Integrating animal movement with habitat suitability for estimating dynamic landscape connectivity

Abstract

ContextHigh-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species potential to link patches or populations are of importance.\n\nObjectivesWe introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.\n\nMethodsWe used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.\n\nResultsSimulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corresponding to previous findings for this species.\n\nConclusionsWe show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.