Publications by authors named "Steven J Micheletti"

Understanding spatial patterns of genetic differentiation and local adaptation is critical in a period of rapid environmental change. Climate change and anthropogenic development have led to population declines and shifting geographic distributions in numerous species. The streamside salamander, , is an endemic amphibian with a small geographic range that predominantly inhabits small, ephemeral streams.

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Understanding mechanisms that underlie species range limits is at the core of evolutionary ecology. Asymmetric gene flow between larger core populations and smaller edge populations can swamp local adaptation at the range edge and inhibit further range expansion. However, empirical tests of this theory are exceedingly rare.

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According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery's abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data.

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Background: Disparity in the timing of biological events occurs across a variety of systems, yet the understanding of genetic basis underlying diverse phenologies remains limited. Variation in maturation timing occurs in steelhead trout, which has been associated with greb1L, an oestrogen target gene. Previous techniques that identified this gene only accounted for about 0.

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A broad portfolio of phenotypic diversity in natural organisms can buffer against exploitation and increase species persistence in disturbed ecosystems. The study of genomic variation that accounts for ecological and evolutionary adaptation can represent a powerful approach to extend understanding of phenotypic variation in nature. Here we present a chromosome-level reference genome assembly for Chinook salmon (; 2.

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High-density genome-wide sequencing increases the likelihood of discovering genes of major effect and genomic structural variation in organisms. While there is an increasing availability of reference genomes across broad taxa, the greatest limitation to whole-genome sequencing of multiple individuals continues to be the costs associated with sequencing. To alleviate excessive costs, pooling multiple individuals with similar phenotypes and sequencing the homogenized DNA (Pool-Seq) can achieve high genome coverage, but at the loss of individual genotypes.

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Organisms typically show evidence of adaptation to features within their local environment. However, many species undergo long-distance dispersal or migration across larger geographic regions that consist of highly heterogeneous habitats. Therefore, selection may influence adaptive genetic variation associated with landscape features at residing sites and along migration routes in migratory species.

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Species' geographic range limits are most often not demarcated by obvious dispersal barriers. Poor-quality habitat at the edge of a species' range can prevent range expansion by preventing outward migration or through reducing adaptive potential resulting from decreased genetic diversity. We identified habitat variables that constrain gene flow across the entire geographic range of an endemic salamander (Ambystoma barbouri) in the eastern United States, and we tested whether increased resistance resulting from these variables provides cryptic dispersal barriers at the range edges.

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The central-marginal hypothesis (CMH) predicts that population size, genetic diversity and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes.

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