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Habitat Evaluation Techniques for Moose Management in Interior Alaska

Project 5.20, Federal Aid in Wildlife Restoration Grant. Project Duration: July 1, 2007–June 30, 2012. Principal Investigators: Thomas F. Paragi, Kalin A. Kellie and C. Tom Seaton, Fairbanks.

Although moose abundance and herd composition have been estimated using aerial surveys in defined geographic areas since the late 1970s, those attributes have not been linked to habitat capability. Similarly, harvest reports for moose and their predators (wolves and brown bears region-wide, black bears in some areas) are also coded to geographic areas (Uniform Coding Unit or UCU). We will create databases of historical moose abundance and composition and wildlife harvest that can be spatially linked to habitat capabilities and factors of social and economic systems (e.g., distance to communities) necessary to understand the effectiveness of wildlife management strategies.

The GIS framework allows results of future research on environmental or physiological variables (e.g., effect of snow depth on reproduction or survival) to be incorporated as a spatial attribute. Linking historical measures of moose abundance, predator abundance, and wildlife harvest to a spatial model of historic snow depth and vegetative cover may allow retrospective analysis of management decisions or population dynamics in some situations. Ultimately, spatial models will provide an objective framework for setting moose population objectives and could help forecast outcomes of intensive management scenarios. Expected results include:

1 Definition of year-round moose habitat by GMU to provide the adjusted basis for density estimates in Survey and Inventory reporting.
2 Consistent and transparent definition of winter range based on vegetative cover types, average peak snow depth, and habitat use patterns in winter for extrapolating moose density estimates beyond survey boundaries when setting population objectives in intensive management.
3 Increased number of GMUs in Region III where we have indices of the relative nutritional status of moose (e.g., twinning rate and proportional browse removal).
4 A habitat-based means to select location of late winter population and browse surveys from knowledge of current vegetation and historic snow depth for areas where little or no moose data exist.