Net displacement and temporal scaling: Model fitting, interpretation and implementation
Abstract Net displacement is an integral component of numerous ecological processes and is critically dependent on the tortuosity of a movement trajectory and hence on the temporal scale of observation. Numerous attempts have been made to quantitatively describe net displacement while accommodating...
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crwiley:10.1111/2041-210x.12978 2024-09-15T18:04:44+00:00 Net displacement and temporal scaling: Model fitting, interpretation and implementation Street, Garrett M. Avgar, Tal Börger, Luca Photopoulou, Theoni Mississippi State University Office of Research and Economic Development Mississippi State University Forest and Wildlife Research Center 2018 http://dx.doi.org/10.1111/2041-210x.12978 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F2041-210X.12978 https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12978 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/2041-210X.12978 https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12978 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Methods in Ecology and Evolution volume 9, issue 6, page 1503-1517 ISSN 2041-210X 2041-210X journal-article 2018 crwiley https://doi.org/10.1111/2041-210x.12978 2024-08-06T04:17:43Z Abstract Net displacement is an integral component of numerous ecological processes and is critically dependent on the tortuosity of a movement trajectory and hence on the temporal scale of observation. Numerous attempts have been made to quantitatively describe net displacement while accommodating tortuosity, typically evoking a power law, but scale‐dependency in tortuosity limits the utility of approaches based on power law relationships that must assume scale‐invariant tortuosity. We describe a phenomenological model of net displacement that permits both scale‐variant and scale‐invariant movement. Movement trajectories are divided into pairs of relocations specifying start‐ and end‐points, and net displacements between points are calculated across a vector of time intervals. A bootstrap is implemented to create new datasets that are independent both across and within time intervals, and the model is fitted to the bootstrapped dataset using log–log regression. We apply this model to simulated trajectories and both fine‐grain and coarse‐grain trajectories obtained from an Aldabra giant tortoise Aldabrachelys gigantea , African elephants Loxodonta africana , black‐backed jackals Canis mesomelas and Northern elephant seals Mirounga angustirostris . The model was able to quantify the characteristics of net displacement from simulated movement trajectories corresponding to both scale‐variant (e.g. correlated random walks) and scale‐invariant (e.g. random walk) movement models. Furthermore, the model produced identical outputs across time vectors corresponding to different intervals and absolute ranges of time for scale‐invariant models. The model characterized the tortoise as generally exhibiting long scale‐invariant steps, which was corroborated by visual comparison of model outputs to observed trajectories. Elephants, jackals and seals exhibited movement parameters consistent with their known movement behaviours (nomadism, territoriality and widely ranging searching). We describe how the model may be used to ... Article in Journal/Newspaper Elephant Seals Wiley Online Library Methods in Ecology and Evolution 9 6 1503 1517 |
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Wiley Online Library |
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English |
description |
Abstract Net displacement is an integral component of numerous ecological processes and is critically dependent on the tortuosity of a movement trajectory and hence on the temporal scale of observation. Numerous attempts have been made to quantitatively describe net displacement while accommodating tortuosity, typically evoking a power law, but scale‐dependency in tortuosity limits the utility of approaches based on power law relationships that must assume scale‐invariant tortuosity. We describe a phenomenological model of net displacement that permits both scale‐variant and scale‐invariant movement. Movement trajectories are divided into pairs of relocations specifying start‐ and end‐points, and net displacements between points are calculated across a vector of time intervals. A bootstrap is implemented to create new datasets that are independent both across and within time intervals, and the model is fitted to the bootstrapped dataset using log–log regression. We apply this model to simulated trajectories and both fine‐grain and coarse‐grain trajectories obtained from an Aldabra giant tortoise Aldabrachelys gigantea , African elephants Loxodonta africana , black‐backed jackals Canis mesomelas and Northern elephant seals Mirounga angustirostris . The model was able to quantify the characteristics of net displacement from simulated movement trajectories corresponding to both scale‐variant (e.g. correlated random walks) and scale‐invariant (e.g. random walk) movement models. Furthermore, the model produced identical outputs across time vectors corresponding to different intervals and absolute ranges of time for scale‐invariant models. The model characterized the tortoise as generally exhibiting long scale‐invariant steps, which was corroborated by visual comparison of model outputs to observed trajectories. Elephants, jackals and seals exhibited movement parameters consistent with their known movement behaviours (nomadism, territoriality and widely ranging searching). We describe how the model may be used to ... |
author2 |
Photopoulou, Theoni Mississippi State University Office of Research and Economic Development Mississippi State University Forest and Wildlife Research Center |
format |
Article in Journal/Newspaper |
author |
Street, Garrett M. Avgar, Tal Börger, Luca |
spellingShingle |
Street, Garrett M. Avgar, Tal Börger, Luca Net displacement and temporal scaling: Model fitting, interpretation and implementation |
author_facet |
Street, Garrett M. Avgar, Tal Börger, Luca |
author_sort |
Street, Garrett M. |
title |
Net displacement and temporal scaling: Model fitting, interpretation and implementation |
title_short |
Net displacement and temporal scaling: Model fitting, interpretation and implementation |
title_full |
Net displacement and temporal scaling: Model fitting, interpretation and implementation |
title_fullStr |
Net displacement and temporal scaling: Model fitting, interpretation and implementation |
title_full_unstemmed |
Net displacement and temporal scaling: Model fitting, interpretation and implementation |
title_sort |
net displacement and temporal scaling: model fitting, interpretation and implementation |
publisher |
Wiley |
publishDate |
2018 |
url |
http://dx.doi.org/10.1111/2041-210x.12978 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F2041-210X.12978 https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12978 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/2041-210X.12978 https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12978 |
genre |
Elephant Seals |
genre_facet |
Elephant Seals |
op_source |
Methods in Ecology and Evolution volume 9, issue 6, page 1503-1517 ISSN 2041-210X 2041-210X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/2041-210x.12978 |
container_title |
Methods in Ecology and Evolution |
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9 |
container_issue |
6 |
container_start_page |
1503 |
op_container_end_page |
1517 |
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1810442346267934720 |