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ABSTRACT Understanding the movement patterns and behavior of marine organisms is fundamental for numerous ecological, conservation and management applications. Over the past several decades, advancements in tracking technologies and analytical methods have revolutionized our ability to study marine animal movements. Oceanic zooplankton often make up the bulk of the macroscopic animal biomass in the oceans, yet we know very little about the life histories, migrations and long-term behaviors of these ecologically important animals. In this Review, we consider recent developments in marine movement ecology and animal tracking techniques of gelatinous zooplankton, and discuss the challenges, opportunities and future directions in this rapidly evolving field.
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Learning and Animal Movement
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.
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- PAR ID:
- 10281662
- Date Published:
- Journal Name:
- Frontiers in Ecology and Evolution
- Volume:
- 9
- ISSN:
- 2296-701X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fevo.2021.681704
