Meeting Abstract
The spatial distribution of predators is often linked to their prey, but not all prey patches are of equal quality. The energetic cost of accessing a patch contributes to its value and thereby influences the spatial structure of a population. However, species distribution models often ignore the effects of movement because of the lack of methods for quantifying habitat accessibility. To close this gap, we applied the energy landscape conceptual model, which interprets animal movement from the cost of transport through heterogeneous environments, to analyze the influence of winds on the distribution of the Red-footed Booby (Sula sula), a marine predator. In May-September 2016, we tracked fifteen breeding birds at the Kilauea Point National Wildlife Refuge, HI with combination GPS/accelerometer devices. By regressing acceleration-derived energy costs against wind conditions and other variables, we developed an environmental flight cost model. This cost of transport model was applied in an anisotropic (directional) least-cost path analysis to quantify the cost of transport throughout the colony’s foraging territory as a function of wind. Preliminary qualitative examination suggests the energy windscape model better predicts foraging site selection of tracked birds than a distance-to-colony null model. We will validate the method by fitting GAMs to the utilization distribution (UD) as a function of the energy windscape and null models, which we will use to predict UDs at independently tracked sites in Hawaii. We expect to find that energy windscapes quantify habitat accessibility for seabirds, which is particularly valuable for species distribution modeling of mobile organisms.
