Director of the Botanic Garden
The research in my group focuses on conservation biology and biogeography of relict, endemic and threatened plants. Our main study and model taxa are woody plants with disjunct distribution pattern, with main interest on the genus Zelkova and Ulmus (Ulmaceae), Pterocarya (Juglandaceae) and Quercus (Fagaceae), as well as Pinus (Pinaceae), Ptilostemon (Asteraceae), Clematis (Ranunculaceae)
Additional interest touches the evolutionary processes, biogeographical patterns and conservation issues of aquatic, arctic and alpine plants, both at regional and global scale.
We use various biogeographical, molecular and dendrochronological methods and are conducting intensive fieldwork in the Alps and adjacent mountain chains, in the Mediterranean (e.g., Crete, Sicily), in Transcaucasia (e.g., Georgia, Azerbaijan) and in Eastern Asia (e.g., China, Japan, Vietnam).
Our group is closely connected to the Botanic Garden of the University of Fribourg (I am a director of the Garden) and is intensively collaborating with the Natural History Museum Fribourg (NHMF).
Internationally, we are closely collaborating with the Shanghai Chenshan Botanic Garden (Shanghai Chenshan Plant Science Research Center, Chinese Academy of Sciences).
Conservation biology and biogeography of relict trees with disjunct distribution pattern (Projects Zelkova, Ulmaceae and Pterocarya, Juglandaceae).
Conservation biology of threatened Quercus (Fagaceae) species of the Mountain Cloud Forests of China and South Eastern Asia.
Conservation biogeography and phylogeography of the alpine and arctic species (e.g. Papaver, Calamagrostis, etc.).
Population genetics and distribution of Pinus cembra (Pinaceae) in Western Prealps.
Conservation biology of climate relict Nuphar pumila (Nymphaeaceae).
Conservation biology and genetic diversity of Ulmus laevis (Ulmaceae).
Conservation biology, niche definition and translocation of Ptilostemon greuteri (Asteraceae).
Life on relict trees: relict woody species as ecosystems of other organisms.
Global conservation status assessemnt of trees using machine learning.