EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Integrating multi-source data and model projections to address carbon cycling in central European forests

Katarina Merganicova1, Roland Hollos2, Zoltan Barcza1,2,5, Jan Merganic3, Zuzana Sitkova4, Daniel Kurjak3, Martin Mokros1, Peter Fleischer3, Hrvoje Marjanovic6, Dora Hidy5, Katarina Strelcova3, and Tomas Hlasny1
Katarina Merganicova et al.
  • 1Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic, (
  • 2Eötvös Loránd University, Department of Meteorology, Budapest, Hungary
  • 3Technical University in Zvolen, Faculty of Forestry, Zvolen, Slovakia (
  • 4National Forest Centre - Forest Research Institute Zvolen, Zvolen, Slovakia
  • 5Eötvös Loránd University, Faculty of Science, Excellence Center, Martonvásár, Hungary
  • 6Croatian Forests Research Institute, Department for Forest Management and Forestry Economics, Zagreb, Croatia

Carbon cycling in forest ecosystems is affected by a number of interacting environmental factors. Here we analyse carbon sequestration in temperate forests composed of three common Central European species: Norway spruce, European beech and oak along an extended environmental gradient across Central Europe using long-term monitoring data and process-based modelling of forest dynamics. For the analyses we used selected ICP forest monitoring plots, long-term forest research plots from thinning trials, and highly-equipped intensively monitored plots from five central European countries: Croatia, Hungary, Slovakia, Poland and the Czech Republic. Their temporal development was simulated using a process-based model Biome-BGCMuSo, which is sensitive to soil and climate conditions. Since such models of forest growth dynamics implicitly describe relationships between forest productivity and environmental conditions, their implementation can reveal the main factors affecting carbon cycling in forests along the gradients of latitude, altitude, or other environmental factors as long as they are included in the models. The study indicates that by linking long-term monitoring data and forest growth modelling we can not only test the model capacity to simulate forest dynamics, but above all we can increase our capacity to address main challenges faced by the central European forestry with respect to the global climate change.  

How to cite: Merganicova, K., Hollos, R., Barcza, Z., Merganic, J., Sitkova, Z., Kurjak, D., Mokros, M., Fleischer, P., Marjanovic, H., Hidy, D., Strelcova, K., and Hlasny, T.: Integrating multi-source data and model projections to address carbon cycling in central European forests , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13412,, 2020