Effects of detritivorous invertebrates on the decomposition of rice straw: evidence from a microcosm experiment
Decomposition of crop residues is a key process in agricultural systems that influences nutrient cycling and productivity. To clarify the roles of different groups of invertebrates in decomposition in paddy fields, we conducted a microcosm experiment, testing the effects of soil eluate filtered through a 21 μm mesh (control treatment) against the effects of microfauna (< 0.1 mm) and small gastropods (juvenile golden apple snails (Pomacea canaliculata), ca. 2 mm shell diameter), both separately and in combination, on rice straw decomposition. Rice straw in litterbags was incubated at the soil surface and in the soil together with standardized amounts of the respective detritivores for 10 and 21 days. Compared to the control treatment, snails and microfauna enhanced the reduction in straw mass on the soil surface by 19 and 22%, respectively. Both groups combined increased the reduction in straw biomass by 30%. Below the soil surface, the contribution of detritivores to decomposition was smaller, reducing straw biomass by just 1% (snails), 11% (microfauna) and 14% (snails + microfauna) compared to the control. The effects of microfauna and snails on decomposition were not fully additive, a pattern that could be due to competition or trophic interactions. Model selection using Akaike’s information criterion on nested linear mixed effects models led to a model including the main effects (snails, microfauna, position and time), several two-way interactions and the three-way interaction snails * microfauna * litterbag_position as the most parsimonious description of the data. Keeping straw accessible to aquatic invertebrate detritivores should be a suitable management strategy to enhance decomposition in paddy fields, although trade-offs with other management issues such as pest control need to be considered.
KeywordsMicrofauna Ecosystem function Golden apple snail Pomacea canaliculata Oryza sativa
We would like to thank the staff at the Crop and Environmental Science Department of the International Rice Research Institute for their hospitality during the microcosm experiment. We are grateful to Sylvia (Bong) Villareal, Liberty Almazan, Carmencita Bernal, Arriza Arida and Alberto Naredo for their support. This study was funded in part through the project ‘Land-use intensity and Ecological Engineering—Assessment Tools for risks and Opportunities in irrigated rice based production systems’ (LEGATO), German Federal Ministry for Education and Research (BMBF), Grant No. 01LL09 17L.
- Bartoń K (2015) Multi-model inference. R package version 1.15.6. https://CRAN.R-project.org/package=MuMIn. Accessed 9 April 2017
- Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information–theoretic approach. Springer, New YorkGoogle Scholar
- de Vries FT, Thebault E, Liiri M, Birkhofer K, Tsiafouli MA, Bjornlund L, Jorgensen HB, Brady MV, Christensen S, de Ruiter PC, d’Hertefeldt T, Frouz J, Hedlund K, Hemerik L, Hol WHG, Hotes S, Mortimer SR, Setala H, Sgardelis SP, Uteseny K, van der Putten WH, Wolters V, Bardgett RD (2013) Soil food web properties explain ecosystem services across European land use systems. Proc Natl Acad Sci USA 110:14296–14301CrossRefPubMedPubMedCentralGoogle Scholar
- Dobermann A, Fairhurst TH (2002) Rice straw management. Better Crops Int 16:7–11Google Scholar
- Gelman A, Su Y-S (2016) Arm: data analysis using regression and multilevel/hierarchical models. R package version 1.9-3. https://CRAN.R-project.org/package=arm. Accessed 9 April 2017
- Kuznetsova A, Brockhoff PB, Christensen RHB (2016) lmerTest: tests in linear mixed effects models. R package version 2.0-33. https://CRAN.R-project.org/package=lmerTest. Accessed 9 April 2017
- Okada H, Niwa S, Takemoto S, Komatsuzaki M, Hiroki M (2011) How different or similar are nematode communities between a paddy and an upland rice fields across a flooding-drainage cycle? Soil Biol Biochem 43:2142–2151Google Scholar
- R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Accessed 9 April 2017
- Schmidt A, John K, Arida G, Auge H, Brandl R, Horgan FG, Hotes S, Marquez L, Radermacher N, Settele J, Wolters V, Schadler M (2015b) Effects of residue management on decomposition in irrigated rice fields are not related to changes in the decomposer community. PLoS ONE 10(7):e0134402. https://doi.org/10.1371/journal.pone.0134402 CrossRefPubMedPubMedCentralGoogle Scholar
- Turbé A, De Toni A, Benito P, Lavelle P, Lavelle P, Ruiz N, Van der Putten WH, Labouze E, Mudgal S (2010) Soil biodiversity: functions, threats and tools for policy makers. Report for European Commission (DG Environment). Bio Intelligence Service, Institut de Recherche pour le Dévelloppement (IRD) and Netherlands Institute of Ecology (NIOO), ParisGoogle Scholar
- van der Putten WH, Bardgett RD, de Ruiter PC, Hol WHG, Meyer KM, Bezemer TM, Bradford MA, Christensen S, Eppinga MB, Fukami T, Hemerik L, Molofsky J, Schadler M, Scherber C, Strauss SY, Vos M, Wardle DA (2009) Empirical and theoretical challenges in aboveground-belowground ecology. Oecologia 161:1–14CrossRefPubMedPubMedCentralGoogle Scholar
- Wall DH, Bradford MA, St MG, John JA, Trofymow V, Behan-Pelletier DDE, Bignell JM, Dangerfield WJ, Parton J, Rusek W, Voigt V, Wolters HZ, Gardel FO, Ayuke R, Bashford OI, Beljakova PJ, Bohlen A, Brauman S, Flemming JR, Henschel DL, Johnson TH, Jones M, Kovarova JM, Kranabetter L, Kutny K-C, Lin M, Maryati D, Masse A, Pokarzhevskii H, Rahman MG, Sabara J-A, Salamon MJ, Swift A, Varela HL, Vasconcelos D White, Zou X (2008) Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent. Glob Change Biol 14:2661–2677Google Scholar