Decomposition Patterns of Foliar Litter and Deadwood in Managed and Unmanaged Stands: A 13-Year Experiment in Boreal Mixedwoods
- 367 Downloads
Litter decomposition is a major driver of carbon (C) and nitrogen (N) cycles in forest ecosystems and has major implications for C sequestration and nutrient availability. However, empirical information regarding long-term decomposition rates of foliage and wood remains rare. In this study, we assessed long-term C and N dynamics (12–13 years) during decomposition of foliage and wood for three boreal tree species, under a range of harvesting intensities and slash treatments. We used model selection based on the second-order Akaike’s Information Criterion to determine which decomposition model had the most support. The double-exponential model provided a good fit to C mass loss for foliage of trembling aspen, white spruce, and balsam fir, as well as aspen wood. These litters underwent a rapid initial phase of leaching and mineralisation, followed by a slow decomposition. In contrast, for spruce and fir wood, the single-exponential model had the most support. The long-term average decay rate of wood was faster than that of foliage for aspen, but not of conifers. However, we found no evidence that fir and spruce wood decomposed at slower rates than the recalcitrant fraction of their foliage. The critical C:N ratios, at which net N mineralisation began, were higher for wood than for foliage. Long-term decay rates following clear-cutting were either similar or faster than those observed in control stands, depending on litter material, tree species, and slash treatment. The critical C:N ratios were reached later and decreased for all conifer litters following stem-only clear-cutting, indicating increased N retention in harvested sites with high slash loads. Partial harvesting had weak effects on C and N dynamics of decaying litters. A comprehensive understanding of the long-term patterns and controls of C and N dynamics following forest disturbance would improve our ability to forecast the implications of forest harvesting for C sequestration and nutrient availability.
Keywordslong-term decay rate woody debris foliage partial cutting clear-cut C:N ratio litterbag
We are grateful to Josée Frenette, Mylène Bélanger, Émilie Robert, Alfred Coulombe, and Mario Major for field assistance, Serge Rousseau for laboratory analyses, and William F. J. Parsons for English revision. We are also thankful to two anonymous reviewers and Dr. Stephen Hart for their comprehensive review of the manuscript. This study was supported by grants from the Programme de financement de la recherche et du développement en aménagement forestier of the Ministère des Forêts, de la Faune et des Parcs du Québec, from the Cooperative Research Development Program to Drapeau and collaborators (NSERC, RDC475301-14), and Discovery Grant to Brais (NSERCs 217118) of the Natural Sciences and Engineering Research Council of Canada, by the Lake Duparquet Research and Teaching Forest, and by the industrial partner Tembec Inc.
- Burnham KP, Anderson DR. 2002. Model selection and multimodel inference. A practical information-theoretic approach. New York: Springer.Google Scholar
- Cornelissen JHC, Sass-Klaassen U, Poorter L, Van Geffen K, Van Logtestijn RSP, Van Hal J, Goudzwaard L, Sterck FJ, Klaassen RKWM, Freschet GT, Van der Wal A, Eshuis H, Zuo J, De Boer W, Lamers T, Weemstra M, Cretin V, Martin R, Den Ouden J, Berg MP, Aerts R, Mohren GMJ, Hefting MM. 2012. Controls on coarse wood decay in temperate tree species: birth of the LOGLIFE experiment. AMBIO 41:231–45.CrossRefPubMedPubMedCentralGoogle Scholar
- Cotrufo MF, Wallenstein MD, Boot CM, Denef K, Paul E. 2013. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Chang Biol 19:988–95.CrossRefPubMedGoogle Scholar
- Environment Canada. 2015. Canadian climate normals or averages 1981–2010. Available from http://climate.weatheroffice.gc.ca/climate_normals/index_e.html2015.
- Harmon ME, Franklin JF, Swanson FJ, Sollins P, Gregory SV, Lattin JD, Anderson NH, Cline SP, Aumen NG, Sedell JR, Lienkaemper GW, Cromack JRK, Cummins KW. 1986. Ecology of coarse woody debris in temperate ecosystems. In: Caswell H, Ed. Advances in ecological research. Orlando: Academic Press. p 133–302.CrossRefGoogle Scholar
- Mazerolle MJ. 2015. AICcmodavg: model selection and multimodel inference based on (Q)AIC(c). R package version 2.0-3. Available from https://cran.r-project.org/web/packages/AICcmodavg/AICcmodavg.pdf2015.
- R Development Core Team. 2015. R: a language and environment for statistical computing. Version 2.15.2. Vienna: R Foundation for Statistical Computing. Available from http://www.r-project.org/2012.
- Saucier J-P, Bergeron J-F, Grondin P, Robitaille A. 1998. Les régions écologiques du Québec méridional (3rd version). L’Aubelle 124:S1–12.Google Scholar
- Šnajdr J, Cajthaml T, Valášková V, Merhautová V, Petránková M, Spetz P, Leppänen K, Baldrian P. 2011. Transformation of Quercus petraea litter: successive changes in litter chemistry are reflected in differential enzyme activity and changes in the microbial community composition. FEMS Microbiol Ecol 75:291–303.CrossRefPubMedGoogle Scholar
- Soil Classification Working Group. 1998. The Canadian system of soil classification. Ottawa: National Research Council of Canada, Agriculture and Agri-Food Canada.Google Scholar