Fine-scale genetic structure of an endangered population of the Mormon metalmark butterfly (Apodemia mormo) revealed using AFLPs

Abstract

We investigated the genetic structure and diversity of an endangered Canadian population of the Mormon metalmark butterfly (Apodemia mormo) using, for the first time, amplified fragment length polymorphism (AFLP) markers generated from non-lethal samples of butterfly wing tissue. Based on 326 loci, our analyses show a high degree of spatial genetic structure within the population, indicating limited gene flow, despite a small geographic range (\20 km). We found that geographic distance, particularly measured along valley bottoms, restricts gene flow within this population. However, other potential barriers to movement and genetic exchange were also identified, in particular urban development. Overall, the population exhibited low levels of genetic diversity. Future management should focus on increasing gene flow between the most isolated sub-populations, and through urban areas, by preserving and restoring as many habitat patches as possible.

Identifying and reducing AFLP genotyping error: an example of tradeoffs when comparing population structure in broadcast spawning versus brooding oysters

“…We suspect that the skewed distribution of locus-specific error rates observed here is not unusual, compromising average genotyping error as a sole criterion for choosing a final data set. Others have noted the same thing, for example, by removing 'singleton' loci from the optimum data set as judged with AFLPSCORE (Crawford et al, 2011).…”

“…In our experience using these methods, it is rarely clear which thresholds are more desirable, those giving lower average error and smaller data sets or those yielding higher error and larger data sets, but they make it possible to explore trade-offs using objective and repeatable criteria. Two studies that have used these tools to compare population genetic informativeness of low and high stringency data sets found that the latter, with fewer scored loci, seemed to provide slightly more explanatory power with respect to population structure (Herrmann et al, 2010;Crawford et al, 2011).…”

“…Effects on estimation of genetic diversity and population structure have mostly been hypothesized (Bonin et al, 2004), demonstrated with simulations (Caballero et al, 2008), and only recently explored empirically (Arrigo et al, 2009;Herrmann et al, 2010;Crawford et al, 2011). Bonin et al (2004) hypothesized that 0.1% average genotyping error among loci may provide little improvement for population genetic inferences compared with 2%.…”

Population genetic structure and genetic diversity of the threatened White Mountain arctic butterfly (Oeneis melissa semidea)

“…Jefferson (Anthony 1970;McFarland 2003). Some butterflies show a low ability or propensity to disperse among such fragmented habitat patches (e.g., Brussard et al 1974;Britten et al 1995;Vandewoestijne and Baguette 2004;Keyghobadi et al 2006;Sigaard et al 2008;Leidner and Haddad 2010;Crawford et al 2011;Polic et al 2014), and historically, few WMA adults have been observed in areas of the alpine zone between meadows (McFarland 2003). This suggests that dispersal, and hence, gene flow, may be limited among meadows for the WMA (Anthony 1970;McFarland 2003).…”

“…As such, genetic data would be particularly useful for studying and characterizing the WMA population and enabling conservation plans to be developed. Not only are genetics now recognized to play a major role in the fates of threatened populations (Spielman et al 2004;Frankham 2010), but molecular data also can be used to infer behavioural and demographic characteristics that may not otherwise be easily discernible or attainable through traditional monitoring (Charman et al 2010;Darvill et al 2010;Crawford et al 2011). Thus far, genetic analysis has played an indispensable role in the study of numerous endangered butterfly populations (Harper et al 2003;Vandewoestijne and Baguette 2004;Gompert et al 2006;Sigaard et al 2008;Habel et al 2010b;Crawford et al 2011;Kodandaramaiah et al 2012).…”