Identifying and tracking regional bird movements with meteorological radar

Meteorological radars are powerful tools that enable aeroecologists to continuously monitor movement of biomass through the air. Until now, this work has focused on studying bird migration patterns averaged within a radar range. There is,however, much more information available as the radars make spatially explicit observations. Within this project we will open a new research field by generating tools to study movement within the spatial extent of a meteorological radar. Using the opportunities created by modern dual-polarization radars we will develop a machine learning model to identify and track bird flocks. We will especially focus on using the temporal information in the radar data. Through repeated radar measurements we will track these movements across space and time. Going forward this makes it possible for regional movement studies to bridge the methodological gap between fine-scale, individual-based tracking studies and continental-scale monitoring of bird migration. In particular, it enables novel studies of the roles of habitat, topography and environmental stressors on movements that are not feasible with current methodology. This work will allow for strategic planning to avoid conflicts between birds, airplanes and wind turbines. In addition, this approach lets radar enrich ongoing studies of individual birds with information on population movement. Ultimately, we want to apply the methodology to data from continental radar networks to study movement across scales.