Dissertation Research: Are Relatively Small Populations more Vulnerable to increased Inbreeding Depression and Decreased Heritability for Traits with a Quantitative Genetic Basis

New Mexico State University, Las Cruces NM

Investigators

Abstract

0105148 Milligan The performance of individuals within populations and the ability of populations to respond to selection, e.g., due to environmental changes, have received special attention by conservation biologists. In particular, small relative to large populations are generally regarded as either containing individuals expressing deleterious genes or lacking sufficient genetic variation to respond to selection. The quantitative genetics measures of inbreeding depression and heritability quantify these effects, and ideally such measures would be available for both small and large populations of the same species. This study is using innovative molecular genetic methods to measure these quantities in populations of Aquilegia (Ranunculaceae; columbines) that vary dramatically in total population size. DNA genotypes will be used to determine how related inviduals are within the populations; statistical models will then be used to estimate the quantitative genetics parameters describing inbreeding depression and heritability. Because populations of different sizes will be studied, a relationship between these measures and population size can be detected if it exists. Conservation biology has increasingly relied upon molecular genetic variation. However, to fully understand how that variation relates to adaptive differentiation, evolutionary potential, and resistance to the threat of extinction--all critical concerns of conservation biology--a better understanding of the quantitative genetic basis of adaptive traits is critical. Furthermore, the assumptions mentioned above about how population size affects that basis require empirical testing in natural populations. This novel study addresses and empirically tests important phenomena in biological conservation using measurements of quantitative genetics in field environments.