  Vital rates such as survival and recruitment have always been important in
the study of population and community ecology. At the individual level,
physiological processes such as energetics are critical in understanding
biomechanics and movement ecology and also scale up to influence food webs and
trophic cascades. Although vital rates and population-level characteristics are
tied with individual-level animal movement, most statistical models for
telemetry data are not equipped to provide inference about these relationships
because they lack the explicit, mechanistic connection to physiological
dynamics. We present a framework for modeling telemetry data that explicitly
includes an aggregated physiological process associated with decision making
and movement in heterogeneous environments. Our framework accommodates a wide
range of movement and physiological process specifications. We illustrate a
specific model formulation in continuous-time to provide direct inference about
gains and losses associated with physiological processes based on movement. Our
approach can also be extended to accommodate auxiliary data when available. We
demonstrate our model to infer mountain lion (in Colorado, USA) and African
buffalo (in Kruger National Park, South Africa) recharge dynamics.
