Quantifying risk of whale–vessel collisions across space, time, and management policies
Abstract Transportation industries can negatively impact wildlife populations, including through increased risk of mortality. To mitigate this risk successfully, managers and conservationists must estimate risk across space, time, and alternative management policies. Evaluating this risk at fine spa...
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crwiley:10.1002/ecs2.2713 2024-05-19T07:45:16+00:00 Quantifying risk of whale–vessel collisions across space, time, and management policies Crum, Nathan Gowan, Timothy Krzystan, Andrea Martin, Julien National Oceanic and Atmospheric Administration 2019 http://dx.doi.org/10.1002/ecs2.2713 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2713 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2713 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.2713 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2713 en eng Wiley http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ Ecosphere volume 10, issue 4 ISSN 2150-8925 2150-8925 Ecology Ecology, Evolution, Behavior and Systematics journal-article 2019 crwiley https://doi.org/10.1002/ecs2.2713 2024-04-22T07:36:25Z Abstract Transportation industries can negatively impact wildlife populations, including through increased risk of mortality. To mitigate this risk successfully, managers and conservationists must estimate risk across space, time, and alternative management policies. Evaluating this risk at fine spatial and temporal scales can be challenging, especially in systems where wildlife–vehicle collisions are rare or imperfectly detected. The sizes and behaviors of wildlife and vehicles influence collision risk, as well as how much they co‐occur in space and time. We applied a modeling framework based on encounter theory to quantify the risk of lethal collisions between endangered North Atlantic right whales and vessels. Using Automatic Identification System vessel traffic data and spatially explicit estimates of right whale abundance that account for imperfect detection, we modeled risk at fine spatiotemporal scales before and after implementation of a vessel speed rule in the southeastern United States. The expected seasonal mortality rates of right whales decreased by 22% on average after the speed rule was implemented, indicating that the rule is effective at reducing lethal collisions. The rule's effect on risk was greatest where right whales were abundant and vessel traffic was heavy, and its effect varied considerably across time and space. Our framework is spatiotemporally flexible, process‐oriented, computationally efficient and accounts for uncertainty, making it an ideal approach for evaluating many wildlife management policies, including those regarding collisions between wildlife and vehicles and cases in which wildlife may encounter other dangerous features such as wind farms, seismic surveys, or fishing gear. Article in Journal/Newspaper North Atlantic Wiley Online Library Ecosphere 10 4 |
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Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
topic |
Ecology Ecology, Evolution, Behavior and Systematics |
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Ecology Ecology, Evolution, Behavior and Systematics Crum, Nathan Gowan, Timothy Krzystan, Andrea Martin, Julien Quantifying risk of whale–vessel collisions across space, time, and management policies |
topic_facet |
Ecology Ecology, Evolution, Behavior and Systematics |
description |
Abstract Transportation industries can negatively impact wildlife populations, including through increased risk of mortality. To mitigate this risk successfully, managers and conservationists must estimate risk across space, time, and alternative management policies. Evaluating this risk at fine spatial and temporal scales can be challenging, especially in systems where wildlife–vehicle collisions are rare or imperfectly detected. The sizes and behaviors of wildlife and vehicles influence collision risk, as well as how much they co‐occur in space and time. We applied a modeling framework based on encounter theory to quantify the risk of lethal collisions between endangered North Atlantic right whales and vessels. Using Automatic Identification System vessel traffic data and spatially explicit estimates of right whale abundance that account for imperfect detection, we modeled risk at fine spatiotemporal scales before and after implementation of a vessel speed rule in the southeastern United States. The expected seasonal mortality rates of right whales decreased by 22% on average after the speed rule was implemented, indicating that the rule is effective at reducing lethal collisions. The rule's effect on risk was greatest where right whales were abundant and vessel traffic was heavy, and its effect varied considerably across time and space. Our framework is spatiotemporally flexible, process‐oriented, computationally efficient and accounts for uncertainty, making it an ideal approach for evaluating many wildlife management policies, including those regarding collisions between wildlife and vehicles and cases in which wildlife may encounter other dangerous features such as wind farms, seismic surveys, or fishing gear. |
author2 |
National Oceanic and Atmospheric Administration |
format |
Article in Journal/Newspaper |
author |
Crum, Nathan Gowan, Timothy Krzystan, Andrea Martin, Julien |
author_facet |
Crum, Nathan Gowan, Timothy Krzystan, Andrea Martin, Julien |
author_sort |
Crum, Nathan |
title |
Quantifying risk of whale–vessel collisions across space, time, and management policies |
title_short |
Quantifying risk of whale–vessel collisions across space, time, and management policies |
title_full |
Quantifying risk of whale–vessel collisions across space, time, and management policies |
title_fullStr |
Quantifying risk of whale–vessel collisions across space, time, and management policies |
title_full_unstemmed |
Quantifying risk of whale–vessel collisions across space, time, and management policies |
title_sort |
quantifying risk of whale–vessel collisions across space, time, and management policies |
publisher |
Wiley |
publishDate |
2019 |
url |
http://dx.doi.org/10.1002/ecs2.2713 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2713 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2713 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.2713 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2713 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Ecosphere volume 10, issue 4 ISSN 2150-8925 2150-8925 |
op_rights |
http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.1002/ecs2.2713 |
container_title |
Ecosphere |
container_volume |
10 |
container_issue |
4 |
_version_ |
1799485256754003968 |