Date Approved

8-2015

Graduate Degree Type

Thesis

Degree Name

Biology (M.S.)

Degree Program

Biology

First Advisor

Amy L. Russell

Second Advisor

James N. McNair

Third Advisor

Jennifer A. Moore

Abstract

Accurate and unbiased estimates of current effective population size are of primary importance in making informed decisions for conservation purposes. One species of concern, the eastern red bat (Lasiurus borealis), is experiencing ongoing population losses due to wind turbine collisions. The proportion of the population being affected is currently unknown, although recent estimates of total fatalities at wind turbines over the time from 2000-2011 are in the hundreds of thousands for this species alone. The roosting habits of eastern red bats make it difficult to monitor their census population size (Nc); thus, genetic estimates of effective population size (Ne) may provide an alternative monitoring tool. Because they mutate rapidly, microsatellite loci are one of the most promising classes of genetic data for monitoring recent changes in effective population size. To test the accuracy of microsatellite-based estimators for monitoring population declines in large populations, simulated microsatellite data sets were created based on eastern red bat population parameters under multiple scenarios of decline. Simulated data sets were then analyzed using coalescent-based msvar analyses, frequency-based M-ratio tests, and simple measures of genetic diversity. When parameters estimated using msvar were compared to the known parameters with which data sets were created, it was found that msvar produced precise and unbiased estimates of ancestral effective population size (NA), but routinely yielded imprecise estimates of current Ne that were typically biased upwards by an order of magnitude or more. M-ratios correctly indicated decline in 40.3% of data sets, mostly those simulated under demographic scenarios with a large NA. θ (= 4Neμ) was calculated using the known parameters, coalescent point estimates, repeat number variance, homozygosity, and mean allele frequencies. Of these, the coalescent estimates of θ were the least accurate when compared to known θ. These results indicate that caution is warranted when using genetic data to estimate current Ne, particularly for large (Ne ≥ 1000) populations, and that coalescent-based estimates of Ne may be of little practical utility in monitoring large populations over short timescales.

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