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Behavior underpins the predictive power of a trait‐based model of butterfly movement
1. Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141018/ https://www.ncbi.nlm.nih.gov/pubmed/32273981 http://dx.doi.org/10.1002/ece3.5957 |
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author | Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. |
author_facet | Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. |
author_sort | Evans, Luke C. |
collection | PubMed |
description | 1. Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short‐term movements. 2. Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random‐walk model of butterfly movement that incorporates relationships between wingspan and sex‐specific movement behaviors. 3. The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates. 4. We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex‐ and species‐specific movement behaviors. 5. We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting. |
format | Online Article Text |
id | pubmed-7141018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71410182020-04-09 Behavior underpins the predictive power of a trait‐based model of butterfly movement Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. Ecol Evol Original Research 1. Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short‐term movements. 2. Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random‐walk model of butterfly movement that incorporates relationships between wingspan and sex‐specific movement behaviors. 3. The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates. 4. We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex‐ and species‐specific movement behaviors. 5. We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting. John Wiley and Sons Inc. 2020-03-06 /pmc/articles/PMC7141018/ /pubmed/32273981 http://dx.doi.org/10.1002/ece3.5957 Text en © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title | Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title_full | Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title_fullStr | Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title_full_unstemmed | Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title_short | Behavior underpins the predictive power of a trait‐based model of butterfly movement |
title_sort | behavior underpins the predictive power of a trait‐based model of butterfly movement |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141018/ https://www.ncbi.nlm.nih.gov/pubmed/32273981 http://dx.doi.org/10.1002/ece3.5957 |
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