Tree and forest management under climate change

 Forest development is one of the major issues in climate change. Already now, forests do have great difficulties in coping with current changes in temperature and precipitation. Especially the combination of high temperature and long dry periods cause the trees to weaken and eventually die back. Reliable knowledge of tree developments under future climate conditions could give a strong fundament for adaptation measures.

In the framework of the current project EDE4.0 (started 2020) funded by the Federal Ministry of Food and Agriculture (BMEL), the South German Climate Office supports forest management in Baden-Württemberg with regional decadal climate predictions and high-resolution regional climate models in order to adapt to future extreme events. Coordinated by EDI GmbH, an application will be developed, based on artificial intelligence, linking climate and forest data with economic data and local experts’ knowledge in order to support sustainable forest management of selected stocks.

The collaboration with the Institute of Geography and Geoecology (IfGG) at KIT adds scientific forest knowledge to the project. As local and regional experience plays a major role in the successful implementation of the envisaged application, several stakeholders, including the forest office Karlsruhe and the Ministry of Food, Rural Areas and Consumer Protection Baden-Württemberg, accompany the project as associated partners.

By combining decadal predictions and climate model ensembles, model output should guide both the planting process but also the tree species selection for a future climate in regional forest stands. The medium-term forecasts help to assess the risk of extreme weather events during the growth phase of tree seedlings, while the long-term climate information can be used to estimate future probabilities of forest-related extreme events such as droughts.

Preliminary model results (3km regional climate model ensemble) indicate for the greater Karlsruhe region an increase of the maximum number of consecutive dry days (daily precipitation sum less than 1mm) from 40 days in the period 2021-2050 to 55 days with regard to 2071-2100. The annual average number of dry periods (more than 5 consecutive days with less than 1mm precipitation) is projected to increase from 10 periods (2051-2050) to 14 in 2071-2100. Calculations are based on the RCP8.5 scenario and picture an ensemble mean for 4 regional climate model ensemble members. 

Linking modelling data to forest inventories and local expertise via artificial intelligence, the project aims to support decision making on an economic basis but also helps to maintain ecosystem services of forests and trees in the future.

Website: http://ede4.0.edi.gmbh/de/

Press release: https://www.kit.edu/kit/pi_2021_020_protecting-and-managing-forests-with-ai.php

Interactive movie about the project: https://www.sek.kit.edu/video/ede40/

Working Groups: "Regional Climate and Weather Hazards" , "Regional Climate and Water Cycle"