Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana

Moose (Alces alces) are widely distributed across >100,000 km2 of Montana yet occur at low densities and garner minimal funding. Traditional monitoring methods present challenges of low precision and high cost. During 2012–2015, we tested the efficacy of applying patch occupancy modeling to moose...

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Main Authors: DeCesare, Nicholas J., Newby, Jesse R., Podruzny, Kevin M., Wash, Keri, Gude, Justin A.
Format: Article in Journal/Newspaper
Language:English
Published: Intermountain Journal of Science 2017
Subjects:
Online Access:https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197
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spelling ftmontanastunojs:oai:ojs.arc.lib.montana.edu:article/1197 2024-09-09T18:56:36+00:00 Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana DeCesare, Nicholas J. Newby, Jesse R. Podruzny, Kevin M. Wash, Keri Gude, Justin A. 2017-12-31 application/pdf https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197 eng eng Intermountain Journal of Science https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197/972 https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197 Copyright (c) 2017 Intermountain Journal of Sciences Intermountain Journal of Sciences; Vol. 23 No. 1-4 December (2017); 67-68 1081-3519 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-peer-reviewed Abstract 2017 ftmontanastunojs 2024-07-10T03:16:13Z Moose (Alces alces) are widely distributed across >100,000 km2 of Montana yet occur at low densities and garner minimal funding. Traditional monitoring methods present challenges of low precision and high cost. During 2012–2015, we tested the efficacy of applying patch occupancy modeling to moose sightings made by hunters of other cervids for cost-effective statewide monitoring. We used phone surveys to collect sightings and allocated each spatially to grid cells and temporally to 1-week sessions within a 5-week hunting season. For each cell we estimated covariates with hypothesized relevance to occupancy by moose or detectability by hunters, including characterization of vegetation, topography, accessibility by humans, hunter effort, and spatial correlation. We sampled ?45,500 hunters per year at a cost of $12,000–$15,000. Of responding hunters, 14% reported ?1 moose sighting which accumulated to 4,800–6,800 sightings annually. Statewide occupancy estimates were robust and consistent across years of sampling, averaging ? = 0.30 (SE=0.005, range=0.30–0.31). Forested vegetation types reduced the probability of detection but increased the probability of occupancy, while shrub and riparian vegetation types increased both detection and occupancy rates. The amount of sampling effort expended affected detection rates but did not affect occupancy estimates. We expect occupancy estimates to be less sensitive to population changes in areas with higher abundance, making this approach better suited for monitoring change at the range periphery. Alternate count-based analysis techniques such as n-mixture models may offer an alternative to make best use of hunter sightings for monitoring statewide moose populations. Article in Journal/Newspaper Alces alces Montana State University Library Open Journal Systems
institution Open Polar
collection Montana State University Library Open Journal Systems
op_collection_id ftmontanastunojs
language English
description Moose (Alces alces) are widely distributed across >100,000 km2 of Montana yet occur at low densities and garner minimal funding. Traditional monitoring methods present challenges of low precision and high cost. During 2012–2015, we tested the efficacy of applying patch occupancy modeling to moose sightings made by hunters of other cervids for cost-effective statewide monitoring. We used phone surveys to collect sightings and allocated each spatially to grid cells and temporally to 1-week sessions within a 5-week hunting season. For each cell we estimated covariates with hypothesized relevance to occupancy by moose or detectability by hunters, including characterization of vegetation, topography, accessibility by humans, hunter effort, and spatial correlation. We sampled ?45,500 hunters per year at a cost of $12,000–$15,000. Of responding hunters, 14% reported ?1 moose sighting which accumulated to 4,800–6,800 sightings annually. Statewide occupancy estimates were robust and consistent across years of sampling, averaging ? = 0.30 (SE=0.005, range=0.30–0.31). Forested vegetation types reduced the probability of detection but increased the probability of occupancy, while shrub and riparian vegetation types increased both detection and occupancy rates. The amount of sampling effort expended affected detection rates but did not affect occupancy estimates. We expect occupancy estimates to be less sensitive to population changes in areas with higher abundance, making this approach better suited for monitoring change at the range periphery. Alternate count-based analysis techniques such as n-mixture models may offer an alternative to make best use of hunter sightings for monitoring statewide moose populations.
format Article in Journal/Newspaper
author DeCesare, Nicholas J.
Newby, Jesse R.
Podruzny, Kevin M.
Wash, Keri
Gude, Justin A.
spellingShingle DeCesare, Nicholas J.
Newby, Jesse R.
Podruzny, Kevin M.
Wash, Keri
Gude, Justin A.
Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
author_facet DeCesare, Nicholas J.
Newby, Jesse R.
Podruzny, Kevin M.
Wash, Keri
Gude, Justin A.
author_sort DeCesare, Nicholas J.
title Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
title_short Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
title_full Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
title_fullStr Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
title_full_unstemmed Occupancy Modeling of Hunter Sightings for Monitoring Moose in Montana
title_sort occupancy modeling of hunter sightings for monitoring moose in montana
publisher Intermountain Journal of Science
publishDate 2017
url https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197
genre Alces alces
genre_facet Alces alces
op_source Intermountain Journal of Sciences; Vol. 23 No. 1-4 December (2017); 67-68
1081-3519
op_relation https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197/972
https://arc.lib.montana.edu/ojs/index.php/IJS/article/view/1197
op_rights Copyright (c) 2017 Intermountain Journal of Sciences
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