Scale Of Gene Flow Research Articles

Surrounding landscape, habitat and hybridization dynamics drive population structure and genetic diversity in the Saltmarsh Sparrow

Abstract Determining factors that shape a species’ population genetic structure is beneficial for identifying effective conservation practices. We assessed population structure and genetic diversity for Saltmarsh Sparrow (Ammospiza caudacuta), an imperiled tidal marsh specialist, using 13 microsatellite markers and 964 individuals sampled from 24 marshes across the breeding range. We show that Saltmarsh Sparrow populations are structured regionally by isolation-by-distance, with gene flow occurring among marshes within ~110 to 135 km of one another. Isolation-by-resistance and isolation-by-environment also shape genetic variation; several habitat and landscape features are associated with genetic diversity and genetic divergence among populations. Human development in the surrounding landscape isolates breeding marshes, reducing genetic diversity, and increasing population genetic divergence, while surrounding marshland and patch habitat quality (proportion high marsh and sea-level-rise trend) have the opposite effect. The distance of the breeding marsh to the Atlantic Ocean also influences genetic variation, with marshes farther inland being more divergent than coastal marshes. In northern marshes, hybridization with Nelson’s Sparrow (A. nelsoni) strongly influences Saltmarsh Sparrow genetic variation, by increasing genetic diversity in the population; this has a concomitant effect of increasing genetic differentiation of marshes with high levels of introgression. From a conservation perspective, we found that the majority of population clusters have low effective population sizes, suggesting a lack of resiliency. To conserve the representative breadth of genetic and ecological diversity and to ensure redundancy of populations, it will be important to protect a diversity of marsh types across the latitudinal gradient of the species range, including multiple inland, coastal, and urban populations, which we have shown to exhibit signals of genetic differentiation. It will also require maintaining connectivity at a regional level, by promoting high marsh habitat at the scale of gene flow (~130 km), while also ensuring “stepping stone” populations across the range.

The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical data sets.

The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the ΔK method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of K and is sensitive to uneven sampling. If this finding holds for empirical data sets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of K to re-estimate genetic structure in 41 empirical microsatellite data sets; 15 from a broad range of taxa and 26 from one phylogenetic group, coral. We compared alternative estimates of K (Puechmaille statistics) with traditional (ΔK and posterior probability) estimates and found widespread disagreement of estimators across data sets. Thus, one estimator alone is insufficient for determining the optimal number of clusters; this was regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) did not necessarily clarify which clustering solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to ΔK. Disagreement between traditional and recent estimators may have important biological implications, such as previously unrecognized population structure, as was the case for many studies reanalysed here.

There Is No 'Rule of Thumb': Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates.

The application of high-density polymorphic single-nucleotide polymorphisms (SNP) markers derived from high-throughput sequencing methods has heralded plenty of biological questions about the linkages of processes operating at micro- and macroevolutionary scales. However, the effects of SNP filtering practices on population genetic inference have received much less attention. By performing sensitivity analyses, we empirically investigated how decisions about the percentage of missing data (MD) and the minor allele frequency (MAF) set in bioinformatic processing of genomic data affect direct (i.e., parentage analysis) and indirect (i.e., fine-scale spatial genetic structure – SGS) gene flow estimates. We focus specifically on these manifestations in small plant populations, and particularly, in the rare tropical plant species Dinizia jueirana-facao, where assumptions implicit to analytical procedures for accurate estimates of gene flow may not hold. Avoiding biases in dispersal estimates are essential given this species is facing extinction risks due to habitat loss, and so we also investigate the effects of forest fragmentation on the accuracy of dispersal estimates under different filtering criteria by testing for recent decrease in the scale of gene flow. Our sensitivity analyses demonstrate that gene flow estimates are robust to different setting of MAF (0.05–0.35) and MD (0–20%). Comparing the direct and indirect estimates of dispersal, we find that contemporary estimates of gene dispersal distance (σrt = 41.8 m) was ∼ fourfold smaller than the historical estimates, supporting the hypothesis of a temporal shift in the scale of gene flow in D. jueirana-facao, which is consistent with predictions based on recent, dramatic forest fragmentation process. While we identified settings for filtering genomic data to avoid biases in gene flow estimates, we stress that there is no ‘rule of thumb’ for bioinformatic filtering and that relying on default program settings is not advisable. Instead, we suggest that the approach implemented here be applied independently in each separate empirical study to confirm appropriate settings to obtain unbiased population genetics estimates.

Comparing direct vs. indirect estimates of gene flow within a population of a scattered tree species

The comparison between historical estimates of gene flow, using variance in allelic frequencies, and contemporary estimates of gene flow, using parentage assignment, is expected to provide insights into ecological and evolutionary processes at work within and among populations. Genetic variation at six microsatellite loci was used to quantify genetic structure in the insect-pollinated, animal-dispersed, low-density tree Sorbus torminalis L. Crantz, and to derive historical estimates of gene flow. The neighbourhood size and root-mean-squared dispersal distance inferred from seedling genotypes (N(b) = 70 individuals, sigma(e) = 417 m) were similar to those inferred from adult genotypes (N(b) = 114 individuals, sigma(e) = 472 m). We also used parentage analyses and a neighbourhood model approach after an evaluation of the statistical properties of this method on simulated data. From our data, we estimated even contributions of seed- and pollen-mediated dispersal to the genetic composition of established seedlings, with both fat-tailed pollen and seed dispersal kernels, and slightly higher mean distance of pollen dispersal (248 m) as compared to seed dispersal (135 m). The resulting contemporary estimate of gene dispersal distance (sigma(c) = 211 m) was approximately twofold smaller than the historical estimates. Besides different assumptions and statistical nuances of both approaches, this discrepancy is likely to reflect a recent restriction in the scale of gene flow which requires manager's attention in a context of increasing forest fragmentation.

Spatial scale of local adaptation in a plant‐pathogen metapopulation

The rate and scale of gene flow can strongly affect patterns of local adaptation in host-parasite interactions. I used data on regional pathogen occurrence to infer the scale of pathogen dispersal and to identify pathogen metapopulations in the interaction between Plantago lanceolata and its specialist phytopathogen, Podosphaera plantaginis. Frequent extinctions and colonizations were recorded in the metapopulations, suggesting substantial gene flow at this spatial scale. The level of pathogen local adaptation was assessed in a laboratory inoculation experiment at three different scales: in sympatric host populations, in sympatric host metapopulations and in allopatric host metapopulations. I found evidence for adaptation to sympatric host populations, as well as evidence indicating that local adaptation may extend to the scale of the sympatric host metapopulation. There was also variation among the metapopulations in the degree of pathogen local adaptation. This may be explained by regional differences in the rate of migration.

An RAPD (random amplified polymorphic DNA) analysis of genetic population structure of Balea biplicata (Gastropoda: Clausiliidae) in fragmented floodplain forests of the Elster/Saale riparian system.

Eight German populations of the land snail Balea biplicata (Mollusca: Clausiliidae) were studied using the randomly amplified polymorphic DNA-polymerase chain reaction and morphometrics (principal component and discriminant analysis) to examine population structure and gene flow patterns in a fragmented landscape mosaic along the Elster/Saale riparian system, Germany. A variety of population genetic analyses targeting either more on the geographic scale of gene flow (genetic distances, F statistics, Mantel test) or on local genotypic structure (heterozygosity, linkage disequilibrium, bottleneck probability) showed that (1) the population system in total is governed by high gene flow independent of geographic distance, (2) genetic structure on the narrower sampling scale is mainly determined by stochastic processes due to genetic drift in small isolated and frequently recolonized populations, and (3) the morphometrical variation of the populations was related neither to habitat nor to genetic heterogeneity. The potentials for active and passive dispersal capacity of the snails and possible environmental impacts on their population structure are discussed.