Greater trophic diversity of soil animal communities under land use and warmer climate

Greater trophic diversity of soil animal communities under land use and warmer climate | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article Greater trophic diversity of soil animal communities under land use and warmer climate Zheng Zhou, Nico Eisenhauer, Andrew Barnes, Melanie Pollierer, and 26 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5227558/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Mar, 2026 Read the published version in Nature Ecology & Evolution → Version 1 posted You are reading this latest preprint version Abstract More than half of all life on Earth lives belowground and regulates a wide range of ecosystem functions via their diverse trophic interactions. However, information on how trophic diversity of soil animals varies across functional groups and major environmental gradients is lacking. Here, we use stable isotope analysis (13C/12C and 15N/14N ratios) of 28 high-rank taxa of soil animals from 343 sites across 15 countries to inspect the variability in trophic diversity across climate regions and land-use types. We found that trophic diversity of soil-animals communities is higher for microbial than for detritus feeders and predators, and increases in agricultural ecosystems compared to woodlands (+38%) and in tropical compared to temperate climates (+53%). The larger trophic diversity was related to both exploration of more diverse basal resources and longer trophic chains, possibly because of greater niche partitioning in resource-limited environments. Overall, this first comprehensive assessment of soil animal trophic diversity highlights that soil animals may broaden their trophic niches under global change, which potentially buffers global-change impacts on ecosystem functions and stability in the short term, while the increased flexibility in foraging may pose risks with long-term biodiversity and ecosystem health implications. Biological sciences/Ecology/Stable isotope analysis Biological sciences/Ecology/Macroecology Biological sciences/Ecology/Biodiversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Main Soils are the most biodiverse habitats on Earth contributing to about 59% of global biodiversity 1 . Approximately 90% of the carbon fixed by plants in terrestrial ecosystems enters the belowground system 4 and is processed in soil food webs by microorganisms and invertebrate decomposers, with the latter serving as prey for predators 5,6 . Soil food webs are characterised by major energy fluxes in terrestrial ecosystems and trophic interactions among an exceptionally diverse spectrum of organisms occupying different niches. Consequently, soil food webs are of essential importance for carbon and nitrogen cycling, and thereby for ecosystem functions and services 7 . Beyond belowground processes, trophic interactions of soil organisms extend to the biodiversity and functionality of the aboveground system, fostering feedback loops between above- and belowground compartments of terrestrial ecosystems 5,8,9 . It has been shown that the functional diversity of soil animals (rather than species richness alone) is closely associated with litter decomposition, carbon and nutrient cycling and plant growth 2,10,11 . The diversity of functions driven by soil animals in food webs is based on their trophic diversity 2,7 . Unravelling the factors influencing trophic niches and trophic diversity is therefore crucial for understanding species coexistence and ecosystem stability 12,13 . Soil animals fulfil diverse roles within soil food webs and are often classified into functional groups 14,15 . For instance, detritivores serve as primary decomposers breaking down and consuming dead plant material, thereby contributing to decomposition processes 16,17 . Microbivores, as secondary decomposers, influence the growth and dispersal of prokaryotes and fungi, indirectly regulating nutrient cycling by changing the activity and composition of microbial communities 18–20 . Predators play a crucial role in population regulation and maintenance of biodiversity through top-down control, or alter habitat structure and nutrient cycling through ecological engineering effects 4,21,22 . Understanding the trophic diversity within these functional groups and how they respond to environmental changes, such as land use and climate, is crucial for understanding their resilience and the ecosystem functions they provide. Across the globe, land-use change alters the composition of ecological communities and often leads to a decline in ecosystem functions, which are at the core of sustainable development goals 23–25 . Land use changes the structure and energy flux in soil food webs, and also shifts trophic positions of soil animals 26–29 , ultimately influencing the stability and functioning of ecosystems 30 . However, it is still not clear how land use alters the trophic diversity of soil animals and whether land-use effects differ among functional groups of soil animals across climatic regions. Moreover, recent global assessments of soil animals demonstrated changes in richness and density with latitude 31–33 , highlighting that climate-driven changes in soil biodiversity and functions likely vary among biomes. However, existing large-scale studies focus on changes in the taxonomic and functional composition of soil communities, mostly of soil microorganisms 34,35 , while little is known about changes in the trophic diversity of soil animal functional groups and entire communities. Trophic diversity of animal functional groups is shaped by different, non-mutually exclusive mechanisms: large trophic diversity may be due to either large trophic diversity within taxa (niche expansion) or large trophic dissimilarity among taxa (niche partitioning) 36 . Besides, large trophic diversity may arise due to a broad range of basal resources or be due to a high number of trophic levels 37,38 . Trophic diversity is likely to respond to environmental changes with shifts in niche partitioning or expansion 37 . On the other hand, environmental changes, e.g., land-use intensification, may lead to increased generalism, resulting in trophic homogenization and thus lower diversity 37 . To our knowledge, no study has explored these mechanisms in soil animal communities, particularly across environmental gradients and functional groups. Here we complied an unprecedentedly comprehensive dataset comprising 15,893 records on 28 high-rank taxa of soil animals across 343 sites globally (Fig. 1), leveraging published and unpublished stable isotope ( 13 C, 15 N) data to investigate the differences in trophic diversity of soil animal taxa across functional groups and biomes, and explore the underlying mechanisms (niche expansion and partitioning). The concentration of 13 C in consumer tissue provides insight into basal resources used by consumers, while the concentration of 15 N reflects their trophic level 38,39 . We used corrected standard stable isotope ellipse areas in the 13 C - 15 N space to reflect trophic diversity, and used the isotopic distance among taxa within functional groups to reflect trophic dissimilarity 40–42 . We explored variation in trophic diversity and dissimilarity among functional groups of soil animals (detritivores, microbivores, predators and herbivores), and how these trophic traits are modulated by land use (woodlands vs. agricultural ecosystems) and climate (temperate vs tropical; temperature and precipitation). We aimed at assessing differences in trophic diversity among different functional groups of soil animals and how they change across biomes and land use types (Fig 1). We hypothesised that (1) trophic diversity is higher for microbivores and herbivores compared to detritivores and predators due to more pronounced niche partitioning among taxa within these functional groups; (2) trophic diversity of soil animals is larger in biomes with higher taxonomic diversity, specifically in woodlands and tropical regions compared to agricultural ecosystems and temperate regions, respectively. In addition, we explored the mechanisms contributing to differences among functional groups and biomes, and tested whether niche expansion or partitioning drives differences in trophic diversity among functional groups and biomes, and if variations in trophic diversity are related to both variations in basal resources and trophic levels. Trophic diversity differs among functional groups Overall, the trophic diversity and niche differentiation depend on the position of functional groups within the food web (Figs. 2a, S1a, Table S1). Conforming to our first hypothesis, the trophic diversity (SEAc) of microbivores was 53.3% and 51.9% greater than that of detritivores and predators, respectively (Fig. 2a, Table S1). Trophic diversity of taxa within functional groups exhibited similar patterns to the trophic diversity of their respective functional groups (Fig. 2a,b, Table S2). Both trophic diversity of individual taxa within functional groups (niche expansion) and trophic dissimilarity among taxa (niche partitioning) contributed to the overall trophic diversity of functional groups, with the influence of niche expansion being stronger (Figs. 2e,f, S2a, Table S5). Besides, larger trophic diversity resulted from both higher variability in δ 13 C and δ 15 N values as indicators of variability in the use of basal resources and in trophic level (Figs. 2c,d, S2b, Table S4). Microbivores exhibit larger trophic diversity compared to other functional groups, due to the combination of higher variability in basal resources and trophic levels (Fig. S3a,b). Presumably, the small body size of microbivores enables them to access a wide range of microhabitats within the pore space of soils 15,43 , allowing microbivores to exploit a diverse spectrum of microorganisms with distinct stable isotope compositions 38 . This may result in the occupation of a wider range of trophic niches and exploitation of a larger diversity of basal resources compared to e.g., detritivores. It has been suggested that microorganisms are trophic analogues of animals, occupying distinct trophic levels 44 . Consequently, by feeding on different microorganisms, microbivores are likely to vary in stable isotope values. In fact, it has been documented that microbivores, such as springtails and oribatid mites, occupy a wide range of trophic levels 45,46 , while detritivores have narrower ranges 47,48 , and this is confirmed by the large variation in δ 15 N values of microbivores in our study (Fig S3b, Table S4). Contrary to microbivores, detritivores are larger and more mobile, and are therefore likely to integrate a wider range of food resources by foraging at larger spatial scales than microbivores 49 . Combined with the high incidence of generalist feeding in detritivores 15,37 , this results in more homogeneous trophic niches and reduced overall trophic diversity. Predatory taxa had both smaller trophic diversity (Fig. 2b, Table S2) and trophic dissimilarity (Fig. S1a, Table S3) compared to other functional groups, indicating that they not only exhibit lower trophic diversity within each predator taxon (lower niche expansion), but also occupy similar trophic niches among different predator taxa (lower niche partitioning). This similarity contributed to the overall reduced trophic diversity among predators compared to other functional groups (Fig. 2a, Table S1). Soil predators tend to be generalists and hunt the most accessible prey, which are often r-strategists characterised by high abundance, high metabolism and limited defence, such as springtails 50 , which is also indicated by their smaller variations in δ 13 C values (Fig. S3a). This similarity in prey selection likely contributes to the similarity of trophic niches among predators 51 and emphasises their role in coupling different energy channels in soil food webs 8,52 . Herbivores had an intermediate trophic diversity and did not differ significantly from the other functional groups (Fig. 2a, Table S1). They showed large variability in δ 13 C but not in δ 15 N values (Fig. S3), indicating that the trophic diversity among belowground herbivores is predominantly a consequence of variations in the use of basal resources rather than trophic levels. Aboveground herbivore invertebrate taxa typically specialise in consuming specific plant species based on plant species-specific traits, including species-specific nutrient composition, N concentration and chemical defences, which can be attributed to coevolutionary dynamics between consumers and their host-plants 53,54 . These food preferences based on plant species-specific traits might similarly apply to soil herbivores, which mainly feed on roots 55 . Overall, our results showed that trophic diversity and niche differentiation of soil animals depend on the position of functional groups within the food web. Functional groups that couple different energy channels, either through less selective (detritivores) or generalistic (predators) feeding, exhibit lower trophic diversity and niche differentiation. Higher trophic diversity in agricultural and tropical systems Across the globe, intensive land use is considered a threat to soil biodiversity 25,56 . However, in contrast to our second hypothesis, the trophic diversity of soil animals tended to be greater in agricultural systems than in woodlands (on average by 35.8 ± 11.7%; Fig. 3a; Table S6), being significantly greater by 37.3 ± 17.8%, 57.6 ± 16.7% and 69.4 ± 17.0% in detritivores, microbivores and predators, respectively. Similar to the present study, a study using the same isotopic method showed that trophic diversity of birds is higher in disturbed (urban) than in natural ecosystems, with generalists using the novel niches created by human modification 36 . Agricultural land use typically reduces the supply of aboveground residues to soil animals due to the removal of crops, thereby aggravating resource shortage of soil animals 57,58 . However, agricultural land use is also associated with increased input of nutrients via fertilisation, thereby potentially augmenting resource heterogeneity 28,59 , which likely contributed to the larger variations in δ 15 N than δ 13 C values in agricultural than woodland ecosystems (Fig. S4b). Although most soil animals are trophic generalists, they exhibit specific preferences for similar resources when resources are abundant, thereby living as so-called 'choosy generalists' 15,60,61 . Abundant resource supply might result in niche homogenization due to animals predominantly using the resources in ample supply as may be the case in woodlands, which typically have thicker litter layers compared with agricultural systems. Conversely, scarcity of resources may result in trophic differentiation by forcing animals to also exploit non-preferred resources 37 . In fact, agricultural land use has been shown to increase trophic diversity among individuals in springtail communities 62 . In agricultural systems, soil animals may partition their niches due to restricted and heterogeneous resource supply, and may also opportunistically incorporate novel resources 63 , thus leading to higher trophic diversity at the community level. This was confirmed by lower trophic dissimilarity of the taxa within the same functional group (less niche partitioning, i.e., niche homogeneity) in woodlands compared to agricultural systems (Fig. S1b; Table S3). Furthermore, the trophic dissimilarity between functional groups, such as microbivores and detritivores, was also larger in agricultural than woodland ecosystems (Fig. S5b). The mismatch between biodiversity and trophic diversity indicates that soil animals may be able to adapt their trophic niches to environmental changes, thus partly maintaining their populations and associated soil functions. Confirming our second hypothesis, trophic diversity of soil animals tended to be greater in tropical than in temperate regions (on average by 46.6 ± 11.7%; Fig. 3b, Tables S6), being significantly greater by 60.6 ± 17.8%, 43.1 ± 16.7% and 62.5 ± 17.0% in detritivores, microbivores and predators, respectively. Recent global compilations reported soil animals, including macrofauna, mesofauna and microfauna, having lower density but higher taxonomic richness in the tropics than at higher latitudes 31–33 . Thus, the larger trophic diversity in the tropics may be related to increased taxonomic richness, which is also indicated by our results of increasing trophic diversity with taxon richness (Fig. S6, Table S7). Further, it also aligns with higher trophic dissimilarity of taxa within the same functional group (niche partitioning) in the tropics compared to temperate systems (Figs. S1b, S4a, Table S3). However, even when accounting for the effect of taxonomic richness, effects of climate on trophic diversity remained strong (Table S7). Presumably, at least in part this may be related to low accumulation of litter and the depletion of soil organic matter in the tropics 64 . Low-latitude ecosystems such as tropical rainforests typically develop on old and weathered soils deficient in nutrients, being particularly phosphorus-limited 65 , which is also reflected by decreasing litter nutrient concentrations towards the tropics 66 . Animals in the tropics exhibit higher metabolism and predation rates than those in high latitude ecosystems, leading to intensified interactions and stress 33,67 . Consequently, generalist species may compete more intensely for high-quality food resources that are scarce. We also tested effects of land use and climate on trophic diversity at higher taxonomic resolution, namely at family-, genus- and species level. This analysis confirmed the pattern of higher trophic diversity in agricultural systems and in the tropics to be robust across taxonomic scales (Fig. S7, Table S8). Thus, except for higher taxonomic richness, limitations in the quality and quantity of food resources, and increased interactions may drive niche partitioning among soil animals, as indicated by larger trophic dissimilarity at both the level of high-ranking taxa and species. Therefore, the higher trophic diversity of soil animals in the tropics is likely due to both niche partitioning and niche expansion. Climatic drivers of trophic diversity Structural equation modelling (SEM) was used to explore which environmental factors are responsible for the observed differences in trophic diversity between high-latitude and tropical regions. SEM indicates that trophic diversity of, and distance among, taxa increased with annual temperature (Fig 4). Higher temperature is associated with increased metabolism and predation rates among invertebrate animals, intensifying interactions and predation stress 33,67 , and resulting in the partitioning of trophic niches and increased trophic diversity of soil animals. However, higher annual precipitation resulted in similar trophic positions of different taxa (Fig 4). Soil animals, especially smaller taxa, heavily rely on soil moisture 68,69 . Higher moisture increases the availability of resources, which may lead to niche homogenization among soil taxa and consequently reduce trophic diversity. Meanwhile, excessive moisture may also be detrimental due to water filling of soil pores and anoxic conditions 43 . This may result in the loss of habitable space for soil animals, consequently increasing the similarity in trophic niches among taxa and decreasing the trophic diversity of soil animals. Overall, the effects of higher temperature and higher precipitation partly cancelled each other out and resulted in larger trophic diversity of soil animals in the tropics. Conclusions and implications Based on a large and unique dataset on stable isotope ratios of soil animals, we analysed the trophic diversity of major functional groups of soil animals and their variations across land-use systems and biomes. Our findings indicate that microbivores are more trophically diverse than detritivores and predators, suggesting that the former play more diverse functional roles in soil food webs. Additionally, trophic diversity of soil animals was higher in agricultural systems than in woodlands despite the decline in biodiversity, suggesting that soil animals may broaden their trophic niches when faced with resource shortages and frequent disturbances. The ability of soil animals to broaden their trophic niches in response to global changes, such as land-use and climate change, may help buffer ecosystems against instability by promoting resilience through diversified resource use. Specific functional groups of soil animals, particularly microbial feeders, could enhance ecosystem functions like nutrient cycling and decomposition by exploiting underutilised or rare resources. This resilience in trophic niches suggests that soil communities may adapt in ways that maintain ecosystem stability, but also highlights potential risks of increasing flexible foraging behaviour 70 , with implications for long-term biodiversity and ecosystem health. Methods Field sites and sampling The study was based on extensive data collection and analysis across 343 study sites and 15 countries. About half of the data were published before (53.6%) 46–48,62,71–93 , while other data were compiled for this study. The dataset comprised 15,893 sample records of paired δ 13 C and δ 15 N values in soil animals distributed across four climatic regions: subarctic, temperate, subtropical, and tropical. The investigated ecosystem types included woodlands, agricultural systems and grasslands. Mean annual precipitation and temperature were included as abiotic drivers and were retrieved from WorldClim 94 based on latitude and longitude. The details of study sites are listed in Table S8. For details on the sampling methods for published data see 46–48,62,71–93 . For unpublished data, standard extraction methods were used. Nematodes were sampled by extracting 5 cm diameter soil cores encompassing the litter layer and the top 0–5 cm of the mineral soil. Soil meso- and macrofauna were sampled by using heat Berlese or Kempson extractors 95 and preserved in 70-96% ethanol. Sampling methods deviations are listed directly in the Table S8. Animals were classified into 26 high-rank taxonomic groups and further into five major functional groups as follows: herbivores (Hemiptera, Orthoptera, Thysanoptera, and Lepidoptera), detritivores (Lumbricina, Diplopoda, Isopoda, Isoptera, Dermaptera, Blattodea, Gastropoda, and Enchytraeidae), microbivores (Collembola, Oribatida, Nematoda, Protura, Prostigmata, Psocoptera, and Symphyla) and predators (Araneae, Chilopoda, Diplura, Formicidae, Mesotigmata, Opiliones, and Pseudoscorpiones) and groups displaying mixed feeding (Diptera and Coleoptera) 15,96 . It has been shown that high-rank animal taxa in soil typically are trophically and functionally consistent 96 . Stable isotope analysis Animals were identified to family- (86.9%), genus- (70.1%) or species- level (58.5%) before being processed for stable isotope analysis. Before stable isotope analysis, animals were dried at 50-60°C for 24 h, then weighed and enclosed in tin capsules; sample weights ranged from 0.01 to 1.0 mg. For small-sized animals, the whole body of individual animals were used for stable isotope analysis, with multiple individuals were bulked when more biomass was required, for large-sized animals we used body parts dominated by muscle tissue (e.g., legs) 97 . Stable isotope ratios of 13 C/ 12 C and 15 N/ 14 N were measured using a system comprising an elemental analyser and a mass spectrometer; for details of the individual set ups see Table S8. Ratios between the heavy isotope and the light isotope ( 13 C/ 12 C, 15 N/ 14 N; R) were presented in parts per thousand relative to the standard using the delta notation, denoted as δ 13 C or δ 15 N = (R sample /R standard − 1) × 1000 (‰). Vienna PD Belemnite and atmospheric nitrogen served as the standards for 13 C and 15 N, respectively. Calculation of trophic diversity and dissimilarity Trophic diversity of soil animals can be determined by computing the standard ellipse area (SEA) based on the position of soil animals within the δ 13 C-δ 15 N biplot of taxonomic and functional groups at each site. We used corrected standard ellipse area (SEAc) instead of SEA in our study, which is more robust in handling small and variable sample sizes than SEA 40 . The relationship between SEA and SEAc can be formulated as SEAc = SEA(n sample size -1)(n sample size -2) -1 . We visualise some examples of the SEAc of detritivores, microbivores and predators in woodland the agricultural systems by randomly picked 5 sites for each group (Fig. S8). Moreover, to further mitigate potential bias stemming from small sample sizes, ellipses were exclusively computed for taxonomic and functional groups that consisted of five or more samples per site. To assess trophic dissimilarity among taxonomic groups within each functional group, we calculated the mean pairwise distance between the centroids of isotopic-positions of taxonomic groups within each functional group. We used uncalibrated stable isotope values (δ 13 C and δ 15 N) for assessing trophic diversity and trophic dissimilarity of soil animals, as calibration using litter δ 13 C and δ 15 N values did not significantly affect SEAc and trophic dissimilarity. We calculated the standard deviation of δ 13 C and δ 15 N values within the same functional group at each site. These values served as indicators of the variation in both basal resource use and trophic position among functional groups. Statistical analyses All analyses were done in R 4.0.3 98 . To assess the effects of land use and climate on the SEAc and trophic dissimilarity of soil animals, we selected the subsets from tropical/temperate and agricultural systems/ woodlands from the whole dataset. We fitted linear mixed-effects models (LMMs) using log-transformed SEAc and trophic dissimilarity, and then applied contrasts between tropical and temperate ecosystems, as well as between agricultural systems and woodlands to estimate effect sizes. We conducted three separate LMMs for log-transformed SEAc of functional groups, SEAc of taxonomic groups and trophic dissimilarity. The models included functional groups (herbivores, detritivores, microbivores and predators), land use (agricultural systems, woodlands), biome (tropical, temperate) and their interactions as fixed effects, with site included as random effect. For estimating effect sizes of land use and climate, we used the emmeans package to compute the estimated marginal means in the linear models. Then, we used the contrast function from the emmeans package to calculate contrasts between temperate versus tropical and woodland versus agriculture 99 . Additionally, we built another model and included sampling number and family richness as covariates to inspect their effects on the log-transformed SEAc of functional groups. The models included functional groups, land use, climate, sampling number and family richness as fixed effects, with site included as random effect. We checked model assumptions of the most parsimonious models by fitting model residuals versus the results of fitted models. To elucidate the drivers behind larger functional group SEAc, we employed two separate LMMs. One model included SEAc of taxonomic groups and trophic dissimilarity as explanatory variables, while the other explored variations in δ 13 C and δ 15 N as separate explanatory variables. We then used the estimated value of the coefficient for each independent variable to estimate their contribution to SEAc of functional groups. For exploring whether temperature or precipitation are responsible for the observed differences in trophic diversity among the four latitudinal zones, we used structural equation modelling (SEM) employing maximum likelihood estimation to provide insight into how environmental factors affected trophic diversity of soil animals. The SEM included MTP and MAP as direct climatic effects. Furthermore, we included SEAc of taxonomic groups and trophic dissimilarity as mediators affected by environmental factors. The data was z-score scaled before SEM analysis. To determine the goodness of fit of the model, we used χ 2 -test, the comparative fit index (CFI) > 0.95 and the standardised root-mean-square residual (SRMR) with values ≤ 0.05 as threshold for significance 100 . Our SEM adequately described the data (p = 0.33, df = 3, CFI = 0.999, RMSEA = 0.022, SRMR = 0.007, AIC = 1724.75). We also built a competing model that allows for direct climate effects on SEAc, but the model had higher AIC (1725.32), and both MTP and MAP had no significant effects on SEAc (Fig. S9), thus we used the previous model in the main text. The SIBER package was used for calculating the trophic diversity of soil animals 40 . The lme4 package was used to fit LMMs 101 and the emmeans package to compute the estimated marginal means in the linear models 99 . The SEM analysis was performed with the lavaan package 102 . All mixed models were visually checked to meet the assumption of residual homogeneity of variance. Results were visualised using the ggplot2 package 103 . Declarations Acknowledgements The work was supported by the Alexander von Humboldt foundation in the framework of a Research group linkage programme 1071297 - RUS - IP “Structure and functioning of belowground food webs across temperate and tropical eco- systems”. Z.Z. was supported by the China Scholarship Council (CSC, 202004910314). A.M.P. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the framework of the Emmy Noether program (Project number 493345801) and iDiv (DFG–FZT 118, 202548816). S.S. and M.J. acknowledge support by DFG in the framework of the collaborative German–Indonesian research project CRC990 – EFForTS (192626868 – SFB 990). M.M.P. was funded by the DFG Priority Program 1374 ‘BiodiversityExploratories’ (SCHE 376/38- 2). N.E. acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG; German Centre for Integrative Biodiversity Research, FZT118; Ei 862/29-1; Ei 862/31-1). References Anthony, M. A., Bender, S. 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Journal of Statistical Software 67 , 1–48 (2015). Rosseel, Y. lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software 48 , 1–36 (2012). Wickham, H. Ggplot2: Elegant Graphics for Data Analysis . (Springer-Verlag New York, 2016). Additional Declarations There is NO Competing Interest. Supplementary Files FigS1Paireddistance.pdf Fig S1. Trophic dissimilarity (mean pairwise stable isotopic distance among the trophic-position centroids) of taxa in each functional group (a) and their variation between climatic regions and land-u FigS2contributionsacorssfunctionalgroups.pdf Fig S2. The estimated value of the coefficient for (a) taxa SEAc and taxa dissimilarity in different functional groups of soil animals and (b) variation in 13C and 15N values to SEAc of different func FigS3Variationof13Cand15N.pdf Fig S3. Site-based variation of δ13C (a) and δ15N (b) in different functional groups, average values and 95% confidence interval, the number in the bar indicate the number of replicated sites. FigS4contributionsindifferentecosystems.pdf Fig S4 The estimated value of the coefficient for (a) SEAc and taxa dissimilarity (b) Variation of 13C and 15N to estimate their contribution to SEAc of different land use systems (woodland, agricultu FigS5Distancebetweenmicrobivoresanddetritivores.pdf Fig S5 Trophic dissimilarity of microbivores and detritivores between climatic regions (a) and land-use systems (b). FigS6SEAcsamplingsizeandrichness.pdf Fig S6. The relation between sampling size and family richness with log-transformed SEAc (trophic diversity) of functional groups. FigS7SEAcacrosstaxonomiclevels.pdf Fig S7 The SEAc across different taxonomic levels in different land-use systems (woodland, agricultural systems) and climatic regions (temperate, tropical), means ± standard error. FigS8VisualizationofSEAcforrandomlypickedsites.pdf Fig S8 Visualization of SEAc of (a) detritivores, (b) microbivores and (c) predators for randomly picked five sites in woodland and agricultural systems. Each dot represents one individual in woodland FigS9CompetingSEM.pptx Fig S9. Competing structural equation model illustrating the effects of climatic variables on trophic niches of soil animals with no significant direct effects on trophic diversity of functional grou TablesS1S7.xlsx Tables S1-7 Cite Share Download PDF Status: Published Journal Publication published 16 Mar, 2026 Read the published version in Nature Ecology & Evolution → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Alexei","middleName":"","lastName":"Tiunov","suffix":""},{"id":372178472,"identity":"1a9ddefc-e5f6-497a-8816-34b1d4f9bf75","order_by":28,"name":"Stefan Scheu","email":"","orcid":"https://orcid.org/0000-0003-4350-9520","institution":"University of Goettingen, J.F. Blumenbach Institute of Zoology and Anthropology","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Scheu","suffix":""},{"id":372178473,"identity":"d728bb96-78db-4de6-ac80-66cdf2e63cf7","order_by":29,"name":"Anton Potapov","email":"","orcid":"https://orcid.org/0000-0002-4456-1710","institution":"University of Göttingen","correspondingAuthor":false,"prefix":"","firstName":"Anton","middleName":"","lastName":"Potapov","suffix":""}],"badges":[],"createdAt":"2024-10-08 19:05:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5227558/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5227558/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41559-026-03014-4","type":"published","date":"2026-03-16T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":67949122,"identity":"13c0a079-d9fa-4d28-b64c-a4ecbf973f57","added_by":"auto","created_at":"2024-10-31 15:05:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":568098,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of the 343 sampling sites across 15 countries. \u003c/strong\u003ePoint size in (a) represents the number of sites at the respective locality. b-s: soil animals considered in this study, including nematodes (Nematoda) (b), enchytraeid worms (Enchytraeidae) (c), earthworms (Lumbricina) (d), moss mites (Oribatida) (e), predatory mites (Mesostigmata) (f), spiders (Araneae) (g), springtails (Collembola) (h), proturans (Protura) (i), bristletails (Diplura) (j), garden centipedes (Symphyla) (k), sucking mites (Prostigmata) (l), harvestmen (Opiliones) (m), woodlice (Isopoda) (n), millipedes (Diplopoda) (o), centipedes (Chilopoda) (p), ants (Formicidae) (q), false scorpions (Pseudoscorpiones) (r), and beetles (Coleoptera) (s). The right panel illustrates the hierarchical approach of the study: (1) assessing differences in trophic diversity among different functional groups of soil animals, (2) examining how trophic diversity of soil animals changes across biomes and land-use types, and (3) understanding the mechanisms of changes in trophic diversity, e.g., niche expansion or partitioning. Photographs by Frank Ashwood (c-s) and Haifeng Yin (b).\u003c/p\u003e","description":"","filename":"Fig1Map.png","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/5d569b443f6b211630e440fe.png"},{"id":67948884,"identity":"5043146a-cb89-4386-b04f-423e08e2d1c2","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":439694,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrophic diversity (calibrated stable isotope ellipse area; SEAc) of different functional groups of soil animals (colour coded)\u003c/strong\u003e. (a) Trophic diversity of functional groups, means and 95% confidence intervals. (b) Trophic diversity of each taxon, means ± standard errors, numbers in bars indicate the number of replicate sites. (c) Relationship between log-transformed trophic diversity and variations in δ\u003csup\u003e13\u003c/sup\u003eC values in each functional group. (d) Relationship between log-transformed trophic diversity and variations in δ\u003csup\u003e15\u003c/sup\u003eN values in each functional group. (e) Relationship between trophic diversity of functional groups and the mean trophic diversity of taxa in each functional group. (f) Relationship between trophic diversity of functional groups and the mean pairwise distance between the centroids of trophic-positions of taxa in each functional group. Black lines denote overall model fit and coloured lines indicate different functional groups, all linear relationships in the figure were significant. R\u003csup\u003e2\u003c/sup\u003e values represent the proportion of variance explained across functional groups. Asterisks indicate significant effects: *** p\u0026lt;0.001. For details of the model results see Tables S1,2,4 and 5.\u003c/p\u003e","description":"","filename":"Fig2SEAofFGandtaxa.png","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/e7bd69a0039358c39d7f3344.png"},{"id":67949120,"identity":"258e8954-5536-4a14-b92b-def298748617","added_by":"auto","created_at":"2024-10-31 15:05:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":220052,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrophic diversity (calibrated stable isotope ellipse area; SEAc) of functional groups of soil animals\u003c/strong\u003e in (a) different land-use types (woodlands, agricultural systems) and (b) climatic regions (temperate, tropical); means with 95% confidence intervals. (c) Effects of land use on trophic diversity (SEAc) of different functional groups of soil animals in tropical and temperate regions; effect sizes are given as log-response ratios (with 95% confidence intervals) of contrasts between agriculture and woodland; asterisks indicate significant effects, (*) p \u0026lt; 0.1, * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Fig3SEALanduseandclimate.png","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/b59f06bcae6ab1078b205f4c.png"},{"id":67948888,"identity":"07c614f8-bf94-43e2-ac98-e97ea6388ec8","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48890,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural equation model illustrating the effects of climatic variables on trophic niches of soil animals\u003c/strong\u003e, showing how temperature and precipitation affect the trophic diversity of functional groups via niche partitioning (trophic diversity of taxa) and niche expansion (trophic dissimilarity among taxa). Numbers adjacent to arrows are standardised path coefficients that show effect sizes and directions (blue – positive, red – negative) of the relationships; arrow width is proportional to the strength of path coefficients. Grey arrows represent non-significant paths; *p \u0026lt; 0.05, **p \u0026lt; 0.01, and ***p \u0026lt; 0.001. Black numbers next to response variables in the model denote the proportion of variance explained based on R\u003csup\u003e2\u003c/sup\u003e.\u0026nbsp; Our SEM adequately described the data (p = 0.33, df = 3, CFI = 0.999, RMSEA = 0.022, SRMR = 0.007).\u003c/p\u003e","description":"","filename":"Fig4SEM.png","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/58b65c3f8d3ed50d5ed982a5.png"},{"id":104777783,"identity":"a68225e5-addf-49d5-8f7a-ee0ee58c2d0d","added_by":"auto","created_at":"2026-03-17 07:12:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2454531,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/59cdfa88-6494-4e5f-8891-1b26b8487501.pdf"},{"id":67949785,"identity":"8b3e8310-5693-472c-ac7b-0fba12966151","added_by":"auto","created_at":"2024-10-31 15:13:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":128524,"visible":true,"origin":"","legend":"Fig S1. Trophic dissimilarity (mean pairwise stable isotopic distance among the trophic-position centroids) of taxa in each functional group (a) and their variation between climatic regions and land-u","description":"","filename":"FigS1Paireddistance.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/2b526a1c5f78e56c9a5bdf69.pdf"},{"id":67949119,"identity":"ec19e31c-dd09-490c-9281-6ce8c47fc36b","added_by":"auto","created_at":"2024-10-31 15:05:56","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":100816,"visible":true,"origin":"","legend":"Fig S2. The estimated value of the coefficient for (a) taxa SEAc and taxa dissimilarity in different functional groups of soil animals and (b) variation in 13C and 15N values to SEAc of different func","description":"","filename":"FigS2contributionsacorssfunctionalgroups.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/670b283bb20b2519fd6e77da.pdf"},{"id":67948898,"identity":"5e53b53a-bb55-47b8-96ff-25dd4870a3ec","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":160395,"visible":true,"origin":"","legend":"Fig S3. Site-based variation of \u0026#x03B4;13C (a) and \u0026#x03B4;15N (b) in different functional groups, average values and 95% confidence interval, the number in the bar indicate the number of replicated sites.","description":"","filename":"FigS3Variationof13Cand15N.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/7204345edbc13830a6c2a517.pdf"},{"id":67948894,"identity":"0fceee56-3bf6-4de4-919e-54c089a8519e","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":6747,"visible":true,"origin":"","legend":"\u003cp\u003eFig S4 The estimated value of the coefficient for (a) SEAc and taxa dissimilarity (b) Variation of 13C and 15N to estimate their contribution to SEAc of different land use systems (woodland, agricultu\u003c/p\u003e","description":"","filename":"FigS4contributionsindifferentecosystems.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/8d2e5265c78e0df2c68ae8b1.pdf"},{"id":67948885,"identity":"7b90ee3e-56bc-4e91-9a98-f59cac6b2ec8","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5032,"visible":true,"origin":"","legend":"Fig S5 Trophic dissimilarity of microbivores and detritivores between climatic regions (a) and land-use systems (b).","description":"","filename":"FigS5Distancebetweenmicrobivoresanddetritivores.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/96f7b70b52344d8a86aecd82.pdf"},{"id":67948892,"identity":"3a471292-5a3b-4963-acbf-9b9f824a3d7b","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":287731,"visible":true,"origin":"","legend":"\u003cp\u003eFig S6. The relation between sampling size and family richness with log-transformed SEAc (trophic diversity) of functional groups.\u003c/p\u003e","description":"","filename":"FigS6SEAcsamplingsizeandrichness.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/ddd30b8c38f13fd8b3ca77ab.pdf"},{"id":67948896,"identity":"db713ca4-6f50-4509-a541-2efa1de8eeeb","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":31357,"visible":true,"origin":"","legend":"\u003cp\u003eFig S7 The SEAc across different taxonomic levels in different land-use systems (woodland, agricultural systems) and climatic regions (temperate, tropical), means ± standard error.\u003c/p\u003e","description":"","filename":"FigS7SEAcacrosstaxonomiclevels.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/9deecd29bdad75df412b4512.pdf"},{"id":67949123,"identity":"ee62c934-6251-46c7-a498-056894761248","added_by":"auto","created_at":"2024-10-31 15:05:56","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":76502,"visible":true,"origin":"","legend":"\u003cp\u003eFig S8 Visualization of SEAc of (a) detritivores, (b) microbivores and (c) predators for randomly picked five sites in woodland and agricultural systems. Each dot represents one individual in woodland\u003c/p\u003e","description":"","filename":"FigS8VisualizationofSEAcforrandomlypickedsites.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/9060ffc9d23ae43285b734ba.pdf"},{"id":67949124,"identity":"accc164d-63e5-4230-88fb-1d966690b201","added_by":"auto","created_at":"2024-10-31 15:05:56","extension":"pptx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":63572,"visible":true,"origin":"","legend":"\u003cp\u003eFig S9. Competing structural equation model illustrating the effects of climatic variables on trophic niches of soil animals with no significant direct effects on trophic diversity of functional grou\u003c/p\u003e","description":"","filename":"FigS9CompetingSEM.pptx","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/56959f718c7563672827def8.pptx"},{"id":67948890,"identity":"d4a3c3c7-71bd-4e6d-826d-927c7fe6b7b5","added_by":"auto","created_at":"2024-10-31 14:57:56","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":16060,"visible":true,"origin":"","legend":"\u003cp\u003eTables S1-7\u003c/p\u003e","description":"","filename":"TablesS1S7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5227558/v1/368587656a5f84a551436a44.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Greater trophic diversity of soil animal communities under land use and warmer climate","fulltext":[{"header":"Main","content":"\u003cp\u003eSoils are the most biodiverse habitats on Earth contributing to about 59% of global biodiversity\u003csup\u003e1\u003c/sup\u003e. Approximately 90% of the carbon fixed by plants in terrestrial ecosystems enters the belowground system\u003csup\u003e4\u003c/sup\u003e and is processed in soil food webs by microorganisms and invertebrate decomposers, with the latter serving as prey for predators\u003csup\u003e5,6\u003c/sup\u003e. Soil food webs are characterised by major energy fluxes in terrestrial ecosystems and trophic interactions among an exceptionally diverse spectrum of organisms occupying different niches. Consequently, soil food webs are of essential importance for carbon and nitrogen cycling, and thereby for ecosystem functions and services\u003csup\u003e7\u003c/sup\u003e. Beyond belowground processes, trophic interactions of soil organisms extend to the biodiversity and functionality of the aboveground system, fostering feedback loops between above- and belowground compartments of terrestrial ecosystems\u003csup\u003e5,8,9\u003c/sup\u003e. It has been shown that the functional diversity of soil animals (rather than species richness alone) is closely associated with litter decomposition, carbon and nutrient cycling and plant growth\u003csup\u003e2,10,11\u003c/sup\u003e. The diversity of functions driven by soil animals in food webs is based on their trophic diversity\u0026nbsp;\u003csup\u003e2,7\u003c/sup\u003e. Unravelling the factors influencing trophic niches and trophic diversity is therefore crucial for understanding species coexistence and ecosystem stability\u003csup\u003e12,13\u003c/sup\u003e.\u0026nbsp;Soil animals fulfil diverse roles within soil food webs and are often classified into functional groups\u003csup\u003e14,15\u003c/sup\u003e. For instance, detritivores serve as primary decomposers breaking down and consuming dead plant material, thereby contributing to decomposition processes\u003csup\u003e16,17\u003c/sup\u003e. Microbivores, as secondary decomposers, influence the growth and dispersal of prokaryotes and fungi, indirectly regulating nutrient cycling by changing the activity and composition of microbial communities\u003csup\u003e18\u0026ndash;20\u003c/sup\u003e. Predators play a crucial role in population regulation and maintenance of biodiversity through top-down control, or alter habitat structure and nutrient cycling through ecological engineering effects\u003csup\u003e4,21,22\u003c/sup\u003e. Understanding the trophic diversity within these functional groups and how they respond to environmental changes, such as land use and climate,\u0026nbsp;is crucial for understanding their resilience and the ecosystem functions they provide.\u003c/p\u003e\n\u003cp\u003eAcross the globe, land-use change alters the composition of ecological communities and often leads to a decline in ecosystem functions, which are at the core of sustainable development goals\u003csup\u003e23\u0026ndash;25\u003c/sup\u003e. Land use changes the structure and energy flux in soil food webs, and also shifts trophic positions of soil animals\u003csup\u003e26\u0026ndash;29\u003c/sup\u003e,\u0026nbsp;ultimately influencing the stability and functioning of ecosystems\u003csup\u003e30\u003c/sup\u003e. However, it is still not clear how land use alters the trophic diversity of soil animals and whether land-use effects differ among functional groups of soil animals across climatic regions. Moreover, recent global assessments of soil animals demonstrated changes in richness and density with latitude\u003csup\u003e31\u0026ndash;33\u003c/sup\u003e, highlighting that climate-driven changes in soil biodiversity and functions likely vary among biomes. However, existing large-scale studies focus on changes in the taxonomic and functional composition of soil communities, mostly of soil microorganisms\u003csup\u003e34,35\u003c/sup\u003e,\u0026nbsp;while little is known about changes in the trophic diversity of soil animal functional groups and entire communities.\u003c/p\u003e\n\u003cp\u003eTrophic diversity of animal functional groups is shaped by different, non-mutually exclusive mechanisms: large trophic diversity may be due to either large trophic diversity within taxa (niche expansion) or large trophic dissimilarity among taxa (niche partitioning)\u003csup\u003e36\u003c/sup\u003e. Besides, large trophic diversity may arise due to a broad range of basal resources or be due to a high number of trophic levels\u003csup\u003e37,38\u003c/sup\u003e. Trophic diversity is likely to respond to environmental changes with shifts in niche partitioning or expansion\u003csup\u003e37\u003c/sup\u003e. On the other hand, environmental changes, e.g., land-use intensification, may lead to increased generalism, resulting in trophic homogenization and thus lower diversity\u0026nbsp;\u003csup\u003e37\u003c/sup\u003e. To our knowledge, no study has explored these mechanisms in soil animal communities, particularly across environmental gradients and functional groups.\u003c/p\u003e\n\u003cp\u003eHere we complied an unprecedentedly comprehensive dataset comprising 15,893 records on 28 high-rank taxa of soil animals across 343 sites globally (Fig. 1), leveraging published and unpublished stable isotope (\u003csup\u003e13\u003c/sup\u003eC, \u003csup\u003e15\u003c/sup\u003eN) data to\u0026nbsp;investigate the differences in trophic diversity of soil animal taxa across functional groups and biomes, and explore the underlying mechanisms (niche expansion and partitioning).\u0026nbsp;The concentration of \u003csup\u003e13\u003c/sup\u003eC in consumer tissue provides insight into basal resources used by consumers, while the concentration of \u003csup\u003e15\u003c/sup\u003eN reflects their trophic level\u003csup\u003e38,39\u003c/sup\u003e. We used corrected standard stable isotope ellipse areas in the \u003csup\u003e13\u003c/sup\u003eC - \u003csup\u003e15\u003c/sup\u003eN space to reflect trophic diversity, and used the isotopic distance among taxa within functional groups to reflect trophic dissimilarity\u003csup\u003e40\u0026ndash;42\u003c/sup\u003e. We explored variation in trophic diversity and dissimilarity among functional groups of soil animals (detritivores, microbivores, predators and herbivores), and how these trophic traits are modulated by land use (woodlands vs. agricultural ecosystems) and climate (temperate vs tropical; temperature and precipitation). We aimed at assessing differences in trophic diversity among different functional groups of soil animals and how they change across biomes and land use types (Fig 1). We hypothesised that (1) trophic diversity is higher for microbivores and herbivores compared to detritivores and predators due to more pronounced niche partitioning among taxa within these functional groups; (2) trophic diversity of soil animals is larger in biomes with higher taxonomic diversity, specifically in woodlands and tropical regions compared to agricultural ecosystems and temperate regions, respectively. In addition, we explored the mechanisms contributing to differences among functional groups and biomes, and tested whether niche expansion or partitioning drives differences in trophic diversity among functional groups and biomes, and if variations in trophic diversity are related to both variations in basal resources and trophic levels.\u003c/p\u003e"},{"header":"Trophic diversity differs among functional groups","content":"\u003cp\u003eOverall,\u0026nbsp;the\u0026nbsp;trophic diversity and niche differentiation depend on the position of functional groups within the food web (Figs. 2a, S1a, Table S1). Conforming to our first hypothesis,\u0026nbsp;the trophic diversity (SEAc) of microbivores was 53.3% and 51.9% greater than that of detritivores and predators, respectively (Fig. 2a, Table S1). Trophic diversity of taxa within functional groups exhibited similar patterns to the trophic diversity of their respective functional groups (Fig. 2a,b, Table S2). Both trophic diversity of individual taxa within functional groups (niche expansion) and trophic dissimilarity among taxa (niche partitioning) contributed to the overall trophic diversity of functional groups, with the influence of niche expansion being stronger (Figs. 2e,f, S2a, Table S5). Besides, larger trophic diversity resulted from both higher variability in \u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values as indicators of variability in the use of basal resources and in trophic level (Figs. 2c,d, S2b, Table S4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMicrobivores exhibit larger trophic diversity compared to other functional groups, due to the combination of higher variability in basal resources and trophic levels (Fig. S3a,b). Presumably, the small body size of microbivores enables them to access a wide range of microhabitats within the pore space of soils\u003csup\u003e15,43\u003c/sup\u003e, allowing microbivores to exploit a diverse spectrum of microorganisms with distinct stable isotope compositions\u003csup\u003e38\u003c/sup\u003e. This may result in the occupation of a wider range of trophic niches and exploitation of a larger diversity of basal resources compared to e.g., detritivores. It has been suggested that microorganisms are trophic analogues of animals, occupying distinct trophic levels\u003csup\u003e44\u003c/sup\u003e. Consequently, by feeding on different microorganisms, microbivores are likely to vary in stable isotope values. In fact, it has been documented that microbivores, such as springtails and oribatid mites, occupy a wide range of trophic levels\u003csup\u003e45,46\u003c/sup\u003e,\u0026nbsp;while detritivores have narrower ranges\u003csup\u003e47,48\u003c/sup\u003e,\u0026nbsp;and this is confirmed by the large variation in \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values of microbivores in our study (Fig S3b, Table S4). Contrary to microbivores, detritivores are larger and more mobile, and are therefore likely to integrate a wider range of food resources by foraging at larger spatial scales than microbivores\u003csup\u003e49\u003c/sup\u003e. Combined with the high incidence of generalist feeding in detritivores\u003csup\u003e15,37\u003c/sup\u003e, this results in more homogeneous trophic niches and reduced overall trophic diversity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePredatory taxa had both smaller trophic diversity (Fig. 2b, Table S2) and trophic dissimilarity (Fig. S1a, Table S3) compared to other functional groups, indicating that they not only exhibit lower trophic diversity within each predator taxon (lower niche expansion), but also occupy similar trophic niches among different predator taxa (lower niche partitioning). This similarity contributed to the overall reduced trophic diversity among predators compared to other functional groups (Fig. 2a, Table S1). Soil predators tend to be generalists and hunt the most accessible prey, which are often r-strategists characterised by high abundance, high metabolism and limited defence, such as springtails\u003csup\u003e50\u003c/sup\u003e, which is also indicated by their smaller variations in \u0026delta;\u003csup\u003e13\u003c/sup\u003eC values (Fig. S3a). This similarity in prey selection likely contributes to the similarity of trophic niches among predators\u003csup\u003e51\u003c/sup\u003e and emphasises their role in coupling different energy channels in soil food webs\u003csup\u003e8,52\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHerbivores had an intermediate trophic diversity and did not differ significantly from the other functional groups (Fig. 2a, Table S1). They showed large variability in \u0026delta;\u003csup\u003e13\u003c/sup\u003eC but not in \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values (Fig. S3), indicating that the trophic diversity among belowground herbivores is predominantly a consequence of variations in the use of basal resources rather than trophic levels. Aboveground herbivore invertebrate taxa typically specialise in consuming specific plant species based on plant species-specific traits, including species-specific nutrient composition, N concentration and chemical defences, which can be attributed to coevolutionary dynamics between consumers and their host-plants\u003csup\u003e53,54\u003c/sup\u003e. These food preferences based on plant species-specific traits might similarly apply to soil herbivores, which mainly feed on roots\u003csup\u003e55\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOverall, our results showed that trophic diversity and niche differentiation of soil animals depend on the position of functional groups within the food web. Functional groups that couple different energy channels, either through less selective (detritivores) or generalistic (predators) feeding, exhibit lower trophic diversity and niche differentiation.\u003c/p\u003e"},{"header":"Higher trophic diversity in agricultural and tropical systems ","content":"\u003cp\u003eAcross the globe, intensive land use is considered a threat to soil biodiversity\u003csup\u003e25,56\u003c/sup\u003e. However, in contrast to our second hypothesis, the trophic diversity of soil animals tended to be greater in agricultural systems than in woodlands (on average by 35.8 \u0026plusmn; 11.7%; Fig. 3a; Table S6), being significantly greater by 37.3 \u0026plusmn; 17.8%, 57.6 \u0026plusmn; 16.7% and 69.4 \u0026plusmn; 17.0% in detritivores, microbivores and predators, respectively. Similar to the present study, a study using the same isotopic method showed that trophic diversity of birds is higher in disturbed (urban) than in natural ecosystems, with generalists using the novel niches created by human modification\u003csup\u003e36\u003c/sup\u003e. Agricultural land use typically reduces the supply of aboveground residues to soil animals due to the removal of crops, thereby aggravating resource shortage of soil animals\u003csup\u003e57,58\u003c/sup\u003e. However, agricultural land use is also associated with increased input of nutrients via fertilisation, thereby potentially augmenting resource heterogeneity\u003csup\u003e28,59\u003c/sup\u003e, which likely contributed to the larger variations in \u0026delta;\u003csup\u003e15\u003c/sup\u003eN than \u0026delta;\u003csup\u003e13\u003c/sup\u003eC values in agricultural than woodland ecosystems (Fig. S4b). Although most soil animals are trophic generalists, they exhibit specific preferences for similar resources when resources are abundant, thereby living as so-called \u0026apos;choosy generalists\u0026apos;\u0026nbsp;\u003csup\u003e15,60,61\u003c/sup\u003e. Abundant resource supply might result in niche homogenization due to animals predominantly using the resources in ample supply\u0026nbsp;as may be the case in woodlands, which typically have thicker litter layers compared with agricultural systems.\u0026nbsp;Conversely, scarcity of resources may result in trophic differentiation by forcing animals to also exploit non-preferred resources\u0026nbsp;\u003csup\u003e37\u003c/sup\u003e. In fact, agricultural land use has been shown to increase trophic diversity among individuals in springtail communities\u0026nbsp;\u003csup\u003e62\u003c/sup\u003e. In agricultural systems, soil animals may partition their niches due to restricted and heterogeneous resource supply, and may also opportunistically incorporate novel resources\u003csup\u003e63\u003c/sup\u003e\u003csub\u003e,\u0026nbsp;\u003c/sub\u003ethus leading to higher trophic diversity at the community level. This was confirmed by lower trophic dissimilarity of the taxa within the same functional group (less niche partitioning, i.e., niche homogeneity) in woodlands compared to agricultural systems (Fig. S1b; Table S3). Furthermore, the trophic dissimilarity between functional groups,\u0026nbsp;such as microbivores and detritivores,\u0026nbsp;was also larger in agricultural than woodland ecosystems (Fig. S5b). The mismatch between biodiversity and trophic diversity indicates that soil animals may be able to adapt their trophic niches to environmental changes, thus partly maintaining their populations and associated soil functions.\u003c/p\u003e\n\u003cp\u003eConfirming our second hypothesis, trophic diversity of soil animals tended to be greater in tropical than in temperate regions (on average by 46.6 \u0026plusmn; 11.7%; Fig. 3b, Tables S6), being significantly greater by 60.6 \u0026plusmn; 17.8%, 43.1 \u0026plusmn; 16.7% and 62.5 \u0026plusmn; 17.0% in detritivores, microbivores and predators, respectively. Recent global compilations reported soil animals, including macrofauna, mesofauna and microfauna, having lower density but higher taxonomic richness in the tropics than at higher latitudes\u0026nbsp;\u003csup\u003e31\u0026ndash;33\u003c/sup\u003e. Thus, the larger trophic diversity in the tropics may be related to increased taxonomic richness, which is also indicated by our results of increasing trophic diversity with taxon richness (Fig. S6, Table S7). Further, it also aligns with higher trophic dissimilarity of taxa within the same functional group (niche partitioning) in the tropics compared to temperate systems (Figs. S1b, S4a, Table S3). However, even when accounting for the effect of taxonomic richness, effects of climate on trophic diversity remained strong (Table S7). Presumably, at least in part this may be related to low accumulation of litter and the depletion of soil organic matter in the tropics\u0026nbsp;\u003csup\u003e64\u003c/sup\u003e. Low-latitude ecosystems such as tropical rainforests typically develop on old and weathered soils deficient in nutrients, being particularly phosphorus-limited\u0026nbsp;\u003csup\u003e65\u003c/sup\u003e, which is also reflected by decreasing litter nutrient concentrations towards the tropics\u0026nbsp;\u003csup\u003e66\u003c/sup\u003e. Animals in the tropics exhibit higher metabolism and predation rates than those in high latitude ecosystems, leading to intensified interactions and stress\u0026nbsp;\u003csup\u003e33,67\u003c/sup\u003e. Consequently, generalist species may compete more intensely for high-quality food resources that are scarce. We also tested effects of land use and climate on trophic diversity at higher taxonomic resolution, namely at family-, genus- and species level. This analysis confirmed the pattern of higher trophic diversity in agricultural systems and in the tropics to be robust across taxonomic scales (Fig. S7, Table S8). Thus, except for higher taxonomic richness, limitations in the quality and quantity of food resources, and increased interactions may drive niche partitioning among soil animals, as indicated by larger trophic dissimilarity at both the level of high-ranking taxa and species. Therefore, the higher trophic diversity of soil animals in the tropics is likely due to both niche partitioning and niche expansion.\u0026nbsp;\u003c/p\u003e"},{"header":"Climatic drivers of trophic diversity ","content":"\u003cp\u003eStructural equation modelling (SEM) was used to explore which environmental factors are responsible for the observed differences in trophic diversity between high-latitude and tropical regions. SEM indicates that trophic diversity of, and distance among, taxa increased with annual temperature (Fig 4). Higher temperature is associated with increased metabolism and predation rates among invertebrate animals, intensifying interactions and predation stress\u0026nbsp;\u003csup\u003e33,67\u003c/sup\u003e, and resulting in the partitioning of trophic niches and increased trophic diversity of soil animals. However, higher annual precipitation resulted in similar trophic positions of different taxa (Fig 4). Soil animals, especially smaller taxa, heavily rely on soil moisture\u0026nbsp;\u003csup\u003e68,69\u003c/sup\u003e. Higher moisture increases the availability of resources, which may lead to niche homogenization among soil taxa and consequently reduce trophic diversity. Meanwhile, excessive moisture may also be detrimental due to water filling of soil pores and anoxic conditions\u0026nbsp;\u003csup\u003e43\u003c/sup\u003e. This may result in the loss of habitable space for soil animals, consequently increasing the similarity in trophic niches among taxa and decreasing the trophic diversity of soil animals. Overall, the effects of higher temperature and higher precipitation partly cancelled each other out and resulted in larger trophic diversity of soil animals in the tropics.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Conclusions and implications","content":"\u003cp\u003eBased on a large and unique dataset on stable isotope ratios of soil animals, we analysed the trophic diversity of major functional groups of soil animals and their variations across land-use systems and biomes. Our findings indicate that microbivores\u0026nbsp;are more\u0026nbsp;trophically diverse than\u0026nbsp;detritivores and predators, suggesting that the former play more diverse functional roles in soil food webs. Additionally, trophic diversity of soil animals was higher in agricultural systems than in woodlands despite the decline in biodiversity, suggesting that soil animals may broaden their trophic niches when faced with resource shortages and frequent disturbances. The ability of soil animals to broaden their trophic niches in response to global changes, such as land-use and climate change, may help buffer ecosystems against instability by promoting resilience through diversified resource use. Specific functional groups of soil animals, particularly microbial feeders, could enhance ecosystem functions like nutrient cycling and decomposition by exploiting underutilised or rare resources. This resilience in trophic niches suggests that soil communities may adapt in ways that maintain ecosystem stability, but also highlights potential risks of increasing flexible foraging behaviour\u003csup\u003e70\u003c/sup\u003e, with implications for long-term biodiversity and ecosystem health.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eField sites and sampling\u003c/h2\u003e\n\u003cp\u003eThe study was based on extensive data collection and analysis across 343 study sites and 15 countries. About half of the data were published before (53.6%)\u0026nbsp;\u003csup\u003e46\u0026ndash;48,62,71\u0026ndash;93\u003c/sup\u003e, while other data were compiled for this study. The dataset comprised 15,893\u0026nbsp;sample records of paired \u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values in soil animals distributed across four climatic regions: subarctic, temperate, subtropical, and tropical. The investigated ecosystem types included woodlands, agricultural systems and grasslands. Mean annual precipitation and temperature were included as abiotic drivers and were retrieved from WorldClim\u0026nbsp;\u003csup\u003e94\u003c/sup\u003e based on latitude and longitude. The details of study sites are listed in Table S8.\u003c/p\u003e\n\u003cp\u003eFor details on the sampling methods for published data see\u0026nbsp;\u003csup\u003e46\u0026ndash;48,62,71\u0026ndash;93\u003c/sup\u003e. For unpublished data, standard extraction methods were used. Nematodes were sampled by extracting 5 cm diameter soil cores encompassing the litter layer and the top 0\u0026ndash;5 cm of the mineral soil. Soil meso- and macrofauna were sampled by using heat Berlese or Kempson extractors\u0026nbsp;\u003csup\u003e95\u003c/sup\u003e and preserved in 70-96% ethanol. Sampling methods deviations are listed directly in the Table S8.\u003c/p\u003e\n\u003cp\u003eAnimals were classified into 26 high-rank taxonomic groups and further into five major functional groups as follows: herbivores (Hemiptera, Orthoptera, Thysanoptera, and Lepidoptera), detritivores (Lumbricina, Diplopoda, Isopoda, Isoptera, Dermaptera, Blattodea, Gastropoda, and Enchytraeidae), microbivores (Collembola, Oribatida, Nematoda, Protura, Prostigmata, Psocoptera, and Symphyla) and predators (Araneae, Chilopoda, Diplura, Formicidae, Mesotigmata, Opiliones, and Pseudoscorpiones) and groups displaying mixed feeding (Diptera and Coleoptera)\u0026nbsp;\u003csup\u003e15,96\u003c/sup\u003e. It has been shown that high-rank animal taxa in soil typically are trophically and functionally consistent\u0026nbsp;\u003csup\u003e96\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eStable isotope analysis\u003c/h2\u003e\n\u003cp\u003eAnimals were identified to family- (86.9%), genus- (70.1%) or species- level (58.5%) before being processed for stable isotope analysis. Before stable isotope analysis, animals were dried at 50-60\u0026deg;C for 24 h, then weighed and enclosed in tin capsules; sample weights ranged from 0.01 to 1.0 mg. For small-sized animals, the whole body of individual animals were used for stable isotope analysis, with multiple individuals were bulked when more biomass was required, for large-sized animals we used body parts dominated by muscle tissue (e.g., legs)\u0026nbsp;\u003csup\u003e97\u003c/sup\u003e. Stable isotope ratios of \u003csup\u003e13\u003c/sup\u003eC/\u003csup\u003e12\u003c/sup\u003eC and \u003csup\u003e15\u003c/sup\u003eN/\u003csup\u003e14\u003c/sup\u003eN were measured using a system comprising an elemental analyser and a mass spectrometer; for details of the individual set ups see Table S8. Ratios between the heavy isotope and the light isotope (\u003csup\u003e13\u003c/sup\u003eC/\u003csup\u003e12\u003c/sup\u003eC, \u003csup\u003e15\u003c/sup\u003eN/\u003csup\u003e14\u003c/sup\u003eN; R) were presented in parts per thousand relative to the standard using the delta notation, denoted as \u0026delta;\u003csup\u003e13\u003c/sup\u003eC or \u0026delta;\u003csup\u003e15\u003c/sup\u003eN = (R\u003csub\u003esample\u003c/sub\u003e/R\u003csub\u003estandard\u003c/sub\u003e \u0026minus; 1) \u0026times; 1000 (\u0026permil;). Vienna PD Belemnite and atmospheric nitrogen served as the standards for\u0026nbsp;\u003csup\u003e13\u003c/sup\u003eC and \u003csup\u003e15\u003c/sup\u003eN, respectively.\u003c/p\u003e\n\u003ch2\u003eCalculation of trophic diversity and dissimilarity\u003c/h2\u003e\n\u003cp\u003eTrophic diversity of soil animals can be determined by computing the standard ellipse area (SEA) based on the position of soil animals within the \u0026delta;\u003csup\u003e13\u003c/sup\u003eC-\u0026delta;\u003csup\u003e15\u003c/sup\u003eN biplot of taxonomic and functional groups at each site. We used corrected standard ellipse area (SEAc) instead of SEA in our study, which is more robust in handling small and variable sample sizes than SEA\u0026nbsp;\u003csup\u003e40\u003c/sup\u003e. The relationship between SEA and SEAc can be formulated as SEAc = SEA(n\u003csub\u003esample size\u003c/sub\u003e -1)(n\u003csub\u003esample size\u003c/sub\u003e -2)\u003csup\u003e-1\u003c/sup\u003e. We visualise some examples of the SEAc of detritivores, microbivores and predators in woodland the agricultural systems by randomly picked 5 sites for each group (Fig. S8). Moreover, to further mitigate potential bias stemming from small sample sizes, ellipses were exclusively computed for taxonomic and functional groups that consisted of five or more samples per site. To assess trophic dissimilarity among taxonomic groups within each functional group, we calculated the mean pairwise distance between the centroids of isotopic-positions of taxonomic groups within each functional group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe used uncalibrated stable isotope values (\u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN) for assessing trophic diversity and trophic dissimilarity of soil animals, as calibration using litter \u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values did not significantly affect SEAc and trophic dissimilarity. We calculated the standard deviation of \u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN values within the same functional group at each site. These values served as indicators of the variation in both basal resource use and trophic position among functional groups.\u003c/p\u003e\n\u003ch2\u003eStatistical analyses\u003c/h2\u003e\n\u003cp\u003eAll analyses were done in R 4.0.3\u0026nbsp;\u003csup\u003e98\u003c/sup\u003e. To assess the effects of land use and climate on the SEAc and trophic dissimilarity of soil animals, we selected the subsets from tropical/temperate and agricultural systems/ woodlands from the whole dataset. We fitted linear mixed-effects models (LMMs) using log-transformed SEAc and trophic dissimilarity, and then applied contrasts between tropical and temperate ecosystems, as well as between agricultural systems and woodlands to estimate effect sizes. We conducted three separate LMMs for log-transformed SEAc of functional groups, SEAc of taxonomic groups and trophic dissimilarity. The models included functional groups (herbivores, detritivores, microbivores and predators), land use (agricultural systems, woodlands), biome (tropical, temperate) and their interactions as fixed effects, with site included as random effect.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor estimating effect sizes of land use and climate, we used the \u003cem\u003eemmeans\u003c/em\u003e package to compute the estimated marginal means in the linear models. Then, we used the contrast function from the \u003cem\u003eemmeans\u003c/em\u003e package to calculate contrasts between temperate versus tropical and woodland versus agriculture\u0026nbsp;\u003csup\u003e99\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, we built another model and included sampling number\u0026nbsp;and family richness as covariates to inspect their effects on the log-transformed SEAc of functional groups. The models included functional groups, land use, climate, sampling number and family richness as fixed effects, with site included as random effect. We checked model assumptions of the most parsimonious models by fitting model residuals versus the results of fitted models.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo elucidate the drivers behind larger functional group SEAc, we employed two separate LMMs. One model included SEAc of taxonomic groups and trophic dissimilarity as explanatory variables, while the other explored variations in \u0026delta;\u003csup\u003e13\u003c/sup\u003eC and \u0026delta;\u003csup\u003e15\u003c/sup\u003eN as separate explanatory variables. We then used the estimated value of the coefficient for each independent variable to estimate their contribution to SEAc of functional groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor exploring whether temperature or precipitation are responsible for the observed differences in trophic diversity among the four latitudinal zones, we used structural equation modelling (SEM) employing maximum likelihood estimation to provide insight into how environmental factors affected trophic diversity of soil animals. The SEM included MTP and MAP as direct climatic effects. Furthermore, we included SEAc of taxonomic groups and trophic dissimilarity as mediators affected by environmental factors. The data was z-score scaled before SEM analysis. To determine the goodness of fit of the model, we used \u0026chi;\u003csup\u003e2\u003c/sup\u003e-test, the comparative fit index (CFI) \u0026gt; 0.95 and the standardised root-mean-square residual (SRMR) with values \u0026le; 0.05 as threshold for significance\u0026nbsp;\u003csup\u003e100\u003c/sup\u003e. Our SEM adequately described the data (p = 0.33, df = 3, CFI = 0.999, RMSEA = 0.022, SRMR = 0.007, AIC = 1724.75). We also built a competing model that allows for direct climate effects on\u0026nbsp;SEAc, but the model had higher AIC (1725.32), and both\u0026nbsp;MTP and MAP had no significant effects\u0026nbsp;on\u0026nbsp;SEAc (Fig. S9), thus we used the previous model in the main text.\u003c/p\u003e\n\u003cp\u003eThe SIBER package was used for calculating the trophic diversity of soil animals\u0026nbsp;\u003csup\u003e40\u003c/sup\u003e. The \u003cem\u003elme4\u003c/em\u003e package was used to fit LMMs\u0026nbsp;\u003csup\u003e101\u003c/sup\u003e and the \u003cem\u003eemmeans\u003c/em\u003e package to compute the estimated marginal means in the linear models\u0026nbsp;\u003csup\u003e99\u003c/sup\u003e. The SEM analysis was performed with the \u003cem\u003elavaan\u003c/em\u003e package\u0026nbsp;\u003csup\u003e102\u003c/sup\u003e. All mixed models were visually checked to meet the assumption of residual homogeneity of variance. Results were visualised using the \u003cem\u003eggplot2\u003c/em\u003e package\u0026nbsp;\u003csup\u003e103\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe work was supported by the Alexander von Humboldt foundation in the framework of a Research group linkage programme 1071297 - RUS - IP \u0026ldquo;Structure and functioning of belowground food webs across temperate and tropical eco- systems\u0026rdquo;. Z.Z. was supported by the China Scholarship Council (CSC, 202004910314). A.M.P. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the framework of the Emmy Noether program (Project number 493345801) and iDiv (DFG\u0026ndash;FZT 118, 202548816). S.S. and M.J. acknowledge support by DFG in the framework of the collaborative German\u0026ndash;Indonesian research project CRC990 \u0026ndash; EFForTS (192626868 \u0026ndash; SFB 990). M.M.P. was funded by the DFG Priority Program 1374 \u0026lsquo;BiodiversityExploratories\u0026rsquo; (SCHE 376/38- 2). N.E. acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG; German Centre for Integrative Biodiversity Research, FZT118; Ei 862/29-1; Ei 862/31-1).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnthony, M. A., Bender, S. F. \u0026amp; van der Heijden, M. G. A. Enumerating soil biodiversity. \u003cem\u003eProc. Natl. Acad. Sci. 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(Springer-Verlag New York, 2016).\u003c/li\u003e\n\u003c/ol\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5227558/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5227558/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"More than half of all life on Earth lives belowground and regulates a wide range of ecosystem functions via their diverse trophic interactions. However, information on how trophic diversity of soil animals varies across functional groups and major environmental gradients is lacking. Here, we use stable isotope analysis (13C/12C and 15N/14N ratios) of 28 high-rank taxa of soil animals from 343 sites across 15 countries to inspect the variability in trophic diversity across climate regions and land-use types. We found that trophic diversity of soil-animals communities is higher for microbial than for detritus feeders and predators, and increases in agricultural ecosystems compared to woodlands (+38%) and in tropical compared to temperate climates (+53%). The larger trophic diversity was related to both exploration of more diverse basal resources and longer trophic chains, possibly because of greater niche partitioning in resource-limited environments. Overall, this first comprehensive assessment of soil animal trophic diversity highlights that soil animals may broaden their trophic niches under global change, which potentially buffers global-change impacts on ecosystem functions and stability in the short term, while the increased flexibility in foraging may pose risks with long-term biodiversity and ecosystem health implications.","manuscriptTitle":"Greater trophic diversity of soil animal communities under land use and warmer climate","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-31 14:57:51","doi":"10.21203/rs.3.rs-5227558/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-ecology-and-evolution","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"natecolevol","sideBox":"Learn more about [Nature Ecology \u0026 Evolution](http://www.nature.com/natecolevol/)","snPcode":"","submissionUrl":"","title":"Nature Ecology \u0026 Evolution","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0496851a-311b-4aa5-a6b2-57e599256330","owner":[],"postedDate":"October 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39610042,"name":"Biological sciences/Ecology/Stable isotope analysis"},{"id":39610043,"name":"Biological sciences/Ecology/Macroecology"},{"id":39610044,"name":"Biological sciences/Ecology/Biodiversity"}],"tags":[],"updatedAt":"2026-03-17T07:12:27+00:00","versionOfRecord":{"articleIdentity":"rs-5227558","link":"https://doi.org/10.1038/s41559-026-03014-4","journal":{"identity":"nature-ecology-and-evolution","isVorOnly":false,"title":"Nature Ecology \u0026 Evolution"},"publishedOn":"2026-03-16 04:00:00","publishedOnDateReadable":"March 16th, 2026"},"versionCreatedAt":"2024-10-31 14:57:51","video":"","vorDoi":"10.1038/s41559-026-03014-4","vorDoiUrl":"https://doi.org/10.1038/s41559-026-03014-4","workflowStages":[]},"version":"v1","identity":"rs-5227558","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5227558","identity":"rs-5227558","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}