Date of Award:

5-1992

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Wildland Resources

Department name when degree awarded

Fisheries and Wildlife

Committee Chair(s)

John A. Bissionette

Committee

John A. Bissionette

Committee

Barrie Gilbert

Committee

James Gessaman

Abstract

Subnivean prey appeared to be the primary reason for subnivean access point use by martens. A logistic regression was used to create a predictive model for differential access point use. Prey biomass in grams and percent ground cover of coarse woody debris (CWD) were used as variables in the model. Goodness of fit of the multivariate model was 0.216; biomass was significant al p = 0.0003, CWD was significant at p = 0.0718. Mean values for prey biomass at used and unused access points were 174.2 g and 81 g, respectively, while mean values of CWD were 24.7% and 18.5%, respectively. Both CWD and prey can be used to predict access point use by martens. CWD provides access to the subnivean zone. Martens appear lo key in on access points with higher levels of prey.

Red squirrel middens were found at 33% of used and 16% of unused access points (p = 0.015, n = 90). There was no significant difference in prey biomass or CWD based upon the presence or absence of a squirrel midden. Prey biomass was significantly related to access point use (p = 0.0022) and the relationship was strengthened when squirrels were included in the biomass estimates (p = 0.0001). It is likely that red squirrel middens were used as access points by martens because of the opportunity to prey on red squirrels as a prey item.

Seed boluses were used to estimate the relative prey abundance at subnivean access points. Use of seed boluses in winter was correlated with prey abundance values obtained by snap trapping after the snow melt (J2 = 0.0134, ¢2 = 0.435).

A program for direct entry of raw telemetry data in a Geographic Information System (GIS) data base was developed. With this method telemetry data can be interpreted directly al a number of scales to determine habitat patterns using area rather than point data.

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