Certainty and integration of options in animal movement

Abstract

Physical energy defines the energy landscape and determines the species-specific cost of movement, thus influencing movement decisions. In unpredictable and dynamic environments, observing the locomotion of others increases individual certainty in the distribution of physical energy to increase movement efficiency. Beyond the physical energy landscape, social sampling increases certainty in all ecological landscapes that influence animal movement (including fear and resource landscapes), and individuals use energy to express each of these. We call for the development of an 'optimal movement theory' (OMT) that integrates the multidimensional reality of movement decisions by combining ecological landscapes according to a single expectation of energy cost-benefit, where social sampling provides up-to-date information under uncertain conditions. This mechanistic framework has implications for predicting individual movement patterns and for investigating the emergence of aggregations.

Keywords: Bayesian theory; decision making; movement ecology; optimal movement theory; physical intelligence; social information.