Differentiating the Lévy walk from a composite correlated random walk

1. Understanding how to find targets with very limited information is a topic of interest in many disciplines. In ecology, such research has often focused on the development of two movement models: i) the Lévy walk and; ii) the composite correlated random walk and its associated area-restricted sear...

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Main Authors: Auger-Méthé, Marie, Derocher, Andrew E., Plank, Michael J., Codling, Edward A., Lewis, Mark A.
Format: Text
Language:unknown
Published: arXiv 2014
Subjects:
Online Access:https://dx.doi.org/10.48550/arxiv.1406.4355
https://arxiv.org/abs/1406.4355
id ftdatacite:10.48550/arxiv.1406.4355
record_format openpolar
spelling ftdatacite:10.48550/arxiv.1406.4355 2023-05-15T18:42:26+02:00 Differentiating the Lévy walk from a composite correlated random walk Auger-Méthé, Marie Derocher, Andrew E. Plank, Michael J. Codling, Edward A. Lewis, Mark A. 2014 https://dx.doi.org/10.48550/arxiv.1406.4355 https://arxiv.org/abs/1406.4355 unknown arXiv https://dx.doi.org/10.1111/2041-210x.12412 arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Quantitative Methods q-bio.QM FOS Biological sciences article-journal Article ScholarlyArticle Text 2014 ftdatacite https://doi.org/10.48550/arxiv.1406.4355 https://doi.org/10.1111/2041-210x.12412 2022-04-01T12:52:41Z 1. Understanding how to find targets with very limited information is a topic of interest in many disciplines. In ecology, such research has often focused on the development of two movement models: i) the Lévy walk and; ii) the composite correlated random walk and its associated area-restricted search behaviour. Although the processes underlying these models differ, they can produce similar movement patterns. Due to this similarity and because of their disparate formulation, current methods cannot reliably differentiate between these two models. 2. Here, we present a method that differentiates between the two models. It consists of likelihood functions, including one for a hidden Markov model, and associated statistical measures that assess the relative support for and absolute fit of each model. 3. Using a simulation study, we show that our method can differentiate between the two search models over a range of parameter values. Using the movement data of two polar bears (\textit{Ursus maritimus}), we show that the method can be applied to complex, real-world movement paths. 4. By providing the means to differentiate between the two most prominent search models in the literature, and a framework that could be extended to include other models, we facilitate further research into the strategies animals use to find resources. Text Ursus maritimus DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Quantitative Methods q-bio.QM
FOS Biological sciences
spellingShingle Quantitative Methods q-bio.QM
FOS Biological sciences
Auger-Méthé, Marie
Derocher, Andrew E.
Plank, Michael J.
Codling, Edward A.
Lewis, Mark A.
Differentiating the Lévy walk from a composite correlated random walk
topic_facet Quantitative Methods q-bio.QM
FOS Biological sciences
description 1. Understanding how to find targets with very limited information is a topic of interest in many disciplines. In ecology, such research has often focused on the development of two movement models: i) the Lévy walk and; ii) the composite correlated random walk and its associated area-restricted search behaviour. Although the processes underlying these models differ, they can produce similar movement patterns. Due to this similarity and because of their disparate formulation, current methods cannot reliably differentiate between these two models. 2. Here, we present a method that differentiates between the two models. It consists of likelihood functions, including one for a hidden Markov model, and associated statistical measures that assess the relative support for and absolute fit of each model. 3. Using a simulation study, we show that our method can differentiate between the two search models over a range of parameter values. Using the movement data of two polar bears (\textit{Ursus maritimus}), we show that the method can be applied to complex, real-world movement paths. 4. By providing the means to differentiate between the two most prominent search models in the literature, and a framework that could be extended to include other models, we facilitate further research into the strategies animals use to find resources.
format Text
author Auger-Méthé, Marie
Derocher, Andrew E.
Plank, Michael J.
Codling, Edward A.
Lewis, Mark A.
author_facet Auger-Méthé, Marie
Derocher, Andrew E.
Plank, Michael J.
Codling, Edward A.
Lewis, Mark A.
author_sort Auger-Méthé, Marie
title Differentiating the Lévy walk from a composite correlated random walk
title_short Differentiating the Lévy walk from a composite correlated random walk
title_full Differentiating the Lévy walk from a composite correlated random walk
title_fullStr Differentiating the Lévy walk from a composite correlated random walk
title_full_unstemmed Differentiating the Lévy walk from a composite correlated random walk
title_sort differentiating the lévy walk from a composite correlated random walk
publisher arXiv
publishDate 2014
url https://dx.doi.org/10.48550/arxiv.1406.4355
https://arxiv.org/abs/1406.4355
genre Ursus maritimus
genre_facet Ursus maritimus
op_relation https://dx.doi.org/10.1111/2041-210x.12412
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1406.4355
https://doi.org/10.1111/2041-210x.12412
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