Unravelling the uncertainties of predictions of natural disturbances on landscape vegetation patterns

Background

Forests worldwide provide essential services such as carbon sequestration, water storage, and timber provision. Changes in drivers such as temperature and precipitation are changing forest dynamics worldwide, including changes in forests fires frequency and intensity.

Models of forest dynamics at landscape scale (FLM) help us understand the complex interactions between vegetation, disturbances, such as fire, and their drivers. These models offer insights into the impacts of changing disturbance regimes on forest ecosystems in the long-term.

However, a comprehensive assessment of the uncertainty in fire formulations within FLM is still lacking. Therefore, improving model formulations and systematically evaluating their performance are crucial steps towards reducing uncertainty in these models.

Aim of the project

The main goals of this project are to improve the formulation of fire disturbance and post-fire vegetation recovery in forest landscape models, and to assess the risks caused by fire disturbances to the provision of ecosystem services in areas with increasing fire disturbances.

Project lead

Dr. Olalla Díaz-Yáñez, Prof. Dr. Harald Bugmann, Prof. Dr. Verena Griess

Collaborators

Dr. Alvaro G. Gutierrez (University of Chile)

Students

Paloma Juliá Martínez (PhD, ongoing)

Funding

Swiss National Science Foundation COST Action: CA19139 - Process-based models for climate impact attribution across sectors (PROCLIAS)

Contact

Dr. Olalla Díaz-Yáñez (olalla.diaz(at)usys.ethz.ch)