We describe four extensions to existing Bayesian methods for the analysis of genetic structure in populations: (i) use of beta distributions to approximate the posterior distribution of f and theta(B); (ii) use of an entropy statistic to describe the amount of information about a parameter derived from the data; (iii) use of the Deviance Information Criterion (DIC) as a model choice criterion for determining whether there is evidence for inbreeding within populations or genetic differentiation among populations; and (iv) use of samples from the posterior distributions for f and theta(B) derived from different data sets to determine whether the estimates are consistent with one another. We illustrate each of these extensions by applying them to data derived from previous allozyme and random amplified polymorphic DNA surveys of an endangered orchid, Platanthera leucophaea, and we conclude that differences in theta(B) from the two data sets may represent differences in the underlying mutational processes.

Species that have become rare or endangered due to human disturbance are at increased risk of extinction as a result of environmental, demographic, and genetic stochasticity. Smaller populations, which can be typical of endangered species, are especially vulnerable to loss of variation through stochastic events. For 10 populations of Platanthera leucophaea (Nuttall) Lindley (Orchidaceae), a threatened species, genetic variation at allozyme and random amplified polymorphic DNA (RAPD) loci was measured to assess the potential effects of fragmentation and reduced population size on the future viability of populations. Allozymes revealed very low levels of diversity (AP = 1.18; PP = 12%; HO = 0.008) and high levels of population differentiation (FST = 0.75). Additionally, inbreeding coefficients were very high in five of the 10 populations surveyed, due largely to the fixation of alternative alleles at two loci in different populations. In contrast, every individual displayed a unique RAPD fingerprint, yielding higher levels of polymorphism (PP = 45%) and gene diversity (Nei's H = 0.159). Estimates of population differentiation based on RAPD are moderate as measured by amova (ΦST = 0.21), Wright's F‐statistics (GST = 0.26), or Shannon's information index (Hamong = 0.30). However, genetic and geographic distances are not significantly correlated, suggesting a lack of interpopulation gene flow and/or genetic drift within populations. Population size is not a good predictor of genetic variation in the present study, and it is hypothesized that plant dormancy patterns and chaotic fluctuations in population size from year to year may buffer against stochastic events, especially in small populations.

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