Renwick et al. (2021). Long-term crop rotation diversification enhances maize drought resistance through soil organic matter

Environmental Studies Program, Department of Geography, Institute of Ecology and Evolution, University of Oregon, Eugene, OR,
United States of America

5

Department of Biological Sciences, Boise State University, Boise, ID, United States of America

6

Department of Environmental Science, Policy, & Management, University of California, Berkeley, Berkeley, CA,
United States of America

∗

Author to whom any correspondence should be addressed.

E-mail:

agaudin@ucdavis.edu

Keywords:

agroecology, crop diversity, cover crop, no-till, drought, resilience, risk management

Supplementary material for this article is available

online

Abstract

Climate change adaptation requires building agricultural system resilience to warmer, drier
climates. Increasing temporal plant diversity through crop rotation diversification increases yields
of some crops under drought, but its potential to enhance crop drought resistance and the
underlying mechanisms remain unclear. We conducted a drought manipulation experiment using
rainout shelters embedded within a 36-year crop rotation diversity and no-till experiment in a
temperate climate and measured a suite of soil and crop developmental and eco-physiological traits
in the field and laboratory. We show that diversifying maize-soybean rotations with small grain
cereals and cover crops mitigated maize water stress at the leaf and canopy scales and reduced yield
losses to drought by 17.1

±

6.1%, while no-till did not affect maize drought resistance. Path

analysis showed a strong correlation between soil organic matter and lower maize water stress
despite no significant differences in soil organic matter between rotations or tillage treatments.
This positive relationship between soil organic matter and maize water status was not mediated by
higher soil water retention or infiltration as often hypothesized, nor differential depth of root water
uptake as measured with stable isotopes, suggesting that other mechanisms are at play. Crop
rotation diversification is an underappreciated drought management tool to adapt crop production
to climate change through managing for soil organic matter.

1. Introduction

Climate change will magnify the already persist-
ent global challenge of crop yield loss to drought
[

1

,

2

]. Yield sensitivity and cereal production losses

to drought have increased in recent decades, includ-
ing for major global crops such as maize [

Crop diversity has concurrently declined with trends
toward simplification, specialization, and homogen-
ization at both the farm and landscape scales [

5

] and

such specialization has driven increasing sensitivity of
agriculture to climate change in the U.S. Midwest [

6

].

Crop diversification and reduction in soil dis-

turbance (tillage) could provide new opportunities
to harness agroecosystem processes for resilient crop
production [

7

]. Crop diversity lowers risk through

the widely studied portfolio effect whereby differ-
ent crops respond differentially to stress [

8

], but also

possibly through emergent ecosystem properties like
improved functioning and resilience, i.e. greater long-
term stability due to higher resistance to abiotic or
biotic stress and/or faster recovery [

9

]. Conserva-

tion agriculture approaches combining crop rotation,
no-till, and crop residue retention increase rainfed

Environ. Res. Lett.

16

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L L R Renwick

et al

crop yield in dry climates [

10

], implying poten-

tial to also protect crop yield from dry conditions
in temperate climates. Long-term experimental sites
including where this experiment took place show that
diversification of temperate maize-based crop rota-
tions increases yield, improves yield stability, and
helps mitigate effects of weather variability on maize
yield, particularly in hot and dry years and in no-till
systems [

11

,

12

]. However, the soil-plant mechanisms

underlying greater crop drought resistance through
adoption of these ecological intensification strategies
have not been experimentally tested.

While improving drought resistance of agricul-

tural systems has mostly focused on plant-centric
strategies such as physiological differences between
crop species or genotypes [

13

,

14

], cropping system

strategies considering the long-term impacts of agri-
cultural management on soil properties and interac-
tions with severity of plant water stress under drought
have received little attention. Crop rotation diver-
sification can impact multiple soil biological and
physicochemical properties associated with building
soil organic matter [

15

] and improving soil struc-

ture, water infiltration [

] and retention [

with potential benefits for yield stability [

19

,

20

].

Improved soil structure can also affect root develop-
ment and distribution by depth [

21

–

24

], which could

facilitate root foraging and proliferation for water
acquisition [

25

].

We empirically tested how crop rotation diver-

sification increases maize drought resistance and
potential underlying mechanisms. We imposed a sea-
sonal drought along with ambient and supplemen-
ted rainfall controls in maize grown in plots with
36-year management legacies of crop rotation diver-
sification and disturbance previously show in long-
term data to span the range of maize yield in hot
and dry years [

11

] in a major high-yielding maize-

producing region. We measured a suite of soil and
crop developmental and eco-physiological traits in
the field and laboratory to test if maize plants are less
water stressed under drought in diversified rotations
and whether this relationship is mediated by shifts in
soil organic matter and hydraulic properties as widely
assumed [

] and/or by improved root devel-

opment facilitating deeper or shallower plant water
uptake [

25

].

2. Methods

2.1. Long-term crop rotation and tillage trial

The drought experiment was conducted at a long-
term crop rotation and tillage trial established in 1980
at the University of Guelph Elora Research Station,
Ontario, Canada (43

◦

38

′

27

′′

N, 80

◦

28

′

27

′′

W)

[

27

]. The soil is a Woolwich silt loam, weakly to mod-

erately calcareous Typic Hapludalf, and grey-brown
Luvisol with approximately 4% organic matter and
a 2% slope [

27

]. The site has a humid continental

climate with 946 mm of precipitation annually and
88 mm monthly during the May–October growing
season [

28

]. Average daily temperature ranges from

2

◦

C to 20

◦

C during the growing season, with cool

springs and warm to hot summers [

11

].

The long-term trial is arranged as a random-

ized split-plot design with four replications and rota-
tion as the main plot and tillage as the split plot
(16.8

×

6.1 m) [

,

]. The drought experi-

ment was conducted in first-year maize in three 4-
year rotations along a rotation diversity gradient pre-
viously found to span the range of maize yield in hot
and dry years [

11

]: maize-maize-soy-soy (MMSS),

maize-maize-soy-wheat (MMSW), and maize-maize-
oat/red clover-barley/red clover (MMOrcBrc). Maize,
soy, wheat, oat, and barley were managed as cash
crops and red clover was managed as a cover crop
that was drill-seeded with oat or barley and grown
in relay cropping after small grain harvest. Each rota-
tion main plot was split into two randomly assigned
levels of tillage: conventional tillage and no tillage.
Conventional tillage consisted of moldboard plowing
in the fall and secondary spring cultivation prior to
crop seeding. Prior to initiation of no-till in 2002, no-
till plots received reduced tillage (1980–2001) which
comprised fall chisel plowing in most crops and the
same secondary spring cultivation as in conventional
tillage [

,

]. Fertility, pests, and weeds were

managed conventionally to be non-limiting to crop
yields in all phases of the rotation cycle as described
previously for this long-term trial [

30

,

31

]. During

the drought experiment we report here all maize plots
were fertilized with 11 kg N ha

−

1

, 45 kg P ha

−

1

,

and 35 kg K ha

−

1

as 6–24-6 and 5–20-20 as a starter

and 150 kg N ha

−

1

as UAN as a sidedress based on

pre-sidedress soil nitrate testing. Crop cultivars for
each crop changed over time to reflect increases in
yield potential and typical practices of the region,
with maize DKC 39–97 seeded 12 May 2016 at a rate
of 78 000 seeds ha

−

1

and a row distance of 76.2 cm

(30 inches) in this study period.

2.2. Manipulative drought experiment

In 2016, 36 years after long-term trial establishment,
we modified the experimental design to a split-split-
plot to accommodate a manipulative water experi-
ment with three replications of each rotation-tillage-
water treatment combination. Each rotation-tillage
combination was split and semi-randomly assigned
one of three levels of water inputs: drought, ambient
rainfall, or ambient rainfall plus supplemental irriga-
tion (supplementary information).

A seasonal drought was imposed in the field

using below-canopy rainout shelters inserted between
maize rows and elevated 30–40 cm above the soil sur-
face on wooden stakes (figure S1 (available online
at

stacks.iop.org/ERL/16/084067/mmedia

), supple-

mentary information). All measurements were con-
ducted in 4.8 m of the center row of the three

2

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L L R Renwick

et al

maize rows where shelters were installed to avoid
edge effects. The shelters were installed 22 d before
the onset of maize anthesis and removed 35 d after-
ward to impose drought stress during flowering, the
maize growth stage most vulnerable to drought [

32

]

(figure S1). The percentage of rainfall intercepted
by rainout shelters was estimated halfway through
the drought imposition period by manually col-
lecting rainfall that reached the soil surface both
between plant rows and outside plots and calculat-
ing canopy throughfall and rainout shelter intercep-
tion from water volumes. Irrigation volume in control
plots was based on maize evapotranspiration estim-
ates (supplementary information). A suite of crop
developmental and ecophysiological traits and soil
properties were measured in first-year maize for all
rotations during the drought imposition period in
2016, except for infiltration and soil organic matter
which were measured on the same rotation phase,
first-year maize, in 2018 as noted in the following
sections.

2.3. Plant growth, phenology, physiology, and yield

Maize phenology and growth were monitored dur-
ing maize vegetative and reproductive growth stages
as follows. Vegetative growth stage (leaf number) and
height were measured 11–12 d after the onset of
drought. Leaf Area Index (LAI) was measured 20 d
after the onset of drought using a SS1 SunScan Can-
opy Analysis System (Delta-T Devices, Cambridge,
United Kingdom). Maize shoot biomass was meas-
ured at 34–41 d after onset of drought and the end
of the drought imposition. Maize shoot biomass was
measured by destructively sampling three plants per
plot, which were oven-dried at 80

◦

C for 2 d and

weighed, then ground. For the latter date, biomass N
concentration (% dry weight) was measured by com-
bustion at SGS Canada Inc., Agriculture and Food
(Guelph, ON, Canada).

We monitored three metrics of midday maize

water status: xylem water potential (Scholander
pressure chamber, Model 1000, PMS Instruments,
Albany, OR, USA), stomatal conductance (g

s

) (SC-1

Leaf Porometer, METER Group, USA/Germany), and
canopy temperature (FLIR thermal imaging camera
T420bx), on three separate days during or within 2 d
of maize anthesis (figure S1, supplementary inform-
ation). Midday xylem water potential was measured
using a Scholander pressure chamber (Model 1000,
PMS Instruments, Albany, OR, USA). One shaded
leaf per plot, at the height of the lowest non-senesced
leaf in drought plots, was enclosed in a reflective
aluminum-coated plastic bag for at least 60 min
before removal from the plant and measurement.
Stomatal conductance was measured using an SC-1
Leaf Porometer (METER Group, USA/Germany) on
five plants per plot on a sunlight-acclimated, second-
uppermost fully expanded leaf at midday. Canopy
temperature at midday was estimated via whole-plot

thermal imaging using a FLIR thermal imaging cam-
era (T420bx) that was elevated by a pole 2 m above the
crop canopy, centered on the sampling row, and cap-
tured its entire length excluding edges (4.8 m). Images
were analyzed in FLIR Tools® software to quantify the
average canopy temperature of the sampling row.

At physiological maturity, grain from all remain-

ing plants per plot was hand-harvested, oven-dried at
80

◦

C for 2 d, and weighed. Reported grain yields were

adjusted to 15.5% moisture content. Drought resist-
ance was calculated as the relative (drought/irrigated)
change in a given response variable for each crop
rotation-tillage treatment replicate. Response ratios
were converted to percent changes for data visualiz-
ation. Less change due to drought indicates greater
drought resistance.

2.4. Soil hydraulic properties

One undisturbed core per plot was taken at the end
of the drought imposition in ambient rainfall plots,
from a depth of 5–10 cm using 250 cm

3

stainless steel

rings to generate soil water retention curves via the
simplified evaporation method (Hyprop, WP4 and
Hyprop Fit software; METER Group, USA/Germany)
(supplementary information). Water retained at field
capacity (FC,

−

33 kPa) and permanent wilting point

(PWP,

−

1500 kPa) was extracted from curves and

available water capacity was calculated as the differ-
ence between FC and PWP. Bulk density was calcu-
lated as the dry soil weight per unit volume of each
of the 250 cm

3

undisturbed cores used for soil mois-

ture retention analysis. Infiltration was estimated in
2018 in first-year maize in the same rotation-tillage
treatment combinations as 2016 but different plots
(each 4-year rotation sequence at the long-term trial
is duplicated 2 years out of phase such that first-year
maize occurs every 2 years). Field-saturated hydraulic
conductivity (hereafter ‘infiltration’) was measured
using an automated dual head SATURO infiltrometer
(METER Group, USA/Germany) with one meas-
urement per plot, which controls for variability in
initial soil moisture by saturating the soil prior to
measurement.

2.5. Soil moisture and organic matter

Prior to drought imposition, soil water potential
sensors (MPS-2, METER Group, USA/Germany)
were installed at 15 cm depth in one block (

n

=

6

per water treatment, one replicate of each rotation-
tillage-water treatment combination), in order to
monitor soil drydown under the drought treatment
but not to characterize water treatment-rotation-
tillage interactions. At 42–49 d after the onset of
drought, one 4.4 cm diameter soil core per plot in
the maize row was taken to a depth of 60 cm (hand
sampler with slide hammer, Giddings Machine Com-
pany, Windsor, CO, USA) and divided into 10 cm
increments (figure S1). Gravimetric water content
was measured by weighing and oven-drying at 60

◦

C

3

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L L R Renwick

et al

to a constant weight. In 2018, one soil core per plot
in the maize row was taken in first-year maize in the
same rotation-tillage treatment combinations as 2016
but different plots (each 4-year rotation sequence
at the long-term trial is duplicated 2 years out of
phase such that first-year maize occurs every 2 years).
Cores (0–60 cm, 4.4 cm diameter) were divided into
20 cm increments (hand sampler with slide hammer,
Giddings Machine Company, Windsor, CO, USA)
and analyzed for soil organic matter (%) measured
as percent loss on ignition at Ward Lab (Kearney,
NE, USA).

2.6. Root distribution and stable isotope plant
water sourcing

Roots length distribution by depth was quanti-
fied 42–49 d after the onset of drought using
the same soil cores as for gravimetric water con-
tent (0–60 cm, 10 cm depth increments). Soil was
washed from roots and roots were scanned and ana-
lyzed using WinRHIZO Pro software (Regent Instru-
ments Inc., Canada) to quantify root length density
(cm root cm

−

3

soil). Plant water sourcing from dif-

ferent soil depths was estimated 34–41 d after onset of
drought using natural abundance of hydrogen stable
isotopes in water extracted via cryogenic vacuum dis-
tillation [

33

] from simultaneously collected soil and

plant samples and analyzed by mass spectrometry
[

34

] (supplementary information). Hydrogen isotope

ratios of the soil and plant water were used to assess
plant water sourcing by soil depth using two meth-
ods. First, the estimated water uptake depth was iden-
tified by plotting isotopic compositions of each plant
sample and average isotopic compositions of each
soil depth within a rotation-tillage-water treatment
combination in dual-isotope space and graphically
identifying the soil depth with the most similar iso-
topic composition to each plant xylem sample [

35

].

Second, the proportional contribution of each soil
depth to plant water was determined by averaging
hydrogen isotopic composition for plant and soil
depth replicates for each rotation-tillage-water treat-
ment combination and generating full distributions
of the possible proportional contribution of each soil
depth to plant water using the stable isotope mixing
model IsoSource with source increment set to 1% and
tolerance to 0.05 [

36

].

2.7. Univariate statistical analysis

All statistical analyses were carried out in R 3.6.2. The
lmer() command of the lmerTest package was used
for linear mixed-effects model and the lm() com-
mand of the stats package was used in cases of linear
fixed-effects model when all random effects accoun-
ted for zero variance. Analysis of variance (ANOVA)
with fixed effects (rotation, tillage, water level, and
soil depth where applicable), random effects (block,
main plot, split-plot, and split-split plot where applic-
able) and all interaction terms was used to test

the effect of treatments on plant traits and gra-
vimetric water content. The fixed effect of water
level, random effect of the split-split plot, and cor-
responding interactions were removed to test the
effects of crop rotation and tillage on soil prop-
erties and drought resistance of plant traits. The
assumptions of homogeneity of variance and normal-
ity of the residuals were assessed graphically using
diagnostic plots and quantitatively. Response vari-
ables were transformed as necessary to meet assump-
tions. ANOVA was conducted using the anova()
command of the

stats

package and means compar-

isons were conducted using the CLD() command of
the emmeans package (version 1.4.3.01), both using
Satterthwaite’s method to approximate the degrees
of freedom. In cases of multiple comparisons, the
CLD() command used the Tukey method of

p

-value

adjustment to compare a family of multiple estimates
(alpha

=

0.05).

2.8. Path analysis

We built

a priori

path analysis models based on cur-

rent knowledge and hypotheses representing rela-
tionships between soil organic matter, soil hydraulic
properties, depth of water uptake, plant water stress,
and yield (figure S2). As visualized in figure S2, we
expected increased organic matter to increase water
retention at FC, PWP (a), and/or available water
capacity (b), and/or water infiltration (saturated
hydraulic conductivity), and/or shift the depth of root
water uptake, through the effects of organic matter
on soil structure and root proliferation [

,

].

We expected that improved soil hydraulic proper-
ties and/or shifts in root water uptake depth would
increase plant water status and yield. We then tested
data fit to the

a priori

model using the lavaan pack-

age (v. 0.6–6). All data were standardized by center-
ing and scaling to generate z-scores and a plant water
status index was calculated (supplementary inform-
ation). Following model fitting using the sem()
command, non-significant relationships (

p

> 0.1)

were iteratively removed and model fit was evalu-
ated using the comparative fit index (CFI) (>0.95),
root mean square error of approximation (RMSEA)
(

p

< 0.05), standardized root mean square residual

(SRMR) (

p

< 0.05), and Akaike’s information criteria

(AIC) [

37

,

38

].

3. Results

3.1. Dynamics and severity of drought stress

The imposed drought spanned maize flowering by
1 month on either side. On average, the drought
treatment using rainout shelters intercepted an estim-
ated 56% of rainfall and reduced soil moisture matric
potentials across the drought period by 670 kPa and
220 kPa compared to the irrigated and ambient rain-
fall controls, respectively (figures S1 and S3).

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et al

Figure 1.

Effects of rotation, water level, and tillage on maize productivity and response to water stress: (a) drought resistance of

maize grain yield, (b) maize grain yield at 15.5% moisture, (d) drought resistance of stomatal conductance (g

s

), and (d) canopy

temperature. Drought resistance of maize grain yield and g

s

are defined as the drought-induced change in yield or g

s

as a percent

of the irrigated control. Crop rotation abbreviations: MMSS

=

maize-maize-soy-soy, MMSW

=

maize-maize-soy-wheat,

MMOrcBrc

=

maize-maize-oat/red clover-barley/red clover. Treatment factor abbreviations: R

=

rotation, W

=

water,

T

=

tillage. Asterisks indicate significance of treatment effects from ANOVA (

∗∗∗

p

< 0.001,

∗∗

p

< 0.01,

∗

p

< 0.05, . < 0.1).

Rotation means sharing the same letter or not lettered are not significantly different within a water and/or tillage level
(alpha

=

0.05). Error bars are standard error,

n

=

3 (b) and (c) or

n

=

6 (a), (d).

3.2. Crop rotation diversification maintains plant
water status and yield under drought better than
no-till

Crop rotation diversification improved maize yield
drought resistance (better maintained yield under
drought) (figure

1

(a)) (rotation

p

=

0.037). Drought

reduced maize yield by 53% relative to irrigated con-
ditions in the lowest diversity rotation versus 36% in
the most diverse rotation. No-till did not affect yield
drought resistance (

p

=

0.678) nor rotation diversi-

fication benefits for yield drought resistance (rotation
x tillage

p

=

0.737). Higher drought resistance with

rotation diversification did not penalize productiv-
ity under ambient rainfall or supplemental irrigation
conditions. Rotation diversification increased maize
yield relative to the two-crop maize-soybean rotation
across water levels, by 16%, 27%, and 56% under
irrigated, ambient rainfall, and drought conditions,
respectively (figure

1

(b), rotation

p

< 0.001).

Crop rotation diversification enhanced maize

physiological drought resistance (better maintained
plant water status under drought) (figures

1

(c)–(d))

for two of three measures of plant water stress: sto-
matal conductance and canopy temperature. Maize
in diversified rotations partially maintained stomatal
conductance under drought relative to irrigated con-
ditions in tilled systems (figure

1

(c), rotation

×

tillage

p

=

0.026). In the two diversified rotations, the maize

canopy maintained its temperature despite decreas-
ing water inputs at temperatures similar to that of
irrigated maize across all rotations. In the lowest
diversity rotation, maize canopy temperature became
progressively hotter (more stressed) as water inputs
decreased (figure

1

(d), rotation

p

=

0.073, water

p

=

0.085). Rotation diversification did not affect

xylem water potential (whole-plant water status),
which was higher (less stressed) with no-till but not

with rotation diversification (rotation

p

=

0.830, till-

age

p

=

0.018, water

p

< 0.001) (figure S4). Higher

maize drought resistance with rotation diversifica-
tion was observed despite these plants being taller
with greater canopy development (higher LAI) (LAI
rotation

p

=

0.030; height rotation

p

=

0.012, rota-

tion

×

water

p

=

0.031, water

×

tillage

p

=

0.002)

(figure S5(a) and (d)). Rotation diversification did
not affect shoot biomass shortly after flowering but
increased it at the end of the drought imposition
period under drought (rotation

p

=

0.071, water

p

=

0.012, date

p

< 0.001). At 11–12 d after the onset

of drought, maize vegetative growth stage was more
advanced in the diversified rotation under drought
and no-till ambient rainfall treatments but sim-
ilar regardless of rotation diversification under irrig-
ated and tilled ambient rainfall treatments (rotation

p

=

0.008, rotation

×

water

p

=

0.027) (figure S5(b)).

No-till tended to reduce plant height (

p

=

0.051, till-

age

×

water

p

=

0.002), leaf number (

p

< 0.001), LAI

(

p

=

0.018), and plant population (

p

=

0.028) but did

not affect shoot biomass (

p

=

0.438, figures S5 and

S6). Rotation diversification improved shoot nitro-
gen concentration (water

p

< 0.001, rotation

×

water

p

=

0.043) while increasing maize shoot biomass,

and better maintained shoot nitrogen concentration
under drought (rotation

p

=

0.041) (figure S7),

despite nitrogen application rates across all treat-
ments being designed to be non-limiting to yield (see
section

2

).

3.3. Crop rotation diversification increases soil
moisture with mixed effects on soil water retention
and infiltration

Some soil properties that are often hypothes-
ized to underlie plant drought resistance did not
uniformly improve with crop rotation diversification.

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L L R Renwick

et al

Figure 2.

Effects of rotation and tillage on soil hydraulic properties: (a) soil organic matter, (b) bulk density (5–10 cm), water

retained at (c) field capacity and (d) permanent wilting point (5–10 cm), (e) available water capacity (5–10 cm), and
(f) field-saturated hydraulic conductivity. (g) Effect of rotation, tillage, and water level on gravimetric water content during
maize grain filling (42–49 d after the onset of drought). Crop rotation abbreviations: MMSS

=

maize-maize-soy-soy,

MMSW

=

maize-maize-soy-wheat, MMOrcBrc

=

maize-maize-oat/red clover-barley/red clover. Treatment factor abbreviations:

R

=

rotation, W

=

water, T

=

tillage. Asterisks indicate significance of treatment effects from ANOVA (

∗∗∗

p

< 0.001,

∗∗

p

< 0.01,

∗

p

< 0.05, <0.1). Rotation means sharing the same letter or not lettered are not significantly different within a tillage level and/or

depth (alpha

=

0.05). Error bars are standard error,

n

=

3 (a), (b), (e) or

n

=

6 (c), (d) and (f), (g).

Soil organic matter (%) was highest in the top-
soil (0–20 cm) (depth

p

< 0.001) and tended to

increase with both rotation diversification and no-
till but these effects were statistically nonsignificant
(figure

2

(a), rotation

p

=

0.146, tillage

p

=

0.238).

Soil bulk density, an indicator of soil compaction,
was affected by the interaction of rotation diversific-
ation and tillage (rotation

×

tillage

p

=

0.012), with

lower bulk density (lower compaction) in diverse
rotations in no-till systems but no effect of rota-
tion diversification in tilled systems (figure

2

(b)).

Rotation diversification increased water retention at
field capacity (rotation

p

=

0.080, figure

2

(c)) with

a similar trend at permanent wilting point (rota-
tion

p

=

0.320, figure

2

(d)). Available water capacity

was affected by both rotation diversification and till-
age (rotation

×

tillage

p

=

0.044) (figure

2

(e)) and

was highest in the most diverse rotations under till-
age but did not vary between rotations under no-
till. Field-saturated hydraulic conductivity, a meas-
ure of water infiltration, in the two diverse rota-
tions was not significantly different from infiltra-
tion in the low diversity rotation, but was signi-
ficantly higher in the intermediate diversity rota-
tion than in the most diverse rotation (

p

=

0.020,

figure

2

(f)). Gravimetric water content 42–49 d after

the onset of drought was interactively affected by
rotation (

p

=

0.003), water treatment (

p

=

0.071),

and soil depth (

p

=

0.035, water

×

depth

p

=

0.038)

(figure

2

(g)) and tended to increase with rotation

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L L R Renwick

et al

diversification, though this effect was not statistic-
ally significant across all soil depths and treatment
combinations.

3.4. Tillage and drought impact root distribution
and depth of water uptake

We found that root traits hypothesized to under-
lie plant drought resistance were not affected by
crop rotation diversification. We assessed plant water
sourcing by soil depth using natural abundance of
hydrogen stable isotopes and sampled for root dis-
tribution by soil depth at 34–41 d and 42–49 d after
onset of drought, respectively. The estimated depth
of plant water uptake, the soil depth with the most
similar isotopic composition to each plant xylem
sample (see section

2

), was most strongly affected by

water treatment (

p

< 0.001): maize obtained water

from increasingly deeper depths along a decreas-
ing water gradient (figure

3

(a)) and slightly deeper

uptake depths in no-till (tillage

p

=

0.050). Full dis-

tributions of the possible proportional contribution
of each soil depth to plant water from the stable iso-
tope mixing model IsoSource show a similar pattern
to main uptake depth results, with a greater con-
tribution of shallow depths under irrigated condi-
tions and a greater contribution of deeper soil lay-
ers under drought and ambient rainfall (figures S8
and S9). Water sourcing shifted from the topsoil to
the subsoil under drought, but root length prolifer-
ated in the topsoil (figures

3

(a) and (b)). Maize root

length density (cm root cm

−

3

soil) was highest in

the topsoil (0–10 cm) and was interactively affected
by water treatment (

p

=

0.071), depth (

p

< 0.001,

water

×

depth

p

< 0.001), and tillage (tillage

×

depth

p

=

0.096) (figure

3

(b)). Root length density under

no-till was more strongly concentrated in the 0–10 cm
soil layer whereas under tillage root length density
declined more gradually from the 0–10 cm to 20–
30 cm soil layers (figure

3

(b)).

3.5. Soil organic matter drives higher maize
drought resistance but mechanisms are not fully
resolved

We found that soil organic matter strongly correl-
ated with lower plant water stress and higher yield
across treatments (figure

4

). However, the positive

relationship between soil organic matter and maize
water status was not mediated the mechanisms of soil
water provisioning or root water capture tested in this
experiment. Soil hydraulic properties that are widely
thought to underlie soil-mediated crop drought res-
istance (water retention at field capacity and/or per-
manent wilting point, available water capacity, infilt-
ration) did not drive soil organic matter’s benefit for
plant water status, nor did shoot nitrogen concen-
tration (path models with inferior fit and nonsig-
nificant variables and paths not shown, see figure
S2). An alternative mechanism tested, deeper water
uptake by roots, was not associated with higher soil

Figure 3.

Effects of rotation, tillage, and water level on

(a) estimated depth of plant water sourcing and (b) root
length density by soil depth. The estimated depth of plant
water uptake corresponds to the soil depth with the most
similar isotopic composition to each plant xylem sample.
Crop rotation abbreviations: MMSS

=

maize-maize-

soy-soy, MMSW

=

maize-maize-soy-wheat, MMOrcBrc

=

maize-maize-oat/red clover-barley/red clover. Treatment
factor abbreviations: R

=

rotation, W

=

water, T

=

tillage.

Asterisks indicate significance of treatment effects from
ANOVA (

∗∗∗

p

< 0.001,

∗∗

p

< 0.01,

∗

p

< 0.05, <0.1).

Rotation means sharing the same letter or not lettered are
not significantly different within a water and tillage level
(alpha

=

0.05). Error bars are standard error,

n

=

3 (

n

=

2

for panel a irrigated no-till MMOrcBrc).

organic matter and correlated negatively with plant
water status and yield.

4. Discussion

Our results show that long-term diversification of
aboveground plant communities through diversified
crop rotations enhances crop performance and yield
under drought likely through a belowground man-
agement legacy. We found that diversifying com-
mon maize-soybean rotations with small grain cer-
eals and cover crops improves maize yield and
physiological drought resistance and that soil organic
matter is associated with lower maize water stress
(figures

1

and

4

). Our findings corroborate strong

7

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16

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L L R Renwick

et al

Figure 4.

Final path analysis model of significant drivers of plant water stress, showing direct and indirect effects of soil organic

matter on maize water stress and yield. Soil organic matter is in topsoil (0–20 cm); plant water status index is a function of
stomatal conductance, xylem water potential, and canopy temperature measurements within one week of maize flowering, with
better water status indicating less water stress; plant water uptake depth is the estimated soil depth from which the plant sources
water; all data are z-scores (see section

2

for data processing and analysis). Standardized path coefficients are indicated for each

significant relationship (asterisks indicate significance:

∗∗∗

p

< 0.001,

∗∗

p

< 0.01,

∗

p

< 0.05, <0.1). Black, red, and grey arrows

indicate positive, negative, and nonsignificant effects, respectively. Arrow widths are proportional to standardized coefficients.

n

=

49. Model fit criteria: SRMR

=

0.008, RMSEA

=

0.000–0.249 (90% confidence interval), CFI

=

1.000.

benefits of rotation diversification for maize in pre-
sumed and experimental drought years including in
long-term data from the experimental site where this
experiment took place [

,

] with soil and

crop physiological mechanistic evidence. This work
advances crop diversification as a drought manage-
ment tool not only at the farm or regional scale
through a portfolio effect whereby different crops
respond differently to stress [

–

] but now at

the plant-to-field-scale through improved soil-plant
functioning and plant drought resistance. In the
cooler temperate region where this experiment was
conducted, rotation diversification was a more effect-
ive drought management tool than reducing soil dis-
turbance with no-till, which did not impact drought
resistance of maize yield (figure

1

).

Crop rotation diversification may offer oppor-

tunity to both mitigate and adapt to climate change
through investment in soil organic matter [

43

,

44

],

but linkages between soil organic matter and drought
resistance (figure

4

) are not fully resolved. Rotation

diversification tended to increase soil organic mat-
ter (figure

2

(a)) as found previously in meta-analysis

[

15

] and consistent with trends in soil organic mat-

ter previously reported for these rotations at this

trial [

,

–

]. We provide evidence that field-

scale variation in soil organic matter, likely attribut-
able to management, is associated with lower crop
water stress, in agreement with global and regional
trends that soil organic matter increases crop drought
tolerance [

48

] and reduces crop sensitivity to precipit-

ation variability [

49

] and yield losses and crop insur-

ance payouts under drought [

50

]. However, rota-

tion diversification and higher organic matter did not
consistently increase water infiltration or retention
(figures

2

and

4

), in agreement with recent meta-

analyses but contrary to our expectations and widely
promoted benefits of soil health building manage-
ment and organic matter for soil hydraulic prop-
erties [

51

,

52

]. We also did not find evidence that

deeper water capture by roots [

25

] or higher crop

nitrogen status [

53

] mediate soil organic matter bene-

fits for crop drought resistance (figures

3

and

4

).

Future research should test if soil biological mechan-
isms drive soil organic matter’s benefit for plant water
status, since changes in soil organic matter and bio-
logy are intrinsically linked [

54

] and shifts in the soil

and rhizosphere microbial communities could play
an underappreciated role in influencing crop drought
resistance and productivity [

55

,

56

]. Alternatively,

8

Environ. Res. Lett.

16

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L L R Renwick

et al

increases in soil organic matter and biological activity
may partially ameliorate negative effects of drought
on nitrogen mineralization [

53

] or shifts in soil

organic matter composition may play a role [

47

].

Reduced weed, insect pests, and disease pressure in
diversified rotations [

57

–

60

] may also contribute to

yield gains under drought, but their contribution is
likely small at this site where weeds, insect pests,
and disease are managed to be non-limiting to yield
(see section

2

).

The crop rotation diversification-driven drought

resistance reported here underscores the need
to reconcile breeding- and management-based
approaches for building cropping system drought
resilience. Amidst concerns of reaching a water ceiling
for maize given higher temperature and evapotran-
spiration without gains in rainfall [

61

,

62

], we high-

light the underexploited potential of management-
based approaches for improving plant drought
resistance: rotation diversification increased maize
yield by 56% under drought (figure

1

(b)). Drought-

tolerant maize hybrids increase yield by 5%–7% in
water-limited environments, but the higher tem-
peratures and atmospheric water demand (vapor
pressure deficit) in these environments compared
with our experimentally simulated drought precludes
comparison of yield gains under drought through
breeding versus rotation diversification [

63

,

64

]. Crop

models project increasing value of rotation diver-
sification over time as yield potential increases in
diverse rotations and soil organic matter declines in
low diversity rotations under climate change scen-
arios, causing low diversity rotations to reach a water
ceiling before diversified rotations [

29

]. Integrat-

ing management within breeding programs could
provide synergistic benefits for climate change adapt-
ation, reducing risks of crop failure while enhancing
yield potential under high productivity and stress
conditions [

65

].

Nearly 20% less maize yield lost to drought in

diversified rotations provides a strong rationale to
catalyze adoption and greater research and policy
attention to help shield crop production from
drought. That soil organic matter, rather that plant
traits unique to maize, drives drought resistance
suggests that rotation diversification may benefit
drought resistance of other crops, consistent with
evidence that rotation diversification increases soy-
bean and small grain cereal yields in hot and dry
years [

,

]. Although the mechanisms are not

fully resolved, these results also highlight poten-
tial new levers for wider adoption of diverse rota-
tions, such as integrating management and soil data
including soil organic matter into crop yield risk
and insurance models to improve the accuracy of
crop insurance risk ratings [

50

,

68

,

69

]. Diverse rota-

tions also have multiple co-benefits for agricultural
sustainability including lowering synthetic nitrogen

fertilizer and herbicide use [

59

,

70

], insect pest resist-

ance and damage [

60

], and freshwater toxicity [

71

],

and boosting the disease suppressive potential of the
soil microbiome [

72

].

5. Conclusion

We show that diversification of dominant, low
diversity maize-soy rotations with common small
grain cereals (i.e. wheat, oat, barley) and cover crops,
enhances the climate change adaptation potential of
a major global crop through soil organic matter, des-
pite no significant increase in soil organic matter per
se with diversification. Future research should zoom
in, to understand microbial contributions to plant
drought resistance and capitalize on the potential
of biodiversity and plant-soil feedback for ecological
intensification. It should also scale out, to further test
the potential of crop rotation diversification to reduce
yield risk to drought for maize and other crops and
identify research and policy opportunities to incentiv-
ize rotation diversification for soil health and climate-
smart agriculture.

Data availability statement

The data that support the findings of this study are
available upon reasonable request from the authors.

Acknowledgments

Funding for this research was provided by the
Ontario Ministry of Agriculture, Food and Rural
Affairs and the Grain Farmers of Ontario. This
work was supported by the Agriculture Experi-
ment Station Projects no. CA-D-PLS-2332-H and
the Foundation for Food and Agriculture Research.
We thank the faculty, staff, and students who foun-
ded and have maintained and supported the long-
term trial and acknowledge the particular contri-
butions of Henk Wichers, Ramesh Eerpina, Han-
nah Toews, Michael March, Yixuan Wan, Rebekah
Velasco, Vivian Tieu, and Cameron Ogilvie to trial
management and data collection for the work repor-
ted here. We also thank Leonel Sternberg for host-
ing and training LR in the stable isotope component
of this work. This material is based upon work sup-
ported by the National Science Foundation Gradu-
ate Research Fellowship Program under Grant No.
1650042 to LR. Any opinions, findings, and conclu-
sions or recommendations expressed in this mater-
ial are those of the author(s) and do not necessar-
ily reflect the views of the National Science Found-
ation. LR’s final work on this manuscript was carried
out while funded by a Fondeyct postdoctoral grant
(ANID Fondecyt de Postdoctorado 2021 N

◦

3210036,

Chile).

9

Environ. Res. Lett.

16

(2021) 084067

L L R Renwick

et al

Author contributions

W D maintained the long-term experimental site
where this study took place. W D and A G conceived
and designed the experiment, with methods input
from L R, M G, L S, and T M, and acquired the
required funding. L R established the drought exper-
iment and performed field sampling and laboratory
analyses in consultation with A G and W D and ana-
lyzed the data in consultation with A G, W D, and T B.
L R led writing the manuscript in close consultation
with AG and it was critically revised by T B, M G, W D,
L S, and T M. All authors contributed to the article
and approved the submitted version.

Conflict of interest

The authors declare no competing financial interests.

ORCID iDs

Leah L R Renwick



https://orcid.org/0000-0002-

8669-5661

Lucas Silva



https://orcid.org/0000-0002-4838-

327X

Toby Maxwell



https://orcid.org/0000-0001-5171-

0705

Amélie C M Gaudin



https://orcid.org/0000-0003-

4007-9991

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