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Can Genetic Estimators Provide Robust Estimates of the Effective Number of Breeders in Small Populations?
Author(s) -
Marion Hoehn,
Bernd Gruber,
Stephen D. Sarre,
Rebecca Lange,
Klaus Henle
Publication year - 2012
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0048464
Subject(s) - inbreeding , statistics , estimator , effective population size , confidence interval , sample size determination , biology , population , linkage disequilibrium , genetic diversity , mathematics , demography , genetics , genotype , single nucleotide polymorphism , sociology , gene
The effective population size ( N e ) is proportional to the loss of genetic diversity and the rate of inbreeding, and its accurate estimation is crucial for the monitoring of small populations. Here, we integrate temporal studies of the gecko Oedura reticulata, to compare genetic and demographic estimators of N e . Because geckos have overlapping generations, our goal was to demographically estimate N bI , the inbreeding effective number of breeders and to calculate the N bI /N a ratio ( N a  = number of adults) for four populations. Demographically estimated N bI ranged from 1 to 65 individuals. The mean reduction in the effective number of breeders relative to census size ( N bI /N a ) was 0.1 to 1.1. We identified the variance in reproductive success as the most important variable contributing to reduction of this ratio. We used four methods to estimate the genetic based inbreeding effective number of breeders N bI(gen) and the variance effective populations size N eV(gen) estimates from the genotype data. Two of these methods - a temporal moment-based ( MBT ) and a likelihood-based approach ( TM3 ) require at least two samples in time, while the other two were single-sample estimators - the linkage disequilibrium method with bias correction LDNe and the program ONeSAMP . The genetic based estimates were fairly similar across methods and also similar to the demographic estimates excluding those estimates, in which upper confidence interval boundaries were uninformative. For example, LDNe and ONeSAMP estimates ranged from 14–55 and 24–48 individuals, respectively. However, temporal methods suffered from a large variation in confidence intervals and concerns about the prior information. We conclude that the single-sample estimators are an acceptable short-cut to estimate N bI for species such as geckos and will be of great importance for the monitoring of species in fragmented landscapes.

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