Thomas Wutzler, Martina Mund. (2007). Modelling mean above and below ground litter production based on yield tables. Silva Fennica vol. 41 no. 3 article id 289. https://doi.org/10.14214/sf.289

Keywords: uncertainty; thinnings; soil carbon; biomass turnover; carbon accounting; harvest residues; sensitivity analysis

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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
Mund, Max Planck Institute for Biogeochemistry, Jena, Germany E-mail: mm@nn.de

Category : Research article

article id 449, category Research article

Thomas Wutzler, Ingolf Profft, Martina Mund. (2011). Quantifying tree biomass carbon stocks, their changes and uncertainties using routine stand taxation inventory data. Silva Fennica vol. 45 no. 3 article id 449. https://doi.org/10.14214/sf.449

Keywords: forest management; forest inventory; uncertainty; carbon stocks

Abstract | View details | Full text in PDF | Author Info

For carbon (C) trading or any other verifiable C reports, it would be reasonable to identify and quantify continuous changes in carbon stocks at regional scales without high investments into additional C-specific, time- and labor-intensive inventories. Our study demonstrates the potential of using routine stand taxation data from large scale forestry inventories for verifiable quantification of tree biomass C stocks, C stock change rates, and associated uncertainties. Empirical models, parameters, and equations of uncertainty propagation have been assembled and applied to data from a forest management unit in Central Germany (550 000 ha), using stand taxation inventories collected between 1993 and 2006. The study showed: 1) The use of stand taxation data resulted in a verifiable and sufficiently precise (cv = 7%) quantification of tree biomass carbon stocks and their changes at the level of growth-regions (1700 to 140 000 ha). 2) The forest of the test region accumulated carbon in tree biomass at a mean annual rate of 1.8 (–0.9 to 4.5) tC/ha/yr over the studied period. 3) The taxation inventory data can reveal spatial patterns of rates of C stock changes, specifically low rates of 0.4 tC/ha/yr in the northwest and high rates of 3.0 tC/ha/yr in the south of the study region.

Wutzler, Max Planck Institute for Biogeochemistry, Hans-Knöll-Strasse 10, 07745 Jena, Germany E-mail: twutz@bgc-jena.mpg.de
Profft, Max Planck Institute for Biogeochemistry, Hans-Knöll-Stra§e 10, 07745 Jena, Germany E-mail: ip@nn.de
Mund, Max Planck Institute for Biogeochemistry, Hans-Knöll-Stra§e 10, 07745 Jena, Germany E-mail: mm@nn.de

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