Journal article
Available and missing data to model impact of climate change on European forests
University of Alcalá1
Universidad Nacional de Cuyo2
Technical University of Madrid3
Université de Bordeaux4
University of Bern5
CSIC6
Centre for Ecological Research and Forestry Applications7
Max Planck Institute for Biogeochemistry8
Luke Natural Resources Institute Finland9
Department of Environmental Engineering, Technical University of Denmark10
Air, Land & Water Resources, Department of Environmental Engineering, Technical University of Denmark11
University of Milan12
Queen Mary University of London13
Potsdam Institute for Climate Impact Research14
Leipzig University15
Université de Montpellier16
University of Regensburg17
University of Helsinki18
University of Freiburg19
...and 9 moreClimate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models.
The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts.
Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility.
However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses.
Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests.
Language: | English |
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Publisher: | Elsevier |
Year: | 2020 |
Pages: | 108870 |
ISSN: | 18727026 and 03043800 |
Types: | Journal article |
DOI: | 10.1016/j.ecolmodel.2019.108870 |
ORCIDs: | 0000-0002-2781-5870 , 0000-0001-8100-0659 , 0000-0003-1067-1492 , 0000-0002-6255-9059 , 0000-0001-9633-7350 , 0000-0003-3604-8279 , 0000-0002-3436-123X , 0000-0002-9464-862X and Ibrom, Andreas |