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Integrating the influence of weather into mechanistic models of butterfly movement
BACKGROUND: Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717957/ https://www.ncbi.nlm.nih.gov/pubmed/31497300 http://dx.doi.org/10.1186/s40462-019-0171-7 |
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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 | BACKGROUND: Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. METHODS: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5 °C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. RESULTS: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23 °C and 26 °C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. CONCLUSIONS: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40462-019-0171-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6717957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67179572019-09-06 Integrating the influence of weather into mechanistic models of butterfly movement Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. Mov Ecol Research BACKGROUND: Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. METHODS: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5 °C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. RESULTS: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23 °C and 26 °C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. CONCLUSIONS: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40462-019-0171-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-09-02 /pmc/articles/PMC6717957/ /pubmed/31497300 http://dx.doi.org/10.1186/s40462-019-0171-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Evans, Luke C. Sibly, Richard M. Thorbek, Pernille Sims, Ian Oliver, Tom H. Walters, Richard J. Integrating the influence of weather into mechanistic models of butterfly movement |
title | Integrating the influence of weather into mechanistic models of butterfly movement |
title_full | Integrating the influence of weather into mechanistic models of butterfly movement |
title_fullStr | Integrating the influence of weather into mechanistic models of butterfly movement |
title_full_unstemmed | Integrating the influence of weather into mechanistic models of butterfly movement |
title_short | Integrating the influence of weather into mechanistic models of butterfly movement |
title_sort | integrating the influence of weather into mechanistic models of butterfly movement |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717957/ https://www.ncbi.nlm.nih.gov/pubmed/31497300 http://dx.doi.org/10.1186/s40462-019-0171-7 |
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