Both Environmental Conditions and Intra‐ and Interspecific Interactions Influence the Movements of a Marine Predator

Animal movements are typically influenced by multiple environmental factors simultaneously, and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic, and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply Exponential Random Graph Models (ERGMs) to analyze movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social, or other types of covariates on their movements. We found that intra- and interspecific factors often had stronger effects on movements than environmental variables. ERGMs proved to be a potentially useful tool for studying animal movement network data, especially in the context of spatial attribute heterogeneity.

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Publication Details

Journal
Ecology and Evolution
Published
2024-11-28
DOI
https://doi.org/10.1002/ece3.70659
Citations
3
Primary Topic
Animal Behavior and Reproduction
Type
article
Field-Weighted Citation Impact
3.09

Funders

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article

Both Environmental Conditions and Intra‐ and Interspecific Interactions Influence the Movements of a Marine Predator

Johann Mourier, Marc Soria, Matthew J. Silk, Laurent Dagorn et al.
3 citations
Ecology and Evolution
Animal Behavior and Reproduction
3.09
article

Both Environmental Conditions and Intra‐ and Interspecific Interactions Influence the Movements of a Marine Predator

Johann Mourier, Marc Soria, Matthew J. Silk, Laurent Dagorn, Angélique Demichelis, Tarek Hattab
article en
3 citations

Abstract

Animal movements are typically influenced by multiple environmental factors simultaneously, and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic, and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply Exponential Random Graph Models (ERGMs) to analyze movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social, or other types of covariates on their movements. We found that intra- and interspecific factors often had stronger effects on movements than environmental variables. ERGMs proved to be a potentially useful tool for studying animal movement network data, especially in the context of spatial attribute heterogeneity.

Ecology and EvolutionVol. 14(12)
National Institute for Mathematical and Biological Synthesis (US), Centre National de la Recherche Scientifique (FR), Ifremer (FR), École Pratique des Hautes Études (FR), Université de Montpellier (FR), University of Exeter (GB), Centre d'Écologie Fonctionnelle et Évolutive (FR), Marine Biodiversity Exploitation and Conservation (FR), Institut de Recherche pour le Développement (FR), University of Tennessee at Knoxville (US)
Institut Français de Recherche pour l'Exploitation de la Mer, European Commission, Ministère de la Transition écologique et Solidaire
Life below water
Openalex Percentile: Top 8%
Animal Behavior and Reproduction
3.09
DOIOpen Access PDFOpenAlex
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