Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range
Abstract Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat‐use patterns of individuals within a population. This is especially the case when disturbances are localized within a population's spatial range, as variation in habitat use within a populatio...
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ftdoajarticles:oai:doaj.org/article:30a1b692e79f445ca80777fca38beae9 2023-05-15T15:41:44+02:00 Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range Tyler R. Bonnell Robert Michaud Angélique Dupuch Véronique Lesage Clément Chion 2022-02-01T00:00:00Z https://doi.org/10.1002/ece3.8616 https://doaj.org/article/30a1b692e79f445ca80777fca38beae9 EN eng Wiley https://doi.org/10.1002/ece3.8616 https://doaj.org/toc/2045-7758 2045-7758 doi:10.1002/ece3.8616 https://doaj.org/article/30a1b692e79f445ca80777fca38beae9 Ecology and Evolution, Vol 12, Iss 2, Pp n/a-n/a (2022) capture–recapture data Delphinapterus leucas habitat use network community detection photo identification spatial networks Ecology QH540-549.5 article 2022 ftdoajarticles https://doi.org/10.1002/ece3.8616 2022-12-31T02:01:30Z Abstract Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat‐use patterns of individuals within a population. This is especially the case when disturbances are localized within a population's spatial range, as variation in habitat use within a population can drastically alter the distribution of impacts. Here, we illustrate the potential for multilevel binomial models to generate spatial networks from capture–recapture data, a common data source used in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a population's spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the population's spatial range. Using simulations and 18 years of capture–recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, that is, structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE. Multilevel binomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture–recapture of individuals, and can be especially useful when sampling effort is not evenly distributed. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities. Article in Journal/Newspaper Beluga Beluga* Delphinapterus leucas Directory of Open Access Journals: DOAJ Articles Ecology and Evolution 12 2 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
capture–recapture data Delphinapterus leucas habitat use network community detection photo identification spatial networks Ecology QH540-549.5 |
spellingShingle |
capture–recapture data Delphinapterus leucas habitat use network community detection photo identification spatial networks Ecology QH540-549.5 Tyler R. Bonnell Robert Michaud Angélique Dupuch Véronique Lesage Clément Chion Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
topic_facet |
capture–recapture data Delphinapterus leucas habitat use network community detection photo identification spatial networks Ecology QH540-549.5 |
description |
Abstract Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat‐use patterns of individuals within a population. This is especially the case when disturbances are localized within a population's spatial range, as variation in habitat use within a population can drastically alter the distribution of impacts. Here, we illustrate the potential for multilevel binomial models to generate spatial networks from capture–recapture data, a common data source used in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a population's spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the population's spatial range. Using simulations and 18 years of capture–recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, that is, structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE. Multilevel binomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture–recapture of individuals, and can be especially useful when sampling effort is not evenly distributed. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities. |
format |
Article in Journal/Newspaper |
author |
Tyler R. Bonnell Robert Michaud Angélique Dupuch Véronique Lesage Clément Chion |
author_facet |
Tyler R. Bonnell Robert Michaud Angélique Dupuch Véronique Lesage Clément Chion |
author_sort |
Tyler R. Bonnell |
title |
Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
title_short |
Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
title_full |
Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
title_fullStr |
Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
title_full_unstemmed |
Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
title_sort |
extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range |
publisher |
Wiley |
publishDate |
2022 |
url |
https://doi.org/10.1002/ece3.8616 https://doaj.org/article/30a1b692e79f445ca80777fca38beae9 |
genre |
Beluga Beluga* Delphinapterus leucas |
genre_facet |
Beluga Beluga* Delphinapterus leucas |
op_source |
Ecology and Evolution, Vol 12, Iss 2, Pp n/a-n/a (2022) |
op_relation |
https://doi.org/10.1002/ece3.8616 https://doaj.org/toc/2045-7758 2045-7758 doi:10.1002/ece3.8616 https://doaj.org/article/30a1b692e79f445ca80777fca38beae9 |
op_doi |
https://doi.org/10.1002/ece3.8616 |
container_title |
Ecology and Evolution |
container_volume |
12 |
container_issue |
2 |
_version_ |
1766374629330386944 |