Date of Award

Spring 2012

Project Type

Thesis

Program or Major

Natural Resources

Degree Name

Master of Science

First Advisor

Adrienne Kovach

Abstract

The New England cottontail (Sylvilagus transitionalis ) is a species of conservation concern. Efficient monitoring methods are needed to guide and assess conservation decisions in an adaptive management framework. I used genetic tools and non-invasively collected fecal DNA to determine New England cottontail detection rates during presence/absence surveys and to identify the environmental and behavioral factors that influence detection.

I found New England cottontail detection rates to be high (>90%) when surveys were conducted under ideal conditions. Prior knowledge of cottontail activity, low snow depth, and allowing 2-4 days without high winds following a snowfall are the most important factors positively associated with cottontail detection. I also found that increased patch size reduces detection when search efforts are limited to 20 minutes.

I used genetic mark-recapture methods to produce baseline abundance estimates for New England cottontail populations across their range. I used microsatellite genotyping in conjunction with single session mark-recapture models in the program CAPWIRE to estimate New England cottontail abundance on 17 occupied patches in Maine, New Hampshire, and New York. Precision of estimates was reasonable for most small sites and several large sites, but decreased with increasing subsampling distance. I also evaluated the methodology used and recommended changes to future survey efforts to improve efficiency and precision. These recommendations include allowing at least three days to pass following a snow fall before conducting a population survey, and sampling pellets intensively on sites to provide a better chance of obtaining an adequate number of recaptures. The tools developed herein will be useful in future occupancy monitoring and abundance estimation needed for the adaptive management of New England cottontail populations.

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