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Empirical Evaluation of a Test for Identifying Recently Bottlenecked Populations from Allele Frequency Data
Author(s) -
Luikart Gordon,
Cornuet JeanMarie
Publication year - 1998
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.1998.96388.x
Subject(s) - citation , humanities , genealogy , philosophy , library science , history , computer science
Identifying recently bottlenecked populations (populations severely reduced in size) is important because bottlenecks can increase demographic stochasticity, rate of inbreeding, loss of genetic variation, and fixation of deleterious alleles and, thereby, reduce adaptive potential and increase the probability of population extinction (Frankel & Soulé 1981; Lande 1988, 1994; Leberg 1990; Hedrick & Miller 1992; Mills & Smouse 1994; Frankham 1995 a , 1995 b ; but see Bryant et al. 1986; Goodnight 1987). Unfortunately, it is usually difficult to determine if a population has recently experienced a bottleneck because historical population sizes and levels of genetic variation are seldom known. We developed a statistical test (a sign test for heterozygosity excess) for detecting recent historical bottlenecks using allele frequency data (Cornuet & Luikart 1996). The test requires no data on historical population sizes or levels of genetic variation; it requires only measurements of allele frequencies from 5 to 20 polymorphic loci in a sample of approximately 20-30 individuals. The test has reasonable statistical power when applied to allele frequency data sets generated by computer simulations (Cornuet & Luikart 1996). The performance of the test, however, must be evaluated by means of empirical data from natural populations before it can be used with confidence. Our objectives were to (1) explain to conservation biologists the principle of the sign test for detecting heterozygosity excess and (2) evaluate the reliability of the test by analyzing 56 allozyme and 37 microsatellite data sets from bottlenecked and nonbottlenecked natural populations.

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