Bridging the gaps in animal movement: hidden behaviors and ecological relationships revealed by integrated data streams

Inferences about animal behavior from movement models typically rely solely on location data, but auxiliary biotelemetry and environmental data are powerful and readily available resources for incorporating much more behavioral realism. Integrating multiple data streams can not only reveal hidden behaviors and ecological relationships that would otherwise be difficult or impossible to infer from location data alone, but also facilitate more realistic path reconstruction that respects important ecological features while bridging the information gaps that commonly arise due to measurement error or missing data. Using the bearded seal ( Erignathus barbatus ), a benthic predator associated with Arctic sea ice, we demonstrate how integrating location, dive activity, land cover, bathymetry, and sea ice data in a unified modeling framework allowed us to identify novel behavior states, such as hauling out on seasonal sea ice and those associated with competing foraging strategies (i.e., benthic vs. mid‐water prey). By utilizing multiple data streams, ecologists can move beyond conventional two‐state models (“foraging” and “transit”) and address more interesting hypotheses about activity budgets, resource selection, and many other areas of movement and behavioral ecology. The generality of our approach provides broad applicability to marine and terrestrial species, as well as many types of biotelemetry and environmental data.