Learning and animal movement
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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.
Lewis , M A , Fagan , W F , Auger-Méthé , M , Frair , J , Fryxell , J M , Gros , C , Gurarie , E , Healy , S D & Merkle , J A 2021 , ' Learning and animal movement ' , Frontiers in Ecology and Evolution , vol. 9 , 681704 . https://doi.org/10.3389/fevo.2021.681704
Frontiers in Ecology and Evolution
Copyright © 2021 Lewis, Fagan, Auger-Méthé, Frair, Fryxell, Gros, Gurarie, Healy and Merkle. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
DescriptionAuthors acknowledge the following grants for supporting this research: NSERC Discovery (ML and MA-M), NSF DMS-1853465 (WF and EG), and Canada Research Chairs Program (ML and MA-M).
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