Relevance of individual and environmental drivers of movement of Golden Eagles

An animal's movement is expected to be governed by an interplay between goals determined by its internal state and energetic costs associated with navigating through the external environment. Understanding this ecological process is challenging when an animal moves in two dimensions and even more difficult for birds that move in a third dimension. To understand the dynamic interaction between the internal state of an animal and the variable external environment, we evaluated hypotheses explaining association of different covariates of movement and the trade‐offs birds face as they make behavioural decisions in a fluctuating landscape. We used ~870 000 GPS telemetry data points collected from 68 Golden Eagles Aquila chrysaetos to test demographic, diel, topographic and meteorological hypotheses to determine (1) the probability that these birds would be in motion and (2), once in motion, their flight speed. A complex and sometimes interacting set of potential internal and external factors determined movement behaviour. There was good evidence that reproductive state, manifested as age, sex and seasonal effects, had a significant influence on the probability of being in motion and, to a lesser extent, on speed of motion. Likewise, movement responses to the external environment were often unexpectedly strong. These responses, to northness of slope, strength of orographic updraft and intensity of solar radiation, were regionally and temporally variable. In contrast to previous work showing the role of a single environmental factor in determining movement decisions, our analyses support the hypothesis that multiple factors simultaneously interact to influence animal movement. In particular they highlighted how movement is influenced by the interaction between the individual's internal reproductive state and the external environment, and that, of the environmental factors, topographic influences are often more relevant than meteorological influences in determining patterns of flight behaviour. Further disentangling of how these internal and externals states jointly affect movement will provide additional insights into the energetic costs of movement and benefits associated with achieving process‐driven goals.