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Carbon and timber in German forests - improving projections of current and future CO2 stocks by coupling eco-physiological and empirical forest development models (KNOW)
Project
Project code: 2218WK09A4
Contract period: 01.03.2020
- 28.02.2022
Budget: 201,125 Euro
Purpose of research: Inventory & Assessment
Keywords: old growth wood, natural forest development, silviculture, wood growth
The project aims at estimating future forest development and timber supply potentials in Germany under the influence of progressive global warming. It will create a robust basis for management decisions and will help policymakers, administrations, associations and industry to select appropriate options for future management. For this purpose a process-based forest model (4C) and an empirical forest simulator (WEHAM) are coupled to generate climate-sensitive growth functions that will be used to estimate the climate sensitivity of carbon and timber simulations, e.g. the WEHAM base scenario (which is currently used in policy, timber resource and forest management planning) will be evaluated under different regional climate scenarios (RCP2.6 to 8.5). In parallel, rare extreme weather conditions that have significant implications for tree growth and whose occurrence may be altered due to climate change, are identified. They will be taken into account in evaluations of the simulations, too. The evaluation covers timber volume, associated carbon stocks, and other forest ecosystem services such as habitat provision.
Section overview
Subjects
- Silviculture
- Renewable Resources
- Climate Change
Framework programme
Funding programme
Excutive institution
Funding institution
Project management agencies
Associated projects: KNOW
- Carbon and Timber stock of the German forest - Improvement of projections of current and future CO2 stock by means of ecophysiological and empirical forest growth models
- Carbon and Timber stock of the German forest - Improvement of projections of current and future CO2 stock by means of ecophysiological and empirical forest growth models
