Estimating occupancy probability of moose using hunter survey data
Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distrib...
Published in: | The Journal of Wildlife Management |
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Format: | Article in Journal/Newspaper |
Language: | English |
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2017
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Online Access: | https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-occupancy-probability-of-moose-using-hunter-survey-data(f54e88e5-975b-49fc-bb31-48c6b3b7735a).html https://doi.org/10.1002/jwmg.21207 http://www.scopus.com/inward/record.url?scp=85016445990&partnerID=8YFLogxK |
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ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/f54e88e5-975b-49fc-bb31-48c6b3b7735a 2023-05-15T13:12:53+02:00 Estimating occupancy probability of moose using hunter survey data Crum, Nathan J. Fuller, Angela K. Sutherland, Christopher S. Cooch, Evan G. Hurst, Jeremy 2017-04-01 https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-occupancy-probability-of-moose-using-hunter-survey-data(f54e88e5-975b-49fc-bb31-48c6b3b7735a).html https://doi.org/10.1002/jwmg.21207 http://www.scopus.com/inward/record.url?scp=85016445990&partnerID=8YFLogxK eng eng info:eu-repo/semantics/openAccess Crum , N J , Fuller , A K , Sutherland , C S , Cooch , E G & Hurst , J 2017 , ' Estimating occupancy probability of moose using hunter survey data ' , Journal of Wildlife Management , vol. 81 , no. 3 , pp. 521-534 . https://doi.org/10.1002/jwmg.21207 Alces alces citizen science distribution moose New York occupancy article 2017 ftunstandrewcris https://doi.org/10.1002/jwmg.21207 2022-07-21T07:01:20Z Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (Alces alces) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (Odocoileus virginianus) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused. Article in Journal/Newspaper Alces alces University of St Andrews: Research Portal The Journal of Wildlife Management 81 3 521 534 |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
topic |
Alces alces citizen science distribution moose New York occupancy |
spellingShingle |
Alces alces citizen science distribution moose New York occupancy Crum, Nathan J. Fuller, Angela K. Sutherland, Christopher S. Cooch, Evan G. Hurst, Jeremy Estimating occupancy probability of moose using hunter survey data |
topic_facet |
Alces alces citizen science distribution moose New York occupancy |
description |
Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (Alces alces) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (Odocoileus virginianus) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused. |
format |
Article in Journal/Newspaper |
author |
Crum, Nathan J. Fuller, Angela K. Sutherland, Christopher S. Cooch, Evan G. Hurst, Jeremy |
author_facet |
Crum, Nathan J. Fuller, Angela K. Sutherland, Christopher S. Cooch, Evan G. Hurst, Jeremy |
author_sort |
Crum, Nathan J. |
title |
Estimating occupancy probability of moose using hunter survey data |
title_short |
Estimating occupancy probability of moose using hunter survey data |
title_full |
Estimating occupancy probability of moose using hunter survey data |
title_fullStr |
Estimating occupancy probability of moose using hunter survey data |
title_full_unstemmed |
Estimating occupancy probability of moose using hunter survey data |
title_sort |
estimating occupancy probability of moose using hunter survey data |
publishDate |
2017 |
url |
https://risweb.st-andrews.ac.uk/portal/en/researchoutput/estimating-occupancy-probability-of-moose-using-hunter-survey-data(f54e88e5-975b-49fc-bb31-48c6b3b7735a).html https://doi.org/10.1002/jwmg.21207 http://www.scopus.com/inward/record.url?scp=85016445990&partnerID=8YFLogxK |
genre |
Alces alces |
genre_facet |
Alces alces |
op_source |
Crum , N J , Fuller , A K , Sutherland , C S , Cooch , E G & Hurst , J 2017 , ' Estimating occupancy probability of moose using hunter survey data ' , Journal of Wildlife Management , vol. 81 , no. 3 , pp. 521-534 . https://doi.org/10.1002/jwmg.21207 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1002/jwmg.21207 |
container_title |
The Journal of Wildlife Management |
container_volume |
81 |
container_issue |
3 |
container_start_page |
521 |
op_container_end_page |
534 |
_version_ |
1766254699284004864 |