Modeling Stopover Sites of Migratory Birds’ Routes for Conservation of Population and Prevention of Disease

Modeling migratory paths of birds is an emerging area of complexity science in which attracts interdisciplinary collaborations from ornithologists, computer scientists, epidemiologist, and policy makers. However, due to the unpredictability of climate and habitat changes, our understanding of bird migratory paths is still limited. Not accounting for environmental changes when modeling bird migration will mislead our conservation efforts. Hence, in this paper, we are using validated training data to predict future stopover sites of migratory bird species. We used white-fronted geese migratory paths as training data and modeled stopover sites with Markov Chains to predict future changes on the stopover sites.This prediction will allow researchers to realize how to better conserve the habitat locations at and around stopover sites in the light of current climate changes. Since birds often stop and interact with the nearby environment, our work will also allow researchers to predict potential dangers emerged from long-range migrations, such as new avian viruses along these routes.