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false4DOIDB.PIK 10.5880/PIK.2019.022 Billing, Maik Maik Billing PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Thonicke, Kirsten Kirsten Thonicke 0000-0001-5283-4937 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany von Bloh, Werner Werner von Bloh 0000-0002-7399-2704 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Sakschewski, Boris Boris Sakschewski PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany GFZ Data Services 2019 functional diversity functional traits trait based modeling process-based modeling vegetation modeling natural forests forests Europe EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > COMMUNITY DYNAMICS > BIODIVERSITY FUNCTIONS EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > COMMUNITY DYNAMICS > COMMUNITY STRUCTURE EARTH SCIENCE > BIOSPHERE > VEGETATION > BIOMASS EARTH SCIENCE > BIOSPHERE > VEGETATION > DECIDUOUS VEGETATION EARTH SCIENCE > BIOSPHERE > VEGETATION > EVERGREEN VEGETATION Billing, Maik Maik Billing PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Billing, Maik Maik Billing PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Thonicke, Kirsten Kirsten Thonicke 0000-0001-5283-4937 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Thonicke, Kirsten Kirsten Thonicke 0000-0001-5283-4937 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Thonicke, Kirsten Kirsten Thonicke 0000-0001-5283-4937 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany von Bloh, Werner Werner von Bloh 0000-0002-7399-2704 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany von Bloh, Werner Werner von Bloh 0000-0002-7399-2704 PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Sakschewski, Boris Boris Sakschewski PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany Thonicke Kirsten PIK Potsdam Institute for Climate Impact Research, Potsdam, Germany 1901-01-01/2013-12-31 Dataset 10.1111/jbi.13809 http://www.fao.org/fileadmin/templates/nr/documents/HWSD/HWSD_Documentation.pdf 10.1111/gcb.12870 10.5880/PIK.2018.002 10.1175/2011JHM1369.1 10.1002/2014WR015638 1 CC BY 4.0 LPJmL-FIT is process- and trait-based vegetation model. It is a subversion of the model LPJmL simulating patches of competing individual trees with flexible functional traits and empirically derived relations between these traits. Trait composition, productivity and stability of a forest are a result of environmental and competitive filtering. A detailed description of LPJmL-FIT (basic features and differences to LPJmL) is given by Sakschewski et al. (Sakschewski et al., 2015, https://doi.org/10.1111/gcb.12870). LPJmL-FIT was originally developed for tropical forests and has been adapted to European forests by Thonicke et al. (2020).


The data covers southern and central Europe (29.5°N – 62°N, 11°W – 36°O) on a spatial resolution of 0.5° covering the years 1901-2013. Tree height, leaf and stem traits (specific leaf area, wood density, leaf longevity; aggregated), individual traits of simulated trees, vegetation distribution (foliage projected cover, FPC), vegetation carbon and fire carbon emissions are given on an annual basis. Gross primary productivity is provided monthly. Tree height and leaf and stem traits are biomass weighted.


For evaluation of the dataset R- and MATLAB-scripts are provided.
An overview and description of all variables are found in the file description.
Southern and Central Europe -11 36 29.5 62 Horizon 2020 Framework Programme http://doi.org/10.13039/100010661 641762 ECOPOTENTIAL