Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification

Thesis (M.S.) University of Alaska Fairbanks, 2005 Stratification of moose survey areas is a key step to reduce population estimation variance. In the Yukon and Alaska, use of fixed-area grids for early winter moose counts combined with the increasing availability of GIS and remotely sensed data pro...

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Main Author: Clyde, Karen J.
Format: Thesis
Language:English
Published: 2005
Subjects:
Online Access:http://hdl.handle.net/11122/5990
id ftunivalaska:oai:scholarworks.alaska.edu:11122/5990
record_format openpolar
spelling ftunivalaska:oai:scholarworks.alaska.edu:11122/5990 2023-05-15T13:13:37+02:00 Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification Clyde, Karen J. 2005-05 http://hdl.handle.net/11122/5990 en_US eng http://hdl.handle.net/11122/5990 Forest Sciences Department Thesis ms 2005 ftunivalaska 2023-02-23T21:36:32Z Thesis (M.S.) University of Alaska Fairbanks, 2005 Stratification of moose survey areas is a key step to reduce population estimation variance. In the Yukon and Alaska, use of fixed-area grids for early winter moose counts combined with the increasing availability of GIS and remotely sensed data provide the opportunity to develop standardized and repeatable habitat-based stratifications. I used univariate comparisons, stepwise regression and AIC modeling to describe moose distribution as a function of landscape level variables for an area in west central Yukon during 1998 and 1999. Results quantified early winter habitat use of upland shrub habitats and support previous observations for early winter moose habitat use in Alaska, Minnesota and Montana. Number of patches, in association with areas of alpine and shrubs, were found to be highly influential for survey blocks where moose are expected to be present and in high numbers. Overall, model performance based on relative abundance of moose was less predictive than for blocks where moose were present or absent. Spatial resolution of GIS and remotely sensed data used in this study (25 m grid cells) provided sufficient spatial detail to generate correlations between moose presence and habitat for a first level stratification. Introduction -- Study area -- Early winter moose surveys -- Land cover mapping -- Habitat variables -- Statistical analyses -- Model development and assessment -- Results -- Early winter moose Surveys --Land cover mapping -- Moose presence and absence -- Univariate analyses -- Stepwise regression -- Model assessment -- High/low numbers of observed adult moose -- Univariate analysis -- Stepwise regression -- Model assessment -- Discussion -- Limitations of this study -- Conclusions and recommendation -- Recommendations for conducting habitat-based stratifications -- Literature cited -- List of personal communication -- Tables -- Figures -- Appendices. Thesis Alces alces Alaska Yukon University of Alaska: ScholarWorks@UA Fairbanks Yukon
institution Open Polar
collection University of Alaska: ScholarWorks@UA
op_collection_id ftunivalaska
language English
description Thesis (M.S.) University of Alaska Fairbanks, 2005 Stratification of moose survey areas is a key step to reduce population estimation variance. In the Yukon and Alaska, use of fixed-area grids for early winter moose counts combined with the increasing availability of GIS and remotely sensed data provide the opportunity to develop standardized and repeatable habitat-based stratifications. I used univariate comparisons, stepwise regression and AIC modeling to describe moose distribution as a function of landscape level variables for an area in west central Yukon during 1998 and 1999. Results quantified early winter habitat use of upland shrub habitats and support previous observations for early winter moose habitat use in Alaska, Minnesota and Montana. Number of patches, in association with areas of alpine and shrubs, were found to be highly influential for survey blocks where moose are expected to be present and in high numbers. Overall, model performance based on relative abundance of moose was less predictive than for blocks where moose were present or absent. Spatial resolution of GIS and remotely sensed data used in this study (25 m grid cells) provided sufficient spatial detail to generate correlations between moose presence and habitat for a first level stratification. Introduction -- Study area -- Early winter moose surveys -- Land cover mapping -- Habitat variables -- Statistical analyses -- Model development and assessment -- Results -- Early winter moose Surveys --Land cover mapping -- Moose presence and absence -- Univariate analyses -- Stepwise regression -- Model assessment -- High/low numbers of observed adult moose -- Univariate analysis -- Stepwise regression -- Model assessment -- Discussion -- Limitations of this study -- Conclusions and recommendation -- Recommendations for conducting habitat-based stratifications -- Literature cited -- List of personal communication -- Tables -- Figures -- Appendices.
format Thesis
author Clyde, Karen J.
spellingShingle Clyde, Karen J.
Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
author_facet Clyde, Karen J.
author_sort Clyde, Karen J.
title Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
title_short Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
title_full Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
title_fullStr Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
title_full_unstemmed Using GIS-based and remotely sensed data for early winter moose (Alces alces gigas) survey stratification
title_sort using gis-based and remotely sensed data for early winter moose (alces alces gigas) survey stratification
publishDate 2005
url http://hdl.handle.net/11122/5990
geographic Fairbanks
Yukon
geographic_facet Fairbanks
Yukon
genre Alces alces
Alaska
Yukon
genre_facet Alces alces
Alaska
Yukon
op_relation http://hdl.handle.net/11122/5990
Forest Sciences Department
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