Prioritizing populations based on recovery potential
Abstract For wide‐ranging species, it is often too expensive or politically challenging to effectively implement conservation action across their range. In these cases, conservation actions may be vigorously applied where the situation appears most dire, but inadvertently at the expense of where suc...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-04-01
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| Series: | Conservation Science and Practice |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/csp2.12905 |
| _version_ | 1827970850976956416 |
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| author | Michelle L. McLellan Melanie Dickie Stan Boutin Marcus Becker Bevan Ernst Darcy Peel Kathryn L. Zimmerman Robert Serrouya |
| author_facet | Michelle L. McLellan Melanie Dickie Stan Boutin Marcus Becker Bevan Ernst Darcy Peel Kathryn L. Zimmerman Robert Serrouya |
| author_sort | Michelle L. McLellan |
| collection | DOAJ |
| description | Abstract For wide‐ranging species, it is often too expensive or politically challenging to effectively implement conservation action across their range. In these cases, conservation actions may be vigorously applied where the situation appears most dire, but inadvertently at the expense of where success is more probable. Consequently, it is prudent to use a prioritization approach that highlights areas of probable success. Using Southern Mountain Caribou as a target species, we develop a simple algorithm that integrates scaled habitat quality measures and population characteristics known to affect the demographics of caribou and weights them according to their relative importance as defined by expert opinion. The algorithm ranks subpopulations by their relative conservation status and, as a result, how likely they are to respond to additional conservation efforts and contribute to long‐term species persistence. Sensitivity analyses are then used to measure the implications of variance among key criteria and the potential variance in expert weighting. The transparent method quickly allows for real, or potential changes in criteria values, scaling, or their relative weighting, thus providing a baseline metric for conservation discussion, subpopulation comparisons, and adaptive management action. A web‐based application of the algorithm can be used directly or adapted for other species. This transparent framework can be used by conservation scientists and managers for prioritizing populations for receiving recovery actions to maximize long‐term conservation impact. |
| first_indexed | 2024-04-09T18:59:45Z |
| format | Article |
| id | doaj.art-ee5cf8fe70604070aa801cc42f7dfcc1 |
| institution | Directory Open Access Journal |
| issn | 2578-4854 |
| language | English |
| last_indexed | 2024-04-09T18:59:45Z |
| publishDate | 2023-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Conservation Science and Practice |
| spelling | doaj.art-ee5cf8fe70604070aa801cc42f7dfcc12023-04-08T15:29:39ZengWileyConservation Science and Practice2578-48542023-04-0154n/an/a10.1111/csp2.12905Prioritizing populations based on recovery potentialMichelle L. McLellan0Melanie Dickie1Stan Boutin2Marcus Becker3Bevan Ernst4Darcy Peel5Kathryn L. Zimmerman6Robert Serrouya7Wildlife Science Centre Biodiversity Pathways Mill Bay British Columbia CanadaWildlife Science Centre Biodiversity Pathways Mill Bay British Columbia CanadaDepartment of Biological Sciences University of Alberta Edmonton Alberta CanadaAlberta Biodiversity Monitoring Institute University of Alberta Edmonton Alberta CanadaMinistery of Water, Land and Resource Stewardship Kamloops British Columbia CanadaMinistery of Water, Land and Resource Stewardship Kamloops British Columbia CanadaMinistery of Water, Land and Resource Stewardship Kamloops British Columbia CanadaWildlife Science Centre Biodiversity Pathways Mill Bay British Columbia CanadaAbstract For wide‐ranging species, it is often too expensive or politically challenging to effectively implement conservation action across their range. In these cases, conservation actions may be vigorously applied where the situation appears most dire, but inadvertently at the expense of where success is more probable. Consequently, it is prudent to use a prioritization approach that highlights areas of probable success. Using Southern Mountain Caribou as a target species, we develop a simple algorithm that integrates scaled habitat quality measures and population characteristics known to affect the demographics of caribou and weights them according to their relative importance as defined by expert opinion. The algorithm ranks subpopulations by their relative conservation status and, as a result, how likely they are to respond to additional conservation efforts and contribute to long‐term species persistence. Sensitivity analyses are then used to measure the implications of variance among key criteria and the potential variance in expert weighting. The transparent method quickly allows for real, or potential changes in criteria values, scaling, or their relative weighting, thus providing a baseline metric for conservation discussion, subpopulation comparisons, and adaptive management action. A web‐based application of the algorithm can be used directly or adapted for other species. This transparent framework can be used by conservation scientists and managers for prioritizing populations for receiving recovery actions to maximize long‐term conservation impact.https://doi.org/10.1111/csp2.12905adaptive managementhabitat protectionmountain cariboupopulation viabilityRangifer tarandusspecies recovery |
| spellingShingle | Michelle L. McLellan Melanie Dickie Stan Boutin Marcus Becker Bevan Ernst Darcy Peel Kathryn L. Zimmerman Robert Serrouya Prioritizing populations based on recovery potential Conservation Science and Practice adaptive management habitat protection mountain caribou population viability Rangifer tarandus species recovery |
| title | Prioritizing populations based on recovery potential |
| title_full | Prioritizing populations based on recovery potential |
| title_fullStr | Prioritizing populations based on recovery potential |
| title_full_unstemmed | Prioritizing populations based on recovery potential |
| title_short | Prioritizing populations based on recovery potential |
| title_sort | prioritizing populations based on recovery potential |
| topic | adaptive management habitat protection mountain caribou population viability Rangifer tarandus species recovery |
| url | https://doi.org/10.1111/csp2.12905 |
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