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A test of the hierarchical model of litter decomposition

Abstract

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle–climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO2. Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France—and capturing both within and among site variation in putative controls—we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

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Fig. 1: Study design and site characteristics.
Fig. 2: Competing assumptions for how decomposer communities affect relationships between climate and decomposition rates at regional to global scales.
Fig. 3: Measured variation in decomposition rates and controlling variables within and among sites.
Fig. 4: Estimated effects of temperature and moisture controls on decomposition rates.
Fig. 5: Estimated effects of controls on decomposition rates.

References

  1. Bradford, M. A., Berg, B., Maynard, D. S., Wieder, W. R. & Wood, S. A. Understanding the dominant controls on litter decomposition. J. Ecol. 104, 229–238 (2016).

    Article  CAS  Google Scholar 

  2. Cornwell, W. K. et al. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol. Lett. 11, 1065–1071 (2008).

    Article  PubMed  Google Scholar 

  3. Freschet, G. T., Aerts, R. & Cornelissen, J. H. C. A plant economics spectrum of litter decomposability. Funct. Ecol. 26, 56–65 (2012).

    Article  Google Scholar 

  4. Makkonen, M. et al. Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient. Ecol. Lett. 15, 1033–1041 (2012).

    Article  PubMed  Google Scholar 

  5. Swift, M. J., Heal, O. W. & Anderson, J. M. Decomposition in Terrestrial Ecosystems Studies in Ecology Vol. 5 (Blackwell Scientific, Oxford Univ. Press, Oxford, 1979).

  6. Buchkowski, R. W., Bradford, M. A., Grandy, A. S., Schmitz, O. J. & Wieder, W. R. Applying population and community ecology theory to advance understanding of belowground biogeochemistry. Ecol. Lett. 20, 231–245 (2017).

    Article  PubMed  Google Scholar 

  7. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E. & Pacala, S. W. Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nat. Clim. Change 4, 1099–1102 (2014).

    Article  CAS  Google Scholar 

  8. Tang, J. & Riley, W. J. Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions. Nat. Clim. Change 5, 56–60 (2015).

    Article  CAS  Google Scholar 

  9. Wieder, W. R., Bonan, G. B. & Allison, S. D. Global soil carbon projections are improved by modelling microbial processes. Nat. Clim. Change 3, 909–912 (2013).

    Article  CAS  Google Scholar 

  10. Levin, S. A. The problem of pattern and scale in ecology. Ecology 73, 1943–1967 (1992).

    Article  Google Scholar 

  11. Lauenroth, W. K. & Sala, O. E. Long-term forage production of North American shortgrass steppe. Ecol. Appl. 2, 397–403 (1992).

    Article  CAS  PubMed  Google Scholar 

  12. Berg, B. et al. Litter mass loss rates in pine forests of Europe and Eastern United States: some relationships with climate and litter quality. Biogeochemistry 20, 127–159 (1993).

    Article  Google Scholar 

  13. Harmon, M. E. et al. Long-term patterns of mass loss during the decomposition of leaf and fine root litter: an intersite comparison. Glob. Change Biol. 15, 1320–1338 (2009).

    Article  Google Scholar 

  14. Moore, T. R. et al. Litter decomposition rates in Canadian forests. Glob. Change Biol. 5, 75–82 (1999).

    Article  Google Scholar 

  15. Wall, D. H. et al. Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob. Change Biol. 14, 2661–2677 (2008).

    Google Scholar 

  16. Bonan, G. B., Hartman, M. D., Parton, W. J. & Wieder, W. R. Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Glob. Change Biol. 19, 957–974 (2013).

    Article  Google Scholar 

  17. Averill, C., Waring, B. G. & Hawkes, C. V. Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture. Glob. Change Biol. 5, 1957–1964 (2016).

    Article  Google Scholar 

  18. Strickland, M. S., Keiser, A. D. & Bradford, M. A. Climate history shapes contemporary leaf litter decomposition. Biogeochemistry 122, 165–174 (2015).

    Article  Google Scholar 

  19. Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109, 21390–21395 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Evans, S. E. & Wallenstein, M. D. Climate change alters ecological strategies of soil bacteria. Ecol. Lett. 17, 155–164 (2014).

    Article  PubMed  Google Scholar 

  21. Loescher, H., Ayres, E., Duffy, P., Luo, H. & Brunke, M. Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs. PLoS ONE 9, e83216 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Scherrer, D. & Körner, C. Infra-red thermometry of alpine landscapes challenges climatic warming projections. Glob. Change Biol. 16, 2602–2613 (2010).

    Google Scholar 

  23. Meentemeyer, V. Macroclimate and lignin control of litter decomposition rates. Ecology 59, 465–472 (1978).

    Article  CAS  Google Scholar 

  24. García-Palacios, P., Maestre, F. T., Kattge, J. & Wall, D. H. Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol. Lett. 16, 1045–1053 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Tenney, F. G. & Waksman, S. A. Composition of natural organic materials and their decomposition in the soil: IV. The nature and rapidity of decomposition of the various organic complexes in different plant materials, under aerobic conditions. Soil Science 28, 55–84 (1929).

    Article  CAS  Google Scholar 

  26. Handa, I. T. et al. Consequences of biodiversity loss for litter decomposition across biomes. Nature 509, 218–221 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Powers, J. S. et al. Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient. J. Ecol. 97, 801–811 (2009).

    Article  CAS  Google Scholar 

  28. Crowther, T. W. et al. Biotic interactions mediate soil microbial feedbacks to climate change. Proc. Natl Acad. Sci. USA 112, 7033–7038 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lawrence, C. R., Neff, J. C. & Schimel, J. P. Does adding microbial mechanisms of decomposition improve soil organic matter models? A comparison of four models using data from a pulsed rewetting experiment. Soil Biol. Biochem. 41, 1923–1934 (2009).

    Article  CAS  Google Scholar 

  30. Hall, E. et al. Understanding how microbiomes influence the systems they inhabit: insight from ecosystem ecology. Preprint at https://doi.org/10.1101/065128 (2016).

  31. Aerts, R. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79, 439–449 (1997).

    Article  Google Scholar 

  32. Allison, S. D., Wallenstein, M. D. & Bradford, M. A. Soil-carbon response to warming dependent on microbial physiology. Nat. Geosci. 3, 336–340 (2010).

    Article  CAS  Google Scholar 

  33. Crowther, T. W. et al. Environmental stress response limits microbial necromass contributions to soil organic carbon. Soil Biol. Biochem. 85, 153–161 (2015).

    Article  CAS  Google Scholar 

  34. Frey, S. D., Lee, J., Melillo, J. M. & Six, J. The temperature response of soil microbial efficiency and its feedback to climate. Nat. Clim. Change 3, 395–398 (2013).

    Article  CAS  Google Scholar 

  35. Schimel, J. P. & Weintraub, M. N. The implications of exoenzyme activity on microbial carbon and nitrogen limitation in soil: a theorectical model. Soil Biol. Biochem. 35, 549–563 (2003).

    Article  CAS  Google Scholar 

  36. Buchkowski, R. W., Schmitz, O. J. & Bradford, M. A. Microbial stoichiometry overrides biomass as a regulator of soil carbon and nitrogen cycling. Ecology 96, 1139–1149 (2015).

    Article  PubMed  Google Scholar 

  37. Adair, E. C. et al. Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates. Glob. Change Biol. 14, 2636–2660 (2008).

    Google Scholar 

  38. Currie, W. S. et al. Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale. Glob. Change Biol. 16, 1744–1761 (2010).

    Article  Google Scholar 

  39. Smith, V. C. & Bradford, M. A. Litter quality impacts on grassland litter decomposition are differently dependent on soil fauna across time. Appl. Soil Ecol. 24, 197–203 (2003).

    Article  Google Scholar 

  40. Bradford, M. A., Tordoff, G. M., Eggers, T., Jones, T. H. & Newington, J. E. Microbiota, fauna, and mesh size interactions in litter decomposition. Oikos 99, 317–323 (2002).

    Article  Google Scholar 

  41. Bokhorst, S. & Wardle, D. A. Microclimate within litter bags of different mesh size: implications for the ‘arthropod effect’ on litter decomposition. Soil Biol. Biochem. 58, 147–152 (2013).

    Article  CAS  Google Scholar 

  42. Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).

    Article  CAS  Google Scholar 

  43. Keiser, A. D., Knoepp, J. D. & Bradford, M. A. Disturbance decouples biogeochemical cycles across forests of the southeastern US. Ecosystems 19, 50–61 (2016).

    Article  Google Scholar 

  44. Waring, B., Adams, R., Branco, S. & Powers, J. S. Scale-dependent variation in nitrogen cycling and soil fungal communities along gradients of forest composition and age in regenerating tropical dry forests. New Phytol. 209, 845–854 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Schmitz, O. J. Resolving Ecosystem Complexity (Princeton Univ. Press, Princeton, 2010).

  46. Oakes, M. J. Commentary: individual, ecological and multilevel fallacies. Int. J. Epidemiol. 38, 361–368 (2009).

    Article  PubMed  Google Scholar 

  47. Robinson, W. S. Ecological correlations and the behavior of individuals. Am. Sociol. Rev. 15, 351–357 (1950).

    Article  Google Scholar 

  48. Schuessler, A. A. Ecological inference. Proc. Natl Acad. Sci. USA 96, 10578–10581 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Gelman, A., Shor, B., Bafumi, J. & Park, D. Rich state, poor state, red state, blue state: what’s the matter with Connecticut? Quart. J. Polit. Sci. 2, 345–367 (2008).

    Article  Google Scholar 

  50. Gelman, A. & Hill, J. Data Analysis using Regression and Multilevel/Hierarchical Models (Cambridge Univ. Press, Cambridge, 2007).

  51. Rousk, J. Biomass or growth? How to measure soil food webs to understand structure and function. Soil Biol. Biochem. 102, 45–47 (2016).

    Article  CAS  Google Scholar 

  52. Allison, S. D. et al. Microbial abundance and composition influence litter decomposition response to environmental change. Ecology 94, 714–725 (2013).

    Article  PubMed  Google Scholar 

  53. Anderson, J. P. E. & Domsch, K. H. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem. 10, 215–221 (1978).

    Article  CAS  Google Scholar 

  54. Fierer, N., Schimel, J. P. & Holden, P. A. Influence of drying–rewetting frequency on soil bacterial community structure. Microb. Ecol. 45, 63–71 (2003).

    Article  CAS  PubMed  Google Scholar 

  55. Robertson, G. P. et al. in Standard Soil Methods for Long-Term Ecological Research (eds Robertson, G. P., Coleman, D. C., Bledsoe, C. S. & Sollins, P.) 258–271 (Oxford Univ. Press, Oxford, 1999).

  56. Poorter, H. & Villar, R. in Plant Resource Allocation (eds Bazzaz, F. A. & Grace, J.) 39–72 (Academic Press, San Diego, 1997).

  57. Hendry, G. A. F. & Grime, J. P. Methods in Comparative Plant Ecology (Chapman & Hall, London, 1993).

  58. Cornelissen, J. H. C. et al. Foliar pH as a new plant trait: can it explain variation in foliar chemistry and carbon cycling processes among subarctic plant species and types? Oecologia 147, 315–326 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Hobbs, N. T., Andren, H., Persson, J., Aronsson, M. & Chapron, G. Native predators reduce harvest of reindeer by Sámi pastoralists. Ecol. Appl. 22, 1640–1654 (2012).

    Article  PubMed  Google Scholar 

  60. Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).

    Article  PubMed  Google Scholar 

  61. Fierer, N., Craine, J. M., McLauchlan, K. & Schimel, J. P. Litter quality and the temperature sensitivity of decomposition. Ecology 86, 320–326 (2005).

    Article  Google Scholar 

  62. Conant, R. T. et al. Temperature and soil organic matter decomposition rates – synthesis of current knowledge and a way forward. Glob. Change Biol. 17, 3392–3404 (2011).

    Article  Google Scholar 

  63. Smith, V. C. & Bradford, M. A. Do non-additive effects on decomposition in litter-mix experiments result from differences in resource quality between litters? Oikos 102, 235–242 (2003).

    Article  Google Scholar 

  64. Gelman, A. Scaling regression inputs by dividing by two standard deviations. Stat. Med. 27, 2865–2873 (2008).

    Article  PubMed  Google Scholar 

  65. Baayen, R. H., Davidson, D. J. & Bates, D. M. Mixed-effects modeling with crossed random effects for subjects and items. J. Mem. Lang. 59, 390–412 (2008).

    Article  Google Scholar 

  66. Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R 2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).

    Article  Google Scholar 

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Acknowledgements

We thank R. Pas and M. Hundscheid for lab assistance, and the Röbäcksdalen field station staff for providing land and logistic support at the Umeå site. Research was supported by grants to M.A.B. from the US National Science Foundation (DEB-1457614), The Royal Netherlands Academy of Arts and Sciences (Visiting Professors Programme), and the Netherlands Production Ecology & Resource Conservation Programme for Visiting Scientists. G.F.V. was supported by an NWO-VENI from the Netherlands Organisation for Scientific Research (863.14.013). M.M.-F. and W.H.v.d.P. were supported by a European Research Council grant (ERC-Adv 260-55290), and G.T.F. by grant EC2CO-Multivers. We thank the Bradford lab group for comments on an earlier version of the manuscript.

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M.A.B. and G.F.V. designed the study, co-wrote the manuscript, constructed litterbags and carried out the lab analyses. All authors established, maintained and collected data from the field sites. M.A.B., G.F.V., D.S.M. and S.A.W. analysed data. All authors contributed to data interpretation and writing of the paper.

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Correspondence to Mark A. Bradford.

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Bradford, M.A., Veen, G.F.(., Bonis, A. et al. A test of the hierarchical model of litter decomposition. Nat Ecol Evol 1, 1836–1845 (2017). https://doi.org/10.1038/s41559-017-0367-4

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