41 research outputs found
Data from: Characterizing the physical and genetic structure of the lodgepole pine Ă— jack pine hybrid zone: mosaic structure and differential introgression
Understanding the physical and genetic structure of hybrid zones can illuminate factors affecting their formation and stability. In north central Alberta, lodgepole pine (P. contorta Dougl. ex Loud. var. latifolia) and jack pine (P. banksiana Lamb) form a complex and poorly defined hybrid zone. Better knowledge of this zone is relevant, given the recent host expansion of mountain pine beetle into jack pine. We characterized the zone by genotyping 1998 lodgepole, jack pine and hybrids from British Columbia, Alberta, Saskatchewan, Ontario and Minnesota at 11 microsatellites. Using Bayesian algorithms, we calculated genetic ancestry and used this to model the relationship between species occurrence and environment. In addition, we analyzed the ancestry of hybrids to calculate the genetic contribution of lodgepole and jack pine. Finally we measured the amount of gene flow between the pure species. We found the distribution of the pine classes is explained by environmental variables, and these distributions differ from classic distribution maps. Hybrid ancestry was biased towards lodgepole pine; however gene flow between the two species was equal. The results of this study suggest that the hybrid zone is complex and influenced by environmental constraints. As a result of this analysis, range limits should be redefined
Circumpolar Genetic Structure and Recent Gene Flow of Polar Bears: A Reanalysis.
Recently, an extensive study of 2,748 polar bears (Ursus maritimus) from across their circumpolar range was published in PLOS ONE, which used microsatellites and mitochondrial haplotypes to apparently show altered population structure and a dramatic change in directional gene flow towards the Canadian Archipelago-an area believed to be a future refugium for polar bears as their southernmost habitats decline under climate change. Although this study represents a major international collaborative effort and promised to be a baseline for future genetics work, methodological shortcomings and errors of interpretation undermine some of the study's main conclusions. Here, we present a reanalysis of this data in which we address some of these issues, including: (1) highly unbalanced sample sizes and large amounts of systematically missing data; (2) incorrect calculation of FST and of significance levels; (3) misleading estimates of recent gene flow resulting from non-convergence of the program BayesAss. In contrast to the original findings, in our reanalysis we find six genetic clusters of polar bears worldwide: the Hudson Bay Complex, the Western and Eastern Canadian Arctic Archipelago, the Western and Eastern Polar Basin, and-importantly-we reconfirm the presence of a unique and possibly endangered cluster of bears in Norwegian Bay near Canada's expected last sea-ice refugium. Although polar bears' abundance, distribution, and population structure will certainly be negatively affected by ongoing-and increasingly rapid-loss of Arctic sea ice, these genetic data provide no evidence of strong directional gene flow in response to recent climate change
Spatial and genetic structure of the lodgepole Ă— jack pine hybrid zone
In north-central Alberta, lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia) and jack pine (Pinus banksiana Lamb.) form a mosaic hybrid zone, the spatial extent of which remains poorly defined. We sought to refine the genetic and geographic distribution of this hybrid zone in western North America to provide information important in predicting future risk of mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreaks. We used 29 single nucleotide polymorphism (SNP) markers to discriminate lodgepole pine, jack pine, and their hybrids. We compared and contrasted spatial patterns of hybridization in northern and southern forest zones based on the colonization history of the two species. We found that patterns of introgression were more similar between the zones than expected by chance, but there were significant differences between these regions at specific loci. Using logistic regression, we created a robust predictive model to distinguish among lodgepole pine, jack pine, and their hybrids using a combination of geographic and environmental predictors. Using model selection based on Akaike information criterion, we found that location, elevation, and moisture are important predictors for species class. Quantification of the genetic differences between these two regions, combined with an accurate model for predicting the spatial distribution of lodgepole pine, jack pine, and their hybrids, provides essential information for continued effective management of forest resources
Circumpolar Genetic Structure and Recent Gene Flow of Polar Bears: A Reanalysis
<div><p>Recently, an extensive study of 2,748 polar bears (<i>Ursus maritimus</i>) from across their circumpolar range was published in PLOS ONE, which used microsatellites and mitochondrial haplotypes to apparently show altered population structure and a dramatic change in directional gene flow towards the Canadian Archipelago—an area believed to be a future refugium for polar bears as their southernmost habitats decline under climate change. Although this study represents a major international collaborative effort and promised to be a baseline for future genetics work, methodological shortcomings and errors of interpretation undermine some of the study’s main conclusions. Here, we present a reanalysis of this data in which we address some of these issues, including: (1) highly unbalanced sample sizes and large amounts of systematically missing data; (2) incorrect calculation of <i>F</i><sub><i>ST</i></sub> and of significance levels; (3) misleading estimates of recent gene flow resulting from non-convergence of the program BayesAss. In contrast to the original findings, in our reanalysis we find six genetic clusters of polar bears worldwide: the Hudson Bay Complex, the Western and Eastern Canadian Arctic Archipelago, the Western and Eastern Polar Basin, and—importantly—we reconfirm the presence of a unique and possibly endangered cluster of bears in Norwegian Bay near Canada’s expected last sea-ice refugium. Although polar bears’ abundance, distribution, and population structure will certainly be negatively affected by ongoing—and increasingly rapid—loss of Arctic sea ice, these genetic data provide no evidence of strong directional gene flow in response to recent climate change.</p></div
Landscape modelling spatial bottlenecks: implications for raccoon rabies disease spread
A landscape genetic simulation modelling approach is used to understand factors affecting raccoon rabies disease spread in southern Ontario, Canada. Using the Ontario Rabies Model, we test the hypothesis that landscape configuration (shape of available habitat) affects dispersal, as indicated by genetic structuring. We simulated range expansions of raccoons from New York into vacant landscapes in Ontario, in two areas that differed by the presence or absence of a landscape constriction. Our results provide theoretical evidence that landscape constriction acts as a vicariant bottleneck. We discuss implications for raccoon rabies spread
Comparisons of pairwise <i>F</i><sub><i>ST</i></sub> values for nuclear microsatellites with <i>Φ</i><sub><i>ST</i></sub> values from mitochondrial DNA; the line indicates the expectation of under isolation as given in [56].
<p>(a) S4 Fig from Peacock <i>et al</i>., 2015 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.ref020" target="_blank">20</a>], reproduced here under the terms of its Creative Commons CC0 license. (b) A recreated version of this graph, generated using our recalculated <i>F</i><sub><i>ST</i></sub> and <i>Φ</i><sub><i>ST</i></sub> values. In (b), M’Clintock Channel, Norwegian Bay, and Viscount Melville Sound were excluded because of inadequate sample sizes for mitochondrial DNA (<i>N</i> ≤ 3) and the Laptev Sea was excluded because this MU was significantly out of Hardy–Weinberg equilibrium. Points for brown bears were not recalculated and are not shown. Coloured points indicate intra-cluster MU pairs (coloured as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.g004" target="_blank">Fig 4</a>); grey points indicate inter-cluster MU pairs.</p
Missing data in Peacock <i>et al</i>., 2015 [20].
<p>The size of the square at each management unit–locus intersection is proportional to the amount of missing data at that locus in that management unit. Management unit abbreviations are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.t001" target="_blank">Table 1</a>. Asterisks denote loci that were retained for the reanalysis presented in this paper.</p
Hierarchical analysis of molecular variance (AMOVA) for nuclear microsatellites among management units within the six genetic clusters identified in this paper and shown in Table 2.
<p>For this analysis, we followed Peacock <i>et al</i>., 2015 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.ref020" target="_blank">20</a>] by including northern Davis Strait in the Eastern Archipelago cluster and southern Davis Strait in the Hudson cluster. Western Laptev was included in the Western Basin cluster and Eastern Laptev was included in the Eastern Basin cluster. However, results did not differ significantly when the Laptev Sea and Davis Strait MUs were excluded entirely.</p
Genetic diversity statistics for 18 management units of polar bears.
<p>For microsatellite data, a maximum of 30 individuals have been retained from each management unit from the original dataset of 2,748 individuals, and only the 14 loci indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.g001" target="_blank">Fig 1</a> have been used. Molecular diversity indices for mitochondrial DNA were calculated in Arlequin using pairwise differences with no gamma correction.</p
Hierarchical analysis of molecular variance (AMOVA) for mitochondrial DNA among management units within the six genetic clusters identified in this paper and shown in Table 2.
<p>Note that many management units (incl. the entire Norwegian Bay cluster) were excluded entirely from this AMOVA because of inadequate sampling. Because we lacked sample location information for downloaded haplotypes, we were unable to split Davis Strait or the Laptev Sea into northern/southern or eastern/western samples; therefore, these MUs were removed for this calculation in addition to the MUs that were removed for low sample sizes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148967#pone.0148967.t002" target="_blank">Table 2</a>.</p