Learning and Animal Movement

Mark A. Lewis^1,2*†, William F. Fagan^3†, Marie Auger-Méthé^4,5, Jacqueline Frair⁶, John M. Fryxell⁷, Claudius Gros⁸, Eliezer Gurarie³, Susan D. Healy⁹ and Jerod A. Merkle¹⁰

• ¹Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
• ²Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
• ³Department of Biology, University of Maryland, College Park, College Park, MD, United States
• ⁴Department of Statistics, University of British Columbia, Vancouver, BC, Canada
• ⁵Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada
• ⁶Department of Environmental and Forest Biology, State University of New York, Syracuse, NY, United States
• ⁷Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
• ⁸Physics Department, Goethe University, Frankfurt, Germany
• ⁹School of Biology, University of St Andrews, St Andrews, United Kingdom
• ¹⁰Department of Zoology and Physiology, University of Wyoming, Laramie, WY, United States

Integrating diverse concepts from animal behavior, movement ecology, and machine learning, we develop an overview of the ecology of learning and animal movement. Learning-based movement is clearly relevant to ecological problems, but the subject is rooted firmly in psychology, including a distinct terminology. We contrast this psychological origin of learning with the task-oriented perspective on learning that has emerged from the field of machine learning. We review conceptual frameworks that characterize the role of learning in movement, discuss emerging trends, and summarize recent developments in the analysis of movement data. We also discuss the relative advantages of different modeling approaches for exploring the learning-movement interface. We explore in depth how individual and social modalities of learning can matter to the ecology of animal movement, and highlight how diverse kinds of field studies, ranging from translocation efforts to manipulative experiments, can provide critical insight into the learning process in animal movement.