Scientists map which trees will survive Europe's warming forests
Researchers have created detailed climate projections for 30 European tree species across 860,000 forest plots, predicting which will thrive or fail through 2100. The maps and growth models give forest managers and timber companies concrete data to reshape European woodlands before climate change forces the issue.
Originaltitel: Pan-European maps and models of current and future tree species distributions and their growth potential.
Skogsägare och klimatplanerare kan nu ta beslut om trädslag baserat på detaljerade klimatkartor istället för historiska erfarenheter. Forskargrupper från Tyskland, Österrike och Schweiz har utvecklat prediktionsmodeller för 30 europeiska trädarter genom att analysera över sex miljoner träd från 860 000 skogsplottar. Med dessa modeller kan markägare bedöma vilket trädslag som lämpar sig bäst under framtida klimatförhållanden fram till år 2100. Modellerna täcker tre tidshorisonter (2011–2040, 2041–2070, 2071–2100) och flera klimatscenarier (RCP2.6, RCP4.5, RCP8.5). Forskarna tillhandahåller även Site Index-modeller för 25 arter som prognostiserar tillväxtpotential. Resultaten utgörs av kartor i 1 × 1 km upplösning och beslutsstödsystem för artval. För leverantörer av skogsförvaltning och försäkringsbolag öppnar detta möjligheter att erbjuda klimatanpassade rekommendationer redan idag.
Amid increasing temperatures and extended drought periods, forest managers require comprehensive information regarding the suitability of various tree species under changing climatic conditions. To address this need, we assembled a unique dataset spanning Europe, incorporating multiple data sources such as national forest inventories, forest management plans, and data from ICP Forests. Our database ultimately included over six million individual trees across 860,000 forest plots throughout Europe. Using this extensive dataset, we developed Species Distribution Models (SDM) for 30 and Site Index Models (SIM) for 25 European tree species, the latter limited by data availability. Both model types were used to generate predictions at a spatial resolution of 1 × 1 km for the periods 2011-2040, 2041-2070, and 2071-2100 under climate change scenarios RCP2.6, RCP4.5 and RCP8.5. The model predictions aim to estimate the top height and assess climate suitability across Europe under future climate conditions. One potential application of these models is in a decision support system (DSS) to inform tree species selection and management strategies in the context of climate change. Provided are the models, prediction outputs, and supporting information, as the underlying database is restricted by data use agreements.