article id 289,
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                            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.
                        
                
                                            - 
                            Wutzler,
                            Max Planck Institute for Biogeochemistry, Jena, Germany
                                                        E-mail:
                                                            tm@nn.de
                                                                                          
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                            Mund,
                            Max Planck Institute for Biogeochemistry, Jena, Germany
                                                        E-mail:
                                                            mm@nn.de