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BGC-model parameters for tree species growing in central European forests
Affiliation:1. Institute of Forest Growth Research, University of Natural Resources and Applied Life Sciences, Peter-Jordan-Str. 82, A-1190 Vienna, Austria;2. National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000, USA;1. Department of Environmental Biology, University of Rzeszów, ul. Zelwerowicza 4, Rzeszów, Poland;2. Department of Agrobiology and Environmental Protection, University of Rzeszów, ul. Zelwerowicza 4, Rzeszów, Poland;1. Department of Physical Geography and Geoecology, Faculty of Science, Charles University, Albertov 6, 12843 Prague, Czech Republic;2. Czech Geological Survey, Klárov 3, 11821 Prague, Czech Republic;3. School of Earth and Environmental Sciences, University of St Andrews, St Andrews, UK;4. Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha 6–Suchdol, Prague, 16521, Czech Republic;5. Institute of Meteorology and Water Management - National Research Institute, 01–673 Warsaw, Podleśna Street 61, Poland;6. University of Wrocɬaw, Institute of Geography and Regional Development, Department of Climatology and Atmosphere Protection, pl. Uniwersytecki 1, 50–137 Wrocɬaw, Poland;1. Department of Forest and Landscape Ecology, National Forest Centre – Forest Research Institute Zvolen, T. G. Masaryka 22, Zvolen, Slovakia;2. Faculty of Forestry and Wood Sciences, Czech University of Life Sciences in Prague, Prague, Kamýcká 22, Czech Republic;3. Department of Meteorology, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117 Budapest, Hungary;4. Institute of Ecology and Botany, Centre for Ecological Research, Hungarian Academy of Sciences, Alkotmány 2-4, H-2163 Vácrátót, Hungary;5. Faculty of Forestry and Wood Sciences, Technical University Zvolen, T. G. Masaryka 24, Zvolen, Slovakia;6. Space Research Group, Department of Geophysics and Space Science, Institute of Geography and Earth Sciences, Eötvös Loránd University, H-1117 Budapest, Pázmány Péter sétány 1/C, Hungary;7. Institute of Geography, Humboldt University of Berlin, Rudower Chaussee 16, 12489 Berlin, Germany;1. Chair of Silviculture, Faculty of Environment and Natural Resources, Freiburg University, Tennenbacherstr. 4, 79108, Freiburg, Germany;2. Chair of Forest Inventory and Remote Sensing, Georg-August-Universität Göttingen, Büsgenweg 5, 37077, Göttingen, Germany;1. International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria;2. Chair of Forestry Economics and Forest Planning, University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, Germany;1. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland;2. Chair of Silviculture, Albert-Ludwigs-Universität Freiburg, Germany;3. Silviculture and Forest Ecology of the Temperate Zones, Georg-August-Universität Göttingen, Germany;4. Department of Forest Management and Urban Greenery, Faculty of Forestry, University Sarajevo, Bosnia and Herzegovina;5. Laboratoire d''Etude des Ressources Forêt Bois (LERFoB), INRA Centre of Nancy, Champenoux, France;6. Department of Silviculture, Warsaw University of Life Sciences, Poland;7. Institute of Forest Biology and Silviculture, Aleksandras, Stulginskis University, Kaunas, Lithuania;8. Department of Agriculture and Forest Engineering – Forest Sciences Centre of Catalonia (CTFC), University of Lleida, Spain;9. Department of Silviculture and Forest Management, INIA, Forest Research Centre INIA-CIFOR Forest Research Centre, Crta. La Coruña km 7,5, 28040 Madrid, Spain;10. Sustainable Forest Management Research Institute, University of Valladolid & INIA, Spain;11. Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden;12. Chair for Forest Growth and Yield Science, Technische Universität München, Germany;13. Department of Silviculture, Mendel University, Brno, Czech Republic;14. Institute of Lowland Forestry and Environment, University of Novi Sad, Novi Sad, Serbia;15. Department of Agricultural, Forest and Food Sciences, DISAFA, University of Turin, Turin, Italy;p. Forest Ecology and Forest Management Group, Wageningen University & Research, Wageningen, The Netherlands;q. Department of Silviculture, Institute of Forest Ecology and Silviculture, University of Agriculture, Krakow, Poland;r. Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas, CITAB, Universidade de Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, 5000-801 Vila Real, Portugal;s. Universite Catholique de Louvain, Faculty of Bioscience Engineering & Earth and Life Institute, Louvain-la-Neuve, Belgium;t. Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic;u. currently at: European Commission, Joint Research Centre, Directorate D – Sustainable Resources – Bio-Economy Unit, via E. Fermi 2749 – TP261, I-21027 Ispra, VA, Italy;v. Forest & Nature Lab, Ghent University, Melle-Gontrode, Belgium;w. Department of Silviculture, Forest Research Institute, Sofia, Bulgaria
Abstract:During the last centuries forest management has changed the structure and species composition of central European forests. One option to assess forest management and how management impacts may affect forest development over time is the use of biogeochemical ecosystem simulation models. They integrate key ecosystem processes and have proven to be an appropriate diagnostic tool. If we consider that in the past, forest management has strongly affected the species distribution and the structure of central European forests, existing biogeochemical models need to integrate species-specific parameters so that they can adequately address forest management practices such as species changes, stand density etc. The purpose of this paper is to introduce species-specific parameters for one such model, Biome-BGC, for the following tree species as observed in central European forests: Fagus sylvatica, Quercus robur/petraea, Larix decidua, Pinus sylvestris, Pinus cembra as well as two sets of parameters for Picea abies growing at low and high elevations. We first evaluate and test model results obtained with parameters from the literature and single research plots. This evaluation procedure gives our final species-specific parameters that are then used in the model. Next we validate the quality of the model predictions using these parameters versus field observations covering the growing range of a given species by comparing standing tree volume, volume increment, soil carbon and soil nitrogen on 145 independent plots. Our results demonstrate that the species-specific parameters yielded consistent and unbiased predictions.
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