Seminar: Prof. Fagan on Movement Ecology: Memory, Learning, and Autocorrelation

Dear academic colleagues, please note the forthcoming seminar on

Movement Ecology: Memory, Learning, and Autocorrelation 

given by Prof. Bill Fagan 

Chair of the Department of Biology at the University of Maryland, and head of the Fagan Lab, one of the world‘s leading research groups working on spatial ecology and eco-informatics. 

 

‘‘My research involves meshing field research with theoretical models to address critical questions in ecology and conservation biology. I believe that ecological theory will be strengthened if it is forced to help solve real-world problems, and that conservation biology involves difficult choices that demand quantitative approaches.’’ 

 

The seminar will take place on 

  1. 12. 2017, 10:30 – 12:00 

at Room ZI (MCEV I building), the Faculty of Environmental Sciences, Czech University of Life Sciences Prague.

Prof. Bill Fagan is chair of the Department of Biology at the University of Maryland, USA, and head of the Fagan Lab, one of the world’s leading research groups working on spatial ecology and eco-informatics. The lab’s results shed light on many different problems, including the proper estimation of animal home ranges under serial autocorrelation (see their paper in Ecology), determination of different behavioral modes from animal-tracking data (see the paper in American Naturalist), the role of spatial memory in animal movement (see the paper in Ecology Letters), the role of social learning and experience in bird migrations (see the papers in Science and in Nature Communications), the determinants of land mammal migration distances (see the paper in Ecology Letters), the role of branching structure of river networks in amphibian population persistence (see the paper in PNAS), and in fish biodiversity patterns (see paper in Nature) to name just a few (see other lab’s publications). They uniquely and successfully combine sound ecological theory with practical conservation issues, thus bridging a seemingly insurmountable gap between theoreticians-modelers and field biologists.