In most ecosystems on land, it is largely small organisms such as microbes that break down dead plant material (known as plant litter) into nutrients that are recycled into the soil. Given that microbes need moisture to survive, scientists have long questioned how plant litter undergoes this decomposition in dry ecosystems.

Previous research focused primarily on how solar radiation and other environmental factors affect how quickly plant litter decomposes in these harsh conditions. However, another possibility is that larger decomposers, such as animals like beetles and termites that feed on dead plant material, are better adapted to arid conditions and may be more abundant in areas with low rainfall. As a result, plant litter in dry environments may decompose at similar rates to areas with higher rainfall.

Torsekar, Sagi et al. tested this idea by monitoring how quickly plant litter decomposed at seven sites with similar average temperatures but different rainfall levels. Dozens of baskets with different sized mesh – which excluded some or all animal decomposers based on size – were placed at each site and a technique called pitfall trapping was used to identify the decomposers at each site.

The experiments showed that plant litter broke down at similar rates across five of the seven sites, but decomposition was slower at extremely dry sites. In the winter, when rainfall is typically higher than at other times in the year, microbe decomposers played a bigger role in breaking down the leaf litter than in the (drier) summer months. On the other hand, animal decomposers were more abundant at sites with low rainfall than sites with higher rainfall. Furthermore, decomposition by animals at these arid sites during summer was just as fast as microbial decomposition at the wetter sites in winter.

The findings of Torsekar, Sagi et al. suggest that larger, animal decomposers compensate for the lower microbial decomposition of plant matter in ecosystems with little rainfall. In the future, a better understanding of how nutrients are recycled in dry areas will help predict how different ecosystems will respond to climate change.

Litter decomposition is a key process determining elemental cycling in terrestrial ecosystems (Schlesinger and Bernhardt, 2020). Decomposition is controlled by climate, litter quality, and origin, and the identity and abundance of microbial and faunal decomposers (Bradford et al., 2016; Joly et al., 2023; Swift et al., 1979). Climate regulates decomposition rates directly, but also indirectly by influencing food-web structure and dynamics (Wu et al., 2021). Thus, understanding how climate and decomposers interact is a key step in explaining variation in plant litter decomposition across ecosystems and seasons, and in forecasting the consequences of climate change and biodiversity loss on elemental cycling.

Theory suggests that decomposition is positively associated with moisture and temperature (Swift et al., 1979). Cross-site studies, reviews, and meta-analyses verified this global pattern, showing that plant litter decomposition in microbial litter bags is indeed faster under warm and wet conditions than under cool and dry conditions (Berg et al., 1993; Meentemeyer, 1978; Bradford et al., 2017; Parton et al., 2007; Aerts, 1997; Zhang et al., 2008). This well accepted realization implicitly assumes that microorganisms dominate plant litter decomposition, largely ignoring the growing recognition that animals may play an important role in litter cycling. This role includes mineralizing and excreting assimilated plant nutrients, fragmenting and partly decomposing plant material, and transporting detritus to microbial havens (David, 2014; Frouz, 2018; Griffiths et al., 2021; Auclerc et al., 2022; Sagi et al., 2021; Coulis et al., 2016; Joly et al., 2018; Joly et al., 2020).

Attempts to explore how climate affects faunal decomposition revealed a similar positive association with temperature and precipitation (García-Palacios et al., 2013; Xu et al., 2020). This global pattern, however, may be confounded by compiling the effect of all decomposer fauna together, ignoring the well-established understanding that soil animals of various size groups respond differently to climate (Swift et al., 1979; Johnston and Sibly, 2020). Specifically, larger arthropods can survive and remain active during hot and dry periods when smaller organisms cannot (Cloudsley-Thompson, 1975). Indeed, handful of evidence shows that macro-detritivorous arthropods dominate litter and wood decomposition in warm drylands, especially during warm and dry seasons (Veldhuis et al., 2017; Sagi et al., 2019; Zanne et al., 2022). This suggests that the conceptualization of how animals and climate interact to regulate decomposition rates requires considering the effects of meso-decomposers and those of macro-decomposers separately, particularly in warm drylands.

Detritivorous animals are expected to be exceptionally abundant in arid ecosystems where plant detritus is prevalent year-round but green plant material is available predominantly in short pulses following precipitation events (Ayal et al., 2005). Macrofauna are physiologically and morphologically more adapted to aridity than mesofauna (Cloudsley-Thompson, 1975). Moreover, their large size enables them to remain active during long dry periods by shuttling between existing and self-engineered climatic havens and the hostile foraging grounds on the surface (Sagi and Hawlena, 2021). Consequently, macro-decomposition should be especially important in hot moisture-deprived habitats and periods, whereas the activity of microbes and mesofauna is expected to be minimal.

The predicted negative association between moisture and macro-decomposition in drylands may be reversed in hyper-arid environments. In these environments, the extreme climatic conditions and scarce and unpredictable plant litter availability may limit macro-decomposer populations, diminishing macro-decomposition rates with increasing aridity. Consequently, and in sharp contrast to smaller organisms, macro-decomposition should follow a hump-shaped response to precipitation that peaks in arid ecosystems (Figure 1).

Figure 1

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To test this novel hypothesis, we examined the climate dependency of plant litter decomposition by microorganisms, meso-decomposers, and macro-decomposers along a sharp aridity gradient spanning from mean annual precipitation (MAP) of 22–526 mm. This gradient represents hyper-arid, arid, semiarid, and dry sub-humid Mediterranean climates (Table 1, Figure 2A). We repeated the experiment during hot summer with no precipitation and again during cooler and wetter winter. We hypothesized that both microbial and mesofaunal decomposition should increase with increasing precipitation during the winter, but during the dry summer contribute only minimally to plant litter decomposition across the aridity gradient. In the dry summer, macrofaunal decomposition should follow a hump-shaped response to precipitation, increasing from hyper-arid to arid sites and decreasing gradually in more mesic semiarid and Mediterranean sites. We also predicted that the opposing climatic dependencies of macrofauna and microorganisms and mesofauna should lead to similar overall decomposition rates across the precipitation gradient except in the hyper-arid sites in which decomposers activity is predicted to be minimal regardless of organism size (Figure 1). To reveal the mechanism, we sampled macro-decomposers across the aridity gradient and the two seasons, using pitfall traps. We predicted hump-shaped relationships between precipitation and the abundance, richness, and biomass of macro-decomposers that peak in arid ecosystems.

Figure 2

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Litter removal rate differed across seasons, sites, and mesh sizes, and all interactions between these factors were found significant as well (Figure 3, Table 2). On average, the litter removal rate was 2.6-fold higher in winter than in summer, 1.6-fold higher in meso- than in micro-baskets, and 1.3-fold higher in macro- than in meso-baskets. Litter removal was negligible in the hyper-arid sites during both seasons, while it was highest in the arid sites during summer and in the more mesic sites during winter (Figure 3). Within site and season comparisons between mesh sizes yielded significant differences only in Avdat, Sayeret Shaked, and Havat Shikmim, indicating that faunal effects on decomposition were found only under arid to dry-semiarid conditions (Figure 3). Both macro- and mesofaunal effects were detected in the arid sites (Avdat and Sayeret Shaked), whereas the semiarid Havat Shikmim site exhibited only a mesofaunal effect during both seasons (Figure 3). The macrofaunal, mesofaunal, and microorganismal contributions to litter mass loss peaked under arid, semiarid and Mediterranean climate conditions, respectively (Figure 4). Whole-community litter removal rates were dictated by microorganisms in winter and by macrofauna in summer, resulting in comparable rates across the aridity gradient from Mediterranean to arid climate at the annual scale (Figure 4). In total, the whole-community litter removal rate peaked in Sayeret Shaked (MAP = 148 mm) and significantly decreased under drier and wetter conditions (Figure 4).

Figure 3

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Figure 4

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Macro-decomposer abundance, biomass, and morphospecies richness peaked in the arid sites during both seasons (Figure 5). The macro-decomposer assemblage differed significantly across sites (F_6,229 = 10.6, p-value <0.001) and across seasons (F_1,229 = 13.1, p-value <0.001), where woodlice, millipedes, and snails were substituted by ants and termites with increasing aridity (Figure 6A, B). Assemblage was significantly affected by the interaction between site and season too (F_6,229 = 5.4, p-value <0.001). The experimental site explained much of the assemblage variability across traps (R² = 0.18), whereas experimental season accounted for a smaller fraction (R² = 0.04), and site–season interaction played an intermediate role (R² = 0.10). All pairwise comparisons across sites yielded significant differences in assemblage (Supplementary file 1). In general, ants were the most abundant group, whereas beetles accounted for most of the biomass. However, under mesic conditions, woodlice (Ramat Hanadiv site), millipedes (Ramat Hanadiv and Bet Guvrin), and snails (Havat Shikmim) were dominant (Figure 6C). The Ramat Hanadiv assemblage was distinctively different from all other sites (Figure 6A), as demonstrated by very high Bray–Curtis (BC) dissimilarity indices compared to the other sites, regardless of the season (Supplementary file 2). There were parallels between the spatial and temporal axes of aridity, as winter communities in the most arid sites (Nahal Shita, Meishar, and Avdat) were relatively similar to the summer communities of the more mesic sites (Sayeret Shaked, Havat Shikmim, and Bet Guvrin) (Figure 6A, B; Supplementary file 2). The arid sites, where macro-decomposer assemblages flourished and were responsible for the highest litter mass loss, showed interesting seasonal dynamics. BC dissimilarity across seasons was higher in Sayeret Shaked than in Avdat (BC = 0.79 and 0.72, respectively). Cross-site dissimilarity between Sayeret Shaked and Avdat was higher in winter than in summer (BC = 0.85 and 0.72, respectively).

Figure 5

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Figure 6

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Our goal was to investigate how climate interacts with soil biota of different size categories to influence litter decomposition. We used litter baskets of different mesh sizes that were placed along a sharp precipitation gradient during hot–dry summer and again during colder–wetter winter. Our results suggest that decomposers respond differently to precipitation levels based on their size, leading to similar overall decomposition rates across the gradient, except in hyper-arid sites. We found that microbial decomposition was minimal during the summer. In the winter, microbial decomposition was positively associated with precipitation, governing the whole-community decomposition. In both seasons, mesofaunal decomposition was moderate and followed a hump-shaped response to precipitation, peaking in semiarid sites. Macro-decomposition contributed minimally to whole-community decomposition during the winter, but during the summer dominated decomposition in the two arid sites. Using pitfall trapping, we found that macro-decomposer richness, abundance, and biomass followed a hump-shaped response to precipitation, peaking in arid environments.

The puzzle of why plant litter decomposition in arid-lands is decoupled from annual precipitation and is faster than expected based on microbial decomposition models has bothered scientists for half a century (Meentemeyer, 1978; Noy-Meir, 1974; Whitford et al., 1981), and was later termed the dryland decomposition conundrum (Throop and Archer, 2009). Attempts to resolve this conundrum have focused predominantly on abiotic weathering agents, such as photodegradation (Austin and Vivanco, 2006; Austin, 2011) and thermal degradation (Day et al., 2019), alternative sources of moisture such as fog, dew, and atmospheric water vapor (Evans et al., 2020) and soil–litter mixing (Throop and Archer, 2009; Throop and Belnap, 2019). We, in turn, hypothesized that the opposing climatic dependencies of macrofauna and that of microorganisms and mesofauna should lead to similar overall decomposition rates across precipitation gradients, except in hyper-arid environments in which decomposers activity is predicted to be minimal regardless of organism size. Our results largely agree with this hypothesis. Whole-community decomposition was minimal in hyper-arid sites in both summer and winter. In the winter, microbial decomposition dominated the whole-community decomposition, demonstrating a positive response to precipitation that reached a maximum in the most mesic Mediterranean site. In contrast, macro-decomposition has contributed only little to the whole-community decomposition during the winter, but dominated the arid sites’ decomposition in the summer. These findings supported the long-suggested but largely overlooked hypothesis that macro-decomposition governs plant litter decomposition in deserts (Meentemeyer, 1978; Noy-Meir, 1974; Whitford et al., 1981). The opposing climatic dependencies of micro- and macro-decomposers have led to similar or even higher annual decomposition rates in arid sites compared to those measured in more mesic sites. Consequently, we highlighted that differential climatic dependencies of different-sized decomposers rather than abiotic factors explain the discrepancy between classic decomposition models and the observed decomposition rates in drylands. This realization provided a plausible resolution to the longstanding dryland decomposition conundrum, and exposed a hidden mechanism that may account for unexplained variation in plant litter decomposition across biomes.

Canonically, faunal decomposition is expected to be positively associated with temperature and moisture (García-Palacios et al., 2013). We, however, hypothesized that climate dependencies of mesofauna and macrofauna should differ due to the lower sensitivity of macrofauna to high temperature and low moisture, and the ability of macro-decomposers to shuttle between the hostile environment aboveground and the climatic havens belowground (Sagi and Hawlena, 2021). We also hypothesized that low and unpredictable resource availability in hyper-arid environments should limit macro-decomposer populations. Consequently, we predicted that macro-decomposers should be more prevalent in arid environments in comparison to hyper-arid or more mesic environments. Furthermore, ample resource availability may increase niche space (Macarthur, 1965), resulting in higher macro-decomposer diversity, which in turn can facilitate decomposition through synergistic effects of functionally complementary species (Heemsbergen et al., 2004; Gessner et al., 2010; Boyero et al., 2021; Zeng et al., 2023). Thus, we predicted that macro-decomposition should reflect the variation in the abundance, richness and biomass of macro-decomposers across the precipitation gradient. Our findings supported these predictions. The richness, abundance, and biomass of macro-decomposers followed a hump-shaped relationship with precipitation, peaking in arid environments and diminishing toward hyper-arid or semiarid and Mediterranean sites. Macro-decomposer assemblages were dominated by ants and beetles across the aridity gradient except in the Mediterranean site that was dominated by isopods and millipedes. During the summer, the observed hump-shaped relationship between macro-decomposition and precipitation tightly echoed the variation in richness, abundance, and biomass of macro-decomposers, revealing the mechanistic foundation for the cross-system variation in macro-decomposition.

In winter, macro-decomposer abundance, richness, and biomass were similar to or even higher than those measured during the summer across all sites. Despite this resemblance, macro-decomposition did not reflect the observed variation in macro-decomposer assemblages. This discrepancy could be explained by between-seasons differences in the structure of the macro-decomposer assemblages (Figure 6B). The macro-decomposer summer assemblage in Sayeret Shaked was more similar to the Avdat summer assemblage than to the Sayeret Shaked winter assemblage. The Avdat assemblages were more similar to each other across seasons than the Sayeret Shaked assemblages. This may explain why macro-decomposition in winter was higher in Avdat than in Sayeret Shaked. Termites (Hodotermitidae sp.), that play an important role in decomposition, were more abundant in summer compared to the winter in Sayeret Shaked but not in Avdat. Moreover, our data revealed that several beetle taxa (Adelostoma sp., Akis reflexa (Fabricius, 1775), Dailognatha crenata (Reiche & Saulcy, 1857), Tentyrina sp., and Zophosis sp.) were prevalent in both arid sites during the summer but were absent or very scarce in the winter. Phenological differences in the behavior of dominant macro-decomposers may also contribute to the seasonal differences (Bonato Asato et al., 2023). For instance, Hemilepistus reaumuri (Milne Edwards, 1840), an abundant isopod species in Avdat, and Anacanthotermes ubachi (Navás, 1911), a common termite species in Sayeret Shaked, consume detritus predominantly during the summer and autumn and disperse and reproduce during the winter (Zaady et al., 2003; Shachak et al., 1976). Future studies should explicitly test these explanations. Regardless, the whole-year association between macro-decomposition and the abundance, richness, and biomass of macro-decomposers strongly support our hypothesis.

Theory suggests that plant litter decomposition by meso-decomposers should increase with moisture. This pattern was supported by a cross-biome experiment (Wall et al., 2008). Thus, we hypothesized that both meso-decomposition and microbial decomposition should increase with precipitation and be more prominent in the winter than in the summer. Our results did not coincide with these hypotheses. Litter decomposition by mesofauna followed a unimodal pattern across the precipitation gradient, peaking under semiarid conditions in both seasons (Figure 4). Meso- and macro-decomposition were similar in the hyper-arid and Mediterranean sites. However, meso-decomposition was higher than macro-decomposition in the semiarid sites and much lower than macro-decomposition in the arid sites. These results suggest that meso-decomposers, like macro-decomposers, have adaptations that allow them to strive in moisture-deprived environments. Yet, meso-decomposition peaked in more mesic conditions than macro-decomposition, implying higher moisture dependency. Our findings highlight the need to explore the moisture dependency of mesofauna in greater details, and to generate different predictions for how mesofauna and microorganisms may affect plant litter decomposition.

Faunal decomposition in our study peaked in arid environments, contrasting the positive association between faunal decomposition and precipitation that was found in recent global meta-analyses (García-Palacios et al., 2013; Xu et al., 2020). This discrepancy may reflect underestimation of faunal decomposition rates in drylands, possibly because these studies either deliberately grouped cold and dry environments together (García-Palacios et al., 2013; Wall et al., 2008), or focused solely on precipitation without accounting for differences in temperature (Xu et al., 2020). In cold water-deprived environments and seasons, low temperatures may limit the populations and activity of ectotherm animals (Swift et al., 1979; Johnston and Sibly, 2020). Therefore, ignoring the effect of temperature may lead to falsely smaller faunal effects on decomposition in drylands. This bias may contribute to the positive association between precipitation and faunal decomposition. To reveal the realistic relationships, future studies on faunal decomposition should explore the effects of temperature, precipitation, and the interaction between them. It is important noting that temperature could affect decomposition both directly by determining the activity of ectotherms and indirectly by regulating moisture availability (Sagi and Hawlena, 2024). Thus, using aridity indices that aim to correct for moisture availability cannot resolve the need to account also for temperature per se.

We used litter of one plant species that is common to all seven experimental sites. In this way, we were able to compare decomposition rates across sites without using litter that is exogenous to one or more sites. Decomposer communities are assumed to perceive litter quality based on the chemical composition of the focal litter, and that of past resource inputs that these communities have experienced (Strickland et al., 2009). Plant communities differ substantially between our sites, suggesting that each decomposer community has experienced very different resource inputs, and may have access to alternative litter of various qualities. Thus, it is likely that the perceived quality of S. capensis litter differs between sites, possibly confounding our results. Moreover, our sites were distributed along a single precipitation gradient. Thus, our results may be confounded by other environmental factors that were not accounted for. To determine how general our findings are, future research should repeat our experimental approach using different litter sources, and across multiple climatic gradients.

In conclusion, our work revealed that decomposers of varying size categories have different moisture dependencies. This suggests that microorganisms, meso-decomposers, and macro-decomposers should be considered separately in decomposition models, and emphasizes the need to contemplate animals’ physiology and behavior when investigating zoogeochemical processes. Warm drylands cover 19% of the land surface worldwide and expand rapidly due to unsustainable land-use and climate change (Cartereau et al., 2022). We highlight the importance of macro-decomposition in arid-lands that compensates for the minimal microbial decomposition, providing a plausible resolution to the long-debated dryland decomposition conundrum. Understanding the mechanisms that regulate decomposition in drylands is key for conserving and restoring fundamental ecosystem processes in these ever-growing areas, and in improving our understanding of global processes like C cycling. To date, the general conceptualization of decomposition is largely based on ample research from temperate ecosystems. Thus, prevailing theory centers on focal processes that dominate decomposition in these systems. Our work highlights that in other less studied ecosystems additional processes like the role of animal decomposers may be dominant, opening the door for new exciting research that may shake our conceptualization of decomposition processes.

We performed a manipulative litter mass loss experiment across seven sites representing a sharp MAP gradient ranging from hyper-arid desert to Mediterranean maquis (Figure 2A, Table 1). All sites were chosen to be on calcareous soils formed upon sedimentary limestone rock in natural habitats. The mean annual temperature varies only slightly across sites from 18.7 to 22.3°C. The exact study sites were determined to ensure minimal human disturbance during the year-long experiment. In each of the seven sites we installed litter baskets of three different mesh sizes that control organismal access to litter: micro-baskets allowing entry of only microorganisms (<200 μm), meso-baskets allowing entry of microorganisms and mesofauna (<2 mm), and macro-baskets that were identical to the meso-baskets but with side openings that allow entry of macrofauna (<2 cm). Litter baskets were filled with leaf litter belonging to the annual grass Stipa capensis Thunb. that is native to all seven study sites. This approach allowed us to compare decomposition rates across sites without using exogenous litter that may decompose in a very different rate than local litter (Joly et al., 2023). Twenty-five blocks, each including the three basket types (Figure 2B), were installed in each site for two consecutive experimental periods – a wet cool winter and a dry hot summer (2 periods × 7 sites × 3 treatments × 25 blocks = 1050 baskets in total). We also characterized the macro-decomposer assemblage in each site during the two seasons using pitfall trapping.

All data used in the manuscript has been deposited in an open repository and can be found on the following link https://doi.org/10.6084/m9.figshare.23544993.

1. 1. Torsekar VR
   2. Sagi N
   3. Alfred Daniel J
   4. Hawlena Y
   5. Gavish-Regev E
   6. Hawlena D
   7. Alfred Daniel J

   (2024) figshare

   Contrasting responses to aridity by different-sized decomposers cause similar decomposition rates across a precipitation gradient.

   https://doi.org/10.6084/m9.figshare.23544993

1. 1. Aerts R

   (1997) Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship

   Oikos 79:439.

   https://doi.org/10.2307/3546886

   • Google Scholar
2. 1. Auclerc A
   2. Beaumelle L
   3. Barantal S
   4. Chauvat M
   5. Cortet J
   6. De Almeida T
   7. Dulaurent AM
   8. Dutoit T
   9. Joimel S
   10. Séré G
   11. Blight O
   12. Dulaurent AM

   (2022) Fostering the use of soil invertebrate traits to restore ecosystem functioning

   Geoderma 424:116019.

   https://doi.org/10.1016/j.geoderma.2022.116019

   • Google Scholar
3. 1. Austin AT
   2. Vivanco L

   (2006) Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation

   Nature 442:555–558.

   https://doi.org/10.1038/nature05038

   • PubMed
   • Google Scholar
4. 1. Austin AT

   (2011) Has water limited our imagination for aridland biogeochemistry?

   Trends in Ecology & Evolution 26:229–235.

   https://doi.org/10.1016/j.tree.2011.02.003

   • PubMed
   • Google Scholar
5. Book

   1. Ayal Y
   2. Polis GA
   3. Lubin Y
   4. Goldberg D

   (2005) How can high animal diversity be supported in low-productivity deserts? the role of macrodetritivory and habitat physiognomy

   In: Shachak M, Pickett, STA, Gosz, JR, Perevolotski A, editors. Biodiversity in Drylands: Towards a Unified Framework. Oxford: Oxford University Press. pp. 34–45.

   https://doi.org/10.1093/oso/9780195139853.003.0007

   • Google Scholar
6. 1. Barney JN
   2. Tekiela DR
   3. Barrios-Garcia MN
   4. Dimarco RD
   5. Hufbauer RA
   6. Leipzig-Scott P
   7. Nuñez MA
   8. Pauchard A
   9. Pyšek P
   10. Vítková M
   11. Maxwell BD

   (2015) Global Invader Impact Network (GIIN): toward standardized evaluation of the ecological impacts of invasive plants

   Ecology and Evolution 5:2878–2889.

   https://doi.org/10.1002/ece3.1551

   • PubMed
   • Google Scholar
7. 1. Bates D
   2. Mächler M
   3. Bolker B
   4. Walker S

   (2015) Fitting linear mixed-effects models using lme4

   Journal of Statistical Software 67:1–48.

   https://doi.org/10.18637/jss.v067.i01

   • Google Scholar
8. 1. Berg B
   2. Berg MP
   3. Bottner P
   4. Box E
   5. Breymeyer A
   6. de Anta RC
   7. Couteaux M
   8. Escudero A
   9. Gallardo A
   10. Kratz W
   11. Madeira M
   12. Mälkönen E
   13. McClaugherty C
   14. Meentemeyer V
   15. Muñoz F
   16. Piussi P
   17. Remacle J
   18. de Santo AV

   (1993) Litter mass loss rates in pine forests of Europe and Eastern United States: some relationships with climate and litter quality

   Biogeochemistry 20:127–159.

   https://doi.org/10.1007/BF00000785

   • Google Scholar
9. 1. Bonato Asato AE
   2. Wirth C
   3. Eisenhauer N
   4. Hines J

   (2023) On the phenology of soil organisms: Current knowledge and future steps

   Ecology and Evolution 13:e10022.

   https://doi.org/10.1002/ece3.10022

   • PubMed
   • Google Scholar
10. 1. Boyero L
    2. López-Rojo N
    3. Tonin AM
    4. Pérez J
    5. Correa-Araneda F
    6. Pearson RG
    7. Bosch J
    8. Albariño RJ
    9. Anbalagan S
    10. Barmuta LA
    11. Basaguren A
    12. Burdon FJ
    13. Caliman A
    14. Callisto M
    15. Calor AR
    16. Campbell IC
    17. Cardinale BJ
    18. Jesús Casas J
    19. Chará-Serna AM
    20. Chauvet E
    21. Ciapała S
    22. Colón-Gaud C
    23. Cornejo A
    24. Davis AM
    25. Degebrodt M
    26. Dias ES
    27. Díaz ME
    28. Douglas MM
    29. Encalada AC
    30. Figueroa R
    31. Flecker AS
    32. Fleituch T
    33. García EA
    34. García G
    35. García PE
    36. Gessner MO
    37. Gómez JE
    38. Gómez S
    39. Gonçalves JF
    40. Graça MAS
    41. Gwinn DC
    42. Hall RO
    43. Hamada N
    44. Hui C
    45. Imazawa D
    46. Iwata T
    47. Kariuki SK
    48. Landeira-Dabarca A
    49. Laymon K
    50. Leal M
    51. Marchant R
    52. Martins RT
    53. Masese FO
    54. Maul M
    55. McKie BG
    56. Medeiros AO
    57. Erimba CMM
    58. Middleton JA
    59. Monroy S
    60. Muotka T
    61. Negishi JN
    62. Ramírez A
    63. Richardson JS
    64. Rincón J
    65. Rubio-Ríos J
    66. Dos Santos GM
    67. Sarremejane R
    68. Sheldon F
    69. Sitati A
    70. Tenkiano NSD
    71. Tiegs SD
    72. Tolod JR
    73. Venarsky M
    74. Watson A
    75. Yule CM

    (2021) Impacts of detritivore diversity loss on instream decomposition are greatest in the tropics

    Nature Communications 12:3700.

    https://doi.org/10.1038/s41467-021-23930-2

    • PubMed
    • Google Scholar
11. 1. Bradford MA
    2. Berg B
    3. Maynard DS
    4. Wieder WR
    5. Wood SA

    (2016) Understanding the dominant controls on litter decomposition

    Journal of Ecology 104:229–238.

    https://doi.org/10.1111/1365-2745.12507

    • Google Scholar
12. 1. Bradford MA
    2. Veen GFC
    3. Bonis A
    4. Bradford EM
    5. Classen AT
    6. Cornelissen JHC
    7. Crowther TW
    8. De Long JR
    9. Freschet GT
    10. Kardol P
    11. Manrubia-Freixa M
    12. Maynard DS
    13. Newman GS
    14. Logtestijn RSP
    15. Viketoft M
    16. Wardle DA
    17. Wieder WR
    18. Wood SA
    19. van der Putten WH

    (2017) A test of the hierarchical model of litter decomposition

    Nature Ecology & Evolution 1:1836–1845.

    https://doi.org/10.1038/s41559-017-0367-4

    • PubMed
    • Google Scholar
13. 1. Cartereau M
    2. Leriche A
    3. Baumel A
    4. Ondo I
    5. Chatelain C
    6. Aronson J
    7. Médail F

    (2022) Global bioregionalization of warm drylands based on tree assemblages mined from occurrence big data

    Frontiers of Biogeography 14:e56435.

    https://doi.org/10.21425/F5FBG56435

    • Google Scholar
14. 1. Cloudsley-Thompson JL

    (1975) Adaptations of arthropoda to arid environments

    Annual Review of Entomology 20:261–283.

    https://doi.org/10.1146/annurev.en.20.010175.001401

    • PubMed
    • Google Scholar
15. 1. Coulis M
    2. Hättenschwiler S
    3. Coq S
    4. David JF

    (2016) Leaf litter consumption by macroarthropods and burial of their faeces enhance decomposition in a mediterranean ecosystem

    Ecosystems 19:1104–1115.

    https://doi.org/10.1007/s10021-016-9990-1

    • Google Scholar
16. 1. David JF

    (2014) The role of litter-feeding macroarthropods in decomposition processes: A reappraisal of common views

    Soil Biology and Biochemistry 76:109–118.

    https://doi.org/10.1016/j.soilbio.2014.05.009

    • Google Scholar
17. 1. Day TA
    2. Bliss MS
    3. Placek SK
    4. Tomes AR
    5. Guénon R

    (2019) Thermal abiotic emission of CO2 and CH₄ from l_eaf litter and its significance in a photodegradation assessment

    Ecosphere 10:2745.

    https://doi.org/10.1002/ecs2.2745

    • Google Scholar
18. 1. Evans S
    2. Todd-Brown KEO
    3. Jacobson K
    4. Jacobson P

    (2020) Non-rainfall moisture: a key driver of microbial respiration from standing litter in arid, semiarid, and mesic grasslands

    Ecosystems 23:1154–1169.

    https://doi.org/10.1007/s10021-019-00461-y

    • Google Scholar
19. 1. Frouz J

    (2018) Effects of soil macro- and mesofauna on litter decomposition and soil organic matter stabilization

    Geoderma 332:161–172.

    https://doi.org/10.1016/j.geoderma.2017.08.039

    • Google Scholar
20. 1. García-Palacios P
    2. Maestre FT
    3. Kattge J
    4. Wall DH

    (2013) Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes

    Ecology Letters 16:1045–1053.

    https://doi.org/10.1111/ele.12137

    • PubMed
    • Google Scholar
21. 1. Gessner MO
    2. Swan CM
    3. Dang CK
    4. McKie BG
    5. Bardgett RD
    6. Wall DH
    7. Hättenschwiler S

    (2010) Diversity meets decomposition

    Trends in Ecology & Evolution 25:372–380.

    https://doi.org/10.1016/j.tree.2010.01.010

    • PubMed
    • Google Scholar
22. 1. Griffiths HM
    2. Ashton LA
    3. Parr CL
    4. Eggleton P

    (2021) The impact of invertebrate decomposers on plants and soil

    The New Phytologist 231:2142–2149.

    https://doi.org/10.1111/nph.17553

    • PubMed
    • Google Scholar
23. 1. Heemsbergen DA
    2. Berg MP
    3. Loreau M
    4. van Hal JR
    5. Faber JH
    6. Verhoef HA

    (2004) Biodiversity effects on soil processes explained by interspecific functional dissimilarity

    Science 306:1019–1020.

    https://doi.org/10.1126/science.1101865

    • PubMed
    • Google Scholar
24. 1. Johnston ASA
    2. Sibly RM

    (2020) Multiple environmental controls explain global patterns in soil animal communities

    Oecologia 192:1047–1056.

    https://doi.org/10.1007/s00442-020-04640-w

    • PubMed
    • Google Scholar
25. 1. Joly FX
    2. Coq S
    3. Coulis M
    4. Nahmani J
    5. Hättenschwiler S

    (2018) Litter conversion into detritivore faeces reshuffles the quality control over C and N dynamics during decomposition

    Functional Ecology 32:2605–2614.

    https://doi.org/10.1111/1365-2435.13178

    • Google Scholar
26. 1. Joly F-X
    2. Coq S
    3. Coulis M
    4. David J-F
    5. Hättenschwiler S
    6. Mueller CW
    7. Prater I
    8. Subke J-A

    (2020) Detritivore conversion of litter into faeces accelerates organic matter turnover

    Communications Biology 3:660.

    https://doi.org/10.1038/s42003-020-01392-4

    • PubMed
    • Google Scholar
27. 1. Joly FX
    2. Scherer-Lorenzen M
    3. Hättenschwiler S

    (2023) Resolving the intricate role of climate in litter decomposition

    Nature Ecology & Evolution 7:214–223.

    https://doi.org/10.1038/s41559-022-01948-z

    • PubMed
    • Google Scholar
28. 1. Macarthur RH

    (1965) Patterns of species diversity

    Biological Reviews 40:510–533.

    https://doi.org/10.1111/j.1469-185X.1965.tb00815.x

    • Google Scholar
29. 1. Meentemeyer V

    (1978) Macroclimate and lignin control of litter decomposition rates

    Ecology 59:465–472.

    https://doi.org/10.2307/1936576

    • Google Scholar
30. 1. Noy-Meir I

    (1974) Desert ecosystems: higher trophic levels

    Annual Review of Ecology and Systematics 5:195–214.

    https://doi.org/10.1146/annurev.es.05.110174.001211

    • Google Scholar
31. Software

    1. Oksanen J
    2. Simpson GL
    3. Blanchet FG

    (2022) vegan: Community Ecology Package, version 2.6-8

    R Package.

    https://doi.org/10.32614/CRAN.package.vegan
32. 1. Parton W
    2. Silver WL
    3. Burke IC
    4. Grassens L
    5. Harmon ME
    6. Currie WS
    7. King JY
    8. Adair EC
    9. Brandt LA
    10. Hart SC
    11. Fasth B

    (2007) Global-scale similarities in nitrogen release patterns during long-term decomposition

    Science 315:361–364.

    https://doi.org/10.1126/science.1134853

    • PubMed
    • Google Scholar
33. Software

    1. R Development Core Team

    (2022) R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna, Austria.

    http://www.r-project.org
34. 1. Sagi N
    2. Grünzweig JM
    3. Hawlena D

    (2019) Burrowing detritivores regulate nutrient cycling in a desert ecosystem

    Proceedings. Biological Sciences 286:20191647.

    https://doi.org/10.1098/rspb.2019.1647

    • PubMed
    • Google Scholar
35. 1. Sagi N
    2. Hawlena D

    (2021) Arthropods as the engine of nutrient cycling in arid ecosystems

    Insects 12:726.

    https://doi.org/10.3390/insects12080726

    • PubMed
    • Google Scholar
36. 1. Sagi N
    2. Zaguri M
    3. Hawlena D

    (2021) Macro-detritivores assist resolving the dryland decomposition conundrum by engineering an underworld heaven for decomposers

    Ecosystems 24:56–67.

    https://doi.org/10.1007/s10021-020-00504-9

    • Google Scholar
37. 1. Sagi N
    2. Hawlena D

    (2024) Climate dependence of the macrofaunal effect on litter decomposition-A global meta-regression analysis

    Ecology Letters 27:e14333.

    https://doi.org/10.1111/ele.14333

    • PubMed
    • Google Scholar
38. 1. Scheipl F
    2. Greven S
    3. Küchenhoff H

    (2008) Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models

    Computational Statistics & Data Analysis 52:3283–3299.

    https://doi.org/10.1016/j.csda.2007.10.022

    • Google Scholar
39. Book

    1. Schlesinger WH
    2. Bernhardt E

    (2020) Biogeochemistry: An Analysis of Global Change

    Academic Press.

    https://doi.org/10.1016/B978-0-12-814608-8.09991-6

    • Google Scholar
40. 1. Shachak M
    2. Chapman EA
    3. Steinberger Y

    (1976) Feeding, energy flow and soil turnover in the desert isopod, Hemilepistus reaumuri

    Oecologia 24:57–69.

    https://doi.org/10.1007/BF00545487

    • PubMed
    • Google Scholar
41. 1. Strickland MS
    2. Osburn E
    3. Lauber C
    4. Fierer N
    5. Bradford MA

    (2009) Litter quality is in the eye of the beholder: initial decomposition rates as a function of inoculum characteristics

    Functional Ecology 23:627–636.

    https://doi.org/10.1111/j.1365-2435.2008.01515.x

    • Google Scholar
42. Book

    1. Swift MJ
    2. Heal OW
    3. Anderson JM

    (1979)

    Decomposition in Terrestrial Ecosystems

    University of California Press.

    • Google Scholar
43. Book

    1. Throop HL
    2. Archer SR

    (2009) Resolving the dryland decomposition conundrum: some new perspectives on potential drivers

    In: Lüttge U, Beyschlag W, Büdel B, Francis D, editors. Progress in Botany. Berlin Heidelberg: Springer-Verlag. pp. 171–194.

    https://doi.org/10.1007/978-3-540-68421-3_8

    • Google Scholar
44. 1. Throop HL
    2. Belnap J

    (2019) Connectivity dynamics in dryland litter cycles: moving decomposition beyond spatial stasis

    BioScience 69:602–614.

    https://doi.org/10.1093/biosci/biz061

    • Google Scholar
45. 1. Veldhuis MP
    2. Laso FJ
    3. Olff H
    4. Berg MP

    (2017) Termites promote resistance of decomposition to spatiotemporal variability in rainfall

    Ecology 98:467–477.

    https://doi.org/10.1002/ecy.1658

    • PubMed
    • Google Scholar
46. 1. Wall DH
    2. Bradford MA
    3. St. John MG
    4. Trofymow JA
    5. Behan‐pelletier V
    6. Bignell DE
    7. Dangerfield JM
    8. Parton WJ
    9. Rusek J
    10. Voigt W
    11. Wolters V
    12. Gardel HZ
    13. Ayuke FO
    14. Bashford R
    15. Beljakova OI
    16. Bohlen PJ
    17. Brauman A
    18. Flemming S
    19. Henschel JR
    20. Johnson DL
    21. Jones TH
    22. Kovarova M
    23. Kranabetter JM
    24. Kutny L
    25. Lin K
    26. Maryati M
    27. Masse D
    28. Pokarzhevskii A
    29. Rahman H
    30. Sabará MG
    31. Salamon J
    32. Swift MJ
    33. Varela A
    34. Vasconcelos HL
    35. White D
    36. Zou X

    (2008) Global decomposition experiment shows soil animal impacts on decomposition are climate‐dependent

    Global Change Biology 14:2661–2677.

    https://doi.org/10.1111/j.1365-2486.2008.01672.x

    • Google Scholar
47. 1. Whitford WG
    2. Meentemeyer V
    3. Seastedt TR
    4. Cromack K
    5. Crossley DA
    6. Santos P
    7. Todd RL
    8. Waide JB

    (1981) Exceptions to the aet model: deserts and clear‐cut forest

    Ecology 62:275–277.

    https://doi.org/10.2307/1936687

    • Google Scholar
48. 1. Wu X
    2. Niklas KJ
    3. Sun S

    (2021) Climate change affects detritus decomposition rates by modifying arthropod performance and species interactions

    Current Opinion in Insect Science 47:62–66.

    https://doi.org/10.1016/j.cois.2021.05.002

    • PubMed
    • Google Scholar
49. 1. Xu X
    2. Sun Y
    3. Sun J
    4. Cao P
    5. Wang Y
    6. Chen HYH
    7. Wang W
    8. Ruan H

    (2020) Cellulose dominantly affects soil fauna in the decomposition of forest litter: A meta-analysis

    Geoderma 378:114620.

    https://doi.org/10.1016/j.geoderma.2020.114620

    • Google Scholar
50. 1. Zaady E
    2. Groffman PM
    3. Shachak M
    4. Wilby A

    (2003) Consumption and release of nitrogen by the harvester termite anacanthotermes ubachi navas in the northern negev desert, israel

    Soil Biology and Biochemistry 35:1299–1303.

    https://doi.org/10.1016/S0038-0717(03)00200-1

    • Google Scholar
51. 1. Zanne AE
    2. Flores-Moreno H
    3. Powell JR
    4. Cornwell WK
    5. Dalling JW
    6. Austin AT
    7. Classen AT
    8. Eggleton P
    9. Okada K-I
    10. Parr CL
    11. Adair EC
    12. Adu-Bredu S
    13. Alam MA
    14. Alvarez-Garzón C
    15. Apgaua D
    16. Aragón R
    17. Ardon M
    18. Arndt SK
    19. Ashton LA
    20. Barber NA
    21. Beauchêne J
    22. Berg MP
    23. Beringer J
    24. Boer MM
    25. Bonet JA
    26. Bunney K
    27. Burkhardt TJ
    28. Carvalho D
    29. Castillo-Figueroa D
    30. Cernusak LA
    31. Cheesman AW
    32. Cirne-Silva TM
    33. Cleverly JR
    34. Cornelissen JHC
    35. Curran TJ
    36. D’Angioli AM
    37. Dallstream C
    38. Eisenhauer N
    39. Evouna Ondo F
    40. Fajardo A
    41. Fernandez RD
    42. Ferrer A
    43. Fontes MAL
    44. Galatowitsch ML
    45. González G
    46. Gottschall F
    47. Grace PR
    48. Granda E
    49. Griffiths HM
    50. Guerra Lara M
    51. Hasegawa M
    52. Hefting MM
    53. Hinko-Najera N
    54. Hutley LB
    55. Jones J
    56. Kahl A
    57. Karan M
    58. Keuskamp JA
    59. Lardner T
    60. Liddell M
    61. Macfarlane C
    62. Macinnis-Ng C
    63. Mariano RF
    64. Méndez MS
    65. Meyer WS
    66. Mori AS
    67. Moura AS
    68. Northwood M
    69. Ogaya R
    70. Oliveira RS
    71. Orgiazzi A
    72. Pardo J
    73. Peguero G
    74. Penuelas J
    75. Perez LI
    76. Posada JM
    77. Prada CM
    78. Přívětivý T
    79. Prober SM
    80. Prunier J
    81. Quansah GW
    82. Resco de Dios V
    83. Richter R
    84. Robertson MP
    85. Rocha LF
    86. Rúa MA
    87. Sarmiento C
    88. Silberstein RP
    89. Silva MC
    90. Siqueira FF
    91. Stillwagon MG
    92. Stol J
    93. Taylor MK
    94. Teste FP
    95. Tng DYP
    96. Tucker D
    97. Türke M
    98. Ulyshen MD
    99. Valverde-Barrantes OJ
    100. van den Berg E
    101. van Logtestijn RSP
    102. Veen GFC
    103. Vogel JG
    104. Wardlaw TJ
    105. Wiehl G
    106. Wirth C
    107. Woods MJ
    108. Zalamea P-C

    (2022) Termite sensitivity to temperature affects global wood decay rates

    Science 377:1440–1444.

    https://doi.org/10.1126/science.abo3856

    • PubMed
    • Google Scholar
52. Preprint

    1. Zeng X
    2. Gao H
    3. Wang R
    4. Machjer B
    5. Woon J
    6. Wenda C
    7. Eggleton P
    8. Griffiths H
    9. Ashton L

    (2023) Soil invertebrates are the key drivers of litter decomposition in tropical forests

    Preprints.

    https://doi.org/10.22541/au.167776750.08748069/v1

    • Google Scholar
53. 1. Zhang D
    2. Hui D
    3. Luo Y
    4. Zhou G

    (2008) Rates of litter decomposition in terrestrial ecosystems: global patterns and controlling factors

    Journal of Plant Ecology 1:85–93.

    https://doi.org/10.1093/jpe/rtn002

    • Google Scholar

Author details

1. Viraj R Torsekar

   1. Risk-Management Ecology Lab, Department of Ecology, Evolution & Behavior The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
   2. Theoretical Ecology and Evolution Lab, Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, India

   Contribution

   Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Nevo Sagi

   For correspondence

   viraj.torsekar@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6096-6454

2. Nevo Sagi

   Risk-Management Ecology Lab, Department of Ecology, Evolution & Behavior The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Viraj R Torsekar

   For correspondence

   nevo.sagi@mail.huji.ac.il

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4745-4304

3. J Alfred Daniel

   The National Natural History Collections, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Data curation, Methodology, Writing – review and editing, Identified animal samples

   Competing interests

   No competing interests declared

4. Yael Hawlena

   Risk-Management Ecology Lab, Department of Ecology, Evolution & Behavior The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Data curation, Methodology, Writing – review and editing, Identified animal samples

   Competing interests

   No competing interests declared

5. Efrat Gavish-Regev

   The National Natural History Collections, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Data curation, Methodology, Writing – review and editing, Identified animal samples

   Competing interests

   No competing interests declared

6. Dror Hawlena

   1. Risk-Management Ecology Lab, Department of Ecology, Evolution & Behavior The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
   2. The National Natural History Collections, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Conceptualization, Supervision, Funding acquisition, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9142-1553

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