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Improving National-Scale Carbon Stock Inventories Using Knowledge on Land Use History
Authors:Catharina J E Schulp  Peter H Verburg  Peter J Kuikman  Gert-Jan Nabuurs  Jos G J Olivier  Wim de Vries  Tom Veldkamp
Institution:1. Institute for Environmental Studies, VU University Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands
2. Alterra, Wageningen University and Research Centre, Wageningen, The Netherlands
3. European Forest Institute, Joensuu, Finland
4. PBL Netherlands Environmental Assessment Agency, Bilthoven, The Netherlands
5. ITC Faculty of Geo-Information Science and Earth Observation, University of Twente, PO Box 47, 7500 AA, Enschede, The Netherlands
Abstract:National-scale inventories of soil organic carbon (SOC) and forest floor carbon (FFC) stocks have a high uncertainty. Inventories are often based on the interpolation of sampled information, often using a number of covariables to help such interpolation. The rationale for the choice of these covariables is not always documented, despite the fact that many local-scale studies have identified the factors explaining spatial variability of SOC and FFC stocks. These studies indicate, among others the importance of long-term land use history. Despite this, information on the effects of land use history has never been used to explain variability of carbon stocks in national-scale inventories. We designed an alternative method to improve national-scale inventories of SOC and FCC for the Dutch sand area that takes stock of the findings of detailed case studies. Determinants for SOC and FFC stocks derived from landscape-scale case studies were used to map national-scale spatial variability and to calculate national totals. The resulting national-scale spatial distribution was compared with the SOC stock map from the current Dutch greenhouse gas inventory. Using land use history to explain SOC variability decreased the error of the SOC stock estimate in 60 % of the area. The error in FFC stocks decreased in half of the forest area after including soil fertility, tree species, and forest age as explanatory factors. Estimates with reduced uncertainty will make land use and land management a more attractive and acceptable mitigation option to reduce emissions of greenhouse gases for the LULUCF sector.
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