Evaluation of climate‐related carbon turnover processes in global vegetation models for boreal and temperate forests |
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| Authors: | Martin Thurner Christian Beer Philippe Ciais Andrew D Friend Akihiko Ito Axel Kleidon Mark R Lomas Shaun Quegan Tim T Rademacher Sibyll Schaphoff Markus Tum Andy Wiltshire Nuno Carvalhais |
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| Institution: | 1. Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Stockholm, Sweden;2. Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden;3. Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif‐sur‐Yvette, France;4. Department of Geography, University of Cambridge, Cambridge, UK;5. National Institute for Environmental Studies, Tsukuba, Japan;6. Max Planck Institute for Biogeochemistry, Jena, Germany;7. School of Mathematics and Statistics, University of Sheffield, Sheffield, UK;8. Potsdam Institute for Climate Impact Research, Potsdam, Germany;9. German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Wessling, Germany;10. Met Office Hadley Centre, Exeter, UK;11. CENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal |
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| Abstract: | Turnover concepts in state‐of‐the‐art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation‐based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation‐based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation‐based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large‐scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models. |
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| Keywords: | boreal and temperate forest climate‐related spatial gradients drought stress and insect outbreaks forest mortality frost stress global vegetation model evaluation ISI‐MIP remote sensing based NPP and biomass vegetation carbon turnover rate |
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