Factors of animal movements including migration, dispersal, and home-range size are important to consider when estimating the current and potential distribution of a species.
Many researchers of animal migratory behavior have utilized Geographic Information Systems (GIS) to determine least-cost routes of travel. Estimates of travel cost are often generated using ranking methods such as the Analytic Hierarchical Process (AHP). Increased availability of high-resolution animal tracking and environmental remote-sensing data makes more robust data-driven models of resistance and connectivity possible.
Using light-logging geolocator tracking data for 9 migratory Arctic Terns (Sterna paridiseae, provided by Carsten Egevang) we analyzed the travel pattern for a full annual migration event. A circular-linear regression model was fit to examine the relationship between travel pattern and the underlying environment.
Results/Conclusions
The model shows a strong relationship between wind patterns, net primary productivity (NPP), and travel patterns for the post-breeding migration. These relationships vary by season, showing a lesser effect on path choice for post-wintering Arctic Terns. This model yields promising results for applications to other groups of sea-birds and can be generalized to other species given appropriate environmental layers.