Models for reporting forest litter and soil C pools in national greenhouse gas inventories: methodological considerations and requirements
2016
Didion, Markus | Blujdea, Viorel | Grassi, Giacomo | Hernández, Laura | Jandl, Robert | Kriiska, Kaie | Lehtonen, Aleksi | Saint-André, Laurent | Swiss Federal Research Institute | Institutul de Cercetari si Amenajari Silvice (ICAS) | Joint Research Centre, Institute for Environment & Sustainability ; European Commission | Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria = National Institute for Agricultural and Food Research and Technology (INIA) | Austrian Research Centre for Forests (BFW) | Tartu University Hospital | Natural Resources Institute Finland (LUKE) | Unité de recherche Biogéochimie des Ecosystèmes Forestiers (BEF) ; Institut National de la Recherche Agronomique (INRA) | ANR (ANR-11-LABX-0002-01) ; Swiss Federal Office for the Environment ; MAGRAMA (EG-13-072) ; INIA (EG-13-072) | ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011)
The compilation of GHG inventories has become a common practice to support environmental decision- and policy-making, for example in the context of the UNFCCC. To estimate GHG emissions, simulation models present viable alternatives to measured data. In order to make an informed decision on model selection, clear information on the purpose and applicability of a particular model is needed. This article discusses model requirements with respect to the suitability of estimating the carbon balance of dead wood and litter (dead organic matter; DOM) and soil in forests with a particular focus on policy needs under international processes such as the UNFCCC. Based on criteria established for GHG reporting under the UNFCCC including transparency, consistency, comparability, completeness and accuracy, this paper presents an approach to classify commonly used simulation models for estimating C budgets of DOM and soil in European forests. Among the six discussed models, the authors found a clear trend toward models for providing quantitatively precise, site-specific estimates. To meet reporting needs for national GHG inventories, the authors conclude that there is a need for models producing qualitative realistic and unbiased estimates at larger scales in a transparent and comparable manner.
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