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Evaluating the influence of life ‐ history characteristics on genetic structure: a comparison of small mammals inhabiting complex agricultural landscapes

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ABSTRACT

Conversion of formerly continuous native habitats into highly fragmented landscapes can lead to numerous negative demographic and genetic impacts on native taxa that ultimately reduce population viability. In response to concerns over biodiversity loss, numerous investigators have proposed that traits such as body size and ecological specialization influence the sensitivity of species to habitat fragmentation. In this study, we examined how differences in body size and ecological specialization of two rodents (eastern chipmunk; Tamias striatus and white‐footed mouse; Peromyscus leucopus) impact their genetic connectivity within the highly fragmented landscape of the Upper Wabash River Basin (UWB), Indiana, and evaluated whether landscape configuration and complexity influenced patterns of genetic structure similarly between these two species. The more specialized chipmunk exhibited dramatically more genetic structure across the UWB than white‐footed mice, with genetic differentiation being correlated with geographic distance, configuration of intervening habitats, and complexity of forested habitats within sampling sites. In contrast, the generalist white‐footed mouse resembled a panmictic population across the UWB, and no landscape factors were found to influence gene flow. Despite the extensive previous work in abundance and occupancy within the UWB, no landscape factor that influenced occupancy or abundance was correlated with genetic differentiation in either species. The difference in predictors of occupancy, abundance, and gene flow suggests that species‐specific responses to fragmentation are scale dependent.

No MeSH data available.


Results of the structure (A) and baps (B) analysis for eastern chipmunks across the UWB. structure revealed complex hierarchical genetic structure (upper left) where after iterative runs, the ending number of putative clusters was seven (C1a.1, C1a.2, Cla.3, Clb, C2a, C2b, C2c). In contrast, baps identified 16 putative clusters for chipmunks. Pie charts represent the proportion of individuals assigned to each cluster within each study cell.
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ece32269-fig-0002: Results of the structure (A) and baps (B) analysis for eastern chipmunks across the UWB. structure revealed complex hierarchical genetic structure (upper left) where after iterative runs, the ending number of putative clusters was seven (C1a.1, C1a.2, Cla.3, Clb, C2a, C2b, C2c). In contrast, baps identified 16 putative clusters for chipmunks. Pie charts represent the proportion of individuals assigned to each cluster within each study cell.

Mentions: Both Bayesian clustering programs supported considerable genetic structure in chipmunks, but disagreed on the ideal K. structure detected evidence for hierarchical structure where the first run's highest ΔK occurred at K = 2 regardless if location priors were included (ΔK = 57.152 or 82.812 for no priors and location priors, respectively; Fig. S1). The average likelihoods for K = 2 between the no priors (−56303.0) and location priors (−56304.2) runs also supported K = 2. The first major split generally corresponded to an east–west gradient where eastern individuals were highly assigned to the first cluster and western individuals to the second cluster (Fig. 2A). Iterative runs on the first major cluster eventually revealed four additional subclusters, whereas the second major cluster contained three subclusters (Fig. 2A). There was some evidence for further substructure in multiple subclusters (ΔK = 15.671–18.752 or 25.062–28.123 for no priors or priors, respectively), but assignments within these clusters were either weak (most q = 0.35–0.75) or clusters only occurred within a single study cell. Based on the strong IBD found within study cells and weak assignments within putative clusters, the further substructure likely reflects a combination of false clusters due to IBD (Frantz et al. 2009) and fine‐scale structure within study cells.


Evaluating the influence of life ‐ history characteristics on genetic structure: a comparison of small mammals inhabiting complex agricultural landscapes
Results of the structure (A) and baps (B) analysis for eastern chipmunks across the UWB. structure revealed complex hierarchical genetic structure (upper left) where after iterative runs, the ending number of putative clusters was seven (C1a.1, C1a.2, Cla.3, Clb, C2a, C2b, C2c). In contrast, baps identified 16 putative clusters for chipmunks. Pie charts represent the proportion of individuals assigned to each cluster within each study cell.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5016657&req=5

ece32269-fig-0002: Results of the structure (A) and baps (B) analysis for eastern chipmunks across the UWB. structure revealed complex hierarchical genetic structure (upper left) where after iterative runs, the ending number of putative clusters was seven (C1a.1, C1a.2, Cla.3, Clb, C2a, C2b, C2c). In contrast, baps identified 16 putative clusters for chipmunks. Pie charts represent the proportion of individuals assigned to each cluster within each study cell.
Mentions: Both Bayesian clustering programs supported considerable genetic structure in chipmunks, but disagreed on the ideal K. structure detected evidence for hierarchical structure where the first run's highest ΔK occurred at K = 2 regardless if location priors were included (ΔK = 57.152 or 82.812 for no priors and location priors, respectively; Fig. S1). The average likelihoods for K = 2 between the no priors (−56303.0) and location priors (−56304.2) runs also supported K = 2. The first major split generally corresponded to an east–west gradient where eastern individuals were highly assigned to the first cluster and western individuals to the second cluster (Fig. 2A). Iterative runs on the first major cluster eventually revealed four additional subclusters, whereas the second major cluster contained three subclusters (Fig. 2A). There was some evidence for further substructure in multiple subclusters (ΔK = 15.671–18.752 or 25.062–28.123 for no priors or priors, respectively), but assignments within these clusters were either weak (most q = 0.35–0.75) or clusters only occurred within a single study cell. Based on the strong IBD found within study cells and weak assignments within putative clusters, the further substructure likely reflects a combination of false clusters due to IBD (Frantz et al. 2009) and fine‐scale structure within study cells.

View Article: PubMed Central - PubMed

ABSTRACT

Conversion of formerly continuous native habitats into highly fragmented landscapes can lead to numerous negative demographic and genetic impacts on native taxa that ultimately reduce population viability. In response to concerns over biodiversity loss, numerous investigators have proposed that traits such as body size and ecological specialization influence the sensitivity of species to habitat fragmentation. In this study, we examined how differences in body size and ecological specialization of two rodents (eastern chipmunk; Tamias striatus and white‐footed mouse; Peromyscus leucopus) impact their genetic connectivity within the highly fragmented landscape of the Upper Wabash River Basin (UWB), Indiana, and evaluated whether landscape configuration and complexity influenced patterns of genetic structure similarly between these two species. The more specialized chipmunk exhibited dramatically more genetic structure across the UWB than white‐footed mice, with genetic differentiation being correlated with geographic distance, configuration of intervening habitats, and complexity of forested habitats within sampling sites. In contrast, the generalist white‐footed mouse resembled a panmictic population across the UWB, and no landscape factors were found to influence gene flow. Despite the extensive previous work in abundance and occupancy within the UWB, no landscape factor that influenced occupancy or abundance was correlated with genetic differentiation in either species. The difference in predictors of occupancy, abundance, and gene flow suggests that species‐specific responses to fragmentation are scale dependent.

No MeSH data available.