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Modelling mean above and below ground litter production based on yield tables

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons62608

Wutzler,  T.
Research Group Biogeochemical Model-data Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62495

Mund,  M.
Department Biogeochemical Processes, Prof. E.-D. Schulze, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Wutzler, T., & Mund, M. (2007). Modelling mean above and below ground litter production based on yield tables. Silva Fennica, 41(3): 289. doi:10.14214/sf.289.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-D614-F
Zusammenfassung
Estimates of litter production are a prerequisite for modeling soil carbon stocks and its changes at regional to national scale. However, the required data on biomass removal is often available only for the recent past. In this study we used yield tables as a source of probable past forest management to drive a single tree based stand growth model. Next, simulated growth and timber volume was converted to tree compartment carbon stocks and biomass turnover. The study explicitly accounted for differences in site quality between stands. In addition we performed a Monte Carlo uncertainty and sensitivity analysis. We exemplify the approach by calculating long-term means of past litter production for 10 species by using yield tables that have been applied in Central Germany during the last century. We found that litter production resulting from harvest residues was almost as large as the one from biomass turnover. Differences in site quality caused large differences in litter production. At a given site quality, the uncertainty in soil carbon inputs were 14%, 17%, and 25% for beech, spruce, and pine stands, respectively. The sensitivity analysis, showed that the most influential parameters were associated with foliage biomass and turnover. We conclude that rates of mean past litter production and their uncertainties can reliably be modeled on the basis of yield tables if the model accounts for 1) full rotation length including thinning and final harvest, 2) differences in site quality, and 3) environmental dependency of foliage biomass and foliage turnover.