Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada
Monitoring of widely distributed wildlife species across multiple discrete management units presents challenges for the optimal allocation of monitoring effort. By balancing value in new information gained through monitoring with costs, monitoring effort can be optimally allocated to maximize benefi...
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Laurentian University of Sudbury
2022
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ftlaurentian:oai:zone.biblio.laurentian.ca:10219/3852 2024-04-28T07:53:50+00:00 Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada Priadka, Pauline 2022-01-06 application/pdf https://zone.biblio.laurentian.ca/handle/10219/3852 en eng Laurentian University of Sudbury https://zone.biblio.laurentian.ca/handle/10219/3852 Bayesian state-space model Climate-habitat interactions Linear integer programming Mixed-effects models Optimized monitoring Population uncertainty Population index Selective harvesting Wildlife management Thesis 2022 ftlaurentian 2024-04-03T14:07:51Z Monitoring of widely distributed wildlife species across multiple discrete management units presents challenges for the optimal allocation of monitoring effort. By balancing value in new information gained through monitoring with costs, monitoring effort can be optimally allocated to maximize benefit to wildlife management. The main research objective of this thesis was to identify factors affecting the optimal allocation of monitoring effort for moose (Alces alces) across multiple Wildlife Management Units (WMUs) in Ontario, Canada that have variable moose population densities and dynamics. Moose are a harvested species across their range in North America and require monitoring to ensure sustainable harvest and that population management objectives are met. The main approaches used to monitor moose in the study area included aerial surveys and hunter harvest information, and I used both sources of data collected by the Ontario Ministry of Natural Resources and Forestry. In this thesis, I determined (1) the utility of harvest data as a proxy of moose population abundance under a selective harvest system; (2) the role of synergistic climate-habitat relationships in shaping spatio-temporal variation in moose population dynamics; and (3) the monitoring design that optimized the use of aerial surveys to estimate population abundance, while balancing the needs and monitoring costs of multiple discrete WMUs. My findings revealed that restricted harvest of adult moose reflected spatial variability in moose abundance better than less restricted calf harvest; but this effect was impacted by high levels of both hunter effort and landscape disturbance that can influence the detectability of moose to hunters. Further, my work revealed that moose population response to climate was variable at local (i.e. WMU) scales and was mediated or exacerbated by habitat conditions that can alter ecological links, including parasite transmission and predation. I incorporated my findings of drivers of moose population variability into ... Thesis Alces alces LU|ZONE|UL @ Laurentian University |
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LU|ZONE|UL @ Laurentian University |
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topic |
Bayesian state-space model Climate-habitat interactions Linear integer programming Mixed-effects models Optimized monitoring Population uncertainty Population index Selective harvesting Wildlife management |
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Bayesian state-space model Climate-habitat interactions Linear integer programming Mixed-effects models Optimized monitoring Population uncertainty Population index Selective harvesting Wildlife management Priadka, Pauline Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
topic_facet |
Bayesian state-space model Climate-habitat interactions Linear integer programming Mixed-effects models Optimized monitoring Population uncertainty Population index Selective harvesting Wildlife management |
description |
Monitoring of widely distributed wildlife species across multiple discrete management units presents challenges for the optimal allocation of monitoring effort. By balancing value in new information gained through monitoring with costs, monitoring effort can be optimally allocated to maximize benefit to wildlife management. The main research objective of this thesis was to identify factors affecting the optimal allocation of monitoring effort for moose (Alces alces) across multiple Wildlife Management Units (WMUs) in Ontario, Canada that have variable moose population densities and dynamics. Moose are a harvested species across their range in North America and require monitoring to ensure sustainable harvest and that population management objectives are met. The main approaches used to monitor moose in the study area included aerial surveys and hunter harvest information, and I used both sources of data collected by the Ontario Ministry of Natural Resources and Forestry. In this thesis, I determined (1) the utility of harvest data as a proxy of moose population abundance under a selective harvest system; (2) the role of synergistic climate-habitat relationships in shaping spatio-temporal variation in moose population dynamics; and (3) the monitoring design that optimized the use of aerial surveys to estimate population abundance, while balancing the needs and monitoring costs of multiple discrete WMUs. My findings revealed that restricted harvest of adult moose reflected spatial variability in moose abundance better than less restricted calf harvest; but this effect was impacted by high levels of both hunter effort and landscape disturbance that can influence the detectability of moose to hunters. Further, my work revealed that moose population response to climate was variable at local (i.e. WMU) scales and was mediated or exacerbated by habitat conditions that can alter ecological links, including parasite transmission and predation. I incorporated my findings of drivers of moose population variability into ... |
format |
Thesis |
author |
Priadka, Pauline |
author_facet |
Priadka, Pauline |
author_sort |
Priadka, Pauline |
title |
Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
title_short |
Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
title_full |
Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
title_fullStr |
Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
title_full_unstemmed |
Optimizing monitoring of harvested moose (Alces alces) in Ontario, Canada |
title_sort |
optimizing monitoring of harvested moose (alces alces) in ontario, canada |
publisher |
Laurentian University of Sudbury |
publishDate |
2022 |
url |
https://zone.biblio.laurentian.ca/handle/10219/3852 |
genre |
Alces alces |
genre_facet |
Alces alces |
op_relation |
https://zone.biblio.laurentian.ca/handle/10219/3852 |
_version_ |
1797573584057532416 |