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What can knowledge of the energy landscape tell us about animal movement trajectories and space use? A case study with humans / Rory, Wilson; Adrian, Luckman; Richard, Metcalfe

Journal of Theoretical Biology, Volume: 457, Pages: 101 - 111

Swansea University Authors: Rory, Wilson, Adrian, Luckman, Richard, Metcalfe

Abstract

Recent work has highlighted that ‘energy landscapes’ should affect animal movement trajectories although expected patterns are rarely quantified. We developed a model, incorporating speed, substrate, superstrate and terrain slope, to determine minimized movement costs for an energetically well-under...

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Published in: Journal of Theoretical Biology
ISSN: 00225193
Published: Elsevier 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa43541
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Abstract: Recent work has highlighted that ‘energy landscapes’ should affect animal movement trajectories although expected patterns are rarely quantified. We developed a model, incorporating speed, substrate, superstrate and terrain slope, to determine minimized movement costs for an energetically well-understood model animal, Homo sapiens, negotiating an urban environment, to highlight features that promote increased tortuosity and affect area use. The model showed that high differential travel power costs between adjacent areas, stemming from substantial environmental heterogeneity in the energy landscape, produced the most tortuous least-cost paths across scales. In addition, projected territory size and shape in territorial animals is likely to be affected by the details in the energy landscape. We suggest that cognisance of energy landscapes is important for understanding animal movement patterns and that energetic differences between least cost- and observed pathways might code for, and give an explicit value to, other important landscape-use factors, such as the landscape of fear, food availability or social effects.
Item Description: It is confirmed that the datasets generated in the present study, are available via the Figshare repository and the following links: https://figshare.com/s/1d733bffa08a01806d7c.https://figshare.com/s/6f9be951f5e755a9843d.https://figshare.com/s/9fe7c452064f6f28a6c1.https://figshare.com/s/37bd3d14ec0865df471b.https://figshare.com/s/86b28d95cbee8921f3dd.
Keywords: Optimal movement, Least cost pathways, Tortuosity, Energy landscape, Iso-Energy Polygons
College: College of Engineering
Start Page: 101
End Page: 111