A new study, published in Environmental Research Letters finds large-scale evidence for the protective function of forests against torrential hazards (debris flow, flood). However, increasing disturbances might reduce protective power of forests in the future.
A novel approach for scaling vegetation dynamics based on deep learning was published recently in Methods in Ecology and Evolution. The modeling framework developed by Werner Rammer and Rupert Seidl allows a consistent scaling of local vegetation dynamics (with abundant data and high process understading) to much larger spatial extents (think: country to continental level). At the core, the model harnesses deep learning, which is an exciting new branch of machine learning that revolutionized many fields of computer science in the last years.
A recent remote sensing study, published in Nature Communications, reveals consistently increasing trends in forest canopy mortality over Central Europe.
In a recent study, published in Nature Communications, we found that global disturbance patterns in the temperate biome are highly variable, and shaped by variation in disturbance agents and traits of prevailing tree species.
PhD student Katharina Albrich visited Prof. Monica G. Turner and her team at the University of Wisconsin in Madison!
Natural disturbances such as windthrows, insect outbreaks, and wildfires have intensified in many forest ecosystems around the globe recently. The project “Forest disturbance in a changing world” (RESIN) addresses the causes, consequences, and responses of changing forest disturbance regimes.
Specifically, RESIN aims to
RESIN was started in 2016 and is a 6-year project, bringing together an international team of scientists under the lead of Rupert Seidl from BOKU Vienna.
RESIN is supported by a START grant of the Austrian Science Fund.