part of transforming the food
system (FAO, 2013; Caron et al., 2018; Toussaint and Martínez Blanco,
2020). The right to well-being can serve as the overarching umbrella
of HRBA to addressing climate change within food systems and
includes a right to health, right to food, cultural rights, the rights of
the child and the right to healthy environment (Swinburn et al., 2019).
An HRBA has a specific focus on those groups who are vulnerable
due to poverty, discrimination and historical inequities and involves
meaningful participation of vulnerable groups in governance, design
and implementation of adaptation and mitigation strategies, including
gender responsiveness and integration of Indigenous Peoples’
knowledge (UNHRC 2017; Caron et al., 2018; Mills, 2018). There can
be conflicts and trade-offs, such as between addressing land rights or
traditional fishing grounds, the right to food, and addressing climate
justice concerns (Mills, 2018; Borras et al., 2020; Section 5.13). Adaptation
strategies that incorporate HRBA include legislation, programmes that
address gender inequities in agriculture, agroecology, recognition of
rights to land, fishing areas and other natural resources, protection
of culturally significant seeds, and community-based adaptation that
explicitly involves marginalised groups in governance (Mills, 2018;
Tramel, 2018; Huyer et al., 2019; Borras et al., 2020; Section 5.14).
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5.13
Climate-Change-Triggered Competition,
Trade-offs and Nexus Interactions in Land
and Ocean
This section presents information about the impacts generated by
competition and trade-offs in food systems and discusses opportunities
and challenges associated with the use of the Nexus framework.
5.13.1 Impacts of Global Land Deals on Land Use,
Vulnerable Groups and Adaptation to Climate
Change
Land deals, also known as large-scale land acquisitions (LSLAs),
describe recent changes in access to land globally (Borras et al.,
2011). Since 2000, at least 160 million hectares have been under
negotiation (Land Matrix, 2021). Land deals surged after the 2007–
2008 food price crisis and farmland investment boom (Fairbairn,
2014), with a diverse range of drivers (Arezki et al., 2015; Zoomers
and Otsuki, 2017; Conigliani et al., 2018) including land-based climate
change interventions (Dunlap and Fairhead, 2014; Davis et al., 2015a;
Hunsberger et al., 2017; Franco and Borras, 2019). Examples are the
expansion of biofuel crops (e.g., Yengoh and Armah, 2016; Aha and
Ayitey, 2017), afforestation and reforestation (A/R) projects (Olwig
et al., 2016; Richards and Lyons, 2016; Scheidel and Work, 2018),
REDD+ (Bayrak and Marafa, 2016; Ingalls et al., 2018), conservation
Table 5.17 |
Examples of adaptation responses to drought and floods by food security level and time frame. Adapted from Ilboudo Nébié et al. (2021) Table 4, with information
from Bahadur et al. (2015); Costella et al. (2017); Gros et al. (2019); Ulrichs et al. (2019); Medina Hidalgo et al. (2020); Bacon et al. (2021); and Verschuur et al. (2021).
Food insecurity level and time frame of adaptation
Adaptation response to drought or floods
Acute,
short term
Moderate,
medium term
Chronic,
long term
Resilience type
Forecast-based financing (provides unconditional cash in advance
of extreme event)
X
Anticipatory
: people and systems are better
prepared for climate shock by reduced
exposure or vulnerability.
Early-warning systems/climate services and education for disaster
preparation
X
X
X
Social protection programmes with regular provisions which allow
for asset building, e.g., savings, building of informal networks,
purchase of livestock
X
X
Humanitarian food aid and malnutrition treatment
X
X
Absorptive capacity
: people or systems cope
with climate-related shocks or systems while
and immediately after they occur.
Home-grown nutrition-sensitive school feeding programmes
X
X
Social protection programmes with short-term targeted response,
e.g., short-term cash transfers, food assistance for asset building
such as wells
X
Weather index insurance program
X
X
X
Regional grain banks run by farmer associations
X
X
Adaptive capacity
: can adjust to long-term
climate risks and disasters, reduce vulnerability
to future shocks.
Savings, credit and local food procurement support for smallholder
farmers
X
X
Agroecosystem diversification, other agroecological practices to
strengthen ecosystem services in long term (see Box 5.10)
X
X
Rainwater evacuation infrastructure combined with flood
management and waste collection and urban gardening
X
X
Drought- or flood-resistant crop varieties
X
X
Expand trade partners beyond climactically connected partners
X
X
Gender transformative or responsive agriculture programmes
X
X
areas (Lunstrum, 2016; Schleicher et al., 2019), renewable energy
installations (e.g., Sovacool, 2021) or natural disaster management
(e.g. Uson, 2017).
Land deals raise important social justice questions (Franco et al.,
2017; Hunsberger et al., 2017; Borras and Franco, 2018b; Borras
et al., 2020; Sekine, 2021) (
high confidence
). Specific impacts of
land deals vary according to their purpose, location, actors, land use
history and procedural aspects. However, multi-case analyses identify
severe adverse impacts (Table 5.18). LSLAs are a significant driver of
tropical forest loss (Davis et al., 2020), increasing emissions through
deforestation (Liao et al., 2021) and industrialisation of agriculture
(Rosa et al., 2021). LSLAs entail large water appropriations (Breu
et al., 2016; Chiarelli et al., 2016; Adams et al., 2019), affecting
local populations’ access to water and food security (Dell’Angelo
et al., 2018; Veldwisch et al., 2018). By increasing exported crops,
and limiting local populations’ access to land, LSLAs produce food
security risks (Marselis et al., 2017; Müller et al., 2021b). Negative
livelihoods impacts arise through enclosure of assets, elite capture
(Oberlack et al., 2016), crowding out of small farmers (Nolte and
Ostermeier, 2017) and reducing local populations’ access to commons
(Dell’Angelo et al., 2016; Giger et al., 2019). Indigenous People are
affected, facing high levels of violence in land acquisition conflicts
(Dell’Angelo et al., 2021). The social burdens of land deals tend to be
gendered (e.g., Fonjong et al., 2016; Nyantakyi-Frimpong and Bezner
Kerr, 2017; Atuoye et al., 2021).
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Local populations can experience declining access to livelihood
resources and deteriorating food security, increasing gendered
vulnerabilities (Yengoh et al., 2015; Faye and Ribot, 2017; Atuoye
et al., 2021). Vulnerable groups displaced by land deals may face
higher exposure to climate change (Dell’Angelo et al., 2017).
LSLAs affecting common-pool resources governed by Indigenous
institutions jeopardise the resilience and adaptive capacity of local
socio-ecological systems (Dell’Angelo et al., 2016; D’Odorico et al.,
2017; Hak et al., 2018; Haller, 2019; Haller et al., 2020). Growing
land tenure insecurity may force farmers to engage in unsustainable
farming and forestry practices (Aha and Ayitey, 2017; Gabay and
Alam, 2017) and hinder agroecological innovations to manage
climate risks (Nyantakyi-Frimpong, 2020b). Social justice concerns
and vulnerability of local populations can be addressed by promoting
land redistribution and recognition, particularly for customary lands
of Indigenous and ethnic minorities, and land restitution to those
who were forcibly displaced (Franco et al., 2015; Borras and Franco,
2018a).
Table 5.18 |
Adverse social and ecological risks and impacts of agricultural land deals on land use and vulnerable groups.
Land use dimensions
Impacts and implications
References (2014 to present)
Forestry
Direct and indirect land use change provoked by LSLAs accelerates deforestation of tropical forests
globally (
medium confidence
).
Multi-case analyses
Davis et al. (2020)
Case study examples
Davis et al. (2015b)
Scheidel and Work (2018), Magliocca et al. (2020)
Energy use and access
Expected land use changes provoked by agricultural LSLAs have high fossil-energy footprints. LSLAs
may adversely affect local populations’ access to energy resources (
medium confidence
).
Multi-case analyses
Rosa et al. (2021)
Carbon emissions
LSLAs have high carbon footprints resulting from deforestation and industrialisation of agriculture
(
medium confidence
).
Multi-case analyses
Liao et al. (2021)
Rosa et al. (2021)
Case study examples
Johansson et al. (2020)
Liao et al. (2020)
Water use and access
LSLAs frequently involve water appropriations, which may affect access to water, traditional
agriculture and the human right to food of local populations (
medium confidence
).
Multi-case analyses
Breu et al. (2016)
Chiarelli et al. (2016)
Dell’Angelo et al. (2018)
Case study examples
Adams et al. (2019)
Tejada and Rist (2018)
Food security and nutrition
LSLAs pose food security risks by re-orienting crop production to nutrient-poor crops predominantly
destined for export, and/or excluding local populations from agricultural land (
high confidence
).
Multi-case analyses
Cristina Rulli and D’Odorico (2014)
Mechiche-Alami et al. (2021)
Marselis et al. (2017)
Müller et al. (2021b)
Conceptual studies
Häberli and Smith (2014)
Case study examples
Shete and Rutten (2015)
Mabe et al. (2019)
Bruna (2019)
Hules and Singh (2017)
Moreda (2018)
Atuoye et al. (2021)
Livelihoods
LSLAs often lead to adverse livelihood impacts and increased livelihood vulnerability of local
populations (
high confidence
).
Multi-case analyses
Davis et al. (2014)
Oberlack et al. (2016)
Nolte and Ostermeier, 2017)
Vandergeten et al. (2016)
Schoneveld (2017)
Conceptual studies
Zoomers and Otsuki (2017)
Case study examples
Richards and Lyons (2016)
Shete and Rutten (2015)
Yengoh and Armah (2016)
Mabe et al. (2019)
Gyapong (2020)
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5.13.2 Trade-offs Generated by Agricultural
Intensification and Expansion
Agricultural intensification seeks to increase agricultural productivity
per input unit, reducing the pressure on land use and generating
positive impacts in GHG emissions (Mbow et al., 2019), but valuing
the final effect requires common metrics in terms of carbon capture or
emission reductions (Searchinger et al., 2018). It has been suggested
to address multiple SDGs (SDG2, SDG13, SDG15) but only occasionally
leads to simultaneous positive ecosystem service and well-being
outcomes (Rasmussen et al., 2018). When the process relies only on
increasing input use, there is a risk of generating adverse outcomes
that may override positive effects, such as CO
2
emissions, (McGill et al.,
2018), NOx emissions (Hickman et al., 2017), soil salinisation and
groundwater depletion (Doody et al., 2015; Daliakopoulos et al., 2016;
Fragaszy and Closas, 2016; Foster et al., 2018; Flörke et al., 2019).
Agricultural intensification could meet short-term food security and
livelihood goals, but reduces biological and landscape diversity, and
ecosystem services (
high confidence
) (Campbell et al., 2017; Balmford
et al., 2018; Springmann et al., 2018; Ickowitz et al., 2019; Mbow
et al., 2019). Agricultural intensification can also affect livelihoods
of small-scale producers, compromising food security. It can increase
low-waged casual farm work, increasing gender and income inequity
(Bigler et al., 2017; Clay and King, 2019; Table 5.18).
Land available for provisioning ecosystem services is declining in
many places because of agricultural expansion, bioenergy crops
and reforestation for mitigation (Kongsager, 2018), with adverse
climate impacts (Froese and Schilling, 2019). Cropland expansion can
deteriorate biodiversity (Delzeit et al., 2017), water quality (Ayala
et al., 2016) and carbon storage (Goldstein et al., 2012) and increase
water demands (Yokohata et al., 2020).
A systems-based perspective on land use is needed to address
climate change impacts on nutrition security and ecosystem services
(Springmann et al., 2018; IPCC, 2019b; Willett et al., 2019). Land
Land use dimensions
Impacts and implications
References (2014 to present)
Indigenous People and
commons
LSLAs often have adverse impacts on Indigenous peoples and lands, including land encroachment,
dispossession, and displacement.
Land deals frequently target common land and may increase the vulnerability of customary,
traditional, and Indigenous systems common property, while reducing their adaptive capacity (
high
confidence
).
Multi-case analyses
Dell’Angelo et al. (2016)
Giger et al. (2019)
Dell’Angelo et al. (2021)
Conceptual studies
Haller et al. (2020)
Case study examples
Olwig et al. (2016)
Moreda (2017)
Montefrio (2017)
Scheidel and Work (2018)
Konforti (2018)
Pietilainen and Otero (2019)
Mingorría (2018)
Bukari and Kuusaana (2018)
Haller (2019)
Hak et al. (2018)
Gabay and Alam (2017)
Imbong (2021)
Gender
Impacts and implications of land deals are sometimes experienced in different ways by different
genders (
high confidence
).
Case study examples
Tsikata and Yaro (2014)
Yengoh et al. (2015)
Fonjong et al. (2016)
Nyantakyi-Frimpong and Bezner Kerr (2017)
Elmhirst et al. (2017)
Bottazzi et al. (2018)
Ndi (2019)
Osabuohien et al. (2019)
Porsani et al. (2019)
Atuoye et al. (2021)
Impacts on other climate
change mitigation and
adaptation initiatives
LSLAs may undermine mitigation and adaptation initiatives and other land uses relevant for climate
change mitigation and adaptation (
high confidence
).
Multi-case analyses
Carter et al. (2017)
Case study examples
Borras et al. (2020)
Gabay and Alam (2017)
Nyantakyi-Frimpong (2020b)
Scheidel and Work (2018)
Rodríguez-de-Francisco et al. (2021)
Other environmental
impacts
LSLAs are projected to provoke global environmental change; LSLAs are a potential driver of slope
instability; LSLAs affect natural habitats such as tiger landscapes; LSLAs jeopardize biodiversity (
low
confidence
).
Lazarus (2014)
Chiarelli et al.(2021)
Debonne et al.(2019)
Balehegn (2015)
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sparing sets aside some land for conservation purposes and intensifies
production on farmland (Balmford et al., 2018; Benton et al., 2018;
IPCC, 2019b), with potential to offset GHG emissions (Lamb et al.,
2016). Alternatively, ‘land sharing’ approach employs principles such
as minimising fossil-fuel-based inputs, maximising synergies, and
addressing climate change mitigation and adaptation as well as
biodiversity (Kremen and Miles, 2012; Kremen, 2015; Kremen and
Merenlender, 2018; HLPE, 2019; Section 5.14, Box on Agroecology).
Community-managed initiatives can address biodiversity and
ecosystem conservation, livelihoods, food provisioning and other
ecosystem services (Kremen and Merenlender, 2018; HLPE, 2019).
The concept of sustainable intensification has emerged, looking for
enhancements in environmental outcomes, while maintaining or
increasing agricultural systems performance. There is a potential to find
synergies between agricultural production and landscape systems if
systems are designed to operate within planetary boundaries (Rockström
et al., 2017; Liao and Brown, 2018; Pretty, 2018; Pretty et al., 2018).
5.13.3 Competition between Food Systems in Land and
Ocean
Livestock and aquaculture feeds utilise crops such as soyabean
and maize, with food conversion efficiencies similar in chicken and
Atlantic salmon, and higher in pigs and cattle (Troell et al., 2014;
Fry et al., 2018b; Fry et al., 2018a). Use of wild fish meal and oil has
been decreasing, partly due to concerns regarding vulnerable small
pelagic fish stocks (Bindoff et al., 2019). The instability of wild fish
stocks has increased terrestrial crop feed components (Troell et al.,
2014; Blanchard et al., 2017; FAO, 2017; Cottrell et al., 2018). The use
of wild fish in fish feeds that may have been directly consumed may
put low-income households at risk of food insecurity (Troell et al.,
2014). An increasing demand for aquaculture products intensifies
competition for feed supplies (
medium confidence
) (Troell et al., 2014;
Blanchard et al., 2017). Increases in demands for animal protein and
shifts to pescatarian diets will increase the existing competition for
land resources, particularly in low- and medium-income countries,
with negative impacts on food security (Makkar, 2018), but may be
mitigated by dietary changes, novel feeds and food waste usage for
aquatic systems (Berners-Lee et al., 2018; Hua et al., 2019; Cottrell
et al., 2020).
Competition over use of major aquaculture feed crops (Fry et al., 2016)
with terrestrial livestock (Troell et al., 2014), and fish use by terrestrial
livestock, will also place pressure on fish and crop resources (
medium
confidence
) (Cottrell et al., 2018). Increases in feed prices will affect
fish and meat prices (Troell et al., 2014), and changes in agriculture
will be needed to satisfy aquaculture demands (Blanchard et al., 2017).
Aquaculture and livestock dietary components may also compromise
crops and forage fish that provide essential nutrients for low-income
households increasing nutritional insecurity, in regions of sub-Saharan
Africa, Asia and Latin America (Troell et al., 2014). Waste fish products
can supplement fish meal and oil to reduce competition for feed, as
well as reducing use of fish that could go to human consumption
(
medium confidence
) (Little et al., 2016; Shepherd et al., 2017; Dave
and Routray, 2018; Naylor et al., 2021). Use of algae, bacteria, yeast
and insect diets could replace fishmeal for aquaculture (Cohen et al.,
2018; Hua et al., 2019; Cottrell et al., 2020), not affecting nutritional
profiles (Campanaro et al., 2019), and fish could be reared on waste
by-products of other food production systems (Bava et al., 2019).
Complete fish oil substitutions with microalgae may be possible
without compromising omega-3 contents, but energy usage in diet
production should be considered Cottrell et al. (2020). Substitutions
of plant-based and alternative feeds may decrease food conversion
efficiencies (Cottrell et al., 2020), affect omega-3 content of farmed
seafood (Fry et al., 2016; Shepherd et al., 2017), be problematic for
the fish themselves (Little et al., 2016; Naylor et al., 2021) and lead to
reduced productivity (Shepherd et al., 2017).
Competition will be heightened by other climate impacts, such as
changes in water availability. Water usage is relatively high in animal
production (Abraham et al., 2014; Sultana et al., 2014; de Miguel et al.,
2015; Palhares and Pezzopane, 2015; Weindl et al., 2017). In some
areas, increased demand for plant-based animal feeds will be affected
by sea level rise and competing usage of available freshwater with
other users, and ecosystem needs (Karttunen et al., 2017).
5.13.3.1 Agricultural and river runoff
Flooding on agricultural land will enhance nutrient runoff, creating
eutrophication and increasing harmful phytoplankton blooms,
affecting fisheries and aquaculture, human health and ecosystem
biodiversity. Changes in precipitation, monsoons, runoff and flood
potential combine with deforestation and poor sewage treatment,
Table 5.19 |
Case studies of trade-offs and negative outcomes associated with agricultural intensification on biodiversity and ecosystem services.
Ecosystem service
Trade-offs/negative outcomes
References
Provisioning: water quality
Negative impacts on ephemeral wetlands
Dalu et al. (2017)
Provisioning: water availability
Contribution to water scarcity
Satgé et al. (2019)
Supporting: soil
Increasing erosion risk
Govers et al. (2017)
Regulating: climate
Reduced SOC sequestration
Olsen et al. (2019)
Regulating: pest control
Reduced level of biological control of pests; reduced
number of insectivorous birds
Emmerson et al. (2016)
Cultural: recreational
Reduction of river wildlife
DeBano et al. (2016)
Biodiversity
Reduced global biodiversity
Newbold et al. (2015), Egli et al. (2018), Beckmann et al. (2019)
Biodiversity
Reduction of taxonomic diversity
Jeliazkov et al., (2016), Kehoe et al. (2017), Banerjee et al. (2019)
Biodiversity
Negative impacts on mean population stability
Olivier et al. (2020)
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resulting in larger volumes of nutrients and freshwater reaching coastal
ecosystems (Jin et al., 2018; Nasonova et al., 2018; Tamm et al., 2018).
Rising surface temperatures, ocean acidification and eutrophication
will increase pathogenic
Vibrio
bacterial loads in marine organisms,
with potential transfer to humans (Hernroth and Baden, 2018).
Shallow and microtidal estuaries will be more vulnerable to changing
river runoffs and saltwater intrusions, eutrophication and hypoxia
(
high confidence
) (IPCC, 2019c).
5.13.4 Maladaptation Responses and Sustainable
Solutions
Maladaptation can result in three types of outcomes (Juhola et al., 2016):
(1)
rebounding vulnerability
: short term adaptations that decrease
adaptive capacity and hinder future choices; (2)
shifting vulnerability
:
larger-scale adaptation actions that produce spill-over effects in other
locations; (3)
eroding sustainable development
: adaptation strategies
which increase emissions and deteriorate environmental conditions
and/or social and economic values (Tables 5.20 and 5.21).
Existing climate policies do not adequately consider trade-offs,
adaptive limits, cumulative costs and potential risks of maladaptation
(
robust evidence
,
medium agreement
) (Dovie, 2017; Holsman et al.,
2019; IPCC, 2019b; Work et al., 2019; Thomas, 2020: Table 5.19).
Government policies are seldom coordinated across scales and often
focused on regional short-term risks (
medium evidence
,
medium
agreement
) (Dovie, 2017; Holsman et al., 2019; Rahman and Hickey,
2019; Butler et al., 2020). Past development trajectories and dominant
political economic structures may narrow adaptation pathways, be
restrictive and increase the vulnerability of particular groups (Paprocki,
2018; Quan et al., 2019; Rahman and Hickey, 2019; Work et al., 2019).
Case Studies of Maladaptation
Large-Scale Irrigation Project in Navarre, Spain
Many small-scale producers could not afford the irrigation investment
and had to sell or rent their land to those who joined the irrigation
project. Many large-scale farmers using irrigation switched to corn
and forage and dropped crops with high labour costs. Water costs are
now paid to a private company, and small-scale farmers lost access
to communal water rights. The project increased inequity and land
concentration and lowered crop diversity, with small-scale producers
more vulnerable to climate change. Large-scale intensive farmers are
more exposed to crop price volatility than to climate vulnerability but
have greater access to subsidies and water rights (Albizua et al., 2019).
Constraining Adaptation: Previous Agricultural
Development Pathways in India
Government policies in colonial and postcolonial India invested in
infrastructure, export production and synthetic input use (Gupta,
1998; Davis, 2001), setting the stage for current development
trajectories and closing out other adaptive options. Although
such policies increased national food production, they failed to
address high levels of malnutrition, worsening regional inequities,
degraded natural resources and an agrarian debt crisis (Singh, 2000;
Gupta et al., 2016; Gajjar et al., 2019). Agricultural livelihoods are
increasingly considered unviable, with lower adaptive capacity of
farmers, high debt levels (Gupta et al., 2016), and Indigenous and local
knowledge loss and denigration (Kumar, 2016) alongside lower crop
diversification (Srivastava et al., 2016). Government institutions aimed
at infrastructure often lack adaptive capacity needed to address rural
livelihoods (Singh et al., 2017; Gajjar et al., 2019).
Adaptation options that consider adverse effects for different
groups reduce the risk increasing vulnerability, negatively affecting
socioeconomic factors to deal with climate impacts, or impeding efforts
to implement SDGs (
high confidence
) (Juhola et al., 2016; Antwi-Agyei
et al., 2018; Paprocki and Huq, 2018; Holsman et al., 2019; IPCC, 2019b;
Stringer et al., 2020). Adaptation methods considering historical roots
of current vulnerabilities can identify viable solutions, which are
difficult to undertake because of path dependencies (
high confidence
)
(Ribot, 2014; Albizua et al., 2019; Gajjar et al., 2019; Paprocki, 2019;
Thomas, 2020). Planning techniques that model outcomes for different
groups from different adaptation options could be put in place to
diminish maladaptation risks (Rodríguez et al., 2019).
Inclusive planning initiatives such as community-based anticipatory
adaptation combined with ‘two-way learning’ that considers future
scenarios and different adaptation pathways can prevent maladaptation
(
high confidence
)
(Dovie, 2017; Bezner Kerr et al., 2019; Neset et al.,
2019a; Rahman and Hickey, 2019; Work et al., 2019; Butler et al., 2020;
Nunn et al., 2020; Piggott-McKellar et al., 2020; Westoby et al., 2020;
Table 5.20). Promising policy management tools combine temporal
scales and mitigation–adaptation interactions and consider political
dynamics, socioeconomic impacts and trade-offs for vulnerable groups,
long-term support for policy leaders, efforts to establish livelihood
‘niches’ and ongoing participatory evaluation (Dovie, 2017; Holsman
et al., 2019; Rahman and Hickey, 2019; Work et al., 2019; Butler et al.,
2020). A focus on the most disadvantaged groups can help small-
scale producers at higher risk to prevent maladaptation (FAO, 2018c).
Governance mechanisms have emerged that consider food security,
socio-cultural factors, and land and water rights, using participatory,
inclusive ‘two-way learning’ methods that involve vulnerable people
alongside government (IPCC, 2018; Holsman et al., 2019; IPCC, 2019b;
Rahman and Hickey, 2019; Butler et al., 2020).
5.13.5 Climate Change and Climate Response Impacts on
Indigenous People
Indigenous people and ethnic minorities, many of them having special
cultural associations to local foods, are particularly vulnerable to
climate change owing to changes in the availability of wild foods, crop
failure and food production losses or increased food prices (Norton-
Smith et al., 2016; Otto et al., 2017).
Changes in sea level rise or coastal erosion can reduce ecosystem services
to a point where either subsidies are used to enable human populations
to remain in their place of attachment, or ultimately to displace coastal
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Table 5.20 |
Summary of the emerging literature on potential risks of maladaptation.
Description of
adaptation strat-
egy
Potential negative impacts
Maladaptation typology
(1 = rebounding vul-
nerability, 2 = shifting,
3 = eroding SDGs) and
confidence level
Regions and
countries
affected
Groups affected
References
Agricultural
intensification to
increase productivity,
in places with heavy
rainfall events or rising
pest/disease incidence
Increases GHG emissions, water pollution,
possible insect resistance and costs to
farmers; possibly increases inequities.
May constrain adaptation policy options
for development pathways due to lock-ins
and trade-offs which entrench inequities.
1, 2, 3
Robust evidence, medium
agreement
USA, Africa, Asia
(India, China),
Europe
Farmers, pastoralists/
nearby communities who
rely on water; small-scale
farmers who cannot afford
inputs; policymakers.
Gajjar et al. (2019),
Guodaar et al. (2019),
Houser and Stuart (2019),
Neset et al. (2019b), Quan
et al. (2019), Young and
Ismail (2019)
Livelihood
diversification into
charcoal production
Increases GHG emissions and
deforestation rates
1, 3
medium
Africa (Northern
Ghana), South
America (Peru)
Small-scale food producers;
Indigenous communities
Antwi-Agyei et al. (2018),
Zavaleta et al. (2018),
Young and Ismail (2019)
Irrigation projects or
programmes that are
either large-scale and/
or rely on groundwater
Reduces long-term potential for
hydropower and groundwater availability,
can increase salinisation and cost of water.
Can increase cost of farming and
debt levels of farmers, squeezing out
small-scale producers.
Can reduce water availability for
aquaculture.
1, 2, 3
high
Central
China, India,
Mediterranean
areas, Europe,
USA
Food producers who rely
on irrigation; consumers
who rely on hydropower or
groundwater; small-scale
diversified producers who
cannot afford irrigation;
aquaculture.
Doody et al. (2015), Herbert
et al. (2015), Barik et al.
(2016), Daliakopoulos
et al. (2016) Fragaszy
and Closas (2016) Dalin
et al. (2017), Foster et al.
(2018) Hanaček and
Rodríguez-Labajos (2018),
Albizua et al. (2019), Flörke
et al. (2019) Gajjar et al.
(2019), Zhang et al.(2019a)
Investment in
improved cultivars or
shift to different crops
May displace local varieties; reduces
diversity if too much policy/extension
emphasis falls on a few varieties; may
increase risk of crop loss from pests,
disease or drought if reliant on a few
varieties; may increase fertilizer use;
may lead to loss of Indigenous or local
knowledge.
1, 3
medium
South America
(Bolivia, Pacific
Islands, Asia
Small-scale food producers;
Indigenous communities
Mcleod et al. (2018),
Meldrum et al. (2018),
Neset et al. (2019b)
Rahman and Hickey (2019)
Migration
Can increase the workload of people
left behind (often women), worsen rural
livelihoods and food insecurity; can
lead to worsened living conditions, food
security and poverty in precarious urban
conditions; may increase vulnerability to
flooding in urban locations.
May affect mental health by disrupting
existing social ties.
1, 3
high
Asia, Africa,
Central and
South America
Small-scale low-income
food producers or rural
workers; women
Bettini et al. (2017),
Paprocki (2018), Chen
et al. (2019), Jacobson
et al. (2019), Michael et al.
(2019), Young and Ismail
(2019), Singh and Basu
(2020), Torres and Casey
(2017)
Coastal sea walls,
embankments, canals,
riverbed draining and
dikes to reduce flood
risk
Can degrade coastal mangroves,
deplete open freshwater fisheries, cause
sedimentation of rivers, reduce fish
diversity and increase flooding risk for
particular vulnerable groups; may divert
funds from other more sustainable
measures.
1, 2, 3
high
Asia, South
Pacific Islands,
West Africa
Coastal communities
dependent on mangroves
and fisheries; low-income
rural households with
seasonal dependence on
inland fisheries
Dovie (2017),
Owusu-Daaku (2018),
Freduah et al. (2019), IPCC
(2019c), Rahman and
Hickey (2019), Nunn et al.
(2020) Seddon et al. (2020),
Thomas (2020)
River regulation for
hydropower
May have negative impacts on inland
fisheries.
2, 3
Global
Small-scale inland fisheries
and low-income rural
households with seasonal
dependence on inland
fisheries
FAO (2018c)
Government
policies to manage
coastal fisheries
which promote
overcapitalisation of
fisheries, including
index insurance
Government confiscation of fishing nets
to prevent rapid decline of fish population
can worsen livelihoods for small-scale
fishers; subsidies of pre-mixed fuel to
allow fishers to stay out longer due to
shifting fish populations may increase
total number of fishers and total fish
catch; insurance payments may benefit
larger-scale fishing fleets and push out
small-scale fishers.
1, 3
medium
West Africa
Coastal small-scale fishery
communities
FAO (2018b), Freduah et al.
(2019), Holsman et al.
(2019), Sainsbury et al.
(2019)
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Description of
adaptation strat-
egy
Potential negative impacts
Maladaptation typology
(1 = rebounding vul-
nerability, 2 = shifting,
3 = eroding SDGs) and
confidence level
Regions and
countries
affected
Groups affected
References
Consultative
stakeholder systems
in fisheries or flood
management
May encourage inertia in the system
due to a few powerful stakeholders
participating in the consultative process.
2
low
North America,
Asia
Coastal fisheries
Holsman et al. (2019),
Rahman and Hickey (2019)
Climate services
May reinforce existing inequities if
climate services are attuned to powerful
stakeholders in industry, services are
privatised, there are limited ways to
get input from vulnerable groups and
planning budgets that use climate services
are constrained.
1, 2, 3
medium
North America
Coastal fisheries, farming
Furman et al. (2014),
Webber (2017), Nost
(2019)
Nature-based solutions
mitigation and
adaptation strategies
such as reforestation
or afforestation
Can displace local communities’ access
to land for food production and other
ecosystem services, have negative impacts
on Indigenous rights, reduce biodiversity
and may not reduce GHG as much as
conserving natural forests and wetlands or
agroecological systems such as agroforestry
or other means to increase soil C.
2, 3
medium
Africa, Asia, and
South America,
e.g., Indonesia,
Amazon,
west-central
Africa
Indigenous communities;
small-scale producers
and forest-dependent
communities
Lunstrum et al. (2016),
Work et al. (2019), Seddon
et al. (2020), Cross-Working
Group Box BIOECONOMY
this chapter)
Social safety nets
provide funds which
increase consumption
of processed,
purchased food and
erode Indigenous
knowledge
Decline in Indigenous knowledge of
and collective approaches to seasonal
adaptation strategies in hunting, fishing
and food production; shift in dietary
patterns to more processed and non-local
foods; reduction in farming. Reduced
capacity to respond to hazards through
dispersed settlement, e.g., hunting,
fishing, wild food collection. Increased
population density increases deforestation
and vulnerability.
1, 3
low
South America
(Amazonian
region of Peru),
Africa (South
Africa)
Indigenous communities
Lemos et al. (2016),
Zavaleta et al. (2018)
Community-based
adaptation strategies
Local gender and other social inequities
can lead to ‘elite capture’ that reinforces
inequity; power dynamics between the
funding agency and local participants
can make local community involvement
tokenistic. There may be inadequate
attention to socio-cultural preferences
and structural factors which foster
maladaptation such as inappropriate
crops or animals used.
1, 3
high
Pacific Islands,
Africa, Asia
Small-scale food producers;
Indigenous communities,
other vulnerable groups
such as women and
low-caste groups
McNamara and Buggy
(2017) Jamero et al.
(2018), Singh (2018)
Bezner Kerr et al. (2019)
Piggott-McKellar et al.
(2020), Westoby et al.
(2020)
Digital agriculture for
increased precision
and efficient use of
fertilizers, pesticides,
water
Could lead to net job losses, particularly
for those with lower levels of education;
increased surveillance and employer
scrutiny of lower-skilled workers in fields,
greenhouses and processing plants and
warehouses; separate workers from
employees and companies who collect
data. Overall increased racial, income
inequities and unequal working conditions.
2, 3
low
North America,
South America,
Europe, Asia,
parts of Africa
Farmworkers; small-scale
food producers who cannot
afford digital technologies;
rural communities
(Furman et al. (2014), Rotz
et al. (2019)
Increased credit
access for livelihood
diversification
High interest rates, tight return policies
could increase debt loads for low-income
households, which could rebound
vulnerability. Household may invest in
livelihood strategies which are vulnerable
to climate change impacts, or which
increase GHG.
1, 3
low
Asia
(Bangladesh)
Low-income landless
people or small-scale
producers
Rahman et al. (2018)
Aquaculture
Large-scale coastal aquaculture can
increase soil salinisation and reduce land
available for other food production and
increase migration.
2, 3
low
Asia
(Bangladesh)
Small-scale mixed systems
including rice production
and other rural livelihoods
Paprocki (2018), Paprocki
and Huq (2018)
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residents, thereby removing connections to places of intrinsic value. For
example, the United Houma Nation in Louisiana is experiencing coastal
land loss, sea level rise and strong Gulf hurricanes, which leads to the
relocation of some tribes causing loss of Houma identity (Sullivan and
Rosenberg, 2018). Another example is the relocation of Alaska Native
communities due to climate change (Hamilton et al., 2016)
Expansion of agriculture can bring distress to Indigenous communities
because of environmental deterioration and the stress associated with
relocation or displacement (Otto et al., 2017). A/R programmes can also
bring inequities to Indigenous communities (Godden and Tehan, 2016)
and even violent displacement with tragic results (Celentano et al.,
2017). A/R programmes can negatively affect a range of substantial
and procedural Indigenous Peoples’ rights entrenched in international
human rights law (Table 5.22) and their potential for climate change
adaptation (
high confidence
).
A significant proportion of land targeted for A/R projects is inhabited
and used by Indigenous Peoples and local communities (Cagalanan,
2016). Indigenous Peoples have rights to and/or manage at least
37.9 million km
2
of land and influence land management across
at least 28.1% of the land area (Garnett et al., 2018). At least a
quarter of the global land area is traditionally owned, managed,
used or occupied by Indigenous Peoples, overlapping with 35–40%
of the area that is formally protected (Garnett et al., 2018; Brondizio
et al., 2019). In many cases, A/R is implemented in areas where
tenure rights are insecure and Indigenous Peoples’ rights are at
risk of being disregarded (Naughton-Treves and Wendland, 2014;
Kohler and Brondizio, 2017; Garnett et al., 2018) (
medium evidence
,
high agreement
). Many projects are also found in areas where
complex socio-political contexts challenge management (Jurjonas
and Seekamp, 2019). It is anticipated that A/R projects will create
huge pressures on existing land uses and generate further land use
conflicts (Aggarwal, 2014; Robinson et al., 2014; Paul et al., 2016;
Brancalion and Chazdon, 2017; Pye et al., 2017; Bond et al., 2019).
In addition, many afforestation projects are conducted in regions
that are not bio-climatically suitable, leading to the degradation of
ecosystems that are key to local livelihoods (Veldman et al., 2015;
Robinson et al., 2016b).
Until 2010, most A/F projects had technical, carbon-related goals
and did not consider issues of livelihoods, community involvement
or broader ecosystem impacts (Wolde et al., 2016). New strategies
such as nature-based solutions (Seddon et al., 2020) and forest and
landscape restoration (Brancalion and Chazdon, 2017) integrate a
larger set of social and environmental objectives. Indigenous Peoples
enjoy a range of co-benefits of A/F initiatives such as improved habitat,
fire management or protection from climatic shocks such as drought
(Robinson et al., 2016b; Seddon et al., 2020), provided they are able to
manage carbon funds collectively, meet the monitoring and reporting
requirements, and protect forests from illicit uses and natural disasters
(Wolde et al., 2016).
Policies and safeguards attached to specific A/R initiatives determine
their impact (
high confidence
) (Talor, 2015; West, 2016; Brancalion and
Chazdon, 2017). In countries where there is a great level of devolution
of rights to Indigenous Peoples, there is a risk that the A/R agenda
will lead to recentralisation (
limited evidence
,
medium agreement
)
(Bayrak and Marafa, 2016). Some A/R initiatives specify the need to
respect the rights of Indigenous Peoples and local communities and
protect biodiversity (
medium evidence
,
high agreement
) (Seddon
et al., 2020).
Local communities’ ability to participate in project design, implementation
and monitoring is directly linked to the autonomy and independence
of local institutions (Pye et al., 2017), their ability to formulate by-laws
(Wolde et al., 2016) and handle funds in a transparent way (
medium
evidence
,
high agreement
) (Witasari, 2016). It is further dependent on
cohesion in the community (Cagalanan, 2016), the existence of clear
rules delineating community membership and the presence of elders and
community members with relevant local knowledge (Robinson et al.,
2016b), and gender and out-migration dynamics affecting participation
structures (
robust evidence
,
medium agreement
) (Cormier-Salem and
Panfili, 2016; Witasari, 2016; Wolde et al., 2016; Jurjonas and Seekamp,
2019).
Table 5.21 |
Strategies to avoid maladaptation (adapted from Magnan, 2014; Lim-Camacho et al., 2015; Sovacool et al., 2015; FAO, 2018b; Paprocki and Huq, 2018; Sainsbury
et al., 2019).
Type of maladaptation
Strategies
Environmental
i) Prevent negative effects on ecosystem services
in situ
(e.g., habitat degradation, pollution) that increase exposure to climate hazards.
ii) Avoid increasing pressure on other socio-ecological systems.
iii) Ensure ecosystems’ protective role as natural buffer zones is sustained against current and future climate-related hazards, such as storms, floods and sea
level rise.
iv) Provide some duplication and ensure flexibility of adaptation strategies to reduce risk because of uncertainties about climate change impacts and
ecosystem response (e.g., agrobiodiversity to reduce pest outbreaks).
Socio-cultural
i) Consider local social characteristics and cultural values that could affect risks and environmental dynamics.
ii) Support local skills and knowledge related to climate-related hazards.
iii) Support capacity-building for new skills needed by local communities.
Political-economic
i) Consider the political dynamics and power imbalances and create inclusive processes to involve the most vulnerable and disadvantaged groups in
decisions.
ii) Work to reduce socioeconomic inequities, poverty and food insecurity.
iii) Support livelihood diversification.
iv) Focus on the impacts of adaptation on the poorest, structurally disadvantaged and vulnerable groups, and take power imbalances into account.
v) Work across the full supply chain to consider linkages and possible ripple effects.
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5.13.6 Increased Presence of Financial Actors in the
Agrifood System
Financial actors, markets, institutions and incentives have gained
importance in agricultural commodities and farmland markets in the
past two decades (Clapp and Isakson, 2018; Fairbairn, 2020). New
types of investment vehicles such as commodity index funds that
track prices of commodities and farmland have emerged, and the use
of older vehicles such as forward and futures markets has increased
(Schmidt and Pearson, 2016; Clapp and Isakson, 2018). These trends are
connected to climate change as financial investments are influenced
by the likelihood that climate change will increase commodity and
farmland price variability (
medium confidence
) (Cotula, 2012; Isakson,
2014; Tadesse et al.).
Table 5.22 |
Indigenous rights recognised in international human rights law negatively affected by A/R projects.
Negative impacts of monoculture plantations (and
other A/R projects)
Indigenous Peoples’
rights affected
Degree of certainty
References
Local community not informed, not adequately consulted, not
provided means for meaningful participation in project design,
implementation, and monitoring (with specific attention to
women and poor households); disruption or non-recognition
of local or traditional institutions; elite capture; no access to
third-party grievance mechanisms.
Right to self-determination;
consultation and free, prior
and informed consent (FPIC);
participation
Medium evidence
,
high
agreement
Aggarwal (2014), Maraseni et al. (2014), Ravikumar
et al. (2015), Bayrak and Marafa (2016), Loaiza et al.
(2016), Vijge et al. (2016), Pye et al. (2017), Ryngaert
(2017), Wolde et al. (2016), Brancalion and Chazdon
(2017), Seddon et al. (2020)
Evictions and displacement; dispossession; livelihood precarity;
and criminalisation of forest-dwelling people.
Right not to be forcibly
removed
Medium evidence
,
high
agreement
Mingorría (2014), Richards and Lyons (2016),
Witasari (2016), Corbera et al. (2017), Pye et al.
(2017), Sarmiento Barletti et al. (2020), Brancalion
and Chazdon (2017)
Loss, transfer or acquisition of land. A/R projects involve
changes in land use for medium to long term and often lack
consideration for local dynamics including land tenure and
competition with agriculture or conservation.
Rights to land and territory
Limited evidence
,
high
agreement
Aggarwal (2014), Robinson et al. (2014), Bayrak and
Marafa (2016), Pye et al. (2017), Bond et al. (2019)
A/R projects exacerbate conflicts, accentuate uneven power
relations, increase existing inequities within communities,
exclude the poor and deepen structural injustices, including
racism and stigmatisation.
Rights to land and territory
Limited evidence
,
low
agreement
Aggarwal (2014)
Forest expansion intensifies already acute land shortages for
growing food and forces villagers to take their animals for
grazing to new areas as a result of forests being fenced off.
Rights to land and territory
(with implications for food
security)
Limited evidence
,
high
agreement
Lyons et al. (2014), Wolde et al. (2016), Brancalion
and Chazdon (2017), Mousseau and Teare (2019)
Decreased stream flows and water yields; exacerbated water
scarcity.
Right to water
Robust evidence
,
high
agreement
Veldman et al. (2015), Aitken and Bemmels (2016),
Brancalion and Chazdon (2017), Pye et al. (2017),
Bond et al. (2019), Seddon et al. (2020)
Pollution of lakes with agrochemicals; heavy chemical use,
including the spread of pesticides, herbicides and fertilizers by
aircraft and other means causing runoff into rivers.
Right to a healthy
environment
Medium evidence
,
high
agreement
Richards and Lyons (2016), Johansson and Isgren
(20179, Pye et al. (2017)
Encroachment on other ecosystems with devastating impacts
on biodiversity; pressures on ecologically sensitive ecosystems
such as wetlands; reduction in seed-dispersing animals; planted
tree species becoming invasive, introducing pests and diseases.
Right to a healthy
environment, right to food
Medium evidence
,
high
agreement
Richards and Lyons (2016), Holmes et al. (2017),
Seddon et al. (2020), Ennos et al. (2019)
Loss of habitat, degradation of savannas, native grasslands
(grassy biomes) or mangroves wrongly characterised as
degraded land suitable for afforestation.
Right to a healthy
environment, right to food
Robust evidence
,
high
agreement
Veldman et al: (2015), Cormier-Salem and Panfili
(2016), Brancalion and Chazdon (2017), Bond et al.
(2019), Seddon et al. (2020)
Direct negative health impacts; loss of traditional medicine.
Right to health
Limited evidence
,
medium
agreement
Dotchamou et al. (2016), Johansson and Isgren
(2017)
A/R projects affect burial sites as, for many communities, the
forest is also the resting place for deceased ancestors.
Right to cultural identity and
to main and control their
traditional knowledge
Limited evidence
,
high
agreement
Lyons et al. (2014), Gabriel and Mangahas (2017),
Mousseau and Teare (2019)
Loss of traditional or Indigenous ecological knowledge and
forest management practices
Right to cultural identity and
traditional knowledge
Limited evidence
,
medium
agreement
Bayrak and Marafa (2016)
Increased labour burden. Benefit sharing by direct cash transfer
or in-kind modalities tends to not compensate lost income
opportunities. Some projects bring employment opportunities,
but these are short term and limited and rarely viable if the
opportunity cost of land and labour is considered. Poor farmers
may drop out to regain access to their land for uses that
provide cash returns in the shorter term.
Right to an adequate
standard of living; right to
decent work; right to benefit
sharing
Medium evidence
,
medium
agreement
Boyd et al. (2007), Aggarwal (2014), Cagalanan
(2016), Witasari (2016), Corbera et al. (2017), Pye
et al. (2017)
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Financial investors pool their investments through intermediaries,
alongside other dynamic forces in the global economy, making
unambiguous assessments of their effect difficult (Clapp, 2014; Clapp,
2017). However, assessment of the broader trends at the interface of
financial investment, food system dynamics and climate change shows
potential connections.
Climate-induced variability in food production has the potential to
introduce a new level of uncertainty into food and farmland markets,
encouraging financial investment into products to capitalise on price
volatility and to hedge risks. The new financial instruments enable
investors to speculate more easily on the direction of food and land
prices, especially when they are volatile (Ouma, 2014; Baines, 2017).
5.13.7 Climate Change Interactions with other Drivers—
Food–Water–Health–Energy–Security Nexus
Linkages between food security and nutrition with water and energy
as well as other important socio-environmental issues are increasingly
being described within a nexus framework (see also Chapters 3, 4, 6
and 7), with food systems frequently located at the centre of nexus
concepts (Caron et al., 2018).
Climate change will affect the food–energy–water (FEW) nexus,
commonly in the form of risk multiplier (
high confidence
) (e.g., Conway
et al., 2015; Barik et al., 2016; Keairns et al., 2016; Abbott et al., 2017;
Ebhuoma and Simatele, 2017; Caron et al., 2018; D’Odorico et al.,
2018; de Amorim et al., 2018; Mpandeli et al., 2018; Nhamo et al.,
2018; Soto Golcher and Visseren-Hamakers, 2018; Yang et al., 2018;
Amjath-Babu et al., 2019; Froese and Schilling, 2019; Mercure et al.,
2019; Momblanch et al., 2019; Pastor et al., 2019; Xu et al., 2019).
Xu et al. (2019) modelled the irrigation demand for large-scale
maize production in Northeast China and concluded that increasing
droughts under future climate change would lead to extreme shortage
of irrigation water without adaptive measures. Barik et al. (2016)
described how the growing demand for food in India has led to more
irrigation with a reduction in groundwater levels in some regions.
Increasing demands for food, energy and water can lead to domestic
and international conflict, including political instability and migration,
often in the context of drought (
high confidence
) (Abbott et al., 2017;
Bush and Martiniello, 2017; WEF, 2017; D’Odorico et al., 2018; de
Amorim et al., 2018). de Amorim et al. (2018) conclude that the FEW
nexus is susceptible to many global risks, including extreme weather
events and human migrations, and predominantly endangers vulnerable
communities of less developed countries. There is emerging evidence that
food and water insecurity enhances social conflicts, including protests
and violent riots, at least partially, by accelerating existing grievances
(Heslin, 2021; Koren et al., 2021). Closer coordination at global, regional
and national levels could be recommended to manage these risks.
Meeting growing demands for food, water and energy under a changing
climate requires technical solutions and behavioural change as well as
greater coordination across multilateral institutions and governance.
Supply-side solutions focus on enhancing production, reducing food
waste and loss or lowering water demand through both technological
approaches (e.g., breeding, improved irrigation) and agroecological
approaches, such as agroforestry, underutilised and more adapted
crops, and transition towards a circular economy (Alexander et al.,
2015; Obersteiner et al., 2016; D’Odorico et al., 2018; Nhamo et al.,
2018; Soto Golcher and Visseren-Hamakers, 2018). Demand-side
solutions focus primarily on changes in consumer behaviour towards
healthier diets with lower carbon footprints, particularly reduction of
meat consumption (Alexander et al., 2015; Obersteiner et al., 2016).
Improving the coordination of multilateral organisations could result
in improved cross-boundary management of natural resources,
particularly related to water (Conway et al., 2015; Nhamo et al., 2018;
Soto Golcher and Visseren-Hamakers, 2018).
As relationships between individual subsystems are systemic, integrated
solutions would result in better outcomes across the FEW nexus (
strong
agreement
). Obersteiner et al. (2016) concluded that single-sector
policies can create strong trade-offs with other policy targets and SDGs,
whereas strategies that reduce pressure on food production systems
diminish trade-offs between FEW nexus components. This suggests that
achieving multiple SDGs will require balancing societal demands in the
context of finite natural resources (Jägermeyr et al., 2017; Amjath-Babu
et al., 2019; Momblanch et al., 2019).
Despite concluding that integrated solutions addressing the systemic
connections between the FEW nexus would improve development and
environmental outcomes, there are limitations of integrating multiple
frameworks, both in terms of describing the complexities and in finding
solutions (Leck et al., 2015; Weitz et al., 2017; Wichelns, 2017; Shannak
et al., 2018). Leck et al. (2015) and Weitz et al. (2017) indicate that
evidence of successful implementation and improved outcomes based
on the application of nexus concepts is rare.
5.14
Implementation Pathways to Adaptation
and Co-benefits
5.14.1 State of Adaptation of Food, Feed, Fibre and Other
Ecosystem Products
Since AR5, several adaptation reviews have been done (Ford et al.,
2015; Lesnikowski et al., 2016). In a review of 1159 peer-reviewed
sources, Berrang-Ford et al. (2021b) found that observed adaptations
in food, fibre and other ecosystem products have consisted mainly of
changes in autonomous behaviour changes, such as changing planting
time, followed by technological/infrastructure and ecosystem-based
adaptation approaches, the majority of which have occurred in Africa
and Asia (Figures 5.20 and 5.21, Table 5.22). Several adaptation
options addressed multiple SDGs (e.g., 2, 6, 8, 12) (Figure 5.21).
Assessment of adaptation options was done for 15 potential options
for land and ecosystem transitions (SM5.7, Figure 5.22a). Several
adaptation options have high to medium feasibility, with
robust
evidence
,
high agreement
about the adaptive capacity resilience
building potential of options in relation to climate change impact
drivers (
high confidence
). Policy and planning and production shifts
have limited evidence for feasibility. Most options are technically
and physically feasible, with generally high political and social
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acceptability and environmental feasibility, but have limited evidence
for institutional feasibility. Most adaptation options have medium to
high microeconomic feasibility (
high confidence
) but
limited evidence
for macroeconomic viability.
Among five effectiveness indicators (SM5.7, Figure 5.22b), most
options have
robust evidence
of reduced risk vulnerability to climate
change, with low scores for local governance, substitution of plant or
animal type, community forest management, livelihood diversification
and climate services. Higher-scored options to reduce risk included
increasing biodiversity (at landscape and field level), community seed
banks, conventional breeding (plant and animals), mixed systems
and agroecological approaches (
medium confidence
), suggesting
multiple co-benefits of these options. Most options have high scores
for enhancing social well-being and economic and environmental
benefits (
medium confidence
) but limited evidence for strengthening
institutions for most options. There were low scores for potential
maladaptation (
medium confidence
).
5.14.1.1 Nature-based solutions or ecosystem-based adaptation
There is growing evidence that nature-based solutions (NBS), which
emphasise ecological approaches and biodiversity conservation
(Chapter 1), have high potential to transform land and aquatic systems
Table 5.23 |
State of adaptation in food, fibre and other ecosystem products by actors and vulnerabe groups (source: GAMI database; Berrang-Ford et al., 2021a)).
Actors
N
(%)
Vulnerable groups
Planned,
N
(%)
Implemented,
N
(%)
International or multi-national governance institutions
72 (6%)
Women
134 (12%)
118 (10%)
National government
264 (23%)
Youth
22 (2%)
24 (2%)
Local government
267 (23%)
Elderly
31 (3%)
28 (2%)
Sub-national government
89 (8%)
Low income
201 (17%)
258 (22%)
Private sector corporations
56 (5%)
Disabled
2 (0%)
3 (0%)
Private sector SMEs
80 (7%)
Migrants
12 (1%)
18 (2%)
Civil Society — international/multi-national/national
117 (10%)
Indigenous
95 (8%)
85 (7%)
Civil Society — sub-national or local
257 (22%)
Ethnic minorities
32 (3%)
32 (3%)
Individuals or households
1087 (94%)
State of adaptation across region and category of adaptation response
Evidenc
e
(a) Africa
(b) Asia
0
50
100
150
200
(c) Australasia
Evidenc
e
0
50
100
150
200
(d) Central and South America
(e) Europe
Evidenc
e
0
50
100
150
200
(f) North America
(g) Small Island States
Adaptation response categories
Global
evidence
Infrastructure and technological
293
Sustainable intensification
241
Nature-based adaptation
313
Social, economic and institutional
423
(f)
(d)
(a)
(e)
(b)
(c)
(g)
Figure 5.19 | State of adaptation by region and type of response (based on 1159 peer-reviewed references that addressed adaptation in food, fibre and
other ecosystem products sector; source: Global Adaptation Mapping Initiative (GAMI) database (Berrang-Ford et al., 2021a).
The bars indicate the amount of
evidence for the category
x
region.
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into climate-resilient systems
(medium evidence
,
high agreement
)
(Albert et al., 2017; Brugère et al., 2019; Galappaththi et al., 2020b;
Snapp et al., 2021; Cross-Working Group Box BIOECO; Cross-Chapter
Box NATURAL in Chapter 2).
5.14.1.2 Climate services
Climate services, understood as the production, translation,
communication and use of climate information in decision-making
processes, can contribute to adaptation efforts in agricultural systems
(
medium agreement
,
low evidence
). Climate services can support
decision makers in agriculture by providing tailored information
that can inform the implementation of specific adaptation options
(Vaughan, 2018; Buontempo et al., 2019; Dobardzic et al., 2019; Hank
et al., 2019).
For some high- and medium-income countries, evidence suggests that
climate services have been underutilised (Mase and Prokopy, 2014),
with
limited evidence
in these countries of the impact of climate
services on yields, income, and food security and nutrition. In low-
0
20
40
60
80
100
0
20
40
60
80
100
0
20
40
60
80
100
Evidenc
e
Evidenc
e
Evidenc
e
(f)
(d)
(a)
(e)
(b)
(c)
(g)
Agricultural diversification
Agroforestry
Climate-smart strategies
Cultivar & species improvement
Insuranc
e
Livelihood diversification & migration
Shifting harvest location
Agricultural diversification
Agroforestry
Climate-smart strategies
Cultivar & species improvement
Insuranc
e
Livelihood diversification & migration
Shifting harvest location
Agricultural diversification
Agroforestry
Climate-smart strategies
Cultivar & species improvement
Insuranc
e
Livelihood diversification & migration
Shifting harvest location
(g) Small Island States
State of adaptation across region and specific adaptation options
Adjustment of planting dates
Agroecology
Climate services
Community-based adaptation
Fertilizer
Irrigation
Other financial mechanisms
Adjustment of planting dates
Agroecology
Climate services
Community-based adaptation
Fertilizer
Irrigation
Other financial mechanisms
Adjustment of planting dates
Agroecology
Climate services
Community-based adaptation
Fertilizer
Irrigation
Other financial mechanisms
(c) Australasia
(a) Africa
(b) Asia
(d) Central and South America
(e) Europe
(f) North America
Figure 5.20 | Observed adaptation across regions in food, fibre and other ecosystem products based on the GAMI database (Berrang-Ford et al., 2021a).
The bars indicate the number of evidence for the options
x
region.
income countries, use of climate services can increase yields and
incomes and promote changes in farmers’ practices (
low confidence
)
(Roudier et al., 2014; Roudier et al., 2016; Tarchiani et al., 2017;
Ouedraogo et al., 2018). There is
low confidence
that climate services
are delivering on their potential, whether they are being accessed
by the vulnerable, and how these services are contributing to food
security and nutrition (Ouedraogo et al., 2018; Vaughan et al., 2019).
Improved design and delivery of climate services can enhance
effectiveness (
medium confidence
)
.
Ways to enhance the impact of
climate services include integrating information from multiple sources
at different scales (Bouroncle et al., 2019), participatory collection and
analysis of climate information (Loboguerrero AM, 2018; Tesfaye et al.,
2019; Rossa, 2020), and making forecast information available in local
languages and as verbal communications for farmers who cannot read
(Nkiaka et al., 2019).
In countries with limited climate data, crowd sourcing (outsourcing
data collection to the public) (Minet et al., 2017) and digital tools
present an opportunity for addressing climate risk (
medium confidence
)
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Adaptation options addressing the Sustainable Development Goals
Infrastructure and technological
Sustainable intensification
Nature-based adaptation
Social, economic and institutional
Irrigation
Fertilizer
Cultivar and species improvement
Adjustment of planting dates
Shifting harvest location
Agricultural diversification
Agroecology
Agroforestry
Climate services
Insurance
Other financial mechanisms
Livelihood diversification & migration
Climate-smart strategies
Community-based adaptation
= no data available
/
Sustainable
Development
Goals
SDG
12
SDG
11
SDG
9
SDG
8
SDG
6
SDG
4
SDG
3
SDG
2
SDG
1
Amount of evidence
>300
1
SDG
5
/
SDG
10
/
SDG
16
/
/
/
SDG
14
/
/
SDG
15
/
SDG
7
/
/
Adaptation
categories
Adaptation
options
Confidence level
High
Medium
Low
High
Medium
Low
Limited
or none
Figure 5.21 | How different response types address the SDGs based on GAMI.
(Osgood et al., 2018; Thornton, 2018; Partey et al., 2020; Sotelo et al.,
2020). Bundling additional services such as market information with
climate information may be effective at plugging information gaps
(
low confidence
) (Chatuphale and Armstrong, 2018; Tsan et al., 2019;
Tesfaye et al., 2019)
There may be inequality in access to climate services; their use may tend
to benefit large-scale operations and disadvantage small- and medium-
scale farmers and others who face issues of access due to social and
economic inequity; also some groups such as pastoralists have not
yet benefitted from climate services (
high confidence
) (Furman et al.,
2014; Muema et al., 2018; Awazi et al., 2019; Nyantakyi-Frimpong,
2019; Paudyal et al., 2019; Vaughan et al., 2019; Nidumolu et al., 2020;
Partey et al., 2020). Other challenges include technology ignorance,
data privacy and security, data access permissions, software and
system compatibility, and understanding how to use and derive value
from accessed data (Chatuphale and Armstrong, 2018; Drewry et al.,
2019). More work is needed to understand the factors that prevent
farmers and fishers from benefitting from this new information. Recent
assessments suggest that access to, and value of, climate and weather
information can be enhanced by the development of digital tools
(including radio, text messages, etc.) appropriate to the specific needs
of different vulnerable groups, as well as by including these groups in
their development and building their capacity (
medium confidence
)
(Camacho and Conover, 2019; Gumucio et al., 2020; Sultan et al., 2020).
5.14.1.3 Insurance as a climate impact risk management tool
Insurance is a financial adaptation strategy increasingly used in
agriculture and aquaculture. A relatively new approach to agricultural
insurance risk is the use of financial derivative products, such as index-
based agricultural insurance (IBAI), marketed by financial institutions
to farmers to help them deal with weather-related production risks
(Isakson, 2015; Jensen and Barrett, 2017). The basic idea is to rely on
easily observed weather indices, such as precipitation or temperature,
that co-vary with farm production. Insurance payments are received
when the metric trigger for a region is reached, eliminating the need
to collect farm-specific information. Proponents of index insurance
argue that it can resolve the information costs and incentive problems
inherent in rural financial markets, such as adverse selection, and allow
provision of insurance coverage at a fraction of the costs of loss-based
polices (Jensen and Barrett, 2017). Buyers of index policies do not have
to prove their ownership of assets with weather-related losses. This
lowers transactions costs and makes it more affordable to insure small
plots of land.
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Box 5.11: Agroecology as a Transformative Climate Change Adaptation Approach
Agroecological approaches can increase food system resilience (
robust evidence
,
medium agreement
), while some agroecological practices
such as agroforestry can provide mitigation measures (
medium confidence
)
(Section 5.10.4.2, Table Box 5.11.1, Altieri et al., 2015; Martin
and Willaume, 2016; HLPE, 2019; Bezner Kerr et al., 2021; Snapp et al., 2021). Studies testing agroecological approaches have shown
robust evidence
,
medium agreement
of increasing adaptation effectiveness through reducing risk, improving food security and yield
stability, reducing input costs, and other supporting and provisioning ecosystem services (Section 5.4.4.4 Diacono et al., 2017; Pandey
et al., 2017; Schulte et al., 2017; Calderón, 2018; Bezner Kerr et al., 2019; Côte et al., 2019; Rosa-Schleich et al., 2019; Bezner Kerr et al.,
2021; Snapp et al., 2021). Effective locally relevant agroecological approaches involve participatory processes, co-creation of knowledge
with farmers and attention to social inequities (Bezner Kerr et al., 2021; Santoso et al., 2021; Snapp et al., 2021). To address smallholder
vulnerability to climate change impacts, however, additional policy support beyond agroecology will be needed that is context specific;
for example, addressing farmer capacity, limited political power to access land, water, seeds and other key natural resources, structural
gender inequities, policy and market disincentives that support large-scale monocultures (
high confidence
) (Anderson et al., 2019a; HLPE,
2019; Holt-Giménez et al., 2021; Snapp et al., 2021).
(a) Feasibility
(b) Effectiveness
Adaptation categories
Assessement score
Adaptation option
Shift in production
Policy and planning
Livelihood diversification
Genetic improvement
Collective resource
management
Climate services
Agronomic management (farm level)
Agricultural
diversification
Substitution change plant or animal type
Regional local, food systems strengthening
Local governance
Community based adaptation
Diversification of livelihoods
Conventional breeding
Community seed/feed/fodder banks
Community forest management
Improving weather forecasting & early warning systems
Mixed systems
Agroecological approaches
On-farm diversification
Landscape diversification
Organic management
High
(3)
Medium
Low
(1)
Economic
Institutional
Social
Geophysica
l
Environmental
Technological
Microeconomic viabilit
y
Macroeconomic viabilit
y
Ecological capacit
y
Adaptive capacity/resilience building potential
Physical feasibilit
y
Transparency & accountability potential
Political acceptabilit
y
Legal, regulatory feasibilit
y
Institutional capacity & administrative feasibilit
y
Socio-cultural acceptabilit
y
Technical reources availabilit
y
Reduced risk vulnerabilit
y
Enhanced social wellbeing
Improved environment
Increased economic resource
s
Strengthen institutions
Maladaptiv
e
2.4
2.7
2.7
1.8
2.6
2.2
2.8
3.0
2.5
2.2
2.9
2.8
2.4
2.4
2.4
2.6
2.5
2.3
2.7
3.0
3.0
2.6
2.8
3.0
2.9
3.0
2.9
3.0
2.6
3.0
2.5
3.0
2.8
2.9
2.9
2.9
2.8
2.9
2.9
2.0
2.4
2.6
2.3
2.0
2.6
2.8
2.8
2.3
2.1
2.2
2.3
3.0
2.6
2.6
2.1
2.6
2.7
2.7
2.7
2.6
1.8
1.9
2.6
2.8
2.5
2.7
2.6
2.2
1.0
1.5
2.5
2.6
2.6
2.6
1.8
2.0
2.6
1.9
1.8
2.0
2.7
2.5
2.5
3.0
2.3
3.0
2.6
2.5
3.0
2.5
2.7
2.5
2.0
2.6
2.3
2.3
2.3
2.6
2.4
2.0
2.7
2.3
2.4
2.4
1.77
1.5
1.7
2.7
1.3
2.6
2.1
2.4
1.4
2.0
2.5
2.3
2.3
2.4
2.1
2.6
2.7
2.9
2.8
2.8
2.7
2.5
3.0
2.8
3.0
2.9
2.9
2.8
2.75
2.3
2.5
2.9
2.6
2.4
2.6
2.6
2.1
2.5
2.3
2.3
2.1
2.2
2.3
1.0
1.0
1.1
1.3
1.0
1.3
1.0
1.2
1.6
1.5
1.1
1.3
3.0
2.8
2.9
2.17
2.5
2.7 2.7 2.8 2.5 2.1
2.5 2.1
2.2
1.9
2.2
2.1
2.4
2.8
2.8
2.2
2.6
1.1
Figure 5.22 | Assessment of 11 feasibility indicators (six categories), five effectiveness indicators and maladaptation of adaptation options based on 287
peer-reviewed papers.
See SM5.7 for methods and data. Scores ranging from 1 (low) to 3 (high) were obtained by averaging five or more papers for each option and indicator.
Blank cells were not assessed because of insufficient literature.
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Table Box 5.11.1 |
Dimensions of agroecological transitions as a transformative climate change adaptation strategy, benefits, trade-offs and constraints to implementation.
Different dimensions of agroecological transitions as a
transformative climate change adaptation strategy
Links to climate change impacts, benefits, trade-offs and constraints to imple-
mentation with examples
Environmental
: Agroecology can support long-term productivity and
resilience of food systems by sustaining ecosystem services such as
pollination, SOC, pest and weed control, soil microbial activity, crop
yield stability, water quality and biodiversity (
high confidence
,
see
Section 5.4.4.4, Cross-Working Group Box BIOECONOMY this chapter and
Cross-Chapter Box NATURAL in Chapter 2). (Isbell et al., 2017; Kremen and
Merenlender, 2018; LaCanne and Lundgren, 2018; Beillouin et al., 2019b;
Dainese et al., 2019; Rosa-Schleich et al., 2019; Snapp et al., 2021).
– Biodiversity of functional species groups and responses to climate hazards play an important
role in building stability and productivity in agroecological systems (5.4.4.4). A 5-year study, for
example, in Asia, Africa and Latin America found that smallholder farmers (<2 ha) increased yields
by 25% through promoting pollination (Garibaldi et al., 2016).
– Landscape complexity is an important feature of agroecology which can increase resilience to
extreme events, such as pest and disease outbreaks or floods, and provide multi-purpose benefits
(Sections 5.4.4; 5.10.4.2) (Paolotti et al., 2016; Reed et al., 2016; Kremen and Merenlender, 2018;
LaCanne and Lundgren, 2018; Rosa-Schleich et al., 2019; Holt-Giménez et al., 2021).
– Context-specific: some agroecological systems and practices have lower average crop productivity
than conventional systems, while others can have higher overall crop productivity and farm
profitability (LaCanne and Lundgren, 2018; Barbieri et al., 2019; Rosa-Schleich et al., 2019).
Socio-cultural
:
Effective locally relevant agroecological approaches involve
participatory processes, co-creation of knowledge with farmers and
attention to social inequities, in doing so building farmer capacity (HLPE,
2019; Bharucha et al., 2020; Holt-Giménez et al., 2021; Snapp et al., 2021).
– Agroecology can emphasise social justice concerns, including gender inequities, considered crucial
for climate change adaptations in food production to have positive impacts on food security
and nutrition (Cross-Chapter Box GENDER in Chapter 18; (Smith and Haddad, 2015; HLPE, 2019;
Sylvester and Little, 2020).
– In some contexts, agroecological systems can draw on and support Indigenous knowledge,
farming systems, networks and socio-cultural values (Catacora-Vargas et al., 2017).
Food security and nutrition
: Agroecological practices can increase
household food security and nutrition for producer households, with
more evidence in low- and medium-income countries (
high confidence
)
(Darrouzet-Nardi, 2016; Demeke et al., 2017; Jones, 2017a; Kangmennaang
et al., 2017; Pandey et al., 2017; Luna-Gonzalez and Sorensen, 2018;
Bezner Kerr et al., 2019; Boedecker et al., 2019; Mulwa and Visser, 2020;
Bezner Kerr et al., 2021; Santoso et al., 2021).
– Combinations of practices, such as intercropping, crop rotation and crop diversification, often
outperform individual practices for yield and food security outcomes (Beillouin et al., 2019b;
Bezner Kerr et al., 2021).
– Agroecological systems more effectively support food security and nutrition when complemented
by nutrition and health education, participatory research and other public policies and
programmes which address access to knowledge (
high confidence;
(HLPE, 2019; Bezner Kerr et al.,
2021; 7.4).
Economic
:
Agroecology can support socioeconomic resilience, through
reducing reliance on purchased inputs, enhancing local and regional
economies (HLPE, 2019; Bharucha et al., 2020; Holt-Giménez et al., 2021).
– Multi-level policies and programmes that support urban and peri-urban networks with
agroecological producers, including farmers’ markets, public procurement (e.g., school meals,
hospitals), incentives for short food value chains, and participatory guarantee certification
schemes which build producer–consumer networks are all ways to support agroecological
transitions by consumers (
high confidence
) (Catacora-Vargas et al., 2017; Pérez-Marin et al., 2017;
Mier y Terán Giménez Cacho et al., 2018; Anderson et al., 2019a; HLPE, 2019; Borsatto et al., 2020;
González de Molina, 2020).
– Transitions to agroecology at a global scale, however, may require considerable dietary shifts
which vary by region, and have implications for total food production and farm-level revenues,
especially in the short term (medium confidence, (Muller et al., 2017; Seufert and Ramakutty,
2017; Barbieri et al., 2019; Rosa-Schleich et al., 2019; Smith et al., 2019b; Smith et al., 2020a).
– To address smallholder vulnerability to climate change impacts, additional policy support beyond
agroecology will be needed that is context specific; for example, addressing farmer capacity,
limited political power to access land, water, seeds and other key natural resources, structural
gender inequities, policy and market disincentives that support large-scale monocultures
(Anderson et al., 2019a; Holt-Giménez et al., 2021; Snapp et al., 2021).
Long-term investment
:
Timeframes are an important consideration, as an
agroecological transition involves multiple overlapping stages, of reducing
chemical inputs, experimenting with and applying new agroecological
practices and adjusting them, redesigning the farm, strengthening short
value chains and producer networks (Gliessman, 2014; Padel et al., 2020).
– In the short term, without policy support, the costs of implementing agroecological practices at
the farm scale can outweigh ecological and adaptation benefits, although the timeframe required
is context-specific (Padel et al., 2020).
– In the long term, implementing agroecological practices can increase yields, yield stability
and farm profitability, reduce risks, and build resilience alongside ecological, health and social
co-benefits, but impacts are context-specific (Section 5.4.4.4, Rosa-Schleich et al., 2019; Bezner
Kerr et al., 2021; Snapp et al., 2021).
– In Malawi, for example, studies indicate that smallholder producers using agroecological practices
improved food security and nutrition, livelihoods and provisioning ecosystem services after 2 years
(Kangmennaang et al., 2017; Bezner Kerr et al., 2019; Kansanga et al., 2021), while in the UK,
farmers transitioning to agroecological practices took 3 or more years to realise benefits (Padel
et al., 2020).
Box 5.11 (continued)
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The creation of index insurance requires significant prior research
and extensive data that may not be available or sufficient in lower-
income countries, including identifying the most appropriate farm and
climate variables to include and financial and regulatory support from
the public sector (Economic Commission for Latin America and the
Caribbean and Central American Agricultural Council of the Central
American Integration System, 2013; Economic Commission for Latin
America and the Caribbean and System, 2014). Some insurance
providers bundle it with other services, such as fertilizer use or seeds
that may not be useful to particular farmers and can increase their
overall capital costs (Isakson, 2015). Although proponents see IBAI
as a way to mitigate farmers’ risks associated with more variable
weather patterns (Greatrex et al., 2015), critics argue that derivative-
based insurance products tend to benefit wealthier farmers and fail in
assisting the poorest and most marginalised farmers (Isakson, 2015;
Taylor, 2016). Thus far, there is
low agreement
and
medium evidence
regarding the adaptation potential of derivatives-based insurance
products, signalling a need for further research in this area.
5.14.1.4 Community-based adaptation approaches
Community-based adaptation (CbA) strategies, which involve locally
driven, place-based adaptation approaches, can help build adaptive
capacity to climate change impacts, but require explicit attention to
power dynamics, respect for local and Indigenous knowledge systems,
adequate resources, future climatic trends and coordination at
multiple levels of governance to be effective (
high confidence
) (Spires
et al., 2014; Fernández-Giménez et al., 2015; Nagoda, 2015; Ashley
et al., 2016; Berner et al., 2016; Ensor et al., 2016; Avtar et al., 2019;
Lam et al., 2019; Silwal et al., 2019; McNamara et al., 2020; Piggott-
McKellar et al., 2020; Rossa, 2020; Uchiyama et al., 2020). Since AR5,
there is strong evidence that participation of local stakeholders in
adaptation planning and implementation improves communities’
capacity to monitor and respond to climate change impacts on food,
fibre and forestry systems, provided that adequate resources and local
knowledge on climate change exist. Participatory monitoring of climate
change impacts and participatory scenario development to develop
community action plans are examples, which can help strengthen
community preparation for and response to climate impacts.
Community-based monitoring of forests, coral reefs, seagrass and
mangroves are examples of local natural resource assessment that
can support food security and livelihoods while informing regional and
national climate change planning tools (Carter et al., 2014; Gevaña
et al., 2018; Avtar et al., 2019). Negotiation among many stakeholders
at multiple scales, including inclusive mechanisms to address power
inequities in governance structures and communities, may be needed
for CbA to be effective (Avtar et al., 2019; McNamara et al., 2020).
Indigenous knowledge and community-based management of
fisheries and aquaculture in the Arctic and Asia (Roux et al., 2019;
Chen and Cheng, 2020; Galappaththi et al., 2020a; Schott et al., 2020;
Galappaththi et al., 2021) provide adaptive strategies for sustainable
use. (Iticha and Husen, 2019). Community-based climate services in
the Andes (managed through a collaboration of smallholder producers
and an international partnership) built capacity and knowledge of
climate change dynamics as well as trust in local climate institutions,
providing meaningful information for regional responses to climate
change impacts (Rossa, 2020). Community-based participatory
scenario planning can help identify multiple climate stressors and
vulnerabilities to develop effective adaptation plans (Fernández-
Giménez et al., 2015; Bennett et al., 2016; Cross-Chapter Box MOVING
PLATE this chapter).
Different dimensions of agroecological transitions as a
transformative climate change adaptation strategy
Links to climate change impacts, benefits, trade-offs and constraints to imple-
mentation with examples
Policy tools
:
Investment in agroecological approaches that are designed
for socio-ecological context, farmer-led schools, co-learning platforms, and
networks of farmers, scientists, private sector and civil society can support
agroecological transitions at a regional scale (
high confidence
) (Coe
et al., 2014; Catacora-Vargas et al., 2017; Pérez-Marin et al., 2017; Mier
y Terán Giménez Cacho et al., 2018; Anderson et al., 2019a; González de
Molina, 2020; Lampkin et al., 2020; Padel et al., 2020; Snapp et al., 2021).
Policies can provide incentives (e.g., price premiums, access to credit,
extension service, taxes, regulation) to support agroecological transitions
by producers (HLPE, 2019; Rosa-Schleich et al., 2019; Gerard et al., 2020;
SAPEA, 2020).
– Farm scale and landscape diversity can affect the capacity for producers to implement
agroecological systems. Small to mid-sized farms can more effectively integrate agroecological
methods such as increasing landscape diversity, on-farm diversity and intercrops (
medium
confidence)
(Garibaldi et al., 2016; Herrero et al., 2017; HLPE, 2019). Barriers to adopting
agroecological practices for small to mid-sized farms include limited market options, subsidy
and policy disincentives, lack of extension support, knowledge and insecure land tenure (Jacobi
et al., 2017; Kongsager, 2017; Hernández-Morcillo et al., 2018; Iiyama et al., 2018; Anderson et al.,
2019a; Gerard et al., 2020).
– Barriers for large farms to transition to agroecological practices include knowledge gaps, cost,
significant infrastructure and farm design changes, labour, psycho-social adjustments, policy
disincentives and market lock-ins (Hill, 2014; Rosa-Schleich et al., 2019; Lampkin et al., 2020).
– Some policies and initiatives support large-sized farms to transition to agroecology (Zhou et al.,
2014; Liebman and Schulte, 2015; Ajates Gonzalez et al., 2018; Bellon and Ollivier, 2018; Lampkin
et al., 2020; Padel et al., 2020).
Other drivers of agroecological transitions can include crises
(environmental, economic or social), social movements, changing
socio-cultural values, addressing social inequities, and discourse
(Pérez-Marin et al., 2017; Mier y Terán Giménez Cacho et al., 2018;
Anderson et al., 2019a).
Further research could provide context-specific information about economic and ecological benefits
of some practices and combinations, with effective policies to support their implementation (
high
confidence
) (HLPE, 2019; Rosa-Schleich et al., 2019; Snapp et al., 2021). Institutional support to
monitor the ecosystem services climate change mitigation and adaptation impact of agroecological
systems can inform policy, using systematic methods and indicators (e.g., Barrios et al., 2020; Mottet
et al., 2020) including annual reporting to the United Nations Framework Convention on Climate
Change (UNFCCC) (Snapp et al., 2021).
Box 5.11 (continued)
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An assessment of 32 different CbA initiatives in the Pacific Islands,
including addressing risks to food security, found high-performing
projects had six key entry points: effective methods to improve
adaptive capacity, appropriate to the local context, which moved
beyond narrow geographical definitions of community to consider
equity of impact, and ecosystem-based approaches, jointly addressing
climatic and non-livelihood pressures and consideration of future
climatic trends (McNamara et al., 2020). Low-performing initiatives, in
contrast, were not sustained; these overlooked future climatic trends
in their initiatives, such as beehive susceptibility to climate extremes,
and had dependent, unequal relationships that lacked genuine local
approval or ownership and did not fit local values and context (Spires
et al., 2014; McNamara et al., 2020; Piggott-McKellar et al., 2020). CbA
initiatives can also suffer from not having adequate local knowledge of
potential strategies to address future climatic scenarios, and may lead
to maladaptation, increasing socioeconomic inequities in communities
(Nagoda, 2015). Addressing inequity in power dynamics and building
technical adaptive capacity of local people are some of the ways that
CbA initiatives can support more resilient food systems (McNamara
et al., 2020).
5.14.1.5 Local and regional food systems’ strengthening and
food sovereignty
Food sovereignty brings together adaptation options based on
agroecological methods, access to resources, collective and CbA (HLPE,
2019). Addressing food security and nutrition in light of climate change
impacts and vulnerabilities is considered to arise from a mixture of
globalised supply chains and local production, not one or the other
(Blesh et al., 2019; Stringer et al., 2020). Evidence on strengthening
local and regional food systems with a food sovereignty approach,
in terms of access to resources (land, seeds, water), shortened food
chains and CbA strategies suggest that these strategies can positively
contribute to climate change adaptation in many contexts (
medium
confidence
) (SRCCL) but can also lead to conflict especially regarding
management of mobile resources such as fisheries (Section 5.8, Cross-
Chapter Box MOVING PLATE this chapter). All these options can build
adaptation through actions that strengthen local capacities and the
power to act within food systems. Securing and recognising tenure
for Indigenous Peoples (Hurlbert et al., 2019) and local communities
(Oates et al., 2020) can improve their ability to adapt by increasing
the incentive to invest in resilient infrastructure and sustainable
land management practices. Community seed banks and networks
strengthen local seed systems and realise farmers’ rights favouring
access to a variety of local genetic resources, with landraces often
more adapted to the local social, cultural and ecological environment
and needs, and better adapted to harsh environments without external
inputs (Mousseau, 2015; Bisht et al., 2018; Maharjan and Maharjan,
2018; Otieno et al., 2018; Mbow et al., 2019). This plays a key role
in PPB (Section 5.4.4.5; FAO, 2019e). The integration of informal and
formal seed system elements is important for the adaptive capacity of
smallholder farmers (Westengen and Brysting, 2014; Westengen and
Berg, 2016; FAO, 2019e).
Strengthening both local and regional food systems is a strategy
to increase resilience (Schipanski et al., 2016; Palmer et al., 2017),
resource use efficiency (Mu et al., 2019) and self-reliance (
medium
evidence
,
low agreement
) (Griffin et al., 2015; Chapin et al., 2016; Karg
et al., 2016). Collective trademarks (Quiñones-Ruiz et al., 2015) and
participatory guarantee systems (Niederle et al., 2020) are examples
of innovative institutional strategies to strengthen local and regional
food systems. In the urban context, the city region food system (CRFS)
approach is motivated by reducing dependence on international trade
and associated instability and to facilitate local decision making (Karg
et al., 2016). CRFS includes a network within a regional landscape
around one urban centre and surrounding peri-urban and rural regions
(Blay-Palmer et al., 2018). UPA is promoted as an effective strategy to
adapt to climate change in different contexts (see Section 5.12.5.3,
Dubbeling, 2015; Lwasa et al., 2015). To cope with the effects of
climate change, strengthening regional food systems is becoming
an explicit part of urban and regional policy, being tested in many
different cities worldwide (Dubbeling et al., 2017; Blay-Palmer et al.,
2018; Berner et al., 2019; Sellberg et al., 2020; van der Gaast et al.,
2020). Strengthening both local and regional food systems has to be
balanced against limitations and trade-offs, since modelling exercises
of regionalisation scenarios show urban agriculture cannot achieve
food security in areas with rapid population growth (Le Mouël et al.,
2018). Furthermore, international trade can compensate in cases
where the regional system fails due to extreme events or other related
climate shocks (Section 5.11.8).
5.14.2 Enabling Conditions for Implementing Adaptation
5.14.2.1 Addressing social inequities in food systems
Addressing gender and other social inequities (e.g., racial, ethnicity,
age, income, geographic location) in markets, governance and control
over resources is a key enabling condition for climate-resilient
transitions in land and aquatic ecosystems (
high confidence
) (Pearse,
2017; Vermeulen et al., 2018; Blesh et al., 2019; Rao et al., 2019b;
Cross-Chapter Box GENDER in Chapter 18, Section 5,13,1; Tavenner
et al., 2019). Adaptation strategies can have negative impacts on
marginalised social groups and worsen socioeconomic inequities
unless explicit efforts are made to address unequal power dynamics and
differences in access to resources in agricultural, fisheries, aquaculture,
livestock and forestry systems (
high confidence
)
(Glemarec, 2017;
Haji and Legesse, 2017; Nagoda and Nightingale, 2017; Nightingale,
2017; Rao et al., 2019b; Huyer and Partey, 2020; Mikulewicz, 2020;
Taylor and Bhasme, 2020; Eriksen et al., 2021). Technical approaches to
adaptation that ignore inequities can worsen them; see, for example,
the case study on Climate Smart Agriculture (Box 5.12). Enabling
environments support inclusive decision making, capacity building,
shifts in social rules, norms and behaviours and access to resources
for marginalised groups for climate change adaptation (e.g., Tschakert
et al., 2016; Ziervogel, 2019; Eriksen et al., 2021; Garcia et al., 2021).
5.14.2.2 Incorporating Indigenous knowledge and local
knowledge
Indigenous knowledge (IK) and local knowledge (LK), while an
important component of many adaptation strategies (Reyes-García,
2014; Roue, 2018), continues to be marginalised in food systems;
greater integration will increase effectiveness (
high confidence
)
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(Ford et al., 2015; Brugnach et al., 2017; Figueroa-Helland et al.,
2018). Where Indigenous Peoples have access to and control over
their lands and natural resources, food systems can potentially be
more sustainably managed and more resilient (
high confidence
)
(Rumbach and Foley, 2014; O’Connell-Milne, 2015; Camacho et al.,
2016; Janhiainen, 2017; Kihila, 2018). For example, on Solomon
Islands, community-based adaptation combining with IK-informed
community mapping helped boost agricultural yields sustainably (Leon
et al., 2015), and in China people living in rich plant resource regions
have used their wild plants IK to complement the decrease of crop
yields during extreme droughts to ensure food security (Zhang et al.,
2016). These cases have led scientists and local communities to call
for more practical actions to bridge local knowledge, IK and formal
science (Borquez et al., 2017; Klenk et al., 2017; Mukhopadhyay, 2017;
Olorunfemi, 2017; Reyes-Garcia et al., 2019). Despite this increased
public and scientific recognition, IK is often not acknowledged or used.
Effective adaptation requires a more holistic approach that includes
the recognition of Indigenous rights, governance systems and laws
(
high confidence
) (Robinson et al., 2016a; Brugnach et al., 2017; Magni,
2017; McMillen et al., 2017; McNeeley, 2017; Pearce et al., 2018), and
to couple IK with proactive and regionally coherent adaptation plans,
actions and cooperation (Shaffer, 2014; Melvin et al., 2017; Forbis Jr.
and Hayhoe, 2018; Makondo and Thomas, 2018).
Supporting Indigenous groups’ knowledge and other excluded social
groups can help preserve and harness underutilised resources to
enhance nutritional and economic security, with careful measures in
protecting Indigenous intellectual rights and avoiding commodification
exploitation (Nakashima et al., 2012; Nandal and Bhardwaj, 2014;
Ghosh-Jerath et al., 2015; Ebert, 2017). In some regions, there has been a
loss of IK about food systems, reducing adaptive capacity (Richards et al.,
2019; Panikkar and Lemmond, 2020). Knowledge exchange between
Indigenous elders and youth can support adaptive capacity (Osterhoudt,
2018; Richards et al., 2019; Zin et al., 2019). Education utilising IK and
LK can help prevent maladaptation options (
high confidence
) (Melvin
et al., 2017; Taremwa, 2017; Forbis Jr. and Hayhoe, 2018; Narayan
et al., 2020). There are examples of integrating IK and LK into resource
management systems and school curricula and in local institutions with
existing decision-making process to strengthen their capacity to address
Box 5.12: Is Climate-Smart Agriculture Overlooking Gender and Power Relations?
Climate-smart agriculture (CSA) is an approach that aims to increase agricultural productivity, enhance food security, adapt to climate
change and, where possible, reduce GHG emissions. The effective implementation of climate-smart practices is conceptually linked to an
enabling environment in which policies, institutions and finance can re-orient agricultural systems, thereby supporting development and
enhancing food security in a changing climate (Lipper et al., 2014; Karttunen et al., 2017). However, the concept has received criticism
based on the absence of conceptual clarity of the interrelations between productivity, food security, adaptation and mitigation (Arenas-
Sanchez et al., 2019) and because of limited evidence on the efficacy of CSA for achieving adaptation and mitigation outcomes at a global
scale (Arslan et al., 2015; Lamanna et al., 2016; Chandra et al., 2018). Some argue that CSA operates within an apolitical framework that
tends to minimise issues concerning power, inequity and access, and is overly focused on technical approaches (Taylor, 2017; HLPE, 2019).
CSA is explicitly referenced by more than 30 countries in their Intended Nationally Determined Contributions (INDCs) (Ross et al., 2016),
but measuring the degree of its implementation still represents a challenge.
There is
low agreement
,
medium evidence
on the relationship between CSA and equity (Allen, 2018; Karlsson et al., 2018). CSA can
potentially benefit women if they are able to take advantage of improvements in productivity, food security and adaptation decision
making as a result of the implementation of CSA practices. Nevertheless, these advantages can be unequally realised given male
domination in receiving information and extension services, as well as financial or resource access (Jost et al., 2016). Some (Huyer and
Partey, 2020) argue that CSA may undermine gender equity (Collins, 2018), entrench and solidify power (Haapala, 2018), and result in the
disproportional allocation of new labour-intensive activities to women (Jost et al., 2016). Uptake of some climate-smart technologies can
further marginalise the most disadvantaged local groups (Roncoli et al., 2009; Haapala, 2018). Unequal sharing of benefits and burdens
with respect to emission reduction costs among different agricultural groups has also been observed (Budiman, 2019).
In contrast, emerging research points to the potential of CSA as a supporting condition for gender equity, provided that equity and power
concerns are explicitly included in the approach (Chanana-Nag and Aggarwal, 2020). Some CSA technologies and practices, such as direct
seeding, green manuring and laser land levelling, can have a significant role in reducing the gender gap in labour burden for women
in agriculture (Khatri-Chhetri et al., 2020). The use of participatory approaches can facilitate community-based adaptation of gender-
sensitive CSA practices (Rosimo, 2018). CSA may also empower both men and women: in two villages in India, CSA adoption empowered
both sexes in decision making and use and control of income (Hariharan et al., 2018).
In general CSA programmes have tended to overlook questions of inequity (
medium confidence
), including limited attention to social
conditions that promote Business-As-Usual pathways, although this is now changing. Addressing questions of rights, social injustice,
unequal power relations and inequity would help make CSA-related policy responses more effective in addressing vulnerability (Chandra
et al., 2017; Clapp and Isakson, 2018; Karlsson et al., 2018; Westengen et al., 2018; Ellis and Tschakert, 2019; Eriksen et al., 2019;
Westengen et al., 2019).
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climate change (Huaman and Valdiviezo, 2014; McNamara and Prasad,
2014; Abah et al., 2015; Mistry and Berardi, 2016; Tschakert et al.,
2017; McNeeley et al., 2018; McNeeley et al., 2020). However, there are
limitations of IK and LK to address future climate impacts. Therefore,
it is important that science-based knowledge and other knowledge
coalesce to produce solutions that are sustainable and viable in the face
of projected impacts of climate change. Community-based adaptation
approaches can integrate IK and LK and more formal knowledge
systems, provided efforts to establish relationships of respect, trust and
common understanding between different stakeholders involved (Herath
et al., 2015; Camacho et al., 2016; Fidelman et al., 2017; Inaotombi and
Mahanta, 2019; Lam et al., 2019).
5.14.2.3 System transformation and policy enablers
Recent literature highlights the future challenges of producing the
quantities of food needed to feed a growing world population in a
way that satisfies nutritional needs, benefits everyone equally and
equitably, and minimises the negative impacts of food systems on the
environment and the natural resource base. There is broad agreement
that current trajectories towards the SDGs and countries’ commitments
under the Paris Agreement are slow and that transformation of food
systems is needed (
medium agreement
,
robust evidence
) (Campbell
et al., 2018; Brondizio et al., 2019; Dury et al., 2019; EAT-LANCET, 2019;
FAO, 2019 f; Food and Land Use Coalition, 2019; Sachs et al., 2019;
Searchinger, 2019a; Searchinger T, 2019b; Loboguerrero et al., 2020;
Meridian Institute, 2020; Steiner A, 2020).
Recent reviews have summarised literature on production system
transformations, driven at least in part by a changing climate or
changing climate variability. Such transformations may involve
sometimes substantial shifts in farm and livelihood enterprises
and land configurations, including intensification, diversification,
sedentarisation and abandonment of agriculture (Vermeulen et al., 2018;
Thornton et al., 2019). Relevant literature is summarised in Table 5.24,
showing reported farmers’ perceptions of the drivers of change and
the different outcomes of these changes. The consequences of these
production system transitions have been mixed; in about 40% of cases,
the outcomes at household level have been unequivocally beneficial.
In the other cases, there were detrimental effects on livelihoods, or
a mixture of positive and negative effects. The effects on nutritional
security reported in these studies were limited. Different enablers of
change appear critical if transitions are to have positive outcomes.
Policy environments, defined in terms of multi-level governance
structures and institutions, are a key driver of systems change, as well
as being enablers of and barriers to adaptation responses (Xu et al.,
2008; Namgay et al., 2014; Galvin et al., 2015; Schmidt and Pearson,
2016; Liao and Fei, 2017). Policies around property and grazing rights
are directly linked to small-scale food producer vulnerability, and
land ownership changes will pose a key challenge as climate change
Box 5.13: Supporting Youth Adaptation in Food Systems
Young people are key agents in agrifood systems: both a vulnerable group, and one that can foster systemic change (
high confidence
)
(Brooks et al., 2019; Figure X; IFAD, 2019; Flynn and Sumberg, 2021; HLPE, 2021). Food systems are the largest source of employment for
young people, but do not always provide adequate livelihoods or decent working conditions (HLPE, 2021). Regions with more youthful
populations—such as Sub-Saharan Africa, South Asia and Central America—are both highly vulnerable to climate change impacts and
reliant on agriculture, forestry, aquaculture and fisheries for livelihoods (Brooks et al., 2019; IFAD, 2019; HLPE, 2021). Rural youth in
these sectors are particularly vulnerable, often with less access to land, water, capital and other resources, shaped by family and social
relations, and fewer opportunities (
high confidence
) (Chingala et al., 2017; Ricker-Gilbert and Chamberlin, 2018; IFAD, 2019; Yeboah et al.,
2020; Flynn and Sumberg, 2021; Nhat Lam Duyen, 2021). In these vulnerable regions, climate change compounds other drivers such as
poverty to increase youth out-migration to urban areas or other regions (
medium confidence
) (Zin et al., 2019; Weinreb et al., 2020; HLPE,
2021; Stoltz et al., 2021; Voss, 2021), which can further worsen rural economies. Young low-income rural women may be particularly
marginalised and vulnerable due to systemic gender inequities in access to land, credit, employment, institutions and other resources
(
medium confidence
) (Sah Akwen, 2017; IFAD, 2019; Flynn and Sumberg, 2021).
Youth play a critical role in all sectors of the food system (HLPE, 2021; Figure Box 5.13.1), and some are actively pursuing work and
innovation in agrifood systems (
medium confidence
) (Sah Akwen, 2017; 2019; Yeboah et al., 2020; Flynn and Sumberg, 2021). Climate
change impacts may reduce youth employment options in food systems in some regions, while they are often politically marginalised
(Brooks et al., 2019; IFAD, 2019; HLPE, 2021). At the same time, due to heightened awareness about climate change, youth may be
more willing to apply climate adaptation strategies (
medium confidence
) (Ali and Erenstein, 2017; Jiri et al., 2017; Sah Akwen, 2017;
Chamberlin and Sumberg, 2021; Doherty et al., 2021). Agrifood policy implementation of adaptation strategies could increase inclusive
participation of youth to meet their needs (HLPE, 2021). Inclusive investments in water management, infrastructure, agrifood science,
and policies that increase youth access to land, credit, knowledge, education, skills and other crucial resources can support dignified and
rewarding agrifood employment (Ahsan and Mitra, 2016; Brooks et al., 2019; HLPE, 2021). Digital technologies can support agrifood
adaptations, but digital divides must be overcome to avoid worsening inequities (HLPE, 2021). Initiatives which protect and strengthen
youth engagement and employment in the all points of the food system, including recognition of youth’s critical role and agency through
rights-based approaches, can support sustainable food transitions (HLPE, 2021). Harnessing youth innovation and vision to address
climate change alongside other SDGs such as gender inequity and rural poverty will be a crucial strategy to ensure resilient economies in
food systems (
high confidence
) (Laube, 2016; Brooks et al., 2019; IFAD, 2019; Abay et al., 2021; HLPE, 2021).
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Chapter 5
Food Systems
Food Environments
Consumer behaviour
Diets
Biodiversity
Climate
Wate
r
Health
Land
Consume
r
Family membe
r
Corporat
e
advertisin
g
Corporat
e
advertising
Educato
r
Media influencer
Youth as agent of change
Collective action: associations, cooperatives, trade unions, social movements
FOOD SUPPLY CHAINS
Youth agency, engagement and employment in food systems
Farm and primary
production
Extension
agen
t
Caregive
r
Parent
Cottage
entrepreneur
Wate
r
Scientist
Coop
membe
r
Retail worker
Teacher
Plantation
worker
Farmer,
pastoralist,
fishe
r
Driver
Migrant/- seasonal
worker
Informal
market wa
t
Student
Storage and trade
Processing and packaging
Retail and marketing
Own-account worker/entrepreneur
s
Wage worker
Family labour
Volunteer/intern/apprentice
Environmentt and natural
resources
Adapted from source: Elaborated by authors based on HLPE (2017, 2020a)
Nutritional
requirements specific to life
course stage
Malnutrition (including undernutrition, overweight and
obesity
Figur
e Box 5.13.1 |
Youth agency,
engagement and employment in food system (HLPE,
2021).
Box 5.13 (continued)
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Table 5.24 |
Agricultural and livelihood system transformations from systematic searches of the literature, which are at least partially attributable to climatic factors and that
involve increased or decreased system integration, and major consequences of the change. Information in the table is from the references cited. Sources: updated from (Vermeulen
et al., 2018; Thornton et al., 2019).
Underlying production
system
Primary drivers of change
as stated
Major processes of change as
reported
Consequences of change,
if reported
Reference
Extensive grassland-based systems
Extensive grassland-based,
northwest China
Government policy, climate
Sedentarisation
Diversification (crops, wages)
Income decline, asset holding decline
Liao and Fei, (2017)
Extensive grassland-based,
Peruvian Andes
Multiple climatic and non-climatic
drivers
Diversification (wages, livestock assets,
land)
Extensification
Livestock accumulation in wealthy
households, asset diversification in
poorer households
López-i-Gelats et al.,
(2015)
Extensive grassland-based,
Bhutan
Government policy, labour
constraints, climate
Sedentarisation
Diversification (crops)
Exit
Increased risk, loss of cultural identity,
improved market access, livelihood
‘lock-in’ (inability to change rapidly)
Namgay et al., (2014)
Extensive grassland-based,
Borana, Ethiopia
Increase in climate variability,
resource degradation
Livestock herd diversification (more
small stock and camels, fewer cattle)
Enhanced household resilience
Megersa et al., (2014)
Extensive grassland-based,
Tibetan Plateau
Government policy, climate
Sedentarisation
Diversification (crops, off-farm wages,
trade)
Increased food production, increased
disease burden
Xu et al. (2008)
Extensive grassland-based, Afar,
Ethiopia
Government policy, climate
Sedentarisation
Diversification (crops)
Weakened institutions and cultural
practices, deteriorating natural
resources
Schmidt and Pearson
(2016)
Extensive grassland-based,
Kajiado, Kenya
Government policy, climate,
population growth
Sedentarisation
Diversification (crops, wages,
remittances)
Intensification
Nutritional status remains poor
Galvin et al. (2015)
Extensive grassland-based,
Mongolian Altai
Government policy, climate
Sedentarisation
Diversification (cashmere sales, forest
products)
Fodder shortages, forest over-use,
unsustainable land use system
Lkhagvadorj et al.
(2013)
Extensive grassland based,
Mongolia
Increasing drought, grassland
degradation
Diversification (decreases in sheep and
goats, increases in cattle, decreases in
grain production, increases in fruit and
vegetable production)
Exit from agriculture
Increased household income from
off-farm employment, more diverse
diets
Du et al. (2016)
Extensive grassland-based,
northern Kenya
Climate change and variability
Diversification (crops, wages, migration)
Decreasing adaptive capacity,
over-dependence on local knowledge
for adaptation
Ogalleh et al. (2012)
Extensive systems with crops
Extensive with crops, Eastern
Cape, South Africa
Multiple
Intensification (richer households)
Exit and abandonment (poorer
households)
Livelihood diversification
Wildlife conflicts, loss of cultural identity
Shackleton et al.
(2013)
Extensive with crops, Peruvian
highlands
Economic globalisation, climate
change
Diversification (dairy production, wage
migration)
Conversion (away from staple crops to
feed production)
Intensification (feed production)
Reduced vulnerability to climate
change, but potential loss of
both agrobiodiversity and food
self-sufficiency identified by the author
Lennox (2015)
Extensive with crops, East Africa
Climate
Diversification (crops, livestock, wages)
Intensification (crops, intercrops)
Increasing household vulnerability
Rufino et al. (2013)
Extensive with crops, Ghana
Climate variability, temperature
change
Diversification (off-farm activities)
Reduced vulnerability
Antwi-Agyei et al.
(2018)
Extensive smallholder cropping,
Nepal
Annual and seasonal warming.
Increased precipitation with
changes in patterns.
Diversification and integration (from
growing buckwheat and barley to
vegetables and fruit trees)
Increased household resilience due to
diversification of production
Konchar et al. (2015)
Extensive smallholder mixed
system, Niger
Droughts and famines, and land
degradation
Large-scale regeneration of native trees
and shrubs in the arable landscape
Increased household income, effects on
household food security not yet known
Haglund et al. (2011)
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impacts in the marginal lands intensify (Reid et al., 2014). Collective
action at multiple scales and effective governance structures are also
a key enabler of transformational change, for helping community
initiatives overcome economic, social and technical barriers, and to
strengthen social capital and farmer knowledge (Haglund et al., 2011;
Reed et al., 2017; Vermeulen et al., 2018; Fedele et al., 2019). Market
development has been shown to be a critical factor for successful
adaptation at scale in sub-Saharan Africa (Ouédraogo et al., 2017;
Iiyama et al., 2018; Totin et al., 2018). At the same time, financing
mechanisms may be a crucial enabler for different food system actors:
de-risking agricultural production and food system investments for
producers and input suppliers, for example, that address core market
failures and compensate actors for extra short-term costs that can
lead to longer-term benefits, particularly for small-scale producers and
businesses with comparatively low access to technologies and services
(Vermeulen et al., 2018; Millan, 2019; see Section 5.14.2.5).
The examples in Table 5.24 highlight the uneven impact of adaptation
programmes and projects in general, due in part to differences in
institutional support and failure of policies to take into account
inequities (Clay and King, 2019; Nightingale et al., 2020). Focusing on
transformational adaptation, Vermeulen (2018) suggested the need
to expand the remit of adaptation planning to consider the multi-
functionality of agriculture and a system-wide view of food production
and consumption. Several authors argue that transformational change
must address the personal, practical and political spheres, in view
of the role of power relations and worldviews in shaping practices,
food security and inequity (O’Brien, 2015; Nightingale, 2017; O’Brien,
2018; Eriksen et al., 2019; Gosnell et al., 2019). If it involves new or
unfamiliar technology, transformation may also be highly disruptive,
and the added vulnerabilities of food system actors at risk will need to
be addressed (Herrero et al., 2020; see Box 5.5).
‘Transformation’, defined by IPCC (2019a) as ‘a change in the
fundamental attributes of natural and human systems’, is defined
here as a redistribution of at least a third in the primary factors of
production (land, labour, capital) and/or the outputs and outcomes of
production (the types and amounts of production and consumption of
4
For reference, the SEI Aid-Atlas (https://aid-atlas.org) only reports flows where adaptation is the principal objective, and therefore adaptation spending on agriculture, forestry and fisheries for the same
period is significantly lower with USD 16.52 billion, that is, 21.4% of total adaptation spending.
goods and services arising from multi-functional agricultural systems)
(Vermeulen et al., 2018; Thornton et al., 2019).
5.14.2.4 Finance needs and strategies for adaptation
Current understanding of finance flows and needs for adaptation in
crop agriculture, livestock, fisheries, aquaculture and forest products
relies primarily on top-down projections, with limited data (UNFCCC,
2018; Buchner et al., 2019; Jachnik et al., 2019). By one estimate,
in 2017/2018, agriculture, forestry and land use received 24% of
public adaptation finance (totaling USD 7 billion; half via multilateral
development finance institutions and one-quarter from governments)
and 35% of international grants (with 71% used for adaptation)
(Buchner et al., 2019). According to data from OECD (2020), finance
flows for agriculture, forestry and fisheries have risen fairly linearly
from ca. USD 1.46 billion in 2010 (the year the Rio marker on climate
change adaptation was introduced) to ca. 5.5 billion in 2018. Over
the entire tracked period, the three subsectors combined received a
total of USD 29.82 billion for activities with principal and significant
adaptation components.
4
However, the data set only includes climate-
related development finance from bilateral, multilateral and private
philanthropic sources, whereas private sector finance flows are not
captured as this is notoriously difficult to track (UNEP, 2016; OECD,
2020; cross-ref to Cross-Chapter Box FINANCE in Chapter 17). Most of
the funding (85%) was directed towards agriculture, with forestry (12%)
and fisheries (3%) receiving significantly less, but across the subsectors,
there is consistency in the sense that policy and administrative
management and development receive the lion’s share of support,
which is predominantly given in the form of grants (72%), while debt
instruments (26%) and equity and shares in collective investment
vehicles (2%) contribute less. From a regional perspective, 80% were
directed to Africa (47%), Asia-Pacific (27%), and Latin America and
Caribbean States (7%), whereas Eastern Europe and Western Europe
and Other States received (2%) each and 17% were destined for
‘developing countries’ without regional tags. Finally, it is noteworthy
that 38% of adaptation finance in agriculture, forestry and fisheries is
marked as also having mitigation benefits, and roughly a quarter of
funding is reported as having principal or significant gender objectives.
Underlying production
system
Primary drivers of change
as stated
Major processes of change as
reported
Consequences of change,
if reported
Reference
Other mixed coastal and forest systems
Coastal rice-based, Bangladesh
Increased salinity due to reduced
dry season flows from rivers in
India, use of groundwater for
irrigation
Diversification (from rice cultivation to
aquaculture of shrimp and prawn)
Increased household income, increased
engagement of women, increased
human disease vulnerability
Faruque et al. (2017)
Smallholder cropping systems,
coastal Bangladesh
Increasing frequency and severity
of floods since 2008
Diversification (re-allocation of land
from crops to aquaculture)
Exit (migration away from village)
Mixed impacts on household incomes
and seasonal migration frequency
Fenton et al. (2017)
Smallholder mixed cropping in
forested landscapes in Indonesia
Floods, drought, crop and
livestock disease
Diversification (re-allocation of land
from forests to rubber plantations and
rice)
Intensification (agroforestry)
Extensification (reforestation, forest
protection)
Locally, increased household incomes in
general; more widely, some trade-offs
with biodiversity, water, carbon stocks
Fedele et al. (2018)
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Whether current levels of growth in adaptation finance for agriculture,
forestry and fisheries is keeping up with estimated needs cannot be
assessed because of the large uncertainties that surround adaptation
cost estimates (Cross-Chapter Box FINANCE in Chapter 17). There is,
hence, high agreement that better assessment of adaptation costs
of climate impacts requires considerably more research (Watkiss,
2015; Diaz and Moore, 2017). A recent study focusing on investments
needed to offset the effects of climate change on the prevalence
of hunger concludes that investments in agricultural research and
development (R&D) have to increase from USD 1.62 billion to USD
2.77 billion per year between 2015 and 2050 (Sulser et al., 2021a).
In addition to agricultural R&D, significant investment increases in
water and infrastructure in the range of USD 12.7 billion and USD
10.8 billion are required, respectively, a considerable portion of
which is relevant to the food system. In total, Sulser et al. (2021a)
estimate that annual investment between USD 21.47 billion and
USD 29.8 billion are needed to avoid sliding back from climate-
change-related increases in the prevalence of hunger but recognise
the shortcomings of their approach and acknowledge that ‘a full
analysis of adaptation to climate change in agriculture would
require including many other social, economic, and environmental
dimensions’. For comparison, World Bank (2010) estimated global
costs of USD 70–100 billion per year for agriculture, forestry
and fisheries, infrastructure, water resources, health, ecosystem
services, coastal zones and extreme weather events to adapt to an
approximately 2°C warmer world between 2010 and 2050. While the
World Bank includes more sectors, more recent publications consider
the resulting figures to be significantly too low (Baarsch et al.,
2015; UNEP, 2016; Rossi and Miola, 2017; Hallegatte et al., 2018;
Markandya and González-Eguino, 2019; Chapagain et al., 2020; WGII
Cross-Chapter Box FINANCE in Chapter 17). Therefore, despite the
methodological and data challenges, further efforts are needed to
better capture the economic risks of climate change and provide
estimates of adaptation costs at global to national scales as well as
across sectors (Watkiss, 2015; Diaz and Moore, 2017).
Financial barriers limit implementation of adaptation options in
agriculture, fisheries, aquaculture and forestry (
high confidence
)
(Shukla et al., 2019; FAO et al., 2020). Finance strategies can contribute
to adaptation in these sectors in different ways (Table 5.25) and to
different degrees. Standardised strategies have not yet been developed
for specific adaptation needs, and in current practice, finance strategies
are opportunistically deployed, with developing countries facing
particular challenges due to under-developed financial mechanisms
(Omari-Motsumi et al., 2019).
Many types of financial instruments are employed by diverse actors
(Table 5.26) guided by their mandates (e.g., development, commerce),
capacity (investor, intermediary, donor) and risk appetite. Actors
within a sector or local production area can coordinate their financial
strategies towards common objectives (e.g., reduced supply chain
loss) or participate in joint financial action such as blended finance
structures that combine commercial and concessionary finance to
catalyse additional private investment, enrich the pipeline of bankable
projects, and test business models (FAO, 2020b).
Expanding access to financial services and pooling climate risks
can enable and incentivise climate change adaptation (
medium
confidence
) (Shukla et al., 2019). To mobilise financial instruments
(Table 5.27) towards adaptation needs, individual actors can apply
an adaptation lens to existing or new activities, accounting for
investment characteristics (e.g., development stage; cash flow profile),
requirements (e.g., amount; risk–return) and context (e.g., regulatory
landscape) (Havemann et al., 2020). Risk-layering can match financial
instruments to severity and probability climate risks (Hochrainer-
Stigler and Reiter, 2021).
5.14.2.5 Constraints on adaptation finance for food, feed, fibre
and other ecosystem products
Flow of adaptation finance in the agriculture, fisheries, aquaculture
and forestry sectors is impeded by weak measurement and
benchmarking of financial and resilience outcomes (Kramer et al.,
2019; Negra et al., 2020), and challenges in assessing repayment
capacity of investee producers and companies (
medium confidence
).
Immature information systems (e.g., weak analytics, fragmented
Table 5.25 |
Potential adaptation finance strategies for categories of climate-related risks in the agriculture, fisheries, aquaculture and forestry sectors.
Finance strategies
Reduced food availability
Low food safety / dietary health
Diminished livelihoods
Declining ecosystem services
Reduce vulnerability
Avoid staple failure
:
Vouchers to
producers for improved production
inputs
Diversify production strategies
:
Invest
in alternative crops/species/harvest
methods
Increase producer capacity
: Fund
technical assistance programmes
Incentivise improved management
:
Improved access to credit based on
environmental performance
Anticipate/minimise
impacts
Minimise impact of extreme
weather
: Fund early-warning
systems
Diversify products in supply chains
:
Finance processing equipment for
alternative food products
Moderate food price spikes
:
National food reserves
Minimise resource depletion
:
Subsidise micro-lending for
water-efficient technologies
Steer capital towards
climate resilience
Develop climate-resilient production
technologies
:
Fund R&D for
improved genetics (crops, fish,
livestock) and management
Build nutrition-sensitive food systems
:
Finance early-stage market building for
diversified food products
Increase resilience of supply chain
infrastructure
: Finance improved
storage and transport facilities
Disincentivise low-resilience
production:
Screen investments
based on climate risk disclosures
Pool climate-related
risks
Distribute climate-related risks:
Securitise investments in production
systems
De-risk diversified food supply chains
:
Invest in producer aggregation to
improve supply chain efficiency
Insure against supply chain
risks
: Subsidised index insurance
programmes
Detect high-risk production systems
:
Invest in supply chain monitoring/
traceability mechanisms
Compensate for
climate-related
impacts
Compensate for production losses
:
Financial transfers to affected
producers
Avoid food shortages
:
Subsidise food
importation
Avoid selling off productive assets
:
Fund social support for low-income
households
Ecological restoration
: Direct
development aid to land
rehabilitation projects
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standards) (Woodard et al., 2019; Negra et al., 2020) inhibit effective
due diligence and impact assessment, contributing to uncertainty
and low investor confidence (Havemann et al., 2020; NGFS, 2020).
Improved characterisation of adaptation finance strategies (e.g.,
insurance, subsidies, blended finance) requires increased transaction
volume (Millan et al., 2019) and analysis of financial (e.g., risk–return
profile, investor demand) and resilience (e.g., reduced vulnerability)
effects.
Use of climate-resilient financial strategies and instruments is limited
by weak incentives, which commonly take the form of high upfront
costs (Verdolini et al., 2018), high transaction and intermediation
costs (Havemann et al., 2020) and relatively long pay-off time. Tenant
producers may not experience benefits from adaptation investments
(Woodard et al., 2019). Investors seek low-risk, liquid investments and
credit-worthy counterparties (Havemann et al., 2020), yet small- and
medium-sized producers and supply chain actors often lack access
to formal credit. Given limited experience and weak information for
adaptation finance, sub-optimal outcomes may include imbalanced
allocation of public and private finance (e.g., to less vulnerable regions
and producers; to lower-resilience investments; to short-term benefits)
as well as inequitable division of risks and returns (e.g., within blended
finance structures) (Clapp, 2017; World Bank, 2018; Attridge and
Engen, 2019). Additionally, while risk-sharing finance strategies can
deliver adaptation benefits, they do not inherently reduce overall risk
and commonly cover only specified types of risks (Kellett and Peters,
2014; Watson et al., 2015).
Table 5.26 |
Potential adaptation finance objectives for major actors in agriculture, fisheries, aquaculture and forestry sectors.
Actors
Potential adaptation finance objectives
Private sector
: Focused on capturing positive externalities (i.e., lower risks or costs) from adaptation investments (Woodard et al., 2019). Major considerations include fiduciary
responsibilities; expected rates of return (i.e., risk-adjusted; benchmarked to comparable investments); investment characteristics (e.g., liquidity, structure, size) and contribution to investor
portfolio; material business risks (e.g., supply chain reliability; stranded assets); cost control (e.g., product losses; insurance); legal compliance; and sectoral requirements (e.g., climate risk
disclosure) (Havemann et al., 2020).
Production companies or cooperatives
– Supply chain transactions (e.g., trade finance)
– Sustainable agricultural infrastructure (e.g., capital investment in storage or processing facilities to reduce exposure to climate risks)
– Developing or accessing advisory services (weather data; agronomic information) (Orchard, 2019)
– Risk management (e.g., insurance/reinsurance; budget reserves)
Financial investors and intermediaries
(e.g., banks, asset managers,
venture capital; non-bank financial
institutions)
– Ownership shares in established companies (i.e., private equity) or large publicly traded companies (i.e., listed equities)
– Debt issuance (e.g., working capital; catastrophe bonds; emergency loans)
– Real estate investment
– Financial derivatives
– Technological research and development
– (Impact investors) Bespoke non-financial sustainability objectives (e.g., fairtrade products; financial inclusion) (Havemann et al., 2020)
Public sector
: Encompassing nearly commercial (e.g., specialised commodity boards; bond issuances), partially subsidised (e.g., low-interest loans) and fully subsidised (e.g., R&D; grants)
investments. Major considerations include avoiding negative impacts to citizens (e.g., food price spikes) and specific constituencies (e.g., catastrophic losses to producers) and maintaining/
enhancing public revenues (i.e., taxes from economic activity in agriculture, fisheries, aquaculture and forestry).
Government agencies and multilateral
institutions
– Strengthen enabling environments for sustainable production and ecosystem protection (e.g., price transparency; information exchange;
international coordination)
– Support demonstration projects for sustainable land and resource management (e.g., grants)
– Disaster risk reduction (e.g., national disaster funds; social protection programmes; contingent credit lines; sovereign/sub-sovereign insurance
(Global Commission on Adaptation, 2019)
– Increase resilience through early-warning systems, infrastructure, and capacity building (e.g., climate change adaptation funds)
– Increase revenues for adaptation activities (e.g., income/luxury taxes)
– Reduce production risks (e.g., agricultural subsidies)
– Promote advanced technology implementation (e.g., tax incentives)
– Coordinate and align donor funding with national priorities (e.g., multi-donor national climate change funds)
– Incentivise and de-risk commercial investments (e.g., interest rate reduction programmes, structured financing, guarantee funds)
(Woodard et al., 2019)
Methods to strengthen adaptation finance include updating
regulations and policies to support adaptation finance instruments
(e.g., climate accounting standards), requiring climate-risk disclosure,
improved information-sharing among public and private sector actors
and devolving funding to local actors (
medium confidence
) (Global
Commission on Adaptation, 2019; Millan et al., 2019).
5.14.3 Climate Resilient Development Pathways
Climate resilient development pathways (CRDPs) introduced in AR5
(Denton, 2014) can briefly be described as ‘development trajectories
that integrate adaptation and mitigation to realise the goal of
sustainable development’ (see IPCC (2019a)) for a more extensive
definition). Several characteristics were proposed in SR1.5 by which
such CRDPs could be identified: consistency with principles of
sustainable development; ability to deliver poverty reduction; ability
to enhance social, gender, racial, ethnic and intergenerational equity;
ability to deliver resilience to climate change and other shocks and
stresses; and ability to protect species, biodiversity and ecosystem
goods and services. There is an increasing literature, assessed in SR1.5,
on adaptation pathways approaches, generally for specific regions,
locations and subsectors.
Two recent examples directly related to agriculture and food are the
following: sustaining agrarian livelihoods to mid-century of Nicaraguan
small-scale coffee producers using analyses of suitability and coffee
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Table 5.27 |
Major types of financial instruments suitable to adaptation finance in agriculture, fisheries, aquaculture and forestry sectors (adapted from Havemann et al., 2020).
Financial instrument
Description
Equity
: Ownership stake in a company (e.g., agricultural technology company; processing company) or collective investment vehicle (e.g., agriculture fund; Timber Investment Management
Organization; commodity index fund) providing returns (via dividends and/or sale of equity shares) corresponding to business-related risk (e.g., higher return for higher risk and/or lower
liquidity)
Listed equities
Ownership of shares in a company listed in a public market
Private equity
Ownership of shares in a company or other assets
Junior or risk-absorbing equity
Ownership of lower-tier shares in a company (e.g., common stock) or collective investment vehicle (e.g., first-loss tranche)
Debt
: Capital provided directly or indirectly (via banks or other third-party institutions) to users with defined repayment terms (i.e., timeframe, interest rate); more likely to deliver adaptation
benefits when coupled with capacity building (e.g., technical assistance, education, analytics) (Woodard et al., 2019)
Loan, bond, note, credit line
Direct or indirect provision of capital (e.g., operating loans; dedicated credit line for agricultural trade); concessionary loans may allow for
below-market interest rates
Soft loan
Direct interest-free loan (e.g., funds provided in advance of good/service delivery)
Emergency loan
Lending in response to climate risks or impacts with repayment terms (e.g., return period) that consider necessary relief, recovery and
reconstruction
Catastrophe bond
Risk transfer instrument in which insurers or reinsurers provide high interest payments to investors in exchange for a payout (and repayment
deferment or forgiveness) activated by specific events (e.g., extreme weather)
Impact bond
Subsidised investment providing capital upfront or based on defined outcomes
Subordinated loan
Concessionary capital with a junior position (i.e., accepting higher risk of non-repayment and / or lower rate of return on investment) relative to
other investors
Securitised investments
Aggregation of equity or debt to offer marketable securities to a wider pool of investors with different risk–return appetites
Guarantees
: Commercial and concessionary guarantees that provide compensation for losses due to specified risks (e.g., political risk, performance risk); more likely to deliver adaptation
benefits when linked to robust underwriting standards and verification protocols (Woodard et al., 2019)
Credit guarantee
Compensation for specified losses incurred by agricultural lenders
Payment, performance, surety bonds
De-risking mechanism for transactions between providers and buyers of goods/services; may be used in trade finance and other forms of
intermediation
Insurance
: Policies and other financial instruments that provide compensation for losses based on defined terms and conditions.
Production insurance
Compensation for specified losses related to production (e.g., insurance indexed to specific weather events) or supply chains (e.g., shipping
insurance)
Market and price insurance
Compensation for specified market-related losses (e.g., price or currency fluctuation)
Grants
: Concessionary funding provided by public or philanthropic entities to support climate adaptation costs or outcomes (no expectation of repayment)
Direct support
Funding for provision of goods (e.g., fertilizer, seeds, nursery stock) or services (e.g., technical assistance, product storage) to producers, local
companies or intermediaries (e.g., for agronomic or business management expertise); can reduce credit risk when part of blended finance
arrangements
Performance-based grants
Grants or other concessionary funding contingent on achievement of defined adaptation outcomes (with possible third-party verification
requirement); may support development and testing of new approaches (i.e., design funding; challenges/prizes)
Governmental instruments
Policy incentives
Public policies designed to stimulate adaptation action among targeted groups (e.g., producers, consumers, agri-businesses, financiers) including
direct or indirect subsidies (e.g., producer payments, tax breaks, health insurance), procurement policies (e.g., low carbon and sustainability criteria;
nutrition-sensitive school feeding programmes) and other fiscal measures (e.g., infrastructure development; funding R&D in climate-resilient
practices or technologies)
(Shukla et al., 2019)
Development aid
International or domestic programmes that directly or indirectly fund adaptation actions including financial transfers (e.g., producer support or
anti-poverty programmes) and subsidised credit (
medium confidence
) (Shukla et al., 2019)
Planning grants
Financial support to governments for adaptation planning (e.g., via readiness programmes)
Other instruments
Fintech
Data analytics and risk analysis models used to better assess borrowers’ repayment risk (e.g., due to crop failure) and reduce transaction costs
(e.g., streamlined lending processes); applications may include financial inclusion (e.g., micro-financing; lending to small- and mid-size operators),
alternative repayment programmes (e.g., for larger capital borrowing), insurance (e.g., more granular risk assessment) or digital strategies (e.g.,
crowdfunding, smallholder credit) (Agyekumhene et al., 2018)
Payment for Ecosystem Services (PES)
Funds delivered to land and resource managers in exchange for compliance with specified sustainability practices or environmental outcomes;
PES depends on willing payers (i.e., direct and indirect beneficiaries of ecosystem services such as governments, companies, conservation groups,
philanthropies)
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quality changes under an IPCC Special Report on Emissions Scenarios
(SRES) A2 emissions scenario (Läderach et al., 2017); and development
of participatory pathways to mid-century under RCPs 4.5 and 8.5
support regional adaptation planning in Hawke’s Bay, New Zealand
for agricultural producers and rural communities (Cradock-Henry et al.,
2020). CRDPs mentioned in SROCC include shifting from providing
coastal defences to adapting to seawater inundation in coastal regions
(Renaud et al., 2015) and retreating coastal megacities (Solecki et al.,
2017). Pathway frameworks continue to be used to frame the broad-
scale challenges of development and climate change, thereby linking
different types of food system actor with different responses through
time using a variety of approaches, top-down and participatory,
qualitative and quantitative (Butler et al., 2016; Antle et al., 2017;
Thornton and Comberti, 2017; Collste et al., 2019; Loboguerrero et al.,
2020; Stringer et al., 2020).
While there is consensus that the concept of CRDPs is useful, there
are major challenges in identifying, operationalising, monitoring and
evaluating them (Lin et al., 2017; Bloemen et al., 2018). Management
approaches seldom integrate across spatio-temporal scales and may be
unable to address unidirectional change and extreme events (Holsman
et al., 2019). The socioeconomic complexities and implications of
pursuing integrated outcomes make it difficult to evaluate synergies
and trade-offs associated with different actions in local contexts
through time (Thornton and Comberti, 2017; Ellis and Tschakert, 2019;
Holsman et al., 2019; Orchard, 2019). Case studies by Lo (2019) of
transformation in a fishing town in south China and by Gajjar (2019)
on undesirable path dependencies in development trajectories in urban
and rural India show that overall adaptive capacity of populations
may be decreased though politicisation and entrenchment of existing
inequities, severely limiting the possibilities for future adaptation. A
further challenge of implementation is timely detection of tipping
points and abrupt exposure events in both climate and environmental
systems (Lenton et al., 2019; Trisos et al., 2020), which may alter the
efficacy of current and planned adaptation actions, necessitating a
switch to other, more transformational strategies; in such cases, re-
energising food system actors’ commitment to adaptation action may
well be needed (Bloemen et al., 2018).
Integrated modelling of CRDPs will increasingly be needed to throw
light on key SDG synergies and trade-offs into the future (Bleischwitz
et al., 2018). In investigating possible future pressures on land under
the SSPs, Doelman (2018) projected that the largest changes take place
in sub-Saharan Africa in SSP3 and SSP4, mostly because of continued
high population growth coupled with (projected) sluggish increases
in agricultural efficiency, among other things, leading to expansion of
agricultural land for crop and livestock production and reduced food
security. Lassaletta (2019) evaluated global pig production in the SSPs
and concluded that the future sustainability of pig systems will depend
on production efficiency improvements coupled with other factors such
as use of alternative feed sources and use of slurries on cropland. Such
studies will be increasingly important for quantifying the potential
trade-offs and synergies between different SDGs, to guide adaptation
(and mitigation) action along CRDPs in the future. The current lack
of widely accepted and simple-to-measure indicators for tracking
progress in adaptation is a significant hurdle to overcome. There is a
large literature on the desirable characteristics of future global food
systems, but much less on robust analysis that explicitly addresses
and evaluates the pathways towards these desired futures. Gerten
(2020) estimates that 10.2 billion people can be supported within key
planetary boundaries via spatially redistributed cropland and dietary
changes, among other actions. There are few, if any, analyses for
detailing the plausible pathways to move towards such a future in
ways that are socially, economically and environmentally acceptable
through time; whether such pathways could indeed be made climate-
resilient is unknown. Appropriate monitoring and rapid feedback to
food system actors on what is working and why will be critical to
the successful operationalisation of adaptation actions within CRDPs
(Bosomworth and Gaillard, 2019).
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Cross-Working Group Box BIOECONOMY: Mitigation and Adaptation via the Bioeconomy
Authors:
Henry Neufeldt (Denmark/Germany), Göran Berndes (Sweden), Almut Arneth (Germany), Rachel Bezner Kerr (USA/Canada),
Luisa F Cabeza (Spain), Donovan Campbell (Jamaica), Jofre Carnicer Cols (Spain), Annette Cowie (Australia), Vassilis Daioglou (Greece),
Joanna House (UK), Adrian Leip (Italy/Germany), Francisco Meza (Chile), Michael Morecroft (UK), Gert-Jan Nabuurs (the Netherlands),
Camille Parmesan (UK/USA), Julio C Postigo (USA/Peru), Marta G. Rivera-Ferre (Spain), Raphael Slade (UK), Maria Cristina Tirado von der
Pahlen (USA/Spain), Pramod K. Singh (India), Peter Smith (UK)
Summary Statement
The growing demand for biomass offers both opportunities and challenges to mitigate and adapt to climate change and
natural resource constraints (high confidence). Increased technology innovation, stakeholder integration and transparent
governance structures and procedures at local to global scales are key to successful bioeconomy deployment maximising
benefits and managing trade-offs (high confidence).
Limited global land and biomass resources accompanied by growing demands for food, feed, fibre and fuels, together with prospects for a
paradigm shift towards phasing out fossil fuels, set the frame for potentially fierce competition for land
5
and biomass to meet burgeoning
demands even as climate change increasingly limits natural resource potentials (
high confidence
).
Sustainable agriculture and forestry, technology innovation in bio-based production within a circular economy and international
cooperation and governance of global trade in products to reflect and disincentivise their environmental and social externalities can
provide mitigation and adaptation via bioeconomy development that responds to the needs and perspectives of multiple stakeholders to
achieve outcomes that maximise synergies while limiting trade-offs (
high confidence
).
Background
There is
high confidence
that climate change, population growth and changes in per capita consumption will increase pressures on
managed as well as natural and semi-natural ecosystems, exacerbating existing risks to livelihoods, biodiversity, human and ecosystem
health, infrastructure and food systems (Conijn et al., 2018; IPCC, 2018; IPCC, 2019b; Lade et al., 2020). At the same time, many global
mitigation scenarios presented in Intergovernmental Panel on Climate Change (IPCC) assessment reports rely on large greenhouse gas
(GHG) emissions reduction in the Agriculture, Forestry, and Other Land Use (AFOLU) sector and concurrent deployment of reforestation/
afforestation and biomass use in a multitude of applications (Rogelj et al., 2018; AR6 WGIII Chapter 3 and Chapter 7; Canadell et al.,
2021; Lee et al., 2021)
Given the finite availability of natural resources, there are invariably trade-offs that complicate land-based mitigation unless land
productivity can be enhanced without undermining ecosystem services (e.g., Obersteiner et al., 2016; Campbell et al., 2017; Caron
et al., 2018; Conijn et al., 2018; Heck et al., 2018; WRI, 2018; Smith et al., 2019c). Management intensities can often be adapted to local
conditions with consideration of other functions and ecosystem services, but at a global scale the challenge remains to avoid further
deforestation and degradation of intact ecosystems, in particular of biodiversity-rich systems (Cross-Chapter Box on NBS-NATURAL in
Chapter 2), while meeting the growing demands. Further, increased land use competition can affect food prices and impact food security
and livelihoods (To and Grafton, 2015; Chakravorty et al., 2017), with possible knock-on effects related to civil unrest (Abbott et al., 2017;
D’Odorico et al., 2018).
Developing New Bio-Based Solutions while Mitigating Overall Biomass Demand Growth
Many existing bio-based products have significant mitigation potential. Increased use of wood in buildings can reduce GHG emissions
from cement and steel production while providing carbon storage (Churkina et al., 2020). Substitution of fossil fuels with biomass in
manufacture of cement and steel can reduce GHG emissions where these materials are difficult to replace. Dispatchable power based on
biomass can provide power stability and quality as the contribution from solar and wind power increases (WGIII Chapter 6), and biofuels
can contribute to reducing fossil fuel emissions in the transport and industry sectors (WGIII Chapter 10 and Chapter 11). The use of bio-
based plastics, chemicals and packaging could be increased, and biorefineries can achieve high resource-use efficiency in converting
biomass into food, feed, fuels and other bio-based products (Aristizábal-Marulanda and Cardona Alzate, 2019; Schmidt et al., 2019). There
is also scope for substituting existing bio-based products with more benign products. For example, cellulose-based textiles can replace
cotton, which requires large amounts of water, chemical fertilizers and pesticides to ensure high yields.
5
For lack of space, the focus is on land only, although the bioeconomy also includes sea-related bioresources.
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While increasing and diversified use of biomass can reduce the need for fossil fuels and other GHG-intensive products, unfavourable
GHG balances may limit the mitigation value. Growth in biomass use may in the longer term also be constrained by the need to protect
biodiversity and ecosystems’ capacity to support essential ecosystem services. Biomass use may also be constrained by water scarcity and
other resource scarcities and/or challenges related to public perception and acceptance due to impacts caused by biomass production
and use. Energy conservation and efficiency measures and deployment of technologies and systems that do not rely on carbon, such
as carbon-free electricity supporting, inter alia, electrification of transport as well as industry processes and residential heating (IPCC,
2018; UNEP, 2019), can constrain the growth in biomass demand when countries seek to phase out fossil fuels and other GHG-intensive
products while providing an acceptable standard of living. Nevertheless, demand for bio-based products may become high where full
decoupling from carbon is difficult to achieve (e.g., aviation, bio-based plastics, and chemicals) or where carbon storage is an associated
benefit (e.g., wood buildings, bioenergy with carbon capture and storage (BECCS), biochar for soil amendments), leading to challenging
trade-offs (e.g., food security, biodiversity) that need to be managed in environmentally sustainable and socially just ways.
Changes on the demand side as well as improvements in resource-use efficiencies within the global food and other bio-based systems
can also reduce pressures on the remaining land resources. For example, dietary changes towards more plant-based food (where
appropriate) and reduced food waste can provide climate change mitigation along with health benefits ( WGIII Chapter 7.4 and 12.4,
Willett et al., 2019) and other co-benefits with regard to food security, adaptation and land use (Mbow et al., 2019; Smith et al., 2019c;
WGII Chapter 5). Advancements in the provision of novel food and feed sources (e.g., cultured meat, insects, grass-based protein feed and
cellular agriculture) can also limit the pressures on finite natural resources (WGIII Chapter 12.4, Parodi et al., 2018; Zabaniotou, 2018).
Box Cross-Working Group Box BIOECONOMY.1: Circular Bioeconomy
Circular economy approaches (WGIII-12.6) are commonly depicted by two cycles, where the biological cycle focuses on regeneration in
the biosphere and the technical cycle focuses on reuse, refurbishment and recycling to maintain value and maximise material recovery
(Mayer et al., 2019a). Biogenic carbon flows and resources are part of the biological carbon cycle, but carbon-based products can be
included in, and affect, both the biological and the technical carbon cycles (Kirchherr et al., 2017; Winans et al., 2017; Velenturf et al.,
2019). The integration of circular economy and bioeconomy principles has been discussed in relation to organic waste management
(Teigiserova et al., 2020), societal transition and policy development (Directorate-General for Research Innovation, 2018; Bugge et al.,
2019) as well as coronavirus disease 2019 (COVID-19) recovery strategies (Palahi et al., 2020). To maintain the natural resource base,
circular bioeconomy emphasises sustainable land use and the return of biomass and nutrients to the biosphere when it leaves the
technical cycle.
Biomass scarcity is an argument for adopting circular economy principles for the management of biomass as for non-renewable
resources. This includes waste avoidance, product reuse and material recycling, which keep down resource use while maintaining product
and material value. However, reuse and recycling is not always feasible, such as when biofuels are used for transport and bio-based
biodegradable chemicals are used to reduce ecological impacts where losses to the environment are unavoidable. A balanced approach
to management of biomass resources could take departure in the carbon cycle from a value-preservation perspective and the possible
routes that can be taken for biomass and carbon, considering a carbon budget defined by the Paris Agreement, principles for sustainable
land use and natural ecosystem protection.
Land Use Opportunities and Challenges in the Bioeconomy
Analyses of synergies and trade-offs between adaptation and mitigation in the agriculture and forestry sectors show that outcomes
depend on context, design and implementation, so actions have to be tailored to the specific conditions to minimise adverse effects
(Kongsager, 2018). This is supported in literature analysing the nexus between land, water, energy and food in the context of climate
change, which consistently concludes that addressing these different domains together rather than in isolation would enhance synergies
and reduce trade-offs (Obersteiner et al., 2016; D’Odorico et al., 2018; Soto Golcher and Visseren-Hamakers, 2018; Froehse and Schilling,
2019; Momblanch et al., 2019).
Nature-based solutions addressing climate change can provide opportunities for sustainable livelihoods as well as multiple ecosystem
services, such as flood risk management through floodplain restoration, saltmarshes, mangroves or peat renaturation (Cross-Chapter
Box NATURAL in Chapter 2; UNEP, 2021). Climate-smart agriculture can increase productivity while enhancing resilience and reducing
GHG emissions inherent to production (Lipper et al., 2014; Singh and Chudasama, 2021). Similarly, climate-smart forestry considers the
whole value chain and integrates climate objectives into forest sector management through multiple measures (from strict reserves
Cross-Working Group Box BIOECONOMY (continued)
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to more intensively managed forests) providing mitigation and adaptation benefits (Nabuurs et al., 2018; Verkerk et al., 2020; WGIII
Section 7.3)
Agroecological approaches can be integrated into a wide range of land management practices to support a sustainable bioeconomy and
address equity considerations (HLPE, 2019). Relevant land use practices, such as agroforestry, intercropping, organic amendments, cover
crops and rotational grazing, can provide mitigation and support adaption to climate change via food security, livelihoods, biodiversity
and health co-benefits (Ponisio et al., 2015; Garibaldi et al., 2016; D’Annolfo et al., 2017; Bezner Kerr et al., 2019; Clark et al., 2019;
Córdova et al., 2019; HLPE, 2019; Mbow et al., 2019; Renard and Tilman, 2019; Sinclair et al., 2019; Bharucha et al., 2020; Bezner Kerr
et al., 2021;WGII Cross-Chapter Box NATURAL in Chapter 2). Strategic integration of appropriate biomass production systems into
agricultural landscapes can provide biomass for bioenergy and other bio-based products while providing co-benefits such as enhanced
landscape diversity, habitat quality, retention of nutrients and sediment, erosion control, climate regulation, flood regulation, pollination
and biological pest and disease control (WGIII Chapter12 Box on UNCCD-LDN, Christen and Dalgaard, 2013; Asbjornsen et al., 2014;
Holland et al., 2015; Ssegane et al., 2015; Dauber and Miyake, 2016; Milner et al., 2016; Ssegane and Negri, 2016; Styles et al., 2016;
Zumpf et al., 2017; Cacho et al., 2018; Alam and Dwivedi, 2019; Cubins et al., 2019; HLPE, 2019; Olsson et al., 2019; Zalesny et al., 2019;
Englund et al., 2020). Such approaches can help limit environmental impacts from intensive agriculture while maintaining or increasing
land productivity and biomass output.
Intensive agriculture vs. agroecological agriculture
Figure Cross-Working Group Box BIOECONOMY.1 | Left: High-input intensive agriculture, aiming for high yields of a few crop species, with large
fields and no semi-natural habitats.
Right: Agroecological agriculture, supplying a range of ecosystem services, relying on biodiversity and crop and animal diversity
instead of external inputs, and integrating plant and animal production, with smaller fields and presence of semi-natural habitats. Credit: Jacques Baudry (left); Valérie
Viaud (right), published in van der Werf et al. (2020).
Transitions from conventional to new biomass production and conversion systems include challenges related to cross-sector integration
and limited experience with new crops and land use practices, including needs for specialised equipment (WGII Chapter 5.10, Thornton
and Herrero, 2015; HLPE, 2019). Introduction of agroecological approaches and integrated biomass/food crop production can result in
lower food crop yields per hectare, particularly during transition phases, potentially causing indirect land use change, but can also support
higher and more stable yields, reduce costs, and increase profitability under climate change (Muller et al., 2017; Seufert and Ramakutty,
2017; Barbieri et al., 2019; HLPE, 2019; Sinclair et al., 2019; Smith et al., 2019c; Smith et al., 2020a). Crop diversification, organic
amendments and biological pest control (HLPE, 2019) can reduce input costs and risks of occupational pesticide exposure and food
and water contamination (Gonzalez-Alzaga et al., 2014; European Food Safety Authority Panel on Plant Protection Products and their
Residues et al., 2017; Mie et al., 2017), reduce farmers’ vulnerability to climate change (e.g., droughts and spread of pests and diseases
affecting plant and animal health; Delcour et al., 2015; FAO, 2020a) and enhance provisioning and sustaining ecosystem services, such as
pollination (D’Annolfo et al., 2017; Sinclair et al., 2019).
Barriers towards wider implementation include absence of policies that compensate landowners for providing enhanced ecosystem
services and other environmental benefits, which can help overcome short-term losses during the transition from conventional practices
before longer-term benefits can accrue. Other barriers include limited access to markets, knowledge gaps, financial, technological or
Cross-Working Group Box BIOECONOMY (continued)
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labour constraints, lack of extension support and insecure land tenure (Jacobi et al., 2017; Kongsager, 2017; Hernández-Morcillo et al.,
2018; Iiyama et al., 2018; HLPE, 2019). Regional-level agroecology transitions may be facilitated by co-learning platforms, farmer
networks, private sector, civil society groups, regional and local administration, and other incentive structures (e.g., price premiums,
access to credit, regulation) (Coe et al., 2014; Pérez-Marin et al., 2017; Mier y Terán Giménez Cacho et al., 2018; HLPE, 2019; Valencia
et al., 2019; SAPEA, 2020). With the right incentives, improvements can be made with regard to profitability, making alternatives more
attractive to landowners.
Governing the Solution Space
Literature analysing the synergies and trade-offs between competing demands for land suggest that solutions are highly contextualised
in terms of their environmental, socioeconomic and governance-related characteristics, making it difficult to devise generic solutions
(Haasnoot et al., 2020). Aspects of spatial and temporal scale can further enhance the complexity, for instance where transboundary
effects across jurisdictions or upstream–downstream characteristics need to be considered, or where climate change trajectories might
alter relevant biogeophysical dynamics (Postigo and Young, 2021). Nonetheless, there is broad agreement that taking the needs and
perspectives of multiple stakeholders into account in a transparent process during negotiations improves the chances of achieving
outcomes that maximise synergies while limiting trade-offs (Ariti et al., 2018; Metternicht, 2018; Favretto et al., 2020; Kopáček, 2021;
Muscat et al., 2021). Yet differences in agency and power between stakeholders or anticipated changes in access to or control of
resources can undermine negotiation results even if there is a common understanding of the overarching benefits of more integrated
environmental agreements and the need for greater coordination and cooperation to avoid longer-term losses to all (Aarts and Leeuwis,
2010; Weitz et al., 2017). There is also the risk that strong local participatory processes can become disconnected from broader national
plans, and thus fail to support the achievement of national targets. Thus, connection between levels is needed to ensure that ambition for
transformative change is not derailed at the local level (Aarts and Leeuwis, 2010; Postigo and Young, 2021).
Decisions on land uses between biomass production for food, feed, fibre or fuel, as well as nature conservation or restoration and other
uses (e.g., mining, urban infrastructure), depend on differences in perspectives and values. Because the availability of land for diverse
biomass uses is invariably limited, setting priorities for land use allocations therefore first depends on making the perspectives underlying
what is considered as ‘high-value’ explicit (Fischer et al., 2007; Garnett et al., 2015; de Boer and van Ittersum, 2018; Muscat et al., 2020).
Decisions can then be made transparently based on societal norms, needs and the available resource base. Prioritisation of land use for
the common good therefore requires societal consensus-building embedded in the socioeconomic and cultural fabric of regions, societies
and communities. Integration of local decision making with national planning ensures local actions complement national development
objectives.
International trade in the global economy today provides important opportunities to connect producers and consumers, effectively
buffering price volatilities and potentially offering producers in low-income countries access to global markets, which can be seen as an
effective adaptation measure (Baldos and Hertel, 2015; Costinot et al., 2016; Hertel and Baldos, 2016; Gouel and Laborde, 2021; WGII
Chapter 5.11).. But there is also clear evidence that international trade and the global economy can enhance price volatility, lead to food
price spikes and affect food security due to climate and other shocks, as seen recently due to the COVID-19 pandemic (WGII Chapter 5.12,
Cottrell et al., 2019; WFP-FSIN, 2020; Verschuur et al., 2021). The continued strong demand for food and other bio-based products, mainly
from high- and middle-income countries, therefore, requires better cooperation between nations and global governance of trade to more
accurately reflect and disincentivise their environmental and social externalities. Trade in agricultural and extractive products driving land
use change in tropical forest and savanna biomes is of major concern because of the biodiversity impacts and GHG emissions incurred in
their provision (WGII Cross-Chapter Paper 7, Hosonuma et al., 2012; Forest Trends, 2014; Henders et al., 2015; Curtis et al., 2018; Pendrill
et al., 2019; Seymour and Harris, 2019; Kissinger et al., 2021).
In summary, there is significant scope for optimising use of land resources to produce more biomass while reducing adverse effects (
high
confidence
). Context-specific prioritisation, technology innovation in bio-based production, integrative policies, coordinated institutions
and improved governance mechanisms to enhance synergies and minimise trade-offs can mitigate the pressure on managed as well as
natural and semi-natural ecosystems (
medium confidence
). Yet, energy conservation and efficiency measures, and deployment of
technologies and systems that do not rely on carbon-based energy and materials, are essential for mitigating biomass demand growth as
countries pursue ambitious climate goals (
high confidence
).
Cross-Working Group Box BIOECONOMY (continued)
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Frequently Asked Questions
FAQ 5.1: How is climate change (already) affecting people’s ability to have enough nutritious food?
Climate change has already made feeding the world’s people more difficult. Climate-related hazards have become more common, disrupting
the supply of crops, meat and fish. Rapid changes in weather patterns have put financial strain on producers, while also raising prices and
limiting the choices and quality of produce available to consumers.
Most of our food comes from crops, livestock, aquaculture and fisheries. Global food supply increased dramatically
in the last century, but ongoing climate change has begun to slow that growth, reducing the gains that would have
been expected without climate change. Regionally, negative effects are apparent in regions closer to the equator,
with some positive effects further north and south.
Climate impacts are also negatively affecting the quality of produce, from changes in micronutrient content to
texture, colour and taste changes that reduce marketability. With warmer and more humid condition, many food
pests thrive, food decays more quickly, and food contains more toxic compounds produced by fungi and bacteria.
Warming of the oceans has reduced potential fish catch. The increased carbon dioxide in the atmosphere has led to
ocean acidification, which is already impacting the production of farmed fish and shellfish. Changes in local climate
have forced producers to shift to new locations, changing what they grow or where they work (e.g., pole-ward
shifting fishing grounds).
Climate hazards have increased over the past 50 years and are the major cause of sudden losses of production
(food production shocks). Food shocks occur following droughts, heatwaves, floods, storms and outbreaks of
climate-related pests and combine to cause multiplying impacts. Climate hazards sometimes disrupt food storage
and transport, which impairs the food supply.
All of these negative impacts can lead to increased food prices, and reduced income for producers and retailers as
there are fewer products to sell. Together, these impacts threaten to reduce the supply of varied, nutrient-rich foods
to poor populations that already suffer ill health.
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Crops
(a)
Livestock
(b)
Fisheries
(c)
Aquaculture
(d)
0.0
0.2
0.4
0.6
Shock frequency
0.00
0.02
0.04
0.06
1970
1980
1990
2000
2010
Sh
oc
k
freq
.
(e)
0.00
0.02
0.04
0.06
1970
1980
1990
2000
2010
Sh
ock
freq.
(f)
0.00
0.02
0.04
0.06
1970
1980
1990
2000
2010
Sh
oc
kf
re
q.
(g)
0.00
0.02
0.04
0.06
1970
1980
1990
2000
2010
Year
Sh
oc
kf
re
q.
(h)
Trends in food production shocks in different food supply sectors from 1961-2013
Figure FAQ5.1.1 | Trends in food production shocks in different food supply sectors from 1961 to 2013 (Cottrell et al., 2019).
The red lines in
the time series are the annual shock frequency, and the dashed line is the decadal mean.
Box FAQ 5.1 (continued)
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Frequently Asked Questions
FAQ 5.2: How will climate change impact food availability by mid and late century and who will suffer most?
Climate change impacts will worsen over time, with the period after mid-century seeing more rapid growth in negative impact than in the
early part of this century. The impacts will be global, but people with fewer resources, and those who live in regions where impacts will worsen
more rapidly, will be hurt the most.
Climate change impacts will worsen over time, but the extent depends on how rapidly greenhouse-gas emissions
grow. If the current rate of emissions continues, the impacts will worsen, especially after mid-century, with rapid
growth in the number and severity of extreme weather events. Yields of plants, animals and aquaculture will
decline in most places, and marine and inland fisheries will suffer. Food production in some regions will become
impossible, either because the crops or livestock there cannot survive in the new climatic conditions, or it is too hot
and humid for farm workers to be in the fields.
After harvest, agricultural production passes through the agricultural value chain, supplying animal feeds, industrial
uses and international markets, with some stored for use in the future. Each of these transitions will be affected
by climate change. Food storage facilities will face more challenges in dealing with spoilage. Transportation of
perishable fruits, vegetables and meats will become costlier to maintain quality. Households and food services will
need to spend more on food preservation.
Low-income countries and poor people are at higher risk, as they have limited social safety nets and suffer more
from rising food prices and an unstable food supply. But large famers will also be hurt. Rural communities, especially
smallholder farmers, pastoralists and fishers, are extremely vulnerable because their livelihoods mainly depend on
their production. The urban poor will have to spend more on food.
A flood, for example, may force low-income families out of their homes, affect their employment and reduce their
access to food supplies, with prices often rising after natural disasters. Families will have less access to safe water
supplies, and this combination of lower food supplies, uncertain employment, displacement from home and rising
food costs will increase the number of children who are undernourished.
Impacts of climate change in the food system
Yields reduced
Producer income falls
Pests and disease damage
reduce quality and quantity
Losses of perishable items to
higher temperatures/humidity
More expense to marketing
system
More spoilage,
reduced availability
Impacts in other sectors
reduce income available
Maize yields fall by 23 % in the
21st century with high GHG
emissions (SSP585)
Aflatoxin contamination will
increase in maize in a +2°C
temperature scenario in Europe
Increase in temperature from
17°C to 25 °C increases cold
storage power consumption by
about 11%
Uptake of methyl mercury in fish
and mammals has been found
to increase by 3-5% for each
1°C rise in water temperature
Production (farm,
pasture, fisheries
Post-harvest,
storage
Transportation
Consumption-quality
and availability
Examples (taken from individual sectors of chapter 5)
Figure FAQ5.2.1 | Impacts of climate change on the food system.
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Frequently Asked Questions
FAQ 5.3: Land is going to be an important resource for mitigating climate change: how is the increasing
competition for land threatening global food security and who will be affected the most?
Climate change will affect food production. Meeting future food needs requires greater land shares unless we change what we eat and how
we grow food. Additionally, large-scale land projects that aim to mitigate climate change will increase land competition. Less land will then
be available for food production, increasing food insecurity. People at greater risk from land competition are smallholder farmers, Indigenous
Peoples and low-income groups.
Why is land important?
Land is a limited resource on which humans and ecosystems depend on to grow plants, which capture carbon
dioxide and release oxygen, and provide food, timber and other products. We also have cultural, recreational and
spiritual connections to land.
Climate impacts will increase competition for land use
Reforestation will reduce climate
impacts but increase land competition
Sea level rise will lead to coastal
flooding and land use change
Competition of food production for
people, livestock and fish
Figure FAQ5.3.1 | Climate impacts will increase competition for land use, reducing coastal land for crops and affecting food security for
vulnerable groups.
Adaptation methods like coastal aquaculture and mangrove reforestation reduce climate effects but may increase land competition.
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Why will climate change affect land use?
Climate change results in more frequent heatwaves, extreme rainfall, drought and rising sea levels, which negatively
affect crop yields. More land is thus needed to grow crops, increasing land competition with other food systems
that use crops to feed their animals (e.g., livestock, fish). Where land will be flooded, humans cannot grow crops,
but food production could be adapted to grow seafood instead. Extensive land allocations aiming at reducing
carbon emissions, such as afforestation, reduce land availability for food. Unless carefully managed, competition
for land will increase food prices and food security.
Solutions to reduce land competition and protect food security
Sustainable land management allows land to remain productive and support key functions. Other land practices
include growing cover crops to improve soil quality. Governments can provide incentives to producers to grow
alternative foods and use sustainable practices. Making sure that vulnerable groups (e.g., low-income communities,
Indigenous people and small-scale producers) strengthen land tenure rights will help protect food security.
Food by-products used as alternative food sources and other products reduce waste and increase sustainability.
Dietary changes are another important solution. People that eat high amounts of meat or unhealthy foods could
reduce consumption of these foods and have more diverse diets. These dietary changes will benefit their health and
reduce pressure on land. Regulated labelling, education and other policies which encourage healthy diets can
support these shifts.
Box FAQ 5.3 (continued)
Frequently Asked Questions
FAQ 5.4: What are effective adaptation strategies for improving food security in a warming world?
A variety of adaptation options exist to improve food security in a warming world. Examples of adaptation for crop production include crop
management and livelihood diversification. For livestock-based systems, an example is matching number of animals with the production
capacity of pastures. For fisheries, eliminating overfishing is an effective adaptation practice. For mixed cropping and nature-based systems,
an appropriate adaptation is agroforestry.
Adaptation strategies to enhance food security vary from farm-level interventions to national policies and
international agreements. They cover the following dimensions of food security: availability, access, utilisation
(food quality and safety) and stability.
For the production of crops, adaptation strategies include field and farm-level options such as crop management,
livelihood diversification and social protection such as crop insurance. The most common field management options
are changes in planting schedules, crop varieties, fertilizers and irrigation. For example, farmers can shift their
planting schedules in response to the early or late onset of the rainy season. Moreover, there are new crop insurance
schemes that are based on changes in weather patterns.
For livestock-based systems, adaptation options include matching the number of animals with the production
capacity of pastures; adjusting water management based on seasonal and spatial patterns of forage production;
managing animal diet; more effective use of fodder, rotational grazing; fire management to control woody
thickening of grass; using more suitable livestock breeds or species; migratory pastoralist activities; and activities to
monitor and manage the spread of pests, weeds and diseases.
For ocean and inland fisheries, adaptation options are primarily concentrated in the socioeconomic dimension and
governance and management. In general, eliminating overfishing could help rebuild fish stocks, reduce ecosystem
impacts, and increase fishing’s adaptive capacity. Aquaculture is often viewed as an adaptation option for fisheries
declines. However, there are adaptation strategies specific to aquaculture, including proper species selections at the
operational level, such as the cultivation of brackish species (shrimp, crabs) in inland ponds during dry seasons and
rice–freshwater finfish in wetter seasons.
For so-called mixed farming systems that produce a combination of crops, livestock, fish and trees, these systems’
inherent diversity provides a solid platform for adaptation. A good example is agroforestry, the purposeful
integration of trees or shrubs with crop or livestock systems, which increases resilience against climate risks.
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Overall, nature-based systems or ecosystem-based strategies in food systems, such as agroecology, can be a useful
adaptation method to increase wild and cultivated food sources. Agroecological practices include agroforestry,
intercropping, increasing biodiversity, crop and pasture rotation, adding organic amendments, integration of
livestock into mixed systems, cover crops and minimising toxic and synthetic inputs with adverse health and
environmental impacts.
Box FAQ 5.4 (continued)
Frequently Asked Questions
FAQ 5.5: Climate change is not the only factor threatening global food security: other than climate action, what
other actions are needed to end hunger and ensure access by all people to nutritious and sufficient food all year
round?
Our food systems depend on many factors other than climate change, such as food production, water, land, energy and biodiversity. People’s
access to healthy food can be also be affected by factors such as poverty and physical insecurity. We are all stakeholders in food systems,
whether as producers or consumers, and we can all contribute to the goal of a food-secure world by the choices we make in our everyday lives.
Today more than 820 million people are hungry, and hunger is on the rise in Africa. Two billion people experience
moderate or severe food shortages, and another 2 billion suffer from overnutrition, a state of obesity or being
overweight from unbalanced diets, with related health impacts such as diabetes and heart disease. The changing
climate is already affecting food production. These effects are worsening, affecting food production from crops,
livestock, fish and forests in many places where people already do not have enough to eat. Food prices will be
affected as a result, with increasing risk that poorer people will not be able to buy enough for their families. Food
quality will increasingly be affected too.
Our ability to grow and consume food depends on many factors other than climate change. There are tight
connections between food production, water, land, energy and biodiversity, for example. Other factors like gender
inequity, poverty, political exclusion, remoteness from urban centres and physical insecurity can all affect people’s
access to healthy food.
Food systems are complicated
(
Figure FAQ5.5.1). To improve food production, supply and distribution, we need
to make changes throughout the food supply chain. For instance: improving the way farmers access the inputs
needed to grow food; improving the ways in which food is grown, with climate and market information, training
and technical know-how, water-saving and water-harvesting technologies; adopting new low-cost and less
carbon-intensive storage and processing methods; and creating local networks of producers and processors For
food consumers, we could consider shifts to different diets that are healthier and make more efficient use of natural
resources; depending on context, these could involve rebalancing consumption of meat and highly processed
foods, reducing food loss and waste, and preparing food in more energy-efficient ways. Policymakers can enable
such actions through appropriate price and trade policies, implementing policies for sustainable and low-emission
agriculture, providing safety nets where needed, and empowering women, youth and other socially disadvantaged
groups.
Our food systems need to be robust and sustainable; otherwise we will not be able to manage the additional
pressures imposed on them by climate change. We can all contribute to this goal.
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Conceptual framework of food systems for diets and nutrition
Biophysical &
environmental drivers
Innovation,
technology &
infrastructure drivers
Political & economic
drivers
Socio-cultural drivers
Food environments
Food availability & access
Affordability
Promotion, advertising,
information
Food quality & safety
Consumer behaviour
Choosing where and what
food to acquire, prepare,
cook, store, eat
Diets
Quantity, quality,
diversity, safety
Social,
economic,
environmental
impacts
Food supply chains
Production systems
Storage & distribution
Processing & packaging
Retail & markets
Political, programme & institutional actions
Sustainable Development Goals
Availability
Access
Utilization
Demographic drivers
Nutrition &
health outcomes
Figure FAQ5.5.1 | Conceptual framework of food systems for diets and nutrition (modified from HLPE, 2017a).
Box FAQ 5.5 (continued)
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