Conservation Genetics 

About: Conservation Genetics is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Population & Genetic diversity. It has an ISSN identifier of 1566-0621. Over the lifetime, 2842 publications have been published receiving 77123 citations.

Beyond Bonferroni: Less conservative analyses for conservation genetics

Abstract: Studies in conservation genetics often attempt to determine genetic differentiation between two or more temporally or geographically distinct sample collections. Pairwise p-values from Fisher’s exact tests or contingency Chi-square tests are commonly reported with a Bonferroni correction for multiple tests. While the Bonferroni correction controls the experiment-wise α, this correction is very conservative and results in greatly diminished power to detect differentiation among pairs of sample collections. An alternative is to control the false discovery rate (FDR) that provides increased power, but this method only maintains experiment-wise α when none of the pairwise comparisons are significant. Recent modifications to the FDR method provide a moderate approach to determining significance level. Simulations reveal that critical values of multiple comparison tests with both the Bonferroni method and a modified FDR method approach a minimum asymptote very near zero as the number of tests gets large, but the Bonferroni method approaches zero much more rapidly than the modified FDR method. I compared pairwise significance from three published studies using three critical values corresponding to Bonferroni, FDR, and modified FDR methods. Results suggest that the modified FDR method may provide the most biologically important critical value for evaluating significance of population differentiation in conservation genetics.␣Ultimately, more thorough reporting of statistical significance is needed to allow interpretation of biological significance of genetic differentiation among populations.

A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci

Abstract: Analysis of linkage disequilibrium (\(\hat{r}^2\)=mean squared correlation of allele frequencies at different gene loci) provides a means of estimating effective population size (N e) from a single sample, but this method has seen much less use than the temporal method (which requires at least two samples). It is shown that for realistic numbers of loci and alleles, the linkage disequilibrium method can provide precision comparable to that of the temporal method. However, computer simulations show that estimates of N e based on \(\hat{r}^2\) for unlinked, diallelic gene loci are sharply biased downwards (\(\hat{N}_{\rm e}/N <0.1\) in some cases) if sample size (S) is less than true N e. The bias is shown to arise from inaccuracies in published formula for \(E(\hat{r}^2)\) when S and/or N e are small. Empirically derived modifications to \(E(\hat{r}^2)\) for two mating systems (random mating and lifetime monogamy) effectively eliminate the bias (residual bias in \(\hat{N}_{\rm e}<5\)% in most cases). The modified method also performs well in estimating N e in non-ideal populations with skewed sex ratio or non-random variance in reproductive success. Recent population declines are not likely to seriously affect \(\hat{N}_{\rm e}\), but if N has recently increased from a bottleneck \(\hat{N}_{\rm e}\) can be biased downwards for a few generations. These results should facilitate application of the disequilibrium method for estimating contemporary N e in natural populations. However, a comprehensive assessment of performance of \(\hat{r}^2\) with highly polymorphic markers such as microsatellites is needed.

Development and characterization of polymorphic microsatellite lociin endangered fern Adiantum reniforme var. sinense

Abstract: Fourteen polymorphic microsatellite loci in the endangered fern Adiantum reniforme var. sinense were developed and characterized using the Fast Isolation by AFLP of Sequences Containing repeats (FIASCO) protocol. Polymorphism of each locus was assessed in a bulked sample of 30 individuals from 8 natural populations. The number of alleles per locus varied from 2 to 11, with an average value of 6.2. The ranges of observed and expected heterozygosity were 0.000–0.895 and 0.226–0.868, respectively. These microsatellite markers provide useful tools for the ongoing conservation genetic studies of Adiantum reniforme var. sinense.

The ecology of environmental DNA and implications for conservation genetics

Abstract: Environmental DNA (eDNA) refers to the genetic material that can be extracted from bulk environmental samples such as soil, water, and even air. The rapidly expanding study of eDNA has generated unprecedented ability to detect species and conduct genetic analyses for conservation, management, and research, particularly in scenarios where collection of whole organisms is impractical or impossible. While the number of studies demonstrating successful eDNA detection has increased rapidly in recent years, less research has explored the “ecology” of eDNA—myriad interactions between extraorganismal genetic material and its environment—and its influence on eDNA detection, quantification, analysis, and application to conservation and research. Here, we outline a framework for understanding the ecology of eDNA, including the origin, state, transport, and fate of extraorganismal genetic material. Using this framework, we review and synthesize the findings of eDNA studies from diverse environments, taxa, and fields of study to highlight important concepts and knowledge gaps in eDNA study and application. Additionally, we identify frontiers of conservation-focused eDNA application where we see the most potential for growth, including the use of eDNA for estimating population size, population genetic and genomic analyses via eDNA, inclusion of other indicator biomolecules such as environmental RNA or proteins, automated sample collection and analysis, and consideration of an expanded array of creative environmental samples. We discuss how a more complete understanding of the ecology of eDNA is integral to advancing these frontiers and maximizing the potential of future eDNA applications in conservation and research.

Counting alleles with rarefaction: Private alleles and hierarchical sampling designs

Abstract: The number of alleles (allelic richness) in a population is a fundamental measure of genetic variation, and a useful statistic for identifying populations for conservation. Estimating allelic richness is complicated by the effects of sample size: large samples are expected to have more alleles. Rarefaction solves this problem. This communication extends the rarefaction procedure to count private alleles and to accommodate hierarchical sampling designs.