Genetic Effective Size of a Wild Primate Population: Influence of Current and Historical Demography

Authors

Jay F. Storz, University of Nebraska - LincolnFollow
Uma Ramakrishnan, University of California at San Diego, La Jolla, California
Susan C. Alberts, Duke University, Box 90338, Durham, North Carolina

Date of this Version

September 2002

Comments

Published in Evolution 56:4 (2002), pp. 817–829. Copyright © 2002 The Society for the Study of Evolution. Published by John Wiley & Sons. Used by permission. http://www3.interscience.wiley.com/journal/117958524/home

Abstract

A comprehensive assessment of the determinants of effective population size (N_e) requires estimates of variance in lifetime reproductive success and past changes in census numbers. For natural populations, such information can be best obtained by combining longitudinal data on individual life histories and genetic marker-based inferences of demographic history. Independent estimates of the variance effective size (N_eV, obtained from life-history data) and the inbreeding effective size (N_eI, obtained from genetic data) provide a means of disentangling the effects of current and historical demography. The purpose of this study was to assess the demographic determinants of N_e in one of the most intensively studied natural populations of a vertebrate species: the population of savannah baboons (Papio cynocephalus) in the Amboseli Basin, southern Kenya. We tested the hypotheses that N_eV < N < N_eI (where N = population census number) due to a recent demographic bottleneck. N_eV was estimated using a stochastic demographic model based on detailed life-history data spanning a 28-year period. Using empirical estimates of age-specific rates of survival and fertility for both sexes, individual-based simulations were used to estimate the variance in lifetime reproductive success. The resultant values translated into an N_eV/N estimate of 0.329 (SD = 0.116, 95% CI = 0.172–0.537). Historical N_eI was estimated from 14-locus microsatellite genotypes using a coalescent-based simulation model. Estimates of N_eI were 2.2 to 7.2 times higher than the contemporary census number of the Amboseli baboon population. In addition to the effects of immigration, the disparity between historical N_eI and contemporary N is likely attributable to the time lag between the recent drop in census numbers and the rate of increase in the average probability of allelic identity-by-descent. Thus, observed levels of genetic diversity may primarily reflect the population’s pre-bottleneck history rather than its current demography.