Forest fires are already a global threat. “But considering how climate change is progressing, we are probably only at the beginning of a future that will see more and bigger forest fires,” explains Rupert Seidl, Professor of Ecosystem Dynamics and Forest Management in Mountain Landscapes at TUM.
In many places, fire is part of the natural environment, and many tree species have become naturally adapted to recurrent fires. These adaptations range from particularly thick bark, which protects the sensitive cambium in the trunk from the fire, to the cones of certain types of pine, which open only due to the heat of fire, allowing a quick regeneration and recovery of affected woodland.
AI is accelerating ecosystem models
“The interaction between climate, forest fires, and other processes in the forest ecosystem is very complex, and sophisticated process-based simulation models are required to take account of the different interactions appropriately,” explains Prof. Seidl. A method that has been developed at TUM is using artificial intelligence to significantly expand the field of use of these complex models.
This method involves the training of a deep neural network in order to imitate the behavior of a complex simulation model as effectively as possible. The neural network learns on the basis of how the ecosystem responds to differing environmental influences, but does so using only a fraction of the computing power that would otherwise be necessary for large-scale simulation models. “This allows us to carry out spatially high-resolution simulations of areas of forest that stretch across several million hectares,” explains scientist Dr. Werner Rammer.