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Covering approximately 40% of land surfaces, grasslands provide critical ecosystem services that rely on soil organisms. However, the global determinants of soil biodiversity and functioning remain underexplored. In this study, we investigate the drivers of soil microbial and detritivore activity in grasslands across a wide range of climatic conditions on five continents. We apply standardized treatments of nutrient addition and herbivore reduction, allowing us to disentangle the regional and local drivers of soil organism activity. We use structural equation modeling to assess the direct and indirect effects of local and regional drivers on soil biological activities. Microbial and detritivore activities are positively correlated across global grasslands. These correlations are shaped more by global climatic factors than by local treatments, with annual precipitation and soil water content explaining the majority of the variation. Nutrient addition tends to reduce microbial activity by enhancing plant growth, while herbivore reduction typically increases microbial and detritivore activity through increased soil moisture. Our findings emphasize soil moisture as a key driver of soil biological activity, highlighting the potential impacts of climate change, altered grazing pressure, and eutrophication on nutrient cycling and decomposition within grassland ecosystems.
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ARTICLE
Drivers of soil microbial and detritivore activity
across global grasslands
Julia Siebert1,2,28, Marie Sünnemann 1,2,28, Yann Hautier 3, Anita C. Risch4, Jonathan D. Bakker5,
Lori Biederman6, Dana M. Blumenthal7, Elizabeth T. Borer8, Miguel N. Bugalho9, Arthur A. D. Broadbent 10,
Maria C. Caldeira 11, Elsa Cleland12, Kendi F. Davies13, Anu Eskelinen2,14,15, Nicole Hagenah16,
Johannes M. H. Knops17, Andrew S. MacDougall18, Rebecca L. McCulley 19, Joslin L. Moore20,21,
Sally A. Power 22, Jodi N. Price23, Eric W. Seabloom8, Rachel Standish 24,25, Carly J. Stevens 26,
Stephan Zimmermann27 & Nico Eisenhauer 1,2
Covering approximately 40% of land surfaces, grasslands provide critical ecosystem services
that rely on soil organisms. However, the global determinants of soil biodiversity and func-
tioning remain underexplored. In this study, we investigate the drivers of soil microbial and
detritivore activity in grasslands across a wide range of climatic conditions on ve continents.
We apply standardized treatments of nutrient addition and herbivore reduction, allowing us
to disentangle the regional and local drivers of soil organism activity. We use structural
equation modeling to assess the direct and indirect effects of local and regional drivers on soil
biological activities. Microbial and detritivore activities are positively correlated across global
grasslands. These correlations are shaped more by global climatic factors than by local
treatments, with annual precipitation and soil water content explaining the majority of the
variation. Nutrient addition tends to reduce microbial activity by enhancing plant growth,
while herbivore reduction typically increases microbial and detritivore activity through
increased soil moisture. Our ndings emphasize soil moisture as a key driver of soil biological
activity, highlighting the potential impacts of climate change, altered grazing pressure, and
eutrophication on nutrient cycling and decomposition within grassland ecosystems.
https://doi.org/10.1038/s42003-023-05607-2 OPEN
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Grassland systems covering approximately 40% of the
worlds terrestrial surface, encompass a wide variety of
habitats for soil organisms1,2, which play key roles in
delivering ecosystem functions such as nutrient cycling and
decomposition36. In this context, the key players are soil
microorganisms and detritivores such as earthworms, isopods,
millipedes, and enchytraeids, which primarily feed on litter and
organic materials. Their collective efforts break down organic
matter, thus supplying vital nutrients to plants7. Soil organism
activity is strongly driven by temperature, soil moisture811, and
global change factors, including increased nutrient inputs and
alterations in the range, abundance, and distribution of above-
ground herbivores. However, we lack a broad understanding of
how nutrient inputs and herbivory inuence soil communities
and ecosystem functions in grasslands. At the same time, such
soil organisms may be important mediators of ecosystem
responses to global change2,12,13. Further, a lack of spatially
replicated studies means that we cannot predict how plant pro-
ductivity, grazing, or local abiotic characteristics may mediate
nutrient and herbivory effects on soil organisms14.
Herbivores can play a crucial role in shaping grasslands by
facilitating diverse plant communities and maintaining ecosystem
functioning14. For example, wild herbivores may selectively
consume abundant plant species, altering species
composition1517 and can contribute to maintaining plant
diversity by reducing competition for light18. Moreover, herbi-
vores impact nutrient cycling in grasslands by consuming live
plant material and modifying the quantity and quality of organic
inputs to the soil, e.g. via excreta, and via changes in soil abiotic
conditions14,19,20. At the same time, large native herbivore den-
sities may be reduced via hunting or land conversion, and in
many cases, they are replaced by large numbers of domestic
livestock21,22. Soil communities, processes, and structure are
strongly affected by wild and domestic herbivores, with important
consequences for soil biological activity and ecosystem
multifunctionality14,2325. Herbivores may enhance soil biological
activity by depositing easily-degradable dung and urine or, par-
ticularly under fertile conditions, inducing compensatory
growth19,2628. In contrast, in relatively unproductive systems,
grazers may preferentially feed on the few available nutrient-rich
plants, on which many soil organisms also depend, resulting in
poorer quality of litter, which reduces biological activity15,19,29,30.
Additionally, aboveground herbivores may create harsh envir-
onmental conditions for soil organisms through soil compaction,
negatively affecting pore space and water inltration as well as
increasing the cover of bare soil, resulting in high temperature
uctuations compared to vegetated areas31,32. At the same time,
the interaction between herbivory and nutrients can be context-
specic, as it may vary based on the specic plant species and
local site conditions33.
Predictions suggest that the disruption of the nitrogen cycle
could cause nitrogen (N) deposition to double in the future34,35.
The same applies to phosphorus (P) inputs, which have globally
increased compared to preindustrial levels36,37. The growth and
biomass production of plants depend on nutrients such as
nitrogen, phosphorous, and potassium, and most grasslands are
limited in productivity by nutrient inputs38,39. Nitrogen inputs
may increase the activity of soil organisms by increasing the
amount and quality of plant material that enters the soil
system10,20, but have also been shown to reduce detritivore
activity40. The same applies to soil microbes, as long-term
nitrogen inputs have been shown to have negative effects41. While
the effects of phosphorous inputs on microbial activity remain
less understood, it is known that phosphorous limitation can
impede decomposition4143. Globally, nitrogen to phosphorous
ratios are increasing, leading to a prevalence of phosphorous
limitation in soils36. This limitation can further inhibit microbial
activity, which in turn can impact biological decomposition
processes44. Additionally, although soil microbes are generally
less susceptible to potassium deciency than plants45, they still
benet from increased nutrient inputs, including potassium and
micronutrients from plants that have sufcient nutrient supply.
Given these context-dependent effects of nutrient addition and
herbivory on soil processes, we need standardized manipulations
of herbivores and nutrients across experimental and environ-
mental gradients.
To improve our understanding of how fertilization and her-
bivory may alter ecosystem functioning belowground, we inves-
tigated the effects of nutrient enrichment (NPK fertilization) and
herbivore reduction on soil microbial and detritivore activity
across grasslands worldwide. This globally-coordinated study of
soil biota was carried out within the Nutrient Network
experiment46, with sites in North and South America, Europe,
Asia, and Australia that represent a wide range of grassland
habitats and environmental conditions (Fig. 1a; Table S1). In
2015, we used standardized bait (bait lamina strips) at 18 sites to
assess soil detritivore feeding activity47, and analyzed soil samples
from 26 sites for soil microbial activity (microbial respiration)48.
Throughout the manuscript, we use the term biological activity
to encompass both activities. We used structural equation models
to test which biotic (plant community properties49) and abiotic
properties (soil water content11) determine soil biological activity
worldwide. We hypothesized that (1) reducing aboveground
herbivores would result in a decrease in belowground activity
rates. Furthermore, we expected (2) the impact of added nutrients
on soil biological activity would depend on carbon inputs, with
increased plant biomass due to nutrient additions being asso-
ciated with higher soil biological activity. With the two treatments
in combination (3), the positive effect of nutrients on soil activity
would be stronger than the negative effect of reduced herbivory,
leading to a net increase in soil biological activity. Here, we
expected that the positive effect of nutrients on soil activity would
be stronger than the negative effect of reduced herbivory.
Results
Effects of nutrient addition and herbivore exclusion. Soil det-
ritivore feeding activity ranged from 0.94% to 77% of available bait
substrate removed (Fig. S1a). Soil microbial respiration ranged
from 0.27 μl O
2
h-1 g-1 soil dry weight to 8.93 μl O
2
h-1 g-1 soil dry
weight. (Fig. S1b). Nutrient addition had no signicant effect on
detritivore feeding activity (F=0.08; p=0.78) and soil microbial
activity (F=0.94; p=0.333). Despite high among-site variation
(Fig. S2), herbivore reduction had a positive effect on detritivore
feeding (Fig. 1b; F=3.60; p=0.06), resulting in higher activity
levels when herbivores were reduced (+16.7%). At the same time,
herbivore reduction did not affect soil microbial activity (Fig. 1c;
F=0.29; p=0.59) Similarly, there was no interactive effect of NPK
fertilization and herbivore reduction on detritivore (F=0.21;
p=0.65) and microbial (F=0.63; p=0.43) activity.
Structural equation model analyses. The site-specic environ-
mental conditions and treatments also had strong effects on the
soil environment and the associated plant community, which
became more apparent when the interdependence of variables
was considered. Mean annual precipitation (MAP) and soil water
content were positively correlated (Fig. S6) and structural equa-
tion modeling shows that MAP and soil water were positively
associated with soil detritivore and microbial activity (Figs. 2a and
3a). At the same time, soil biological activity rates increased with
higher amounts of MAP and soil water content, regardless of
other treatment conditions (Figs. S4a, b and S5). Reecting our
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results from linear mixed-effects models, nutrient addition had
no direct effect on soil biotic activity. However, our SEM model
revealed that herbivore reduction directly increased detritivore
activity and indirectly increased activity of all soil microbes and
detritivores via increasing soil water content (Table S3; Figs. 2a, c
and 3a, c). Plant biomass, which increased with site MAP and
both NPK and herbivore reduction treatments, was related with
lower soil microbial activity (see also Fig. S6). At the same time,
we found detritivore and microbial activities to be signicantly
positively correlated (Fig. 4;F=9.15; p=0.003).
Discussion
We conducted a globally-distributed experiment assessing the
responses of soil biological activity to nutrient addition and
herbivory at 26 sites, spanning ve continents and multiple
grasslands. Soil microbial and detritivore activity were associated
with similar drivers at the global scale. Soil biological activity
increased with MAP and soil moisture, suggesting that future
climatic changes related to alterations in the amount and fre-
quency of precipitation as well as evapotranspiration50 may have
major consequences for grassland ecosystem functioning. To
Fig. 1 Global distribution and treatment effects. a Global map of all participating sites in the study. Red dot =data on soil microbial and detritivore activity
(n=18 sites); blue dot =data on soil microbial activity only (n=26 sites). b,cShow two gures where we tested the effect of NPK fertilization, herbivore
reduction, and the interactive effect of NPK fertilization and herbivore reduction on soil detritivore activity (log-scaled) and soil microbial activity (log-
scaled). Points are raw observations; error bars indicate 95% condence intervals. Signicance levels: (*) p-value =0.06, ns not signicant.
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Fig. 2 Structural equation model of soil detritivore activity. a Soil detritivore activity as a best-t Structural Equation Model showing the effects of NPK
fertilization and herbivore reduction (FishersC=1.88; P=0.758; d.f. =4; 18 sites). Black arrows indicate signicant positive and red arrows indicate
signicant negative effects in the model (P< 0.05). Dashed gray arrows indicate non-signicant effects (P> 0.05) that remain in the model based on AIC.
Dark gray double-headed arrows indicate paths that were treated as correlated errors in the model. Arrow widths are proportional to their effect sizes.
Numbers along the arrows are standardized path coefcients. Marginal R2
m
: model variation explained by xed effects; conditional R2
c
: model variation
explained by both xed and random effects. Signicance levels: *p< 0.05; **p< 0.01; ***p< 0.001. bDirect, indirect, and net effect of MAP on soil
detritivore activity, and cdirect, indirect, and net effect herbivore reduction on soil detritivore activity.
Fig. 3 Structural equation model of soil microbial activity. a Soil microbial activity as a best-t Structural Equation Model showing the effects of NPK
fertilization, herbivore reduction (A/C=77.9, FishersC=1.932; P=0.381; d.f. =2; 26 sites). Black arrows indicate signicant positive and red arrows indicate
signicant negative effects in the model (P< 0.05). Dashed gray arrows indicate non-signicant effects (P> 0.05) that remain in the model based on AIC.
Dark gray double-headed arrows indicate paths that were treated as correlated errors in the model. Arrow widths are proportional to their effect sizes.
Numbers along the arrows are standardized path coefcients. Marginal R2
m
: model variation explained by xed effects; conditional R2
c
: model variation
explained by both xed and random effects. Signicance levels: *p< 0.05; **p< 0.01; ***p< 0.001. bDirect, indirect, and net effect of MAP on soil microbial
activity, and cdirect, indirect, and net effect herbivore reduction on soil microbial activity, and ddirect, indirect, and net effect of NPK fertilization on soil
microbial activity (scale of b) differs from cand d.
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determine whether this pattern is causal or due to covariation
with other variables such as geological and historical factors, it
will be necessary to conduct future experimental manipulations.
Both soil biological activity measures are tightly linked to
decomposition processes that determine carbon sequestration
and release11,51, and therefore play a key role in grassland carbon
cycles52. In addition, herbivore presence was associated with
lower soil moisture which may amplify effects of a drier climate.
Moreover, MAP, NPK addition, and herbivore reduction had
indirect negative effects on soil microbial activity by increasing
plant biomass. This indicates that plant community-mediated
changes in soil microbial communities and functions depend on
abiotic and biotic conditions. This study improves our mechan-
istic understanding of factors determining soil biological activity
globally, which is crucial to predict belowground ecosystem
functioning in a changing world and to adopt measures to pre-
serve grassland systems2,46,53,54.
In line with our hypothesis (1), we found a consistent overall
positive effect of herbivore reduction on soil detritivore activity
across all sites. In addition, through our SEM analysis, we
observed that herbivore reduction enhanced soil detritivore
activity directly and also indirectly via an increase in soil water
content. However, while herbivore reduction had no direct effect
on soil microbial activity, it also indirectly increased microbial
activity via increases in soil water content. It has long been
recognized that soil organisms strongly depend on soil moisture
(e.g., residing on water lms within the soil pore system)11,5558.
Conrming this, our results highlight the role of water availability
for both measures of soil biological activity, with higher activity
levels at sites with higher MAP and soil water content. Previous
studies have found herbivores to reduce soil water content59 and
to have negative effects on soil organisms, especially in unpro-
ductive ecosystems17,19,53,60,61. Our results suggest that a reduc-
tion in soil activity with herbivory is the dominant pattern in
grasslands. This nding is consistent with other studies reporting
decreased soil respiration in response to lower soil water
content6264. In our study, soil water content had a signicantly
larger effect on soil microbial activity compared to detritivore
activity. This might be attributed to the fact that the soil water
content data were better aligned with the measure of soil
microbial activity. However, it is also possible that detritivores are
less inuenced by water content than microorganisms due to
their ability to move to deeper soil layers65. This adaptability
allows them to sustain their activity even in drier conditions. In
support of this, Sagi et al.66 discovered that the primary litter
decomposition in the Negev desert during summer was driven by
a woodlice species, in contrast to microbes which lacked the
necessary water for growth.
Other possible mechanisms for direct negative impacts of
(especially larger) herbivores on soil detritivores and thus the
positive effect when they were excluded, entail physical dis-
turbances like trampling and soil compaction53,67,68. These result
in higher bulk density and reduced connectivity of soil pores69
that normally ensure water inltration and air permeability70,71.
Such a reduction in soil pore space has been shown to reduce the
abundance and diversity of soil arthropods and annelids69,72,73.
For example, Collembola and enchytraeids strongly depend on
macropores in their living environment, have hardly any ability to
move through compacted soil, and may thus experience reduced
access to food resources, consequently inhibiting their feeding
activity69. However, even soil animals with considerable bur-
rowing abilities, like earthworms, have been shown to be nega-
tively affected by soil compaction74. Indeed, we found some
evidence for a signicant positive relationship between soil
microbial and detritivore activity and soil porosity across a subset
of sites (Fig. S8). However, given that only a subset of the sites
could be considered for this analysis, this topic needs to be
addressed in future research.
At the same time, we observed increases in plant biomass that
were associated with herbivore reduction, nutrient addition, and
higher levels of precipitation75. It is well-established that vege-
tation cover helps to maintain high levels of soil biological
activity, as evidenced by previous studies7680, which is consistent
with our own ndings. However, higher plant biomass also led to
declines in soil microbial activity which is, in contrast to other
studies reporting positive effects of higher plant biomass on soil
biological activity via bottom up effects of increased
rhizodeposition19,8183. There are several possible explanations.
On one hand, enhanced plant growth could potentially result in
higher transpiration rates84,85, ultimately leading to a reduction
in soil water content over time. On the other hand, herbivore
reduction also led to a less diverse plant community, which could
also decrease microbial respiration. It is also possible that soil
microbial communities have to compete with plants for nutrients,
possibly leading to reduced respiration rates. Follow-up studies
are needed to relate environmental change-induced alterations in
soil microbial communities to ecosystem functions, using stan-
dardized, replicated methods to increase the generality and
robustness of such experiments86,87.
In contrast to our hypotheses (2 & 3), we did not observe an
either signicant effect of nutrient addition soil biological activity
or a signicant interaction between nutrient addition and her-
bivory. Although we applied NPK at high levels, we did not detect
any direct fertilization effect, suggesting that availability of
mineral nutrients is not the main determinant driving soil bio-
logical activity in grasslands. However, soil community responses
and functions can be diverse and context-dependent88. Previous
studies have shown that nutrient addition can alter the soil
community by changing pH, porosity, organic fractions, and
increasing decomposition, but responses of soil microbial
respiration and biomass to NPK addition are highly
variable25,40,41,8991. However, our ndings show a decline in soil
microbial activity due to nutrient addition in global grasslands,
alongside an increase in total plant biomass. Nutrient addition
altered plant communities through by increasing total plant
biomass and reducing plant species richness. Similar effects have
been reported by multiple studies46,9297. As nutrient addition
has been shown to decrease soil organic matter stabilization, we
Fig. 4 Correlation between soil microbial and detritivore activity.
Correlation of soil microbial activity and detritivore activity (both log-
scaled, data from 18 sites included; F=9.15, p=0.003). Color of data
points (blue) indicates soil moisture level of the sample.
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speculate that our results may be connected to shifts in plant or
soil microbial communities that inuence the recalcitrance of
organic matter and its microbial processing98.
Assessing soil microbial activity for a global scale study entailed
some constraints that could have also inuenced our ndings.
Measuring soil microbial activity involved homogenizing, sieving,
and shipping soil samples to a central laboratory, which includes
disruption of soil aggregates, along with potential changes in
microbial activity due to shipping conditions. Additionally,
assessing microbial activity under controlled temperature condi-
tions, differing from the natural environment, might have inu-
enced the correlations observed with mean annual temperature
(MAT). Similarly, the bait lamina test, offering an on-site
approach to assess detritivore activity, has faced recent critique
regarding its use of standardized substrates as accurate indicators
of local plant litter-driven decomposition99 even though this
concern was not directly tested for bait lamina strips.
Overall, our results highlight that reductions in mean annual
precipitation or prolonged drought periods may reduce soil bio-
logical activity that is key for the provisioning of essential eco-
system functions like nutrient cycling and decomposition52,100.
These expected changes in climate could be further amplied by
alterations in the abundance and identity of herbivores as well as
nutrient inputs, with complex feedback mechanisms, including
shifts in local plant community composition and productivity, as
well as abiotic factors like soil compaction. Nutrient addition did
not directly affect soil biological activity across global grasslands,
emphasizing the importance of an indirect effect via plant bio-
mass that should be considered in future studies. These novel
insights into the global drivers of soil biological activity stress the
complex interplay between different components of anthro-
pogenic change that may alter above-belowground interactions
and thus the functioning of global grasslands.
Methods
Experimental design and included sites. Fieldwork was con-
ducted in 2015 within the Nutrient Network Global Experiment
(www.nutnet.org)46 at 26 sites (see Fig. 1a and Table S1). The
sites are located in North and South America, Europe, Asia, and
Australia and are all dominated by herbaceous or low-statured
vegetation (hereafter referred to as grasslands). Moreover, sites
cover wide environmental gradients with elevations ranging from
6 m to 4.241 m a.s.l., mean annual temperatures from 3.3 °C to
22.4 °C, and mean annual precipitation from 324 mm to
1678 mm (Table S1). The experiments were set up at different
times in 20092014 (for details see Table S1).
For our study, we sampled plots at each site, which were
randomly assigned to one of four: Control, nutrient addition,
fenced, nutrient addition and fenced. Each treatment was replicated
three times at each site, leading to a total of 12 plots. Fences
excluded aboveground herbivores weighing more than 50 g. The
plots were 5 × 5 m in size and NPK plots received a fertilization
treatment of nitrogen (N), phosphorus (P), and potassium (K).
Nutrient addition rates and sources are: 10 g N m-2 *year-1 as
timed-release urea [(NH
2
)
2
CO], 10 g P m-2 *year-1 as triple-super
phosphate [Ca(H
2
PO
4
)2], 10 g K m-2 *year-1 as potassium
sulphate [K
2
SO
4
]. Additionally, 100 g of a micronutrient mix
of Fe (15%), S (14%), Mg (1.5%), Mn (2.5%), Cu (1%), Zn (1%), B
(0.2%), and Mo (0.05%) were applied once at the start of the
experiment. In contrast, control plots did not receive additional
nutrients and represent ambient soil conditions. The fences for
herbivore reduction were of 2.3 m height, with few sites having
physical constraints that required fence modication. They were set
up with a 1 cm woven wire mesh extending 090 cm aboveground
and a 30 cm outward-facing ange stapled to the ground to exclude
smaller digging animals. To reduce possible impacts of neighboring
plots, all plots are separated by walkways of at least 1 m width. All
sampling occurred in a single, randomly selected, 2.5 × 2.5 subplot
of each plot. Further details on the experimental set up,
standardized sampling protocols, and nutrient sources are
described in Borer et al.46.
Plant data. Following the standardized Nutrient Network pro-
tocol, total aboveground plant biomass was clipped at peak bio-
mass within two 0.1 × 1 m strips per plot, whose locations are
changed each year (see Borer et al., for details). Sorted plant
material was dried at 60 °C to a constant mass and weighed to the
nearest 0.01 g. For our analyses, we used data on total plant
biomass (i.e., the sum of dead and live plant biomass) from 2015
(i.e., the year of the study) as a proxy for plant-derived inputs to
the soil, such as rhizodeposits and plant litter. Plant species
richness was assessed on-site in a permanent 1 × 1 m quadrat
located in the focal subplot in each plot.
Climate variables. Data on mean annual precipitation (MAP in
mm) and mean annual temperature (MAT in °C) were derived
from the WorldClim database (version 1.4; Hijmans et al.).
Values were interpolated at high resolution from meteorological
stations with 10 to 30 years of data101.
Soil sampling. Soil invertebrate feeding activity was assessed at
16 sites using the bait lamina test (Terra Protecta GmbH, Berlin,
Germany), which is commonly used as a rapid ecosystem func-
tion assessment method11,47. The bait strips are made of PVC
(1 mm × 6 mm × 120 mm) and have 16 holes (1.5 mm in dia-
meter). Holes were lled with an articial organic bait substrate,
which was prepared according to the recommendations of Terra
Protecta, consisting of 70% cellulose powder, 27% wheat bran,
and 3% activated carbon. The bait substrate is primarily con-
sumed by soil collembolas, enchytraeids, and earthworms76,102;
microbial activity plays a minor role in bait loss103105. The bait
strip assessment was done by the principal investigator of each
site. The bait strips were inserted vertically into the soil with the
uppermost hole just beneath the soil surface. A steel knife was
used to create a slot in the soil, before the strips were inserted.
Five strips were spaced 15 cm apart within each plot to account
for within-plot spatial heterogeneity. After three to six weeks of
exposure, the bait strips were removed from the soil and directly
evaluated in the eld. Each hole was rated as 0 (no invertebrate
feeding activity), 0.5 (bait material partly consumed), or 1 (bait
material completely consumed), based on visual inspection. Thus,
soil invertebrate feeding activity could range from 0 (no feeding
activity) to 16 (maximum feeding activity) per strip. Mean bait
consumption of the ve strips was calculated per plot prior to
statistical analyses and expressed as a percentage. Timing varia-
tions resulted from the substantial environmental differences, as
in some cases, short exposure intervals did not yield discernible
changes (for detailed exposure time please see Table S1).
Soil for microbial data was collected from 26 sites six weeks
before peak plant biomass production (local site coordinators
chose specic dates, as seasonality varied across different
latitudes) by taking three subsamples per plot (using a soil corer
with 5 cm diameter and 12 cm depth), which were then
homogenized and sieved using a 2 mm mesh. All soil samples
to Anita Risch in Switzerland following a standardized protocol.
A subset of these samples was then shipped to a centralized lab at
the German Centre for Integrative Biodiversity Research in
Leipzig, Germany. We ensured sample quality during transit by
using postal services with temperature control and fast shipping
methods. Here, we took approximately 6 g of fresh soil to measure
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basal respiration (without the addition of substrate) at hourly
intervals for 24 h at 20 °C using an O
2
-microcompensation
system48. We used four different O
2
-microcompensation devices
to measure all samples simultaneously. Basal respiration, as a
measure of soil microbial activity, was then calculated as the
mean O
2
consumption rate 1424 h after the start of the
measurements (μl O
2
h-1 per g soil dry weight), as the machine
needs some time to measure stable values over an extended
period77. In addition, soil water content [%] was calculated as the
difference between the weight of the fresh soil sample and the
weight of the soil sample per plot after they were dried for at least
48 h at 70 °C. Soil water content was signicantly positively
correlated with soil water holding capacity (R²=0.61, p< 0.001).
Soil porosity was determined as described in Risch et al.25, but
was only available for a subset of 15 sites.
Statistics and reproducibility. To assess the effects of fertiliza-
tion, reduced density of vertebrate herbivores, and their interac-
tion on soil detritivore feeding and microbial respiration across all
sites without accounting for abiotic factors and plant data, we
employed linear mixed-effects models using the lmer function
from the R-package lme4106. The models random intercepts
were organized based on two factors: (1) block nested within site,
and (2) the type of O
2
-microcompensation device (for soil
microbial data) or eld exposure duration (for detritivore data),
as some sites had a longer exposure time due to logistical con-
straints. We also tested a model with treatment duration years as
axed effect, but found that treatment duration had no sig-
nicant impact on soil microbial and detritivore activity, and
consequently excluded treatment durationfrom our explana-
tory parameters. To account for the non-normality of our
response variables, we log-transformed data prior to our analysis.
Figure 1b, c are based on mixed-effects model ts extracted using
the package ggeffects107.
We used structural equation modeling (SEM) to disentangle
direct and indirect pathway effects by which fertilization and
herbivore reduction affected the activity of soil organisms. In
determining the environmental variables for our SEM approach,
we considered factors that could offer meaningful insights into
the dynamics of soil microbial and detritivore activity. These
variables were selected a priori based on their established
inuence on soil microbial and detritivore activity, as well as
their potential to mediate treatment effects. Our choices were
guided by existing literature in the eld. Given that plant
community composition and biomass are strong predictors of soil
microbial and detritivore activity and are thus likely to mediate
the treatment effects, we included plant species richness and total
plant biomass in the SEM (Figs. 2and 3). As soil organisms are
highly dependent on soil moisture108, we included soil water
content as a key abiotic driver. We also chose to include mean
annual precipitation (MAP) as another exogenous variable, as it
was correlated with soil moisture (Fig. S7) with the two soil
activity variables (Figs. 2and S4a, b) and should have long-lasting
effects on soil conditions that are also relevant for our snapshot
assessments. We further selected mean annual temperature as
another exogenous variable. However, the relationship between
mean annual temperature (MAT) and microbial activity was not
statistically signicant (p=0.14), and a similar non-signicant
trend was observed with detritivore activity (p=0.93) (see also
Fig. S4c, d). Although MAT displayed a positive correlation with
plant species richness, this association did not extend to the other
variables in our SEM model (as illustrated in Figs. 2and 3).
Consequently, we decided to exclude MAT from the nal model.
The framework of the piecewiseSEMR package109 allowed us to
test for interactive treatment effects and to account for the
hierarchical study design by including random effects in the
models. We also investigated the effects of soil pH and individual
effects of living and dead plant biomass on soil microbial and
detritivore activity within the model. However, these data were
only available for a small subset of sites and as we found no
signicant direct or indirect effects on biological activity, we
excluded them in the nal model.
The single models that were incorporated in the SEM were
built using LMMs (Table S2). The assumptions of the LMMs were
checked by plotting frequency distributions of each variable and
the variance structure of all models using residual plots for
homogeneity and quantile-quantile plots for normality (i.e., no
correlation between the residuals and the tted parameters of the
model). To meet model assumptions, plant biomass, plant species
richness, soil water content, and detritivore activity were log-
transformed. The relationship between plant richness and total
plant biomass was included as a correlated error term due to
reciprocal effects110.
The number of variables was reduced from the conceptual
model using the Akaike Information Criterion (AIC) that is
implemented in the piecewiseSEMpackage. Standardized
coefcients are reported for each path of the nal model
(Tables S3 and S4, Figs. 2a and 3a). The overall t of the models
was evaluated by using Shipleys test of d-separation obtained
through Fishers C statistic. Correlations were performed between
soil microbial activity and soil detritivore activity. To examine the
impact of herbivore-induced changes in soil structure on
biological activity, we analyzed the correlation between soil
porosity (a measure of soil compaction inuenced by herbivores)
and the two soil activity measures. However, due to insufcient
sample size, we could not include soil porosity in the SEM. The
statistical analyses were performed using the R statistical software
(version 4.2.2.; R Core Team 2022). Data used for creating the
gures can be found in the supplementary data (Figs. 1a, 2and 4
were created with Data 1, Figs. 1b and 3with Data 2).
Reporting summary. Further information on research design is
available in the Nature Portfolio Reporting Summary linked to
this article.
Data availability
The source data that support the ndings of this study can be found in the
supplementary data (Figs. 1a, b, 2and 4were created with Data 1, Fig. 1c and Fig. 3with
Data 2). All other data are available from the corresponding author on reasonable
request.
Code availability
The code is available from the corresponding author upon request.
Received: 31 March 2023; Accepted: 17 November 2023;
References
1. Decaëns, T. Macroecological patterns in soil communities: soil community
macroecology. Glob. Ecol. Biogeogr. 19, 287302 (2010).
2. Bardgett, R. D. & van der Putten, W. H. Belowground biodiversity and
ecosystem functioning. Nature 515, 505511 (2014).
3. Oliver, M. A. & Gregory, P. J. Soil, food security and human health: a review:
soil, food security and human health. Eur. J. Soil Sci. 66, 257276 (2015).
4. Wall, D. H., Nielsen, U. N. & Six, J. Soil biodiversity and human health.
Nature 528,6976 (2015).
5. Geisen, S., Wall, D. H. & van der Putten, W. H. Challenges and opportunities
for soil biodiversity in the anthropocene. Curr. Biol. 29, R1036R1044 (2019).
COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-023-05607-2 ARTICLE
COMMUNICATIONS BIOLOGY | (2023) 6:1220 | https://doi.org/10.1038/s42003-023-05607-2 | www.nature.com/commsbio 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved
6. van der Heijden, M. G. A., Bardgett, R. D. & van Straalen, N. M. The unseen
majority: soil microbes as drivers of plant diversity and productivity in
terrestrial ecosystems. Ecol. Lett. 11, 296310 (2008).
7. Crowther, T. W. et al. Biotic interactions mediate soil microbial feedbacks to
climate change. Proc. Natl Acad. Sci. USA 112, 70337038 (2015).
8. Butenschoen, O., Scheu, S. & Eisenhauer, N. Interactive effects of warming,
soil humidity and plant diversity on litter decomposition and microbial
activity. Soil Biol. Biochem. 43, 19021907 (2011).
9. Riutta, T., Clack, H., Crockatt, M. & Slade, E. M. Landscape-scale implications
of the edge effect on soil fauna activity in a temperate forest. Ecosystems 19,
534544 (2016).
10. Sünnemann, M. et al. Combined effects of land-use type and climate change
on soil microbial activity and invertebrate decomposer activity. Agric. Ecosyst.
Environ. 318, 107490 (2021).
11. Thakur, M. P. et al. Reduced feeding activity of soil detritivores under warmer
and drier conditions. Nat. Clim. Change 8,7578 (2018).
12. Gougoulias, C., Clark, J. M. & Shaw, L. J. The role of soil microbes in the
global carbon cycle: tracking the below-ground microbial processing of plant-
derived carbon for manipulating carbon dynamics in agricultural systems: role
of soil microbes in global carbon cycle: carbon tracking & agro-cosystem
management. J. Sci. Food Agric. 94, 23622371 (2014).
13. Lavelle, P. et al. Soil invertebrates and ecosystem services. Eur. J. Soil Biol. 42,
S3S15 (2006).
14. Bardgett, R. D. & Wardle, D. A. Aboveground-Belowground Linkages. Biotic
Interactions, Ecosystem Processes, and Global Change. (Oxford Univ. Press,
2010).
15. Anderson, T. M. et al. Herbivory and eutrophication mediate grassland plant
nutrient responses across a global climatic gradient. Ecology 99, 822831
(2018).
16. Holt, R. D., Grover, J. & Tilman, D. Simple rules for interspecic dominance
in systems with exploitative and apparent competition. Am. Nat. 144, 741771
(1994).
17. Lind, E. M. et al. Increased grassland arthropod production with mammalian
herbivory and eutrophication: a test of mediation pathways. Ecology 98,
30223033 (2017).
18. Borer, E. T. et al. Finding generality in ecology: a model for globally
distributed experiments. Methods Ecol. Evol. 5,6573 (2014).
19. Bardgett, R. D. & Wardle, D. A. Herbivore-mediated linkages between
aboveground and belowground communities. Ecology 84, 22582268 (2003).
20. Sitters, J. et al. Nutrient availability controls the impact of mammalian
herbivores on soil carbon and nitrogen pools in grasslands. Glob. Change Biol.
26, 20602071 (2020).
21. Wassenaar, T. et al. Projecting land use changes in the Neotropics: the
geography of pasture expansion into forest. Glob. Environ. Change 17,86104
(2007).
22. Neely, C., Bunning, S. & Wilkes, A. Review of evidence on drylands pastoral
systems and climate change. (Food and Agriculture Organization of the United
Nations, 2009).
23. Guitian, R. & Bardgett, R. D. Plant and soil microbial responses to defoliation
in temperate semi-natural grassland. Plant and soil 220, 271277 (2000).
24. Mikola, J. et al. Defoliation and patchy nutrient return drive grazing effects on
plant and soil properties in a dairy cow pasture. Ecol. Monogr. 79, 221244
(2009).
25. Risch, A. C. et al. Global impacts of fertilization and herbivore removal on soil
net nitrogen mineralization are modulated by local climate and soil properties.
Glob. Change Biol. 26, 71737185 (2020).
26. Augustine, D. J. & McNaughton, S. J. Interactive effects of ungulate
herbivores, soil fertility, and variable rainfall on ecosystem processes in a semi-
arid savanna. Ecosystems 9, 12421256 (2006).
27. Bardgett, R. D., Leemans, D. K., Cook, R. & Hobbs, P. J. Seasonality of the soil
biota of grazed and ungrazed hill grasslands. Soil Biol. Biochem. 29, 12851294
(1997).
28. Bardgett, R. D. et al. Soil microbial community patterns related to the history
and intensity of grazing in sub-montane ecosystems. Soil Biol. Biochem. 33,
16531664 (2001).
29. Ritchie, M. E., Tilman, D. & Knops, J. M. H. Herbivore effects on plant and
nitrogen dynamics in oak savanna. Ecology 79, 165177 (1998).
30. Pastor, J., Dewey, B., Naiman, R. J., McInnes, P. F. & Cohen, Y. Moose
browsing and soil fertility in the boreal forests of Isle Royale National Park.
Ecology 74, 467480 (1993).
31. Cole, L., Buckland, S. M. & Bardgett, R. D. Inuence of disturbance and
nitrogen addition on plant and soil animal diversity in grassland. Soil Biol.
Biochem. 40, 505514 (2008).
32. King, K. L. & Hutchinson, K. J. The effects of sheep stocking intensity on the
abundance and distribution of Mesofauna. Pastures J. Appl. Ecol. 13,41
(1976).
33. Borer, E. T. et al. More salt, please: global patterns, responses and impacts of
foliar sodium in grasslands. Ecol. Lett. 22, 11361144 (2019).
34. Galloway, J. N. et al. Transformation of the Nitrogen cycle: recent trends,
questions, and potential solutions. Science 320, 889892 (2008).
35. Vitousek, P. M. et al. Human alteration of the global nitrogen cycle: sources
and consequences. Ecol. Appl. 7, 737750 (1997).
36. Penuelas, J., Janssens, I. A., Ciais, P., Obersteiner, M. & Sardans, J.
Anthropogenic global shifts in biospheric N and P concentrations and ratios
and their impacts on biodiversity, ecosystem productivity, food security, and
human health. Glob. Change Biol. 26, 19621985 (2020).
37. Wang, R. et al. Signicant contribution of combustion-related emissions to the
atmospheric phosphorus budget. Nat. Geosci. 8,4854 (2015).
38. Fay, P. A. et al. Grassland productivity limited by multiple nutrients. Nat.
Plants 1, 15080 (2015).
39. Kaspari, M. The invisible hand of the periodic table: how micronutrients
shape ecology. Annu. Rev. Ecol. Evol. Syst. 52, 199219 (2021).
40. Siebert, J. et al. The effects ofdrought and nutrient addition on soil organisms vary
across taxonomic groups, but are constant across seasons. Sci. Rep. 9, 639 (2019).
41. Treseder, K. K. Nitrogen additions and microbial biomass: a meta-analysis of
ecosystem studies. Ecol. Lett. 11, 11111120 (2008).
42. Janssens, I. A. et al. Reduction of forest soil respiration in response to nitrogen
deposition. Nat. Geosci. 3, 315322 (2010).
43. Ramirez, K. S., Craine, J. M. & Fierer, N. Nitrogen fertilization inhibits soil
microbial respiration regardless of the form of nitrogen applied. Soil Biol.
Biochem. 42, 23362338 (2010).
44. Güsewell, S. & Gessner, M. O. N: P ratios inuence litter decomposition and
colonization by fungi andbacteria in microcosms. Funct. Ecol. 23, 211219 (2009).
45. Moro, H., Kunito, T., Saito, T., Yaguchi, N. & Sato, T. Soil microorganisms are
less susceptible than crop plants to potassium deciency. Arch. Agron. Soil Sci.
60, 18071813 (2014).
46. Borer, E. T. et al. Herbivores and nutrients control grassland plant diversity
via light limitation. Nature 508, 517520 (2014).
47. Kratz, W. The bait-lamina test: General aspects, applications and perspectives.
Environ. Sci. Pollut. Res. 5,9496 (1998).
48. Scheu, S. Automated measurement of the respiratory response of soil
microcompartments: Active microbial biomass in earthworm faeces. Soil Biol.
Biochem. 24, 11131118 (1992).
49. Eisenhauer, N. et al. Plant diversity maintains multiple soil functions in future
environments. eLife 7, e41228 (2018).
50. Konapala, G., Mishra, A. K., Wada, Y. & Mann, M. E. Climate change will
affect global water availability through compounding changes in seasonal
precipitation and evaporation. Nat. Commun. 11, 3044 (2020).
51. Schwarz, B. et al. Warming alters energetic structure and function but not
resilience of soil food webs. Nat. Clim. Change 7, 895900 (2017).
52. Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth
Environ. 2, 720735 (2021).
53. Van Klink, R. et al. Effects of large herbivores on grassland arthropod
diversity. Biol. Rev. 90, 347366 (2015).
54. Bakker, E. S., Ritchie, M. E., Olff, H., Milchunas, D. G. & Knops, J. M. H.
Herbivore impact on grassland plant diversity depends on habitat productivity
and herbivore size. Ecol. Lett. 9, 780788 (2006).
55. Orchard, V. A. & Cook, F. J. Relationship between soil respiration and soil
moisture. Soil Biol. Biochem. 15, 447453 (1983).
56. Blankinship, J. C., Niklaus, P. A. & Hungate, B. A. A meta-analysis of
responses of soil biota to global change. Oecologia 165, 553565 (2011).
57. Hueso, S., García, C. & Hernández, T. Severe drought conditions modify the
microbial community structure, size and activity in amended and unamended
soils. Soil Biol. Biochem. 50, 167173 (2012).
58. Iglesias Briones, M. J., Ineson, P. & Piearce, T. G. Effects of climate change on
soil fauna; responses of enchytraeids, Diptera larvae and tardigrades in a
transplant experiment. Appl. Soil Ecol. 6, 117134 (1997).
59. Hao, Y. & He, Z. Effects of grazing patterns on grassland biomass and soil
environments in China: a meta-analysis. PLoS ONE 14, e0215223 (2019).
60. Andriuzzi, W. S. & Wall, D. H. Responses of belowground communities to
large aboveground herbivores: metaanalysis reveals biomedependent
patterns and critical research gaps. Glob. Change Biol. 23, 38573868 (2017).
61. Seabloom, E. W. et al. Globally consistent response of plant microbiome
diversity across hosts and continents to soil nutrients and herbivores. Nat.
Commun. 14, 3516 (2023).
62. Smith, L. C. et al. Largescale drivers of relationships between soil microbial
properties and organic carbon across Europe. Glob. Ecol. Biogeogr. 30,
20702083 (2021).
63. Wang, Z., Ji, L., Hou, X. & Schellenberg, M. P. Soil respiration in semiarid
temperate grasslands under various land management. PLoS ONE 11,
e0147987 (2016).
64. Cao, G. et al. Grazing intensity alters soil respiration in an alpine meadow on
the Tibetan plateau. Soil Biol. Biochem. 36, 237243 (2004).
65. Steinaker, D. F. & Wilson, S. D. Scale and density dependent relationships
among roots, mycorrhizal fungi and collembola in grassland and forest. Oikos
117, 703710 (2008).
ARTICLE COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-023-05607-2
8COMMUNICATIONS BIOLOGY | (2023) 6:1220 | https://doi.org /10.1038/s42003-023-05607-2 | www.nature.com/commsbio
Content courtesy of Springer Nature, terms of use apply. Rights reserved
66. Sagi, N., Grünzweig, J. M. & Hawlena, D. Burrowing detritivores regulate
nutrient cycling in a desert ecosystem. Proc. R. Soc. B Biol. Sci. 286, 20191647
(2019).
67. Sitters, J. & Andriuzzi, W. S. The Ecology of Browsing and Grazing II. vol. 239
(Springer Int. Publ., 2019).
68. Cumming, D. H. M. & Cumming, G. S. Ungulate community structure and
ecological processes: body size, hoof area and trampling in African savannas.
Oecologia 134, 560568 (2003).
69. Beylich, A., Oberholzer, H.-R., Schrader, S., Höper, H. & Wilke, B.-M.
Evaluation of soil compaction effects on soil biota and soil biological processes
in soils. Soil Tillage Res. 109, 133143 (2010).
70. Horn, R., Domżżał, H., Słowińska-Jurkiewicz, A. & Van Ouwerkerk, C. Soil
compaction processes and their effects on the structure of arable soils and the
environment. Soil Tillage Res. 35,2336 (1995).
71. Richard, G., Cousin, I., Sillon, J. F., Bruand, A. & Guérif, J. Effect of
compaction on the porosity of a silty soil: inuence on unsaturated hydraulic
properties: Soil compaction, pore geometry and hydraulic properties. Eur. J.
Soil Sci. 52,4958 (2001).
72. Duffey, E. The effects of human trampling on the fauna of grassland litter.
Biol. Conserv. 7, 255274 (1975).
73. Chappell, H. G., Ainsworth, J. F., Cameron, R. A. D. & Redfern, M. The effect
of trampling on a chalk grassland ecosystem. J. Appl. Ecol. 8, 869 (1971).
74. Kretzschmar, A. Burrowing ability of the earthworm Aporrectodea longa
limited by soil compaction and water potential. Biol. Fertil. Soils 11,4851
(1991).
75. Borer, E. T. et al. Nutrients cause grassland biomass to outpace herbivory. Nat.
Commun. 11, 6036 (2020).
76. Birkhofer, K. et al. Soil fauna feeding activity in temperate grassland soils
increases with legume and grass species richness. Soil Biol. Biochem. 43,
22002207 (2011).
77. Siebert, J. et al. Extensive grassland-use sustains high levels of soil biological
activity, but does not alleviate detrimental climate change effects. in Adv. Ecol.
Res. 60,2558 (Elsevier, 2019).
78. Lin, Y. et al. Grazing intensity affected spatial patterns of vegetation and soil
fertility in a desert steppe. Agric. Ecosyst. Environ. 138, 282292 (2010).
79. Moreno, B., Garcia-Rodriguez, S., Cañizares, R., Castro, J. & Benítez, E.
Rainfed olive farming in south-eastern Spain: long-term effect of soil
management on biological indicators of soil quality. Agric. Ecosyst. Environ.
131, 333339 (2009).
80. Sánchez-Moreno, S., Cano, M., López-Pérez, A. & Rey Benayas, J. M.
Microfaunal soil food webs in Mediterranean semi-arid agroecosystems. Does
organic management improve soil health? Appl. Soil Ecol. 125, 138147
(2018).
81. Kent, A. D. & Triplett, E. W. Microbial communities and their interactions in
soil and rhizosphere ecosystems. Annu. Rev. Microbiol. 56, 211236 (2002).
82. Sjursen, H., Michelsen, A. & Jonasson, S. Effects of long-term soil warming
and fertilisation on microarthropod abundances in three sub-arctic
ecosystems. Appl. Soil Ecol. 30, 148161 (2005).
83. Eisenhauer, N. et al. Plant diversity effects on soil microorganisms support the
singular hypothesis. Ecology 91, 485496 (2010).
84. Craven, D. et al. Plant diversity effects on grassland productivity are robust to
both nutrient enrichment and drought. Philos.Trans. R. Soc. B Biol. Sci. 371,
20150277 (2016).
85. Gottschall, F. et al. Spatiotemporal dynamics of abiotic and biotic properties
explain biodiversityecosystemfunctioning relationships. Ecol. Monogr.92,
e01490 (2022).
86. Delgado-Baquerizo, M. et al. The proportion of soil-borne pathogens
increases with warming at the global scale. Nat. Clim. Change 10, 550554
(2020).
87. Heintz-Buschart, A. et al. Microbial diversity-ecosystem function relationships
across environmental gradients. Res. Ideas Outcomes 6, e52217 (2020).
88. Beaumelle, L., De Laender, F. & Eisenhauer, N. Biodiversity mediates the
effects of stressors but not nutrients on litter decomposition. eLife 9, e55659
(2020).
89. Galantini, J. & Rosell, R. Long-term fertilization effects on soil organic matter
quality and dynamics under different production systems in semiarid
Pampean soils. Soil Tillage Res. 87,7279 (2006).
90. Liu, L. & Greaver, T. L. A global perspective on belowground carbon dynamics
under nitrogen enrichment: belowground C dynamics under N enrichment.
Ecol. Lett. 13, 819828 (2010).
91. OchoaHueso, R. et al. Microbial processing of plant remains is colimited by
multiple nutrients in global grasslands. Glob. Change Biol. 26, 45724582
(2020).
92. Hautier, Y., Niklaus, P. A. & Hector, A. Competition for light causes plant
biodiversity loss after eutrophication. Science 324, 636638 (2009).
93. Crawley, M. J. et al. Determinants of Species Richness in the Park Grass
Experiment. Am. Nat. 165, 179192 (2005).
94. Harpole, W. S. & Tilman, D. Grassland species loss resulting from reduced
niche dimension. Nature 446, 791793 (2007).
95. Rajaniemi, T. K. Why does fertilization reduce plant species diversity? Testing
three competition-based hypotheses. J. Ecol. 90, 316324 (2002).
96. DiTommaso, A. & Aarssen, L. W. Resource manipulations in natural
vegetation: a review. Vegetatio 84,929 (1989).
97. Stevens, C. J. et al. Anthropogenic nitrogen deposition predicts local grassland
primary production worldwide. Ecology 96, 14591465 (2015).
98. Rocci, K. S. et al. Impacts of nutrient addition on soil carbon and nitrogen
stoichiometry and stability in globally-distributed grasslands. Biogeochemistry
159, 353370 (2022).
99. Joly, F.-X., Scherer-Lorenzen, M. & Hättenschwiler, S. Resolving the intricate
role of climate in litter decomposition. Nat. Ecol. Evol.https://doi.org/10.1038/
s41559-022-01948-z (2023).
100. Guerra, C. A. et al. Tracking, targeting, and conserving soil biodiversity.
Science 371, 239241 (2021).
101. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high
resolution interpolated climate surfaces for global land areas. Int. J. Climatol.
25, 19651978 (2005).
102. Van Gestel, C. A. M., Kruidenier, M. & Berg, M. P. Suitability of wheat straw
decomposition, cotton strip degradation and bait-lamina feeding tests to
determine soil invertebrate activity. Biol. Fertil. Soils 37, 115123 (2003).
103. Hamel, C., Schellenberg, M. P., Hanson, K. & Wang, H. Evaluation of the
bait-lamina testto assess soil microfauna feeding activity in mixed grassland.
Appl. Soil Ecol. 36, 199204 (2007).
104. Simpson, J. E., Slade, E., Riutta, T. & Taylor, M. E. Factors affecting soil fauna
feeding activity in a fragmented lowland temperate deciduous woodland. PLoS
ONE 7, e29616 (2012).
105. Eisenhauer, N. et al. Organic textile dye improves the visual assessment of the
bait-lamina test. Appl. Soil Ecol. 82,7881 (2014).
106. Bates, D., Mächler, M., Bolker, B. & Walker, S.: Fitting linear mixed-effects
models using lme4. arXiv preprint arXiv:1406.5823 (2014).
107. Lüdecke, D. ggeffects: tidy data frames of marginal effects from regression
models. J. Open Source Softw. 3, 772 (2018).
108. Cesarz, S. et al. Tree diversity effects on soil microbial biomass and respiration
are context dependent across forest diversity experiments. Glob. Ecol. Biogeogr.
31, 872885 (2022).
109. Lefcheck, J. S. Piecewise structural equation modelling in R for ecology,
evolution, and systematics. Methods Ecol. Evol. 7, 573579 (2016).
110. Eisenhauer, N. et al. Biodiversity-ecosystem function experiments reveal the
mechanisms underlying the consequences of biodiversity change in real world
ecosystems. J. Veg. Sci. 27, 10611070 (2016).
Acknowledgements
This work was generated using data from the Nutrient Network (http://www.nutnet.org)
experiment, funded at the site-scale by individual researchers. Coordination of soil
sampling was funded by a competitive WSL internal grant to A.C. Risch and S. Zim-
mermann. Coordination and data management for NutNet have been supported by
funding to E. Borer and E. Seabloom from the National Science Foundation Research
Coordination Network (NSF-DEB-1042132) and Long-Term Ecological Research (NSF-
DEB-1234162 to Cedar Creek LTER) programs, and the Institute on the Environment
(DG-0001-13). We also thank the Minnesota Supercomputer Institute for hosting project
data and the Institute on the Environment for hosting Network meetings. J. Siebert, M.
Sünnemann, and N. Eisenhauer acknowledge funding from the German Centre for
Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the DFG (FZT
118). M. N. Bugalho thanks the Portuguese Foundation for Science and Technology
(FCT) for funding through contract DL 57/2016/CP1382/CT0030 and projects UID/BIA/
50027/2013 and POCI-01-0145-FEDER-006821. M. N. Bugalho also thank Rui Alves for
granting access to the study site (comp.pt) We acknowledge the Portuguese Science
Foundation (FCT) for funding the research unit CEF (UIDB/00239/2020). We thank
Felix Gottschall for support with Figs. 2and 3and especially the design of the icons.
Author contributions
N.E. conceived the study; A.C.R. and N.E. developed the idea of a joint add-on project
within the Nutrient Network. E.T.B. and E.W.S. coordinate the Nutrient Network.
A.C.R., S.Z., and J.S. coordinated the global sampling campaign; J.D.B., L.B., D.M.B.,
E.T.B., M.N.B.; A.A.B.B., M.C.C., E.C.; K.F.D.; A.E.; N.H., J.M.H.K., A.S.M., R.L.M.,
J.L.M., S.A.P., J.N.P., E.W.S., R.S. and C.J.S. contributed data; J.S. and Y.H. analyzed the
data; J.S., M.S., and N.E. wrote the manuscript with input from all authors. M.S. revised
the manuscript with input from all authors (Table S5).
Funding
Open Access funding enabled and organized by Projekt DEAL.
Competing interests
The authors declare no competing interests.
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© The Author(s) 2023
1
German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Puschstrasse 4, 04103 Leipzig, Germany.
2
Institute of Biology,
Leipzig University, Puschstrasse 4, 04103 Leipzig, Germany.
3
Ecology and Biodiversity Group, Department of Biology, Utrecht University,
Padualaan 8, 3584 CH Utrecht, The Netherlands.
4
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Community Ecology,
Zuercherstrasse 111, 8903 Birmensdorf, Switzerland.
5
School of Environmental and Forest Sciences, University of Washington, Seattle, WA
98195, USA.
6
Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50010, USA.
7
USDA-ARS Rangeland
Resources & Systems Research Unit, Fort Collins, CO 80526, USA.
8
Department of Ecology, Evolution, and Behavior; University of Minnesota, St.
Paul, MN 55108, USA.
9
Centre for Applied Ecology Prof. Baeta Neves, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017
Lisbon, Portugal.
10
Department of Earth and Environmental Sciences, The University of Manchester, Oxford Road, Manchester M13 9PT, UK.
11
Forest Research Centre, School of Agriculture, University of Lisbon, Lisbon, Portugal.
12
Ecology, Behavior and Evolution Section, University of
California San Diego, 9500 Gilman Dr. #0116, La Jolla, California 92093-0116, USA.
13
Department of Ecology and Evolutionary Biology, University
of Colorado, Boulder, CO 80309, USA.
14
Ecology and Genetics Unit, University of Oulu, P.O. Box 8000, FI-90014 University of Oulu,
Oulu, Finland.
15
Helmholtz Center for Environmental Research UFZ, Department of Physiological Diversity, Permoserstrasse 15, 04318
Leipzig, Germany.
16
Mammal Research Institute, Department of Zoology & Entomology, University of Pretoria, Pretoria, South Africa.
17
Health &
Environmental Sciences Department, Xian Jiatong-Liverpool University, Suzhou, China.
18
Department of Integrative Biology, University of Guelph,
Guelph, Ontario N1G 2W1, Canada.
19
Department of Plant & Soil Sciences, University of Kentucky, Lexington, KY 40546, USA.
20
Arthur Rylah
Institute for Environmental Research, 123 Brown Street, Heidelberg, VIC 3084, Australia.
21
School of Biological Sciences, Monash University, 25
Rainforest Walk, Clayton, VIC 3800, Australia.
22
Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797,
Penrith, NSW 2751, Australia.
23
School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Albury, NSW 2640,
Australia.
24
Harry Butler Institute, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia.
25
Institute of Agriculture, The University
of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia.
26
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ,
UK.
27
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Forest Soils and Biogeochemistry, Zuercherstrasse 111, 8903
Birmensdorf, Switzerland.
28
These authors contributed equally: Julia Siebert, Marie Sünnemann. email: marie.suennemann@idiv.de
ARTICLE COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-023-05607-2
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