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Mapping the connectivity–conflict interface to inform conservation
Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910505/ https://www.ncbi.nlm.nih.gov/pubmed/36574696 http://dx.doi.org/10.1073/pnas.2211482119 |
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author | Vasudev, Divya Fletcher, Robert J. Srinivas, Nishanth Marx, Andrew J. Goswami, Varun R. |
author_facet | Vasudev, Divya Fletcher, Robert J. Srinivas, Nishanth Marx, Andrew J. Goswami, Varun R. |
author_sort | Vasudev, Divya |
collection | PubMed |
description | Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephant Elephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes. |
format | Online Article Text |
id | pubmed-9910505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-99105052023-06-27 Mapping the connectivity–conflict interface to inform conservation Vasudev, Divya Fletcher, Robert J. Srinivas, Nishanth Marx, Andrew J. Goswami, Varun R. Proc Natl Acad Sci U S A Biological Sciences Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephant Elephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes. National Academy of Sciences 2022-12-27 2023-01-03 /pmc/articles/PMC9910505/ /pubmed/36574696 http://dx.doi.org/10.1073/pnas.2211482119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Vasudev, Divya Fletcher, Robert J. Srinivas, Nishanth Marx, Andrew J. Goswami, Varun R. Mapping the connectivity–conflict interface to inform conservation |
title | Mapping the connectivity–conflict interface to inform conservation |
title_full | Mapping the connectivity–conflict interface to inform conservation |
title_fullStr | Mapping the connectivity–conflict interface to inform conservation |
title_full_unstemmed | Mapping the connectivity–conflict interface to inform conservation |
title_short | Mapping the connectivity–conflict interface to inform conservation |
title_sort | mapping the connectivity–conflict interface to inform conservation |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910505/ https://www.ncbi.nlm.nih.gov/pubmed/36574696 http://dx.doi.org/10.1073/pnas.2211482119 |
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