Masters Theses

Date of Award

5-1995

Degree Type

Thesis

Degree Name

Master of Science

Major

Wildlife and Fisheries Science

Major Professor

Michael R. Pelton

Committee Members

David Buehler, Joe Clark, Mary Sue Younger

Abstract

Estimates of population size and other demographic parameters may be biased if capture probability is not equal among all members of the population. However, differences in the capture probability of black bears (Ursus americanus) due to trapsite location and long-term mark-recapture studies have not been investigated. Thus, the focus of my research was to determine the influence of habitat characteristics on trap heterogeneity and determine the effects of long-term trapping on the trap response of black bears in Great Smoky Mountains National Park (GSMNP).

Using existing geographical information system (GIS) habitat use models for black bears, I determined relative probabilities of occurrence of bears (RPOB), for both males and females, around black bear trapsites used from 1989 to 1 993. I used logistic and multiple regression to separately test for relationships between capture parameters (sex and age structure, visitation rate, trapnights/capture, and trapnights/recapture) and local- and landscape-level RPOBs. The sex and age structure of captured bears were not related to RPOB (P ≥ 0. 42 and P ≥ 0. 12, respectively). Local-level models showed no relationships between the capture parameters and RPOB (P ≥ 0. 09) , whereas landscape-level models showed a positive relationship with visitation rate (P ≥ 0.01). These results suggested that habitat characteristics at a landscape level were more related to visitation than characteristics at the local-level. Although RPOB was related to visitation rate, the models had low predictive power, suggesting that other factors such as social interactions, presence of bait, or trap experience also may influence capture parameters. Trap heterogeneity bias does not seem related to RPOB, and likely has only a minimal affect on estimates of demographic parameters.

To determine the extent of trap response bias due to learning, I analyzed the effects of long-term trapping on capture parameters from 1976-1993 using analysis of variance. Visitation rate increased over time (P < 0.001) and may have been related to either an increase in population size or trap response bias due to learning. An increase in the number of visits/capture over time (P < 0.001), combined with a constant percentage of recapture (P > 0.05), further suggested trap response bias. Experienced bears may make more visits to a trapsite before they are captured than do unexperienced bears. The sex of captured bears was biased towards males, but did not change over time (P = 0.355), indicating that any trap response bias was similar for both sexes. Changes in the age structure of captured bears over time likely reflected changes in the population and were not related to a strong trap response bias in any age class. I suggest that the effect of learning by black bears on capture probability can be minimized if relatively long sampling periods are used each year and, during the sampling period, modifications to the trap set are made. Capture success remained constant early in the 14-night sampling period then gradually decreased the last few nights (P = 0.008). A sampling period shorter than 14 nights may considerably decrease the number of captures of experienced bears.

Future research on trap heterogeneity bias should use multivariate methods to relate capture parameters to the RPOBs for males and females simultaneously and should investigate the influence of other factors and habitat characteristics on capture parameters. Future research on trap response bias due to learning should further investigate trends in the capture parameters within the sampling periods. Additionally, the influence of other factors (i.e., population trends, weather, and food availability) on trap response should be investigated.

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