Landscape effects on gene flow for a climate-sensitive montane species, the American pika.

Climate change is arguably the greatest challenge to conservation of our time. Most vulnerability assessments rely on past and current species distributions to predict future persistence but ignore species' abilities to disperse through landscapes, which may be particularly important in fragmented habitats and crucial for long-term persistence in changing environments. Landscape genetic approaches explore the interactions between landscape features and gene flow and can clarify how organisms move among suitable habitats, but have suffered from methodological uncertainties. We used a landscape genetic approach to determine how landscape and climate-related features influence gene flow for American pikas (Ochotona princeps) in Crater Lake National Park. Pikas are heat intolerant and restricted to cool microclimates; thus, range contractions have been predicted as climate changes. We evaluated the correlation between landscape variables and genetic distance using partial Mantel tests in a causal modelling framework, and used spatially explicit simulations to evaluate methods of model optimization including a novel approach based on relative support and reciprocal causal modelling. We found that gene flow was primarily restricted by topographic relief, water and west-facing aspects, suggesting that physical restrictions related to small body size and mode of locomotion, as well as exposure to relatively high temperatures, limit pika dispersal in this alpine habitat. Our model optimization successfully identified landscape features influencing resistance in the simulated data for this landscape, but underestimated the magnitude of resistance. This is the first landscape genetic study to address the fundamental question of what limits dispersal and gene flow in the American pika.

Comparability of multiple data types from the Bering Strait region: cranial and dental metrics and nonmetrics, mtDNA, and Y-chromosome DNA.

Different data types have previously been shown to have the same microevolutionary patterns in worldwide data sets. However, peopling of the New World studies have shown a difference in migration paths and timings using multiple types of data, spurring research to understand why this is the case. This study was designed to test the degree of similarity in evolutionary patterns by using cranial and dental metric and nonmetric data, along with Y-chromosome DNA and mtDNA. The populations used included Inuits from Alaska, Canada, Siberia, Greenland, and the Aleutian Islands. For comparability, the populations used for the cranial and molecular data were from similar geographic regions or had a shared population history. Distance, R and kinship matrices were generated for use in running Mantel tests, PROTEST analyses, and Procrustes analyses. A clear patterning was seen, with the craniometric data being most highly correlated to the mtDNA data and the cranial nonmetric data being most highly correlated with the Y-chromosome data, while the phenotypic data were also linked. This patterning is suggestive of a possible male or female inheritance, or the correlated data types are affected by the same or similar evolutionary forces. The results of this study indicate cranial traits have some degree of heritability. Moreover, combining data types leads to a richer knowledge of biological affinity. This understanding is important for bioarchaeological contexts, in particular, peopling of the New World studies where focusing on reconciling the results from comparing multiple data types is necessary to move forward.

Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme.

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, that is, the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic data sets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of interindividual measures of genotypic dissimilarity may efficiently replace interpopulation measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.

Genomic scanning using AFLP to detect loci under selection in the moss Funaria hygrometrica along a climate gradient in the Sierra Nevada Mountains, Spain.

The common cord moss Funaria hygrometrica has a worldwide distribution and thrives in a wide variety of environments. Here, we studied the genetic diversity in F. hygrometrica along an abiotic gradient in the Mediterranean high mountain of Sierra Nevada (Spain) using a genome scan method. Eighty-four samples from 17 locations from 24 to 2700 m were fingerprinted based on their amplified fragment length polymorphism (AFLP) banding pattern. Using PCA and Bayesian inference we found that the genetic diversity was structured in three or four clusters, respectively. Using a genome scan method we identified 13 outlier loci, which showed a signature of positive selection. Partial Mantel tests were performed between the Euclidean distance matrices of geographic and climatic variables, versus the pair-wise genetic distance of the AFLP dataset and AFLP-positive outliers dataset. AFLP-positive outlier data were significantly correlated with the gradient of the climatic variables, suggesting adaptive variation among populations of F. hygrometrica along the Sierra Nevada Mountains. We highlight the additional analyses necessary to identify the nature of these loci, and their biological role in the adaptation process.

Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta.

This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress), a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion) and Solidago missouriensis (goldenrod) found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

THE USE OF DNA DIVERGENCE TO HELP DETERMINE THE CORRELATES OF EVOLUTION OF MORPHOLOGICAL CHARACTERS.

Even though, from Darwin onwards, interisland evolution has been a cornerstone of evolutionary theory it has not been possible to determine to what extent this geographic variation reflects the phylogeny (e.g., pattern of island colonization) or ecogenetic adaptation to different ecological conditions on each island. Using the morphology of western Canary Island lacertids (Gallotia galloti) as an example, a procedure is explored that gives a preliminary answer to this problem when there are a limited number of islands. The phylogenetic component (represented by patristic distances derived from 1005 mitochondrial DNA [mtDNA] base pairs) can be separated from two potential ecogenetic factors (environmental richness and climate) by partial Mantel tests. This reveals that, although these components interact, some characters are correlated primarily to biodiversity/paucity (e.g., size), others are correlated to wet and lush environments (e.g., dorsal pattern), and others are correlated primarily to the phylogeny (e.g., sexual leg markings). The former two correlations may be due to ecogenetic adaptation to current ecological conditions, wheras the latter reflects historical processes.