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Reactivity continuum modeling of leaf, root, and wood decomposition across biomes

Authors :
Birgit Koehler
Lars J. Tranvik
Source :
Journal of Geophysical Research: Biogeosciences. 120:1196-1214
Publication Year :
2015
Publisher :
American Geophysical Union (AGU), 2015.

Abstract

Large carbon dioxide amounts are released to the atmosphere during organic matter decomposition. Yet the large-scale and long-term regulation of this critical process in global carbon cycling by litter chemistry and climate remains poorly understood. We used reactivity continuum (RC) modeling to analyze the decadal data set of the “Long-term Intersite Decomposition Experiment,” in which fine litter and wood decomposition was studied in eight biome types (224 time series). In 32 and 46% of all sites the litter content of the acid-unhydrolyzable residue (AUR, formerly referred to as lignin) and the AUR/nitrogen ratio, respectively, retarded initial decomposition rates. This initial rate-retarding effect generally disappeared within the first year of decomposition, and rate-stimulating effects of nutrients and a rate-retarding effect of the carbon/nitrogen ratio became more prevalent. For needles and leaves/grasses, the influence of climate on decomposition decreased over time. For fine roots, the climatic influence was initially smaller but increased toward later-stage decomposition. The climate decomposition index was the strongest climatic predictor of decomposition. The similar variability in initial decomposition rates across litter categories as across biome types suggested that future changes in decomposition may be dominated by warming-induced changes in plant community composition. In general, the RC model parameters successfully predicted independent decomposition data for the different litter-biome combinations (196 time series). We argue that parameterization of large-scale decomposition models with RC model parameters, as opposed to the currently common discrete multiexponential models, could significantly improve their mechanistic foundation and predictive accuracy across climate zones and litter categories.

Details

ISSN :
21698953
Volume :
120
Database :
OpenAIRE
Journal :
Journal of Geophysical Research: Biogeosciences
Accession number :
edsair.doi...........bd8ba83ae5d0da569489ca9bc2892644
Full Text :
https://doi.org/10.1002/2015jg002908