Teng et al. (2024). Conservation agriculture improves soil health and sustains crop yields after long-term warming

,

Fusuo Zhang

1

& Manuel Delgado-Baquerizo

5

Climate warming threatens global food security by exacerbating pressures on
degraded soils under intensive crop production. Conservation agriculture is
promoted as a sustainable solution that improves soil health and sustains crop
yields in a changing climate, but these bene

ﬁ

ts may be affected by long-term

warming. Here, we investigate the effects of conservation agriculture com-
pared to conventional agriculture on 17 soil properties, microbial diversity and
crop yields, during eight-years

’

experimental warming. An overall positive

effect of warming on soil health over time under conservation agriculture is
characterized by linear increases in soil organic carbon and microbial biomass
carbon. Warming-triggered shifts in microbial biomass carbon and fungal
diversity (saprogen richness) are directly linked to a 9.3% increase in wheat
yields over eight years, but only under conservation agriculture. Overall,
conservation agriculture results in an average 21% increase in soil health and
supports similar levels of crop production after long-term warming compared
to conventional agriculture. Our work provides insights into the potential
bene

ﬁ

ts of conservation agriculture for long-term sustainable food production

because improved soil health improves resilience to the effects of climate
warming.

Global food security is challenged by climate warming and growth of
the human population

. Soil degradation associated with intensive

agriculture has reduced the availability of land for food production

.

The far-reaching consequences of climate warming combined with the
urgent demand to increase food production require climate-resilient
land management options to simultaneously increase productivity and

promote adaptations to climate change and its mitigation

,

. A sus-

tainable management strategy described as

‘

conservation agriculture

’

is widely promoted as a nature-based solution to maintain food pro-
duction and simultaneously promote soil health

,

m.delgadobaquerizo@gmail.com

–

10

. Soil health is a

holistic concept that integrates the biological, physical and chemical
aspects of soil, demonstrating the continued capacity of soil as a vital

Received: 18 September 2023

Accepted: 3 October 2024

Check for updates

1

State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green

Development, China Agricultural University, 100193 Beijing, PR China.

2

Key Laboratory of Ecosystem Network Observation and Modeling, Institute of

Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), 100101 Beijing, PR China.

3

Geography, College of Life and

Environmental Sciences, University of Exeter, Rennes Drive, Exeter EX4 4RJ, UK.

4

Carbon Management Centre, SRUC-Scotland

’

s Rural College, Edinburgh

EH9 3JG, UK.

5

Laboratorio de Biodiversidad y Funcionamiento Ecosistémico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), Consejo

Superior de Investigaciones Cientí

ﬁ

cas (CSIC), 41012 Sevilla, Spain.

6

Department of Soil Science of Temperate Ecosystems, University of Göttingen, 37077

Göttingen, Germany.

7

These authors contributed equally: Jialing Teng, Ruixing Hou.

e-mail:

tianj@igsnrr.ac.cn

;

cuizl@cau.edu.cn

;

| (2024) 15:8785

1

12

3

4

5

6

78

12

3

4

5

6

7

8

living ecosystem

,

. Conservation agriculture encompasses reduced or

zero/no tillage, permanent soil cover, and diverse crop rotations, and
is applicable in many different farming contexts

,

. A wide range of

environmental bene

ﬁ

ts associated with its implementation, including

improved soil health related to increased soil organic carbon (SOC)
stocks and soil biodiversity

,

, has led to adoption of conservation

agriculture across 12.5% of arable land in one-third of countries
worldwide

11

. However, a paucity of systematic and quantitative

assessments of long-term climate warming effects on the potential of
conservation agriculture to support soil health and crop production
creates uncertainty in its ef

ﬁ

cacy under different future climate

projections

14

. Long-term

ﬁ

eld experiments speci

ﬁ

cally comparing

conservation agriculture with conventional management under
warming conditions are particularly rare

12

,

15

–

, but are urgently needed

to explore the interactive effects of management and warming on crop
yield and soil health

.

Predicting the effectiveness of conservation agriculture as the

climate warms is challenging because of the complex interactive
effects of warming and soil management on crop yields and individual
soil properties

18

19

. In general, climate warming profoundly affects

agricultural activities in many ways, ranging from yield reductions to
loss of SOC and ecosystem functions

,

. Reductions in crop yields in

response to rising temperature are widely reported

22

–

26

, especially at

low latitudes

26

27

, mainly due to drought, disturbed crop growth cycles,

and increased pathogen pressures

25

,

28

. SOC is a

‘

master

’

soil health

indicator that supports multiple soil functions including nutrient and
water cycling and retention, soil structure formation, and ecosystem
productivity

29

31

. Climate warming is anticipated to elevate global SOC

losses by accelerating microbial decomposition

32

–

35

. In addition, rising

temperatures may enhance microbial nitrogen mineralization and lead
to nitrogen loss from terrestrial ecosystems

36

. In contrast, crop residue

retention in conservation agriculture promotes SOC accrual directly
by increasing plant biomass inputs, which also alleviates water and
nutrient limitation for crops by improving soil health, and indirectly by
accelerating microbial turnover and necromass accrual through
organic matter supply

33

. The soil conditions created by conservation

agriculture can counteract the negative effects of climate change on
food production in some regions

37

39

. The complex interactive effects

of warming and soil management create many uncertainties in pre-
diction aggravated by the limitations of process-based crop simulation
models to estimate the effects of climate change on agroecosystem
functions. This is exacerbated by the urgent requirement for empirical
data from long-term

ﬁ

eld warming experiments to improve models

that forecast future farming conditions

40

; to date, short-term

ﬁ

eld-

warming studies have largely focused on natural ecosystems

18

.

Soil microbiome are major contributors to sustainable agriculture

because they drive key processes in agroecosystems prerequisite to
optimizing soil health and crop productivity

41

. Conservation agri-

culture generally promotes the size, diversity, activity and bene

ﬁ

cial

functions of soil microorganisms that contribute to soil health,
including SOC accrual in available and stable pools, and crop
productivity

42

. In particular, reduced tillage supports the develop-

ment of hyphal networks and a more diverse and abundant soil fungal
biomass, which contributes to multiple soil ecosystem functions
including improved substrate and water supply

43

45

. However, the

effects of climate warming on the observed bene

ﬁ

ts of conservation

agriculture for the soil microbiome are dif

ﬁ

cult to anticipate. Intenser

environmental

ﬁ

ltering in warmed forest and grassland soils can create

negative effects on fungal and bacterial diversity

46

47

. Stronger nutrient

acquisition by roots induced by warming may lead to reductions in
mycorrhizal

dependence

and

arbuscular

mycorrhizal

fungal

diversity

48

. Potential increases of soil-borne plant pathogens under

warming conditions are of especial concern in crop production
systems

28

49

, though the increase in soil health that supports healthy

crop growth may help counteract disease threats

50

. Overall, great

uncertainty remains about the response of soil microbiome to inter-
actions between warming and crop management practices, and the
effects on soil health and crop yields.

Our study aims to assess warming effects on: (i) soil health and

crop yields under conservation agriculture (permanent crop residue
cover and no tillage) versus conventional agriculture (crop residue
removal and annual tillage); and (ii) the contribution of the soil
microbiome to supporting soil health and crop yields. We hypothesize
that, under warming conditions, (i) conservation agriculture improves
crop productivity by increasing carbon inputs aboveground (crop
residues) and belowground (crop roots) that stimulates microbial
growth, promoting soil health characterized by carbon accrual; (ii)
improvements in crop yield and soil health relies on changes in the soil
microbiome; (iii) the bene

ﬁ

ts of conservation agriculture are cumula-

tive over time. To test these hypotheses, we conduct an eight-year-
long

ﬁ

eld experiment to investigate the effects of soil management

systems (conservation agriculture versus conventional agriculture)
and warming levels (warming versus ambient) on crop yields and soil
health, and additionally the in

ﬂ

uence of the soil microbiome, on the

North China Plain. Our experiment is conducted using a typical crop
rotation system (winter wheat (

Triticum aestivum

L.)-summer maize

(

Zea mays

L.)). Two levels of warming are imposed using infrared

heaters:

‘

ambient

’

and

‘

+2 °C

’

according to soil warming predicted by

IPCC greenhouse gas scenarios rates for northern China

51

. We simul-

taneously assess 17 soil health indicators, microbial diversity and crop
yields to demonstrate the combined effects of warming and manage-
ment. We

ﬁ

nd that long-term warming increases soil health indicators

and crop productivity, but only under conservation agriculture. The
bene

ﬁ

cial effects of conservation agriculture on microbial biomass

carbon and SOC increase through time under long-term warming.
Improved soil health and shifts in soil fungal diversity are related to the
positive warming effects on crop yields over time under conservation
agriculture. Our work demonstrates the potential for climate resilient
farming through the implementation of conservation agriculture to
improve soil health and sustain crop yields in a warming climate.

Results

Similar wheat yields in conservation agriculture and conven-
tional agriculture under warming

Experimental warming was imposed using infrared heaters to plots
used for wheat and maize cultivation adopting conservation agri-
culture or conventional agriculture (Fig.

a). Over the eight-year study

period, soil temperature and moisture were recorded continuously by
in-situ sensors. As expected, experimental warming increased soil
temperature but decreased soil moisture under both conservation and
conventional agriculture (

P

< 0.05; Fig.

b, c; Supplementary Table 1).

The warming effects were modi

ﬁ

ed by soil management, and soils

under conservation agriculture were cooler (14.0 °C vs. 14.7 °C) and
wetter (17.1% vs. 15.9%) than under conventional agriculture (

P

< 0.001;

Fig.

b, c; Supplementary Table 1).

Winter wheat yields were strongly affected by warming (

P

< 0.001;

Supplementary Table 1), but there was no difference between the two
management types (Fig.

d). Conservation agriculture maintained

similar wheat yields to conventional agriculture both under ambient
and warming conditions (Fig.

d). Across the eight-year study, warming

increased wheat yields by 9.3% and 11.2% under conservation and
conventional agriculture, respectively, when compared with the no
warming treatments (

P

< 0.001; Fig.

d; Supplementary Table 1). We

further assessed the warming effect on wheat yields over eight years
using Cohen

’

s

d

index (Fig.

e). Warming-induced positive effects on

wheat yields strengthened with time under conservation agriculture
(

P

< 0.05), but not under conventional agriculture (Fig.

e). In contrast,

the maize yields were only affected by soil management (

P

< 0.001;

Supplementary Table 1), but not in

ﬂ

uenced by warming (Supplemen-

tary Fig. 1). Conservation agriculture supported larger maize yields

Article

https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

2

than conventional agriculture under both ambient and warming con-
ditions (

P

< 0.001; Supplementary Fig. 1; Supplementary Table 1).

Conservation agriculture improved soil health under warming

Seventeen soil properties, including physical, chemical, and biological
attributes, were analyzed in 2020 using samples from two soil depths
(0

–

5 cm and 5

–

15 cm depth) to evaluate the cumulative effects of long-

term warming on soil health. Principal Component Analysis (PCA) was
used to select representative indicators of soil health (Fig.

a; Sup-

plementary Fig. 2). The

ﬁ

rst two principal components accounted for

75.2% (PC1 = 57.9% and PC2 = 17.3%) and 59.8% (PC1 = 35.8% and PC2 =

24.0%) of the cumulative percent variability in soil health at 0

–

5 cm

and 5

–

15 cm depth, respectively (Fig.

a; Supplementary Fig. 4a). The

soil health score (Cornell Soil Health Assessment Scoring) was affected

by management, warming, and their interaction (

P

< 0.05; Supple-

mentary Table 2). The response of soil health to warming varied
depending on soil management (

P

< 0.05; Supplementary Table 2).

Warming increased the soil health score by 6.3% and 8.1% at 0

–

5 cm

and 5

–

15 cm soil depth under conservation agriculture, but only

increased soil health score by 5.2% at 5

–

15 cm depth under conven-

tional agriculture (

P

< 0.01; Fig.

b; Supplementary Fig. 4b; Supple-

mentary Table 2). The soil health score under conservation agriculture
was 21.5% and 7.1% greater than conventional agriculture at 0

–

5 cm and

5

–

15 cm depth in ambient conditions, respectively (Fig.

b; Supple-

mentary Fig. 4). Warming ampli

ﬁ

ed the advantages of conservation

agriculture in terms of soil health, and resulted in a 31.4% and 10.1%
greater soil health score than conventional agriculture at 0

–

5 cm and

5

–

15 cm depth, respectively (Fig.

b; Supplementary Fig. 4b).

Fig. 1 | Effects of warming and management on soil microclimate and crop
yields. a

Experimental settings for treatments.

b

,

c

Effects of warming and man-

agement on soil temperature and moisture over eight years was estimated by linear
mixed model with sampling time as random factors. Statistical signi

ﬁ

cance is based

on Wald type II

χ

² tests (

n

= 8 independent soil samples per treatment). All reported

P

values result from two-sided statistical tests. Boxplots display the mean (hor-

izontal line), the 25th and 75th percentiles (colored box), the minimum and max-
imum (whiskers).

d

Average winter wheat yields. Boxplots display the mean

(horizontal line), the 25th and 75th percentiles (colored box), the minimum and
maximum (whiskers). The winter wheat yield data were analyzed based on eight
sampling years (

n

= 24 independent soil samples per treatment). Statistical analysis

was performed using a linear mixed model with sampling time as random factors.
Statistical signi

ﬁ

cance is based on Wald type II

χ

² tests. All reported

P

values result

from two-sided statistical tests. Asterisks indicate signi

ﬁ

cant differences in the

warming effect of the individual management system as compared with their
matched ambient condition.

e

Shift in the effect size of warming on crop yields over

time for conservation and conventional agriculture, respectively. A linear regres-
sion model with two-sided test was used for the statistical analysis, and adjusted
R-squared was used. Relationships are denoted with solid lines and

ﬁ

t statistics (R

2

and

P

values) for each management practice. The solid line represents the sig-

ni

ﬁ

cant linear regression (

P

< 0.05), and the gray shading indicates the 95% con-

ﬁ

dence intervals. All reported

P

values result from two-sided statistical tests where

*

P

< 0.05, **

P

< 0.01, and ***

P

< 0.001. Conserv-Amb, conservation agriculture

without warming; Conserv-Warm, conservation agriculture with warming; Conven-
Amb, conventional agriculture without warming; Conven-Warm, conventional
agriculture with warming. Source data are provided as a Source Data

ﬁ

le.

Article

https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

3

We also calculated the warming effects on individual soil indica-

tors that contributed to the soil health score between paired warmed
and ambient plots under the two management systems (Fig.

c

–

g;

Supplementary Fig. 3; Supplementary Fig. 4c

–

g; Supplementary

Table 2). Warming enhanced mean weight diameter (MWD) and the
proportion of soil aggregates larger than 0.25 mm (R

0.25

) under con-

servation agriculture but not conventional agriculture, indicating
better water in

ﬁ

ltration, storage and supply (Fig.

c; Supplementary

Figs. 3

–

5). Warming also promoted nutrient cycling, storage and sup-

ply under conservation agriculture, characterized by increased DOC,
SOC, TN, AK, and NO

3

−

-N concentration under warming (Fig.

c; Sup-

plementary Figs. 3

–

5). Conservation agriculture increased MBC and

MBN and suggested greater microbial activity under warming (Fig.

c;

Supplementary Figs. 3

–

5). We calculated the weighting values of indi-

vidual soil properties and recognized DOC, MBC, SOC, and TN as the
key contributors to the soil health score (Supplementary Fig. 3).

Increased DOC, MBC, SOC, and TN were stimulated by warming and
collectively improved the soil health of conservation agriculture
(Fig.

c

–

g; Supplementary Fig. 3; Supplementary Fig. 4c

–

g). We further

assessed the warming effect on DOC, MBC, SOC, and TN over eight
years (Fig.

d

–

k; Supplementary Fig. 4d

–

k). Across the eight-year

study, the average soil DOC was increased by warming under both
conservation and conventional agriculture (

P

< 0.05; Fig.

d-g; Sup-

plementary Fig. 4d-g; Supplementary Table 1), but changes in MBC and
SOC in response to warming varied depending on soil management at
0

–

5 cm depth (

P

< 0.05; Fig.

d, f; Supplementary Fig. 4d, f; Supple-

mentary Table 1). Warming increased MBC and SOC under conserva-
tion agriculture but not under conventional agriculture (

P

< 0.05;

Fig.

e, f; Supplementary Table 1). Moreover, the positive effects of

warming on MBC and SOC strengthened with time under conservation
agriculture (

P

< 0.05; Fig.

h

–

k), indicating a cumulative bene

ﬁ

t of

conservation agriculture over time for these soil carbon pools.

Fig. 2 | Effects of warming and management on soil attributes and soil health
score at 0-5 cm soil depth. a

Two dimensions of Principal Component Analysis

(PCA) for eigenvalues of the seventeen soil attributes, including MWD, R

0.25

, SM,

BD, pH, DOC, SOC, NH

4

+

-N, NO

3

-

-N, DON, TN, AP, TP, AK, TK, MBC, and MBN. All

parameters were analyzed based on soil sampling in 2020 (

n

= 4 independent soil

samples per treatment).

b

Effects of warming and management on soil health score.

Data are presented with mean values ± s.e.m. Statistical analysis was performed
using two-way ANOVA analysis. Soil health score was evaluated based on soil
sampling in 2020 (

n

= 4 independent soil samples per treatment).

c

Estimates of the

warming effects on soil attributes depending on management. The effect size was
estimated by Cohen

’

d

. Data are presented with mean values ± s.e.m. Statistical

analysis was performed using two-way ANOVA analysis (

n

= 4 independent soil

samples per treatment).

d

–

g

Average of key soil attributes over eight years deter-

mined using a linear mixed model. Statistical signi

ﬁ

cance is based on Wald type II

χ

²

tests (

n

= 24 independent soil samples per treatment). Boxplots display the mean

(horizontal line), the 25th and 75th percentiles (colored box), the minimum and

maximum (whiskers).

h

–

k

Temporal changes of warming effects on key soil

properties over time depending on management. The effect size was estimated by
Cohen

’

d

. The solid line represents the signi

ﬁ

cant linear regression (

P

< 0.05), and

the gray shading indicates the 95% con

ﬁ

dence interval (i.e., error bands represent

slopes ± 95% con

ﬁ

dence intervals). All reported

P

values result from two-sided

statistical tests where *

P

< 0.05, **

P

< 0.01, and ***

P

< 0.001. Conserv-Amb, con-

servation agriculture without warming; Conserv-Warm, conservation agriculture
with warming; Conven-Amb, conventional agriculture without warming; Conven-
Warm, conventional agriculture with warming. MWD, mean weight diameter; R

0.25

,

aggregate content with particle size larger than 0.25 mm; SM soil moisture, BD bulk
density, DOC dissolved organic carbon, SOC soil organic carbon, NH

4

+

-N ammo-

nium, NO

3

−

N nitrate, DON dissolved organic nitrogen, TN total nitrogen, AP avail-

able phosphorus, TP total phosphorus, AK available potassium, TK total potassium,
MBC microbial biomass carbon, MBN microbial biomass nitrogen. Source data are
provided as a Source Data

ﬁ

le.

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https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

4

Effects of warming and management on microbial diversity and
community composition

Soil fungal and bacterial diversity and community composition were
determined across eight years (Fig.

; Supplementary Fig. 6; Supple-

mentary Tables 2

–

3). Our results based on NMDS ordinations and

nested PERMANOVA analysis indicated that soil fungal and bacterial
communities at 0-5 cm depth were affected by management
(R

2

= 0.089

–

0.103,

P

< 0.001), warming (R

2

= 0.014

–

0.017,

P

< 0.01),

and their interaction (R

2

= 0.009

–

0.010,

P

< 0.05) (Fig.

a; Supple-

mentary Table 3). The microbial diversity over eight years, as esti-
mated by richness, was further assessed through linear mixed
modelling (Supplementary Table 1). The soil bacterial richness was not
affected by management, warming, and their interaction (Supple-
mentary Table 1). The total soil fungal richness was in

ﬂ

uenced by

interactions between warming and management (

P

< 0.05; Fig.

c;

Supplementary Table 1), indicating differential responses of the soil
fungal community to warming under conservation and conventional
agriculture. Warming decreased fungal richness by 4.1% compared to
the no-warming treatment under conservation agriculture (

P

< 0.05),

but not under conventional agriculture (Fig.

c). Speci

ﬁ

cally, the

richness of fungal functional guilds was in

ﬂ

uenced by management,

but not warming (Fig.

c; Supplementary Table 1). Conservation agri-

culture supported the greater richness of AMF (

P

< 0.001; Supple-

mentary Table 1) and lesser richness of saprogens and pathogens
(

P

< 0.05; Supplementary Table 1) at 0

–

5 cm soil depth (Fig.

c).

Warming decreased the richness of saprogens under conservation
agriculture only (

P

< 0.05; Supplementary Table 1) (Fig.

c).

Soil fungal and bacterial communities in the 5

–

15 cm soil depth

were affected by management (R

2

= 0.061

–

0.072,

P

< 0.001), warming

(R

2

= 0.024,

P

< 0.01), and their interaction (R

2

= 0.023,

P

< 0.05) (Sup-

plementary Fig. 6b; Supplementary Table 3). Bacterial richness was
only affected by management and was greater under conventional
agriculture (

P

< 0.01; Supplementary Fig. 6c; Supplementary Table 1).

Total fungal richness was not affected by management, but richness of
AMF and saprogen varied between management systems (Supple-
mentary Fig. 6b; Supplementary Table 1). Conservation agriculture
supported more AMF (

P

< 0.001; Supplementary Table 1) and less

saprogens (

P

< 0.05; Supplementary Fig. 6c; Supplementary Table 1).

Warming decreased total fungal richness (

P

< 0.01) and decreased

saprogens (

P

< 0.001) and pathogens (

P

< 0.01) under conventional

agriculture (Supplementary Fig. 6c; Supplementary Table 1).

Soil health and the microbiome contributed to wheat yields
under conservation agriculture with warming

We selected the best soil properties to predict crop yield using linear
mixed models (Fig.

; Supplementary Figs. 7

–

8). The MBC and rich-

ness of saprogens at 0

–

5 cm soil depth, and fungal community

composition at 5

–

15 cm soil depth, were most closely linked to wheat

yields under conservation agriculture (Fig.

a, b; Supplementary

Fig. 7). There were corresponding strong positive correlations

Fig. 3 | Effects of warming and management on microbial diversity and com-
munity composition at 0-5 cm soil depth. a

,

b

Nonmetric multidimensional

scaling (NMDS) ordination of soil fungal and bacterial communities based on the
Bray-Curtis dissimilarity. Statistical analysis was performed using nested permu-
tational multivariate analysis of variance (nested PERMANOVA) analysis.

c

Effects of

warming and management on microbial richness of soil total fungi, fungal guild,
and bacteria. Boxplots display the mean (horizontal line), the 25th and 75th per-
centiles (colored box), the minimum and maximum (whiskers). Data were analyzed

based on eight sampling years (

n

= 24 independent soil samples per treatment).

Statistical analysis was performed using linear mixed model with sampling time as
random factors. Statistical signi

ﬁ

cance is based on Wald type II

χ

² tests. All reported

P

values result from two-sided statistical tests where *

P

< 0.05, **

P

< 0.01, and

***

P

< 0.001. Conserv-Amb, conservation agriculture without warming; Conserv-

Warm, conservation agriculture with warming; Conven-Amb, conventional agri-
culture without warming; Conven-Warm, conventional agriculture with warming.
Source data are provided as a Source Data

ﬁ

le.

Article

https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

5

between wheat yields and MBC, but negative correlations with
saprogen richness (Fig.

b). Soil MBC stimulated by warming,

reductions in saprogen richness and variations of the fungal com-
munity contributed most to wheat yields under conservation agri-
culture (Fig.

b; Supplementary Fig. 7). In addition, the richness of

soil bacteria and pathogens also affected wheat yields under con-
servation agriculture (Fig.

a; Supplementary Fig. 7). In contrast, the

soil microclimate (temperature and moisture) and DOC were most
relevant to wheat yield under conventional agriculture (Fig.

a, c;

Supplementary Fig. 7). Summer maize yields were also affected by
soil properties, but the measured soil variables did not lead to
changes in maize yields under warming (Supplementary Fig. 8). In
conclusion, crop yields under conservation agriculture were more
in

ﬂ

uenced by the soil microbiome (including MBC, fungal richness,

and fungal community composition) than under conventional
agriculture.

The key indicators of soil health were also affected by soil

microbial richness and community composition (Fig.

d, e; Supple-

mentary Fig. 9), especially under conservation agriculture. Soil MBC
and SOC were more relevant to soil fungal richness or community
composition compared with bacteria under conservation agriculture
(Fig.

d, e; Supplementary Fig. 9). The intense relationship between

soil

fungi

and carbon emphasized the

microbially-mediated

mechanisms that underlie soil carbon accrual observed under con-
servation agriculture.

Discussion

This study provides rare empirical evidence for the advantages of
conservation agriculture to improve soil health and sustain crop yields
in a warming world and emphasizes the potential of conservation
agriculture in long-term food security. The bene

ﬁ

ts of conservation

agriculture for multiple soil functions have been reported

, but the

interactive effects of management practices and climate warming on
the maintenance of soil health and crop productivity have not been
tested before in arable land in situ. Both crop yields and key indicators
of soil health (e.g., SOC and MBC) strengthened over time in response
to warming, but only under conservation agriculture. These bene

ﬁ

cial

responses were tightly linked to soil fungal richness and community
composition. In summary, we provide evidence that conservation
agriculture can support greater soil health without compromising crop
yields under long-term warming compared to conventional agriculture
and reveal a key role of the soil microbiome.

The improvement of soil health to deliver resilient

‘

climate-smart

’

farming systems is recognized as a fundamental strategy that is vital to
mitigate and adapt to the adverse effects of climate warming to
maintain global food security

,

52

. We found that conservation

Fig. 4 | Effects of abiotic and biotic factors on winter wheat yield and key
indicators of soil health of 0-5 cm soil depth. a

Individual effect of the model

predictors to winter wheat yield under conservation and conventional agriculture,
respectively. Red, green and orange colors represent microclimate, soil, and
microbial factors, respectively.

b

,

c

Correlations between wheat yield and key

predictors under conservation and conventional agriculture. Solid line in each
panel shows signi

ﬁ

cant model

ﬁ

t using linear mixed-effect regression (

P

< 0.05),

and the shading around the

ﬁ

tted line represents the 95% con

ﬁ

dence intervals (i.e.,

error bands represent slopes ± 95% con

ﬁ

dence intervals).

d

,

e

Correlations between

soil microclimate and microbial diversity and key indicators of soil health at 0

–

5 cm

soil depth under conservation and conventional agriculture. The color denotes the
correlation coef

ﬁ

cient determined by the linear mixed-effects model. Statistical

signi

ﬁ

cance is based on Wald type II

χ

² tests. ST soil temperature, SM soil moisture,

DOC dissolved organic carbon, MBC microbial biomass carbon, SOC soil organic
carbon, TN total nitrogen. Bacteria, Fungi, AMF, Saprogen, and Pathogen indicated
richness of microbial group. F_PC1, F_PC2, B_PC1, and B_PC2 indicated fungal and
bacterial community composition, respectively. All reported

P

values result from

two-sided statistical tests where *

P

< 0.05, **

P

< 0.01, and ***

P

< 0.001. Source data

are provided as a Source Data

ﬁ

le.

Article

https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

6

agriculture improved a suite of soil properties involved in key soil
functions (water in

ﬁ

ltration and storage, carbon and nutrient cycling,

and microbial activity) after eight years of warming (Figs.

5

). Soil C is

considered a principal indicator of soil health and agronomic sus-
tainability due to its impact on physical, chemical and biological
properties

29

,

53

,

54

. Warming can promote plant carbon inputs (includes

root biomass, exudation, and crop resides) to soil, thereby increasing
substrates for the soil microbial community

,

55

. In our study, con-

servation agriculture increased all soil C pools (DOC, MBC, and SOC)
compared to conventional agriculture (Fig.

). Moreover, we observed

positive warming effects on SOC and MBC under conservation agri-
culture that increased linearly with experimental duration (Fig.

i, j),

indicating a long-term advantage of conservation agriculture in sup-
porting microbial activity and contributing to soil carbon accrual

,

18

Reduced soil disturbance under conservation agriculture promotes
soil aggregate formation and stability indicated by MWD and R

0.25

(Fig.

c). Soil aggregate stability is considered a useful indicator of soil

structure that supports multiple soil functions including water trans-
port and storage and the provision of stable microbial habitats con-
ducive to the preferential accumulation of microbial biomass and
necromass formation and further SOC accrual

56

57

. The increased soil

aggregate stability can enhance water conservation and microbial
variables, that directly facilitate nutrient cycling and soil carbon
storage

56

57

. The tighter correlations between soil fungal richness and

community composition, rather than bacteria (Fig.

), suggested soil

fungi may be the major contributor to SOC formation and

accumulation under conservation agriculture. Collectively, conserva-
tion agriculture is a sustainable management and performs better in
adapting climate warming than conventional agriculture in Northern
China Plain. Previous studies found that conservation agriculture
accumulates soil C at the surface rather than the whole soil pro

ﬁ

or even changed distribution of C in the soil pro

ﬁ

le instead of

increasing the total SOC

14

60

. Yet our long-term monitoring only focu-

ses on C accumulation at surface soil (0

–

15 cm) and may overestimate

bene

ﬁ

ts in C sequestration over the whole soil pro

ﬁ

le. The changes of

SOC in the deeper soil pro

ﬁ

les need to be pay more attention in the

future research.

Globally, crop yields under conservation agriculture are estimated

to be 2.5% less than those of conventional agriculture

, but we did not

observe reductions in wheat or maize under conservation agriculture
in either ambient or warming conditions (Fig.

; Supplementary Fig. 1).

Previous studies in the tropics have reported warming decreased crop
yields

,

25

. We found warming increased wheat yields by 9.3% and 11.2%

under conservation and conventional agriculture (Fig.

a), respec-

tively, on temperate semi-arid climate of the North China Plain. Here,
warming extends the growing season allowing earlier planting and
later harvests, and can reduce cold injury and frost damage in
seedlings

51

61

, which directly improves crop growth and productivity

61

In accordance with predictions that crop yields would be enhanced by
warming in middle-to-high latitude regions

,

25

, we observed a positive

relationship between wheat yields and soil temperature under con-
ventional agriculture (Fig.

a). By comparison, increased wheat yields

under conservation agriculture and warming were most strongly
associated with improved soil microbial quality indicated by microbial
biomass carbon (MBC). Positive correlations between crop pro-
ductivity and MBC are reported

62

63

because the microbial biomass is

not only a labile carbon pool but also a nutrient reservoir

64

65

. The soil

microenvironment (soil and temperature) was also relatively impor-
tant for wheat yields under conservation agriculture with warming
(Fig.

a, b) because no tillage and residue retention moderate soil

temperature and retain soil moisture (Fig.

). Importantly, we also

observed that the warming-induced positive effects on wheat yield
strengthened with time (Fig.

b). Warming had no effect on maize

yields regardless of management type (Supplementary Fig. 1); the
maize growing season is in summer (June

–

September) and C4 phy-

siology is adapted to warmer temperatures and drier conditions

. The

results for wheat emphasize the vital role of soil health in reducing the
sensitivity of production of this key cereal crop to long-term changes
in climate and reducing climate-driven yield variability

66

. In con-

sideration of undifferentiated wheat yield and higher maize yield
compared to conventional agriculture both under ambient and
warming conditions, we assumed that conservation agriculture per-
formed better in productivity in a warmer world.

Soil microbiota are prominent actors in SOC accrual, decom-

position and nutrient cycling

67

70

, and consequently strongly in

ﬂ

uence

agroecosystem services

15

,

71

, so it imperative to assess their response to

long-term warming in situ. Reduced soil biodiversity is reported in
some natural ecosystems under warming, mainly due to environ-
mental

ﬁ

ltration by temperature and soil moisture reduction

,

We observed a reduction of total fungal richness, but not of bacteria, in
soil from the 0

–

5 cm depth under conservation agriculture (Fig.

;

Supplementary Fig. 6), corresponding to previous studies showing
greater sensitivity of fungi to warming compared to bacteria

74

75

. The

decrease of fungal richness was predominantly a consequence of a
decrease in saprogen richness under conservation agriculture with
warming (Fig.

; Supplementary Fig. 6). Less saprogen richness may be

linked to slower rates of organic matter decomposition

76

that con-

tributes to SOC accrual in conservation agriculture under warming
(Fig.

), that supports yield increase through the net effect on soil

health (Fig.

a, b). Soil AMF can enhance plant nutrient uptake and

reduce plant stress

71

, and were more diverse under conservation

Fig. 5 | Conceptual model illustrating shifts of soil health, microbial diversity,
and crop yield under conservation agriculture response to warming.

Experi-

mental warming triggered shifts in soil fungal richness and community composi-
tion and resulted in an improved soil health under conservation agriculture,
including increased water in

ﬁ

ltration and storage, carbon and nutrient cycling, and

microbial activity. The improvement in soil health and shifts in soil fungal diversity
contributed to higher crop yields under conservation agriculture. The up or down
arrows showed increased or decreased soil health indicators response to warming
under conservation agriculture. The linear trends indicated warming effects on
crop yields and soil health indicators over time under conservation agriculture.
MWD, mean weight diameter; R

0.25

, aggregate content with particle size larger than

0.25 mm; DOC dissolved organic carbon, SOC soil organic carbon, NO

3

−

nitrate, AK

available potassium, MBC microbial biomass carbon, MBN microbial biomass
nitrogen. The soil microbiome drawing elements were produced using

ﬁ

gdraw.com.

Article

https://doi.org/10.1038/s41467-024-53169-6

| (2024) 15:8785

7

agriculture with warming (Supplementary Table 1). Soil-borne plant
pathogens were less diverse under conservation agriculture with
warming, providing further advantages for crop production and dis-
ease management

,

28

,

41

. Overall, the direct and indirect effects of

conservation agriculture on the fungal community and plant patho-
gens were related to enhanced crops yield and soil health.

In summary, this study provides empirical evidence for the

potential bene

ﬁ

ts of conservation agriculture for long-term sustain-

able food production because improved soil health improves resi-
lience to the effects of climate warming through its effects on physical,
chemical and biological soil properties. However, we recognize that
local climatic conditions are an important driver of soil health and crop
yield

and careful regional assessments are needed when considering

the potential consequences of adopting conservation agriculture

We propose that our

ﬁ

ndings may be generalized to other regions

where water does not limit productivity (e.g., irrigated regions). As
illustrated in Fig.

5

, the combination of conservation agriculture and

experimental warming for eight years on the temperate semi-arid cli-
mate of the North China Plain stimulated an increase in soil health
indicators indicating improved water in

ﬁ

ltration and storage (soil

aggregate stability), carbon and nutrient cycling, and microbial activ-
ity. The improvement in soil health and shifts in soil fungal diversity
(less saprogen richness, increased AMF and less plant pathogens)
supported similar crop yields to conventional agriculture. These

ﬁ

ndings emphasize the potential cumulative bene

ﬁ

ts of conservation

agriculture with time and strengthen the evidence for conservation
agriculture as

‘

climate-smart

’

management tool to adapt to climate

warming and ensure good security by improving soil health.

Methods

Study sites

This study is based on a long-term climate change

ﬁ

eld trial located at

North China Plain at Yucheng Comprehensive Experiment Station of
Chinese Academy of Science (36° 50

’

N, 116° 34

’

E, elevation is 20 m).

The study region has a temperate semi-arid climate with an annual
mean temperature of 13.6 °C, and annual mean precipitation of
575 mm with 70% occurring between June and September. The soil
type of this site is Calcaric Fluvisol (FAO-UNESCO system) with typical
soil texture 12% sand, 66% silt, 22% clay, and a mean pH of 7.1. The
experiment was conducted at a crop rotation system (winter wheat
(

Triticum aestivum

L.)-summer maize (

Zea mays

L.)) since 2010.

Experimental design and soil sampling

The system included four treatments: conventional agriculture with
and without warming (Conven-Warm and Conven-Amb), conservation
agriculture with and without warming (Conserv-Warm and Conserv-
Amb). A randomized complete block design randomized with four
replicates was employed. The warmed soils (+2 °C) were continuously
heated (since February, 2010) using an MSR-2420 infrared heater
(Kalglo Electronics Inc, Bethlehem, PA, USA) suspended approximately
3 m above the ground to achieve a surface soil warming of 2 °C, which
is predicted by IPCC greenhouse gas scenarios rates for northern
China

51

. The control plots (i.e., without warming) were treated with a

‘

dummy

’

infrared heater to simulate the shading effects of the heaters.

There was a 5 m border between adjacent blocks and at least 10 m
between the plots to avoid heating the control plots by the infrared
radiators.

The size of each plot was 2 m × 2 m. Winter wheat was seeded

between 10 and 15 October and harvested during the

ﬁ

rst 10 days of

June. Then summer maize was seeded 5 days later and harvested
during the

ﬁ

rst 10 days of October. After harvest, in the conventional

agriculture treatment, the residues were removed and the soil was
cultivated with a rotary tiller annually. In the conservation agriculture
treatment, all residues were chopped to approximately 5 cm in length
and retained on the soil surface, and adopted no tillage. The

conventional and conservation agriculture treatments had the same
total

N

application rate, but part of the

N

application was from dif-

ferent sources. The total

N

application for conventional agriculture

and conservation agriculture treatments in winter wheat growing
seasons was 285 kg N ha

−

1

yr

−

1

following optimal application of

fertilization

77

78

. For conservation agriculture, the

N

input was

112.5 kg ha

−

1

of mineral fertilizer, 124.5 kg ha

−

1

of urea, and 48 kg ha

−

1

residue N. For conventional agriculture, the N input was 112.5 kg ha

−

1

of

mineral fertilizer, and 172.5 kg ha

−

1

of urea. The total N application for

conventional agriculture and conservation agriculture in summer
maize growing seasons was 207 kg N ha

−

1

yr

−

1

. For conservation agri-

culture, the N input was 175 kg ha

−

1

of urea and 32 kg ha

−

1

residue N. For

conventional agriculture, the

N

input was 207 kg ha

−

1

of urea. All other

management procedures were the same for conventional agriculture
and conservation agriculture.

Three composite soil samples from 0

–

5 and 5

–

15 cm soil depths

were collected for each plot after harvest of winter wheat from 2010 to
2019. Composite samples were collected by hand augur consisting of

ﬁ

ve randomly selected soil cores in each plot, then mixed together to

make a composite sample. All samples were passed through a 2 mm
sieve for subsequent analysis. Soil temperature (ST) and volumetric
soil moisture (SM) at 0

–

15 cm depth was monitored by PT100 ther-

mocouples and FDS100 soil moisture sensors (Unism Technologies
Incorporated, Beijing), respectively.

Assessing crop productivity

Crop yields were determined through harvest of each plot by hand. At
physiological maturity of each crop, 1 m

2

of crop was harvested for

each plot and the sample was threshed using a static machine. Crop
yield was measured after air-drying to a constant value. Plot yield was
recalculated on a dry matter basis and the harvested area was used to
determine yield per unit area (t ha

−

1

).

Assessing soil health

Seventeen soil health indicators were measured as variables to proxy
soil physical, chemical, and biological attributes in 2020 to evaluate
cumulative changes after long-term experimental warming. Soil sam-
ples (0

–

5 cm and 5

–

15 cm depth) were collected after the harvest of

winter wheat to measure soil properties including: aggregate mean
weight diameter (MWD), aggregate content with particle size larger
than 0.25 mm (R

0.25

), soil moisture (SM), bulk density (BD), pH, dis-

solved organic carbon (DOC), soil organic carbon (SOC), NO

3

−

-N, NH

4

+

-

N, dissolved organic nitrogen (DON), total nitrogen (TN), available
phosphorus (AP), total phosphorus (TP), available potassium (AK),
total potassium (TK), microbial biomass carbon (MBC) and microbial
biomass nitrogen (MBN). Soil samples (0

–

5 cm and 5

–

15 cm depth)

were collected after harvest of winter wheat to measure soil properties.

Soil aggregate mean weight diameter (MWD) and content with

particle size larger than 0.25 mm (R

0.25

) was obtained using wet siev-

ing. Soil pH was measured using a 1:2.5 (w/v) soil to 0.01 M CaCl

2

ratio

with a glass electrode. Soil bulk density (BD) was obtained from oven
dry mass relative to the sample volume. The subsamples for SOC and
TN analysis were air-dried at room temperature and determined using
elemental analysis (Vario EL III, Elementar, Germany) and Kjeldahl
digestion

79

. The concentration of DOC and dissolved nitrogen (DN)

was measured according to Jones and Willett

80

:

ﬁ

eld-moist soil samples

(equivalent to 15 g oven-dried soil) were extracted with 60 ml of
0.05 mol/L K

2

SO

4

(soil to solution ratio 1:4) for 1 h, and the extract was

passed through a 0.45 mm membrane

ﬁ

lter and analyzed for DOC and

DN using a Multi 3100 N/C TOC analyzer (Analytik, Germany). Soil NH

4

+

and NO

3

−

were determined by extraction with 2 mol L

−

1

KCl. The DON

concentration was calculated as DN minus NH

4

+

-N and NO

3

−

-N content.

Soil TP was measured by colorimetric analysis after digestion with
sulfuric acid and perchloric acid. Soil AP was determined by the Olsen
method. Soil TK and AK were determined by

ﬂ

ame photometer. The

Article

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| (2024) 15:8785

8

content of MBC and MBN was determined according to method of Wu
et al.

81

: fresh soil samples were fumigated with chloroform (48 h) and

subsequent extracted with 0.5 M K

2

SO

4

(soil to solution ratio 1:4) and

organic carbon and nitrogen in the extractant were measured using an
elemental analyzer (Vario PYRO Cube, Hanau, Germany).

We used the Cornell Soil Health Assessment (CSHA) scoring

method to calculate soil health scores

82

. The total data set, including

17 soil indicators (physical attributes: MWD, R

0.25

, SM, BD; chemical

attributes: soil pH, SOC, DOC, TN, DON, NH

4

+

-N, NO

3

−

-N, AP, TP, AK,

TK; biological attributes: MBC and MBN), were normalized as indivi-
dual CSHA scores

53

82

. The weighting value of individual soil indicators

was based on PCA of all soil indicators (Supplementary Fig. 2), repre-
senting the sum of the eigenvectors derived from the

ﬁ

rst three prin-

cipal components, which were selected based on Kaiser

’

s cut-off

(eigenvalues > 1). These

ﬁ

rst three principal components cumulatively

accounted for over 70% of variance, capturing most of the variation
among the soil indicators. The overall soil health score (%) was com-
puted as a weighted average of all individual CSHA scores as
follows

53

82

:

Soil health score

=

A

1

×

w

1

+

A

2

×

w

2

+

A

n

×

w

n

w

1

+

w

2

+

w

n

ð

1

Þ

where

A

is the CSHA score for each individual soil indicator, and

w

is

the weighting value of the soil indicators (Supplementary Fig. 2).

Amplicon sequencing and soil biodiversity

To discern whether climate warming and management practices affect
soil bacterial and fungal diversity, soil DNA was extracted from 0.25 g
soil with PowerSoil Isolation kit (MoBio Laboratories, Carlsbad, CA,
USA) following the modi

ﬁ

ed manufacturer

’

s recommendations. DNA

concentrations were quality checked (NanoDrop One; Thermo Fisher
Scienti

ﬁ

c, Waltham, MA) and quanti

ﬁ

ed (PicoGreen assay; Quant-iT

™

PicoGreen® dsDNA Reagent, Life Technologies). Finally, all DNA sam-
ples were stored at

−

80 °C until sequencing analysis.

The library construction and sequencing of the 16S rRNA gene and

ITS gene were performed. The universal primer sets, 515 F (5

’

-

GTGCCAGCMGCCGCGC-3

’

)

and

907 R

(5

′

-CCGTCAATTCMTT-

TRAGTTT-3

′

) targeting the V4-V5 hypervariable regions of the bacterial

16S rRNA gene, and gITS7F (5

’

-GTGARTCATCGARTCTTTG-3

’

) and

ITS4R (5

’

-TCCTCCGCTTATTGATATGC-3

’

) for the fungal IT, were used

in this study. After PCR and puri

ﬁ

cation, a DNA library was constructed

and run on an Illumina Hiseq platform at MagiGene Biotechnology Co.,
Ltd. (Guangzhou, China).

The raw sequence data were processed with the USEARCH (ver-

sion 11.0.667)

83

software for quality

ﬁ

ltering and assembling of pair-

end reads. Strict quality control steps were applied to the sequencing
data. First, assembled contigs without exact match to one of the bar-
codes sets or primers (degenerate bases were not taken into con-
sideration) were discarded. Subsequently, the remaining sequences
were clustered into high accuracy exact amplicon sequence variants
(ASVs) with the UNOISE

84

. Singletons that found only once across all

samples were removed from subsequent analyses. Taxonomic classi-

ﬁ

cation of each ASV of bacteria and fungi was determined using the

Ribosomal Database Project (RDP) classi

ﬁ

er with a con

ﬁ

dence

threshold of 0.5 against the SILVA

85

and the UNITE

86

database,

respectively. ASVs that were not classi

ﬁ

ed into bacteria or fungi were

removed. To normalize samples to the same total read abundance, an
average of 26,000 and 20,000 sequence reads per sample were ran-
domly selected (resampled) for each sample obtained for 16S rRNA
gene and ITS, respectively. Bacterial and fungal richness was calculated
based on the phylogenetic trees and ASV tables using the R package

picante

.

We obtained the relative abundance of potential arbuscular

mycorrhizal mutualists, saprotrophs, and plant pathotrophs from

amplicon sequencing by parsing the soil fungal phylotypes using
FUNGuild database

87

. Fungi representing <1% of the ASVs were not

considered. Only highly probable and probable guilds were used in
these analyses.

Statistical analyses

Linear mixed models (LMMs) were used to assess the effects of
warming and management practices on soil properties, biodiversity,
and crop yield measured repeatedly across eight years

47

. In the LMMs,

warming (0 for ambient temperature and 1 for warming) and man-
agement practices (0 for conservation agriculture and 1 for conven-
tional agriculture) were considered as

ﬁ

xed effects, while sampling

time (year) was termed as random intercept effects (y ~ warming ×
management + (1 | year)). Wald Type II

χ

² tests were used to calculate

the

P

values from the LMMs. The

lme4

R package was used to imple-

ment LMMs. Differences between four treatments (Conven-Amb,
Coven-Warm, Conserv-Amb, and Conserv-Warm) were estimated
through pairwise comparison with estimated marginal means. The

emmeans

R package was use to implement pairwise comparison. Two-

way ANOVA was used to evaluate the effects of warming and man-
agement practices on soil parameters and soil health score. To evalu-
ate the effects size of warming on crop yield, soil health and each soil
indicator, we calculated Cohen

’

s

d

from different management prac-

tices by comparing them against the common control without warm-
ing through

effsize

R package. The temporal changes of warming

effects on each soil indicator and crop yield were estimated through a
linear regression.

Non-metric multidimensional scaling (NMDS) based on Bray-

Curtis dissimilarity and nested permutational multivariate analysis of
variance (nested PERMANOVA) was used to illustrate the effects of
warming and management practices on soil microbial community
composition through

vegan

R package. To link the soil microbial

diversity and community composition to soil health and crop yield,
the correlations were tested using the linear mixed-effects model, in
which sampling year were termed as random intercept effects. The
correlation r was represented by the regression coef

ﬁ

cients in the

LMMs, and Wald type II

χ

² tests were used to calculate the

P

values

from the LMMs. Hierarchical partitioning analysis to calculate the
individual contributions of each predictor was conducted with the

glmm.hp

R package to determine the relative importance of each

environmental factor

88

. All the analyses were performed in

the R 4.3.0.

Reporting summary

Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.

Data availability

The DNA sequences of the 16S rRNA gene and ITS amplicons in this
study have been deposited in the National Center for Biotechnology
Information (NCBI) under project accession numbers

PRJNA996529

https://www.arb-silva.de/

Silva database is available at

. UNITE database

is available at

https://unite.ut.ee/

. Source data are provided with

this paper.

Code availability

The analysis code that supports the

ﬁ

ndings of this study is available

on GitHub (

https://github.com/bio-carbon/warming_soil_health

)

89

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Acknowledgements

This study was supported by the National Natural Science Foundation of
China (grant nos. U23A20158, Z.L.C., and 32071629, J.T.), National Key
R&D Program of China (2023YFD1901500, J.T.), 2115 Talent Development
Program of China Agricultural University and Beijing Advanced Dis-
ciplines, F.S.Z., Z.L.C., J.B.Z., J.T., and the China Postdoctoral Science
Foundation (2022M71339, J.L.T.). We thank the drawing tools provided
by Figdraw.

Author contributions

All authors contributed intellectual input and assistance to this study
and manuscript preparation. T.J., Z.L.C., and M.D.B. designed the origi-
nal concept and experiment strategy. J.L.T. and R.X.H. collected the
data. J.L.T. and J.T. analyzed the data. R.X.H. carried the

ﬁ

eld experi-

ment. J.L.T., J.T., J.A.J.D., G.Y.Z., Y.K., J.B.Z., Z.L.C., F.S.Z., and M.D.B.
drafted the manuscript and all authors involved in critical revisions and
gave

ﬁ

nal approval for publication.

Competing interests

The authors declare no competing interests.

Additional information

Supplementary information

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Supplementary Material available at

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Correspondence

and requests for materials should be addressed to

Jing Tian, Zhenling Cui or Manuel Delgado-Baquerizo.

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Wittwer and the other, anonymous, reviewer(s) for their contribution to
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