Date of Award

12-2010

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Wildlife and Fisheries Biology

Advisor

Yarrow, Greg K

Committee Member

Jodice , Patrick G

Committee Member

Bridges , William C

Abstract

Annual commercial fur harvest data suggests a decline in South Carolina's mink (Mustela vison) populations over the past century (Butfiloski and Baker 2005). In 1990, DNR began conducting assessments of South Carolina's coastal marshes, revealing mink populations to be scarce to absent in the northern coastal regions (Baker 1999). Since 1999, restoration efforts have re-established mink populations in the Cape Romain National Wildlife Refuge and additional areas in the northern coastal marshes of South Carolina. Because mink are a species of high conservation priority throughout the coastal zone of South Carolina, it is important to develop and implement a reliable population monitoring program that will direct future management and aid in the recovery of coastal mink populations (Kohlsaat et al. 2005).
Spotlight survey data were used to evaluate the relationship of various environmental variables and survey counts during each year of the study (2008 and 2009). Results indicated that actual tide height (P< 0.001) and creek size (P< 0.001) were correlated to mink observations during spotlight counts during 2008 (r2= 0.291), while actual tide height (P= 0.026), creek size (P= 0.039), and Julian date (P< 0.001) were significant variables during 2009 (r2= 0.225). Actual tide height, predicted tide height, and creek size were also used with 2008 spotlight counts to predict survey counts during 2009. Results showed that predicted mink counts, based on actual tide heights (r2= 0.133, P< .001) and predicted tide heights (r2= 0.11, P< 0.001), were correlated to observed counts for 2009 spotlight surveys. A method was also developed to determine optimal survey tide height. Results from the analysis indicated that at a tide height of at least 1.85 meters (6.05 feet) above mean lowest low water level (MLLW), the probability of observing mink was significantly greater (P= 0.035) than at a lower tide height. Survey data were also used in power analyses to determine the probability of spotlight surveys to detect changes in mink counts over multiple survey seasons. Results indicated that an increase in annual spotlight survey effort, length of monitoring effort (5 or 10 years), a less restrictive probability of making a type I error (i.e. alpha level), and a decrease in the standard deviation of survey counts improves the probability of detecting annual changes (increasing and decreasing) in mink survey counts.

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