The combined effects of multiple stressors in an endangered, long‐lived species: Lessons learned and ways forward
Rattachement africain : gb, us, ca. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Exploring solutions to expanding industrial activities and climate change requires assessments of the combined effects of multiple stressors on wildlife populations. We present a spatially explicit state-space model for the health, survival, reproduction, and somatic growth of individuals in a long-lived, wide-ranging species. The model is applied to critically endangered North Atlantic right whales (Eubalaena glacialis) to investigate the combined effects of three primary stressors affecting the species' viability: entanglements in fishing gear, vessel strikes, and prey availability. We estimate exposure to these stressors in space and time and assess how their effects may combine in the pathway from exposure to vital rates. Results suggest that changes in whale distribution after 2010 led to increased entanglement risk. Poorer prey conditions were associated with an increased effect of carrying fishing gear, but, overall, results on combined effects were not conclusive and depended on model formulation. We also incorporated the estimated effects of stressors into a population viability analysis to explore alternative scenarios of stressor reduction. This integrated analysis highlighted the importance of the declining trend in maximum body length and its effect on reproduction, in addition to the documented impact of entanglements on survival. Model development and application elucidated critical data needs and the influence of underlying mechanistic assumptions. Specifically, models for the combined effects of stressors hinge on the availability of extended longitudinal measurements of individual health and life history outcomes, extensive datasets on the spatiotemporal distribution of stressors, and information on individual space use affecting rates of exposure to stressors. Lessons from this data-rich case study will support the generalization of the modeling approach to other long-lived species where measuring the population-level consequences of multiple stressors directly is unfeasible.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- The combined effects of multiple stressors in an endangered, long‐lived species: Lessons learned and ways forward
- Date Crossref
- 01/12/2025
- Éditeur
- Wiley
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of St Andrews Centre for Research into Ecological and Environmental Modelling pays non établi dans la noticeUniversité ou école supérieure
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Office of Science pays non établi dans la noticeOrganisme public
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Biomathematics and Statistics Scotland pays non établi dans la noticeStructure de recherche
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Sonoma State University Department of Biology pays non établi dans la noticeUniversité ou école supérieure
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New England Aquarium pays non établi dans la noticeInstitution
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Southall Environmental Associates (United States) pays non établi dans la noticeEntreprise
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Cabot (United States) pays non établi dans la noticeEntreprise
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Fisheries and Oceans Canada pays non établi dans la noticeOrganisme public
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NOAA National Marine Fisheries Service pays non établi dans la noticeOrganisme public
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NOAA National Marine Fisheries Service Northeast Fisheries Science Center pays non établi dans la noticeOrganisme public
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University of South Carolina pays non établi dans la noticeUniversité ou école supérieure
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Woods Hole Oceanographic Institution Marine Chemistry & pays non établi dans la noticeOrganisme public
Centre for Research into Ecological and Environmental Modelling — University of St Andrews, Office of Science et Biomathematics and Statistics Scotland, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.