Effective Population Size, Genetic Variation, and Their Relevance for Conservation: The Bighorn Sheep in Tiburon Island and Comparisons with Managed Artiodactyls

<div><p>The amount of genetic diversity in a finite biological population mostly depends on the interactions among evolutionary forces and the effective population size (<i>N</i>_<i>e</i>) as well as the time since population establishment. Because the <i>N</i>_<i>e</i> estimation helps to explore population demographic history, and allows one to predict the behavior of genetic diversity through time, <i>N</i>_<i>e</i> is a key parameter for the genetic management of small and isolated populations. Here, we explored an <i>N</i>_<i>e</i>-based approach using a bighorn sheep population on Tiburon Island, Mexico (TI) as a model. We estimated the current (<i>N</i>_<i>crnt</i>) and ancestral stable (<i>N</i>_<i>stbl</i>) inbreeding effective population sizes as well as summary statistics to assess genetic diversity and the demographic scenarios that could explain such diversity. Then, we evaluated the feasibility of using TI as a source population for reintroduction programs. We also included data from other bighorn sheep and artiodactyl populations in the analysis to compare their inbreeding effective size estimates. The TI population showed high levels of genetic diversity with respect to other managed populations. However, our analysis suggested that TI has been under a genetic bottleneck, indicating that using individuals from this population as the only source for reintroduction could lead to a severe genetic diversity reduction. Analyses of the published data did not show a strict correlation between <i>H</i>_<i>E</i> and <i>N</i>_<i>crnt</i> estimates. Moreover, we detected that ancient anthropogenic and climatic pressures affected all studied populations. We conclude that the estimation of <i>N</i>_<i>crnt</i> and <i>N</i>_<i>stbl</i> are informative genetic diversity estimators and should be used in addition to summary statistics for conservation and population management planning.</p>