van Toor, M. L. | bioRxiv Science

bioRxiv2024

Consistent long-distance foraging flights across years and seasons at colony level in a Neotropical bat

All foraging animals face a trade-off: how much time should they invest in exploitation of known resources versus exploration to discover new resources? For group-living central place foragers, balancing these competing goals poses particular challenges. The availability of social information may discourage individuals from investing in risky, expensive but possibly rewarding exploration. We GPS-tracked groups of greater spear-nosed bats (Phyllostomus hastatus) from three colonies on Isla Colon in Panama. In the dry season, when these omnivores forage on the nectar of ephemeral balsa flowers (Ochroma pyramidale), bats consistently travelled long distances to remote, colony-specific foraging areas, bypassing flowering trees closer to their roosts. They continued to use these same areas in the wet season, when feeding on a diverse, presumably ubiquitously distributed diet, but also visited other, similarly distant foraging areas. Foraging areas were shared within, but not always between colonies. Our longitudinal dataset suggests that bats from each colony invest in long-distance commutes to socially learned shared foraging areas, bypassing other available food patches. Rather than investing in exploration to find nearby resources or engaging in a win-stay lost-shift foraging strategy, these bats follow colony specific behaviours consistent with the existence of culturally transmitted preferences for specific feeding grounds.

animal behavior and cognition↗

bioRxiv2017

Integrating animal movement with habitat suitability for estimating dynamic landscape connectivity

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.

ecology↗