Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina
ABSTRACT Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear (Ursus americanus). In South Carolina, USA, where there has been growth in black bear populations a...
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| Format: | Article |
| Language: | English |
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Wiley
2019-09-01
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| Series: | Wildlife Society Bulletin |
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| Online Access: | https://doi.org/10.1002/wsb.1007 |
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| author | Shefali Azad Katherine McFadden Joseph D. Clark Tammy Wactor David S. Jachowski |
| author_facet | Shefali Azad Katherine McFadden Joseph D. Clark Tammy Wactor David S. Jachowski |
| author_sort | Shefali Azad |
| collection | DOAJ |
| description | ABSTRACT Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear (Ursus americanus). In South Carolina, USA, where there has been growth in black bear populations and bear–human‐conflict reports during the past several decades, managers need robust estimates of population size to inform management strategies. We used maximum‐likelihood capture–recapture models, using hair snares to collect DNA samples, to estimate density and abundance for a harvested population of black bear in northwestern South Carolina during 2013 to 2014. Models were tested in a spatially explicit framework using the secr package in Program R. Black bear density was estimated at 0.133 bears/km2 (SE = 0.034) in 2013 and 0.179 bears/km2 (SE = 0.043) in 2014. Black bear abundance in our study area was estimated to be 586 bears (SE = 95) in 2013 and 680 bears (SE = 128) in 2014, which are 2–3‐fold lower than previous estimates. We suggest that these estimates be considered a baseline for state biologists to employ in the population's management and in developing future harvest‐regulation strategies. Overall our study highlighted the potential for model choice to influence density estimates, and we concluded that spatially explicit models were appropriate for this study because geographic closure could not be assumed. © 2019 The Wildlife Society. |
| format | Article |
| id | doaj-art-1934029e1d5c411d8e18f9f7abaa7f57 |
| institution | Kabale University |
| issn | 2328-5540 |
| language | English |
| publishDate | 2019-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-1934029e1d5c411d8e18f9f7abaa7f572024-12-16T13:30:52ZengWileyWildlife Society Bulletin2328-55402019-09-0143350050710.1002/wsb.1007Applying spatially explicit capture–recapture models to estimate black bear density in South CarolinaShefali Azad0Katherine McFadden1Joseph D. Clark2Tammy Wactor3David S. Jachowski4Department of Forestry and Environmental Conservation Clemson University Clemson SC 29634‐0317 USAU.S. Geological Survey, South Carolina Cooperative Fish and Wildlife Research Clemson University Clemson SC 29634 USAU.S. Geological Survey, Northern Rocky Mountain Science Center Southern Appalachian Field Branch 274 Ellington Plant Sciences Building Knoxville TN 37996 USAWildlife and Freshwater Fisheries South Carolina Department of Natural Resources Clemson SC 29631 USADepartment of Forestry and Environmental Conservation Clemson University Clemson SC 29634‐0317 USAABSTRACT Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear (Ursus americanus). In South Carolina, USA, where there has been growth in black bear populations and bear–human‐conflict reports during the past several decades, managers need robust estimates of population size to inform management strategies. We used maximum‐likelihood capture–recapture models, using hair snares to collect DNA samples, to estimate density and abundance for a harvested population of black bear in northwestern South Carolina during 2013 to 2014. Models were tested in a spatially explicit framework using the secr package in Program R. Black bear density was estimated at 0.133 bears/km2 (SE = 0.034) in 2013 and 0.179 bears/km2 (SE = 0.043) in 2014. Black bear abundance in our study area was estimated to be 586 bears (SE = 95) in 2013 and 680 bears (SE = 128) in 2014, which are 2–3‐fold lower than previous estimates. We suggest that these estimates be considered a baseline for state biologists to employ in the population's management and in developing future harvest‐regulation strategies. Overall our study highlighted the potential for model choice to influence density estimates, and we concluded that spatially explicit models were appropriate for this study because geographic closure could not be assumed. © 2019 The Wildlife Society.https://doi.org/10.1002/wsb.1007abundanceblack beardensityhair snareSouth Carolinaspatially explicit capture–recapture |
| spellingShingle | Shefali Azad Katherine McFadden Joseph D. Clark Tammy Wactor David S. Jachowski Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina Wildlife Society Bulletin abundance black bear density hair snare South Carolina spatially explicit capture–recapture |
| title | Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina |
| title_full | Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina |
| title_fullStr | Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina |
| title_full_unstemmed | Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina |
| title_short | Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina |
| title_sort | applying spatially explicit capture recapture models to estimate black bear density in south carolina |
| topic | abundance black bear density hair snare South Carolina spatially explicit capture–recapture |
| url | https://doi.org/10.1002/wsb.1007 |
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