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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
Journal of Theoretical Biology, Volume: 457, Pages: 101 - 111
Swansea University Authors: Manos Lempidakis, Rory Wilson , Adrian Luckman , Richard Metcalfe
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DOI (Published version): 10.1016/j.jtbi.2018.08.024
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...
Published in: | Journal of Theoretical Biology |
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ISSN: | 0022-5193 |
Published: |
Elsevier BV
2018
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Online Access: |
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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. |
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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: |
Faculty of Science and Engineering |
Start Page: |
101 |
End Page: |
111 |