Island biogeography theory explains the genetic diversity of a fragmented rock ptarmigan (Lagopus muta) population

The island biogeography theory is one of the major theories in ecology, and its applicability to natural systems is well documented. The core model of the theory, the equilibrium model of island biogeography, predicts that species diversity on an island is positively related to the size of the island, but negatively related by the island's distance to the mainland. In recent years, ecologists have begun to apply this model when investigating genetic diversity, arguing that genetic and species diversity might be influenced by similar ecological processes. However, most studies have focused on oceanic islands, but knowledge on how the theory applies to islands located on the mainland (e.g., mountain islands, forest islands) is scarce. In this study, we examined how the size and degree of isolation of mountain islands would affect the genetic diversity of an alpine bird, the rock ptarmigan (Lagopus muta). Within our study area, we defined the largest contiguous mountain area as the mainland, while smaller mountains surrounding the mainland were defined as islands. We found that the observed heterozygosity (H o) was significantly higher, and the inbreeding coefficient (F is) significantly lower, on the mainland compared to islands. There was a positive significant relationship between the unbiased expected heterozygosity (H n.b.) and island size (log km2), but a negative significant relationship between H o and the cost distance to the mainland. Our results are consistent with the equilibrium model of island biogeography and show that the model is well suited for investigating genetic diversity among islands, but also on islands located on the mainland.

Patterns of genetic differentiation in Colorado potato beetle correlate with contemporary, not historic, potato land cover

Changing landscape heterogeneity can influence connectivity and alter genetic variation in local populations, but there can be a lag between ecological change and evolutionary responses. Temporal lag effects might be acute in agroecosystems, where land cover has changed substantially in the last two centuries. Here, we evaluate how patterns of an insect pest's genetic differentiation are related to past and present agricultural land cover change over a 150-year period. We quantified change in the amount of potato, Solanum tuberosum L., land cover since 1850 using county-level agricultural census reports, obtained allele frequency data from 7,408 single-nucleotide polymorphism loci, and compared effects of historic and contemporary landscape connectivity on genetic differentiation of Colorado potato beetle, Leptinotarsa decemlineata Say, in two agricultural landscapes in the United States. We found that potato land cover peaked in Wisconsin in the early 1900s, followed by rapid decline and spatial concentration, whereas it increased in amount and extent in the Columbia Basin of Oregon and Washington beginning in the 1960s. In both landscapes, we found small effect sizes of landscape resistance on genetic differentiation, but a 20× to 1,000× larger effect of contemporary relative to historic landscape resistances. Demographic analyses suggest population size trajectories were largely consistent among regions and therefore are not likely to have differentially impacted the observed patterns of population structure in each region. Weak landscape genetic associations might instead be related to the coarse resolution of our historical land cover data. Despite rapid changes in agricultural landscapes over the last two centuries, genetic differentiation among L. decemlineata populations appears to reflect ongoing landscape change. The historical landscape genetic framework employed in this study is broadly applicable to other agricultural pests and might reveal general responses of pests to agricultural land-use change.

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Contrasting effects of habitat discontinuity on three closely related fungivorous beetle species with diverging host-use patterns and dispersal ability

Understanding how landscape structure influences biodiversity patterns and ecological processes are essential in ecological research and conservation practices. Forest discontinuity is a primary driver affecting the population persistence and genetic structure of forest-dwelling species. However, the actual impacts on populations are highly species-specific. In this study, we tested whether dispersal capability and host specialization are associated with susceptibility to forest discontinuity using three closely related, sympatric fungivorous ciid beetle species (two host specialists, Octotemnus assimilis and O. crassus; one host generalist, O. kawanabei). Landscape genetic analyses and the estimation of effective migration surfaces (EEMS) method consistently demonstrated contrasting differences in the relationships between genetic structure and configuration of forest land cover. Octotemnus assimilis, one of the specialists with a presumably higher dispersal capability due to lower wing loading, lacked a definite spatial genetic structure in our study landscape. The remaining two species showed clear spatial genetic structure, but the results of landscape genetic analyses differed between the two species: while landscape resistance appeared to describe the spatial genetic structure of the specialist O. crassus, genetic differentiation of the generalist O. kawanabei was explained by geographic distance alone. This finding is consistent with the prediction that nonforest areas act more strongly as barriers between specialist populations. Our results suggest that differences in host range can influence the species-specific resistance to habitat discontinuity among closely related species inhabiting the same landscape.

Sampling related individuals within ponds biases estimates of population structure in a pond-breeding amphibian

Effective conservation and management of pond-breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding-site connectivity. Population-level studies of pond-breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within-pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome-wide SNPs generated using a double-digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within-pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.

A roadmap for urban evolutionary ecology

Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Asymmetrical habitat coupling of an aquatic predator-The importance of individual specialization

Predators should stabilize food webs because they can move between spatially separate habitats. However, predators adapted to forage on local resources may have a reduced ability to couple habitats. Here, we show clear asymmetry in the ability to couple habitats by Eurasian perch-a common polymorphic predator in European lakes. We sampled perch from two spatially separate habitats-pelagic and littoral zones-in Lake Erken, Sweden. Littoral perch showed stronger individual specialization, but they also used resources from the pelagic zone, indicating their ability to couple habitats. In contrast, pelagic perch showed weaker individual specialization but near complete reliance on pelagic resources, indicating their preference to one habitat. This asymmetry in the habitat coupling ability of perch challenges the expectation that, in general, predators should stabilize spatially separated food webs. Our results suggest that habitat coupling might be constrained by morphological adaptations, which in this case were not related to genetic differentiation but were more likely related to differences in individual specialization.

Functional connectivity and home range inferred at a microgeographic landscape genetics scale in a desert-dwelling rodent

Gene flow in animals is limited or facilitated by different features within the landscape matrix they inhabit. The landscape representation in landscape genetics (LG) is traditionally modeled as resistance surfaces (RS), where novel optimization approaches are needed for assigning resistance values that adequately avoid subjectivity. Also, desert ecosystems and mammals are scarcely represented in LG studies. We addressed these issues by evaluating, at a microgeographic scale, the effect of landscape features on functional connectivity of the desert-dwelling Dipodomys merriami. We characterized genetic diversity and structure with microsatellites loci, estimated home ranges and movement of individuals using telemetry-one of the first with rodents, generated a set of individual and composite environmental surfaces based on hypotheses of variables influencing movement, and assessed how these variables relate to individual-based gene flow. Genetic diversity and structure results evidenced a family-induced pattern driven by first-order-related individuals, notably determining landscape genetic inferences. The vegetation cover and soil resistance optimized surface (NDVI) were the best-supported model and a significant predictor of individual genetic distance, followed by humidity and NDVI+humidity. Based on an accurate definition of thematic resolution, we also showed that vegetation is better represented as continuously (vs. categorically) distributed. Hence, with a nonsubjective optimization framework for RS and telemetry, we were able to describe that vegetation cover, soil texture, and climatic variables influence D. merriami's functional connectivity at a microgeographic scale, patterns we could further explain based on the home range, habitat use, and activity observed between sexes. We describe the relationship between environmental features and some aspects of D. merriami's behavior and physiology.

Partitioning drivers of spatial genetic variation for a continuously distributed population of boreal caribou: Implications for management unit delineation

Isolation by distance (IBD) is a natural pattern not readily incorporated into theoretical models nor traditional metrics for differentiating populations, although clinal genetic differentiation can be characteristic of many wildlife species. Landscape features can also drive population structure additive to baseline IBD resulting in differentiation through isolation-by-resistance (IBR). We assessed the population genetic structure of boreal caribou across western Canada using nonspatial (STRUCTURE) and spatial (MEMGENE) clustering methods and investigated the relative contribution of IBD and IBR on genetic variation of 1,221 boreal caribou multilocus genotypes across western Canada. We further introduced a novel approach to compare the partitioning of individuals into management units (MU) and assessed levels of genetic connectivity under different MU scenarios. STRUCTURE delineated five genetic clusters while MEMGENE identified finer-scale differentiation across the study area. IBD was significant and did not differ for males and females both across and among detected genetic clusters. MEMGENE landscape analysis further quantified the proportion of genetic variation contributed by IBD and IBR patterns, allowing for the relative importance of spatial drivers, including roads, water bodies, and wildfires, to be assessed and incorporated into the characterization of population structure for the delineation of MUs. Local population units, as currently delineated in the boreal caribou recovery strategy, do not capture the genetic variation and connectivity of the ecotype across the study area. Here, we provide the tools to assess fine-scale spatial patterns of genetic variation, partition drivers of genetic variation, and evaluate the best management options for maintaining genetic connectivity. Our approach is highly relevant to vagile wildlife species that are of management and conservation concern and demonstrate varying degrees of IBD and IBR with clinal spatial genetic structure that challenges the delineation of discrete population boundaries.

Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish

As anthropogenic impacts accelerate changes to landscapes across the globe, understanding how genetic population structure is influenced by habitat features and dispersal is key to preserving evolutionary potential at the species level. Furthermore, knowledge of these interactions is essential to identifying potential constraints on local adaptation and for the development of effective management strategies. We examined these issues in Brook Trout (Salvelinus fontinalis) populations residing in the Upper Hudson River watershed of New York State by investigating the spatial genetic structure of over 350 fish collected from 14 different sampling locations encompassing three river systems. Population genetic analyses of microsatellite data suggest that fish in the area exhibit varying degrees of introgression from nearby State-directed supplementation activities. Levels of introgression in these populations correlate with water-way distance to stocking sites, although genetic population structure at the level of individual tributaries as well as their larger, parent river systems is also detectable and is dictated by migration and influenced by habitat connectivity. These findings represent a significant contribution to the current literature surrounding Brook Trout migration and dispersal, especially as it relates to larger interconnected systems. This work also suggests that stocking activities may have far-reaching consequences that are not directly limited to the immediate area where stocking occurs. The framework and data presented here may aid in the development of other local aquatic species-focused conservation plans that incorporate molecular tools to answer complex questions regarding diversity mapping, and genetically important conservation units.

Pathogens in space: Advancing understanding of pathogen dynamics and disease ecology through landscape genetics

Landscape genetics has provided many insights into how heterogeneous landscape features drive processes influencing spatial genetic variation in free-living organisms. This rapidly developing field has focused heavily on vertebrates, and expansion of this scope to the study of infectious diseases holds great potential for landscape geneticists and disease ecologists alike. The potential application of landscape genetics to infectious agents has garnered attention at formative stages in the development of landscape genetics, but systematic examination is lacking. We comprehensively review how landscape genetics is being used to better understand pathogen dynamics. We characterize the field and evaluate the types of questions addressed, approaches used and systems studied. We also review the now established landscape genetic methods and their realized and potential applications to disease ecology. Lastly, we identify emerging frontiers in the landscape genetic study of infectious agents, including recent phylogeographic approaches and frameworks for studying complex multihost and host-vector systems. Our review emphasizes the expanding utility of landscape genetic methods available for elucidating key pathogen dynamics (particularly transmission and spread) and also how landscape genetic studies of pathogens can provide insight into host population dynamics. Through this review, we convey how increasing awareness of the complementarity of landscape genetics and disease ecology among practitioners of each field promises to drive important cross-disciplinary advances.

Landscape permeability and individual variation in a dispersal-linked gene jointly determine genetic structure in the Glanville fritillary butterfly

There is now clear evidence that species across a broad range of taxa harbor extensive heritable variation in dispersal. While studies suggest that this variation can facilitate demographic outcomes such as range expansion and invasions, few have considered the consequences of intraspecific variation in dispersal for the maintenance and distribution of genetic variation across fragmented landscapes. Here, we examine how landscape characteristics and individual variation in dispersal combine to predict genetic structure using genomic and spatial data from the Glanville fritillary butterfly. We used linear and latent factor mixed models to identify the landscape features that best predict spatial sorting of alleles in the dispersal-related gene phosphoglucose isomerase (Pgi). We next used structural equation modeling to test if variation in Pgi mediated gene flow as measured by Fst at putatively neutral loci. In a year when the population was recovering following a large decline, individuals with a genotype associated with greater dispersal ability were found at significantly higher frequencies in populations isolated by water and forest, and these populations showed lower levels of genetic differentiation at neutral loci. These relationships disappeared in the next year when metapopulation density was high, suggesting that the effects of individual variation are context dependent. Together our results highlight that (1) more complex aspects of landscape structure beyond just the configuration of habitat can be important for maintaining spatial variation in dispersal traits and (2) that individual variation in dispersal plays a key role in maintaining genetic variation across fragmented landscapes.

Combining Bayesian genetic clustering and ecological niche modeling: Insights into wolf intraspecific genetic structure

The distribution of intraspecific genetic variation and how it relates to environmental factors is of increasing interest to researchers in macroecology and biogeography. Recent studies investigated the relationships between the environment and patterns of intraspecific genetic variation across species ranges but only few rigorously tested the relation between genetic groups and their ecological niches. We quantified the relationship of genetic differentiation (F ST) and the overlap of ecological niches (as measured by n-dimensional hypervolumes) among genetic groups resulting from spatial Bayesian genetic clustering in the wolf (Canis lupus) in the Italian peninsula. Within the Italian wolf population, four genetic clusters were detected, and these clusters showed different ecological niches. Moreover, different wolf clusters were significantly related to differences in land cover and human disturbance features. Such differences in the ecological niches of genetic clusters should be interpreted in light of neutral processes that hinder movement, dispersal, and gene flow among the genetic clusters, in order to not prematurely assume any selective or adaptive processes. In the present study, we found that both the plasticity of wolves-a habitat generalist-to cope with different environmental conditions and the occurrence of barriers that limit gene flow lead to the formation of genetic intraspecific genetic clusters and their distinct ecological niches.

Environmental extremes drive population structure at the northern range limit of Atlantic salmon in North America

Conservation of exploited species requires an understanding of both genetic diversity and the dominant structuring forces, particularly near range limits, where climatic variation can drive rapid expansions or contractions of geographic range. Here, we examine population structure and landscape associations in Atlantic salmon (Salmo salar) across a heterogeneous landscape near the northern range limit in Labrador, Canada. Analysis of two amplicon-based data sets containing 101 microsatellites and 376 single nucleotide polymorphisms (SNPs) from 35 locations revealed clear differentiation between populations spawning in rivers flowing into a large marine embayment (Lake Melville) compared to coastal populations. The mechanisms influencing the differentiation of embayment populations were investigated using both multivariate and machine-learning landscape genetic approaches. We identified temperature as the strongest correlate with genetic structure, particularly warm temperature extremes and wider annual temperature ranges. The genomic basis of this divergence was further explored using a subset of locations (n = 17) and a 220K SNP array. SNPs associated with spatial structuring and temperature mapped to a diverse set of genes and molecular pathways, including regulation of gene expression, immune response, and cell development and differentiation. The results spanning molecular marker types and both novel and established methods clearly show climate-associated, fine-scale population structure across an environmental gradient in Atlantic salmon near its range limit in North America, highlighting valuable approaches for predicting population responses to climate change and managing species sustainability.

Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change

Landscape genetic studies typically focus on the evolutionary processes that give rise to spatial patterns that are quantified at a single point in time. Although landscape change is widely recognized as a strong driver of microevolutionary processes, few landscape genetic studies have directly evaluated the change in spatial genetic structure (SGS) over time with concurrent changes in landscape pattern. We introduce a novel approach to analyze landscape genetic data through time. We demonstrate this approach using genotyped samples (n = 569) from a large black bear (Ursus americanus) population in Michigan (USA) that were harvested during 3 years (2002, 2006, and 2010). We identified areas that were consistently occupied over this 9-year period and quantified temporal variation in SGS. Then, we evaluated alternative hypotheses about effects of changes in landscape features (e.g., deforestation or crop conversion) on fine-scale SGS among years using spatial autoregressive modeling and model selection. Relative measures of landscape change such as magnitude of landscape change (i.e., number of patches changing from suitable to unsuitable states or vice versa), and during later periods, measures of fragmentation (i.e., patch aggregation and cohesion) were associated with change in SGS. Our results stress the importance of conducting time series studies for the conservation and management of wildlife inhabiting rapidly changing landscapes.

Walking in a heterogeneous landscape: Dispersal, gene flow and conservation implications for the giant panda in the Qinling Mountains

Understanding the interaction between life history, demography and population genetics in threatened species is critical for the conservations of viable populations. In the context of habitat loss and fragmentation, identifying the factors that underpin the structuring of genetic variation within populations can allow conservationists to evaluate habitat quality and connectivity and help to design dispersal corridors effectively. In this study, we carried out a detailed, fine‐scale landscape genetic investigation of a giant panda population from the Qinling Mountains for the first time. With a large microsatellite data set and complementary analysis methods, we examined the role of isolation‐by‐barriers (IBB), isolation‐by‐distance (IBD) and isolation‐by‐resistance (IBR) in shaping the pattern of genetic variation in this giant panda population. We found that the Qinling population comprises one continuous genetic cluster, and among the landscape hypotheses tested, gene flow was found to be correlated with resistance gradients for two topographic factors, slope aspect and topographic complexity, rather than geographical distance or barriers. Gene flow was inferred to be facilitated by easterly slope aspect and to be constrained by topographically complex landscapes. These factors are related to benign microclimatic conditions for both the pandas and the food resources they rely on and more accessible topographic conditions for movement, respectively. We identified optimal corridors based on these results, aiming to promote gene flow between human‐induced habitat fragments. These findings provide insight into the permeability and affinities of giant panda habitats and offer important reference for the conservation of the giant panda and its habitat.

Genetic differentiation in life history traits and thermal stress performance across a heterogeneous dune landscape in Arabidopsis lyrata

Background and Aims

Over very short spatial scales, the habitat of a species can differ in multiple abiotic and biotic factors. These factors may impose natural selection on several traits and can cause genetic differentiation within a population. We studied multivariate genetic differentiation in a plant species of a sand dune landscape by linking environmental variation with differences in genotypic trait values and gene expression levels to find traits and candidate genes of microgeographical adaptation.

Methods

Maternal seed families of Arabidopsis lyrata were collected in Saugatuck Dunes State Park, Michigan, USA, and environmental parameters were recorded at each collection site. Offspring plants were raised in climate chambers and exposed to one of three temperature treatments: regular occurrence of frost, heat, or constant control conditions. Several traits were assessed: plant growth, time to flowering, and frost and heat resistance.

Key Results

The strongest trait-environment association was between a fast switch to sexual reproduction and weaker growth under frost, and growing in the open, away from trees. The second strongest association was between the trait combination of small plant size and early flowering under control conditions combined with large size under frost, and the combination of environmental conditions of growing close to trees, at low vegetation cover, on dune bottoms. Gene expression analysis by RNA-seq revealed candidate genes involved in multivariate trait differentiation.

Conclusions

The results support the hypothesis that in natural populations, many environmental factors impose selection, and that they affect multiple traits, with the relative direction of trait change being complex. The results highlight that heterogeneity in the selection environment over small spatial scales is a main driver of the maintenance of adaptive genetic variation within populations.

The evolution of city life

Urbanization represents a dominant and growing form of disturbance to Earth's natural ecosystems, affecting biodiversity and ecosystem services on a global scale. While decades of research have illuminated the effects of urban environmental change on the structure and function of ecological communities in cities, only recently have researchers begun exploring the effects of urbanization on the evolution of urban populations. The 15 articles in this special feature represent the leading edge of urban evolutionary biology and address existing gaps in our knowledge. These gaps include: (i) the absence of theoretical models examining how multiple evolutionary mechanisms interact to affect evolution in urban environments; (ii) a lack of data on how urbanization affects natural selection and local adaptation; (iii) poor understanding of whether urban areas consistently affect non-adaptive and adaptive evolution in similar ways across multiple cities; (iv) insufficient data on the genetic and especially genomic signatures of urban evolutionary change; and (v) limited understanding of the evolutionary processes underlying the origin of new human commensals. Using theory, observations from natural populations, common gardens, genomic data and cutting-edge population genomic and landscape genetic tools, the papers in this special feature address these gaps and highlight the power of urban evolutionary biology as a globally replicated 'experiment' that provides a powerful approach for understanding how human altered environments affect evolution.

Habitat Fragmentation Reduces Genetic Diversity and Connectivity of the Mexican Spotted Owl: A Simulation Study Using Empirical Resistance Models

We evaluated how differences between two empirical resistance models for the same geographic area affected predictions of gene flow processes and genetic diversity for the Mexican spotted owl (Strix occidentalis lucida). The two resistance models represented the landscape under low- and high-fragmentation parameters. Under low fragmentation, the landscape had larger but highly concentrated habitat patches, whereas under high fragmentation, the landscape had smaller habitat patches that scattered across a broader area. Overall habitat amount differed little between resistance models. We tested eight scenarios reflecting a factorial design of three factors: resistance model (low vs. high fragmentation), isolation hypothesis (isolation-by-distance, IBD, vs. isolation-by-resistance, IBR), and dispersal limit of species (200 km vs. 300 km). Higher dispersal limit generally had a positive but small influence on genetic diversity. Genetic distance increased with both geographic distance and landscape resistance, but landscape resistance displayed a stronger influence. Connectivity was positively related to genetic diversity under IBR but was less important under IBD. Fragmentation had a strong negative influence on the spatial patterns of genetic diversity and effective population size (Ns). Despite habitats being more concentrated and less widely distributed, the low-fragmentation landscape had greater genetic diversity than the high-fragmentation landscape, suggesting that highly concentrated but larger habitat patches may provide a genetic refuge for the Mexican spotted owl.

Past, present, and future of a freshwater fish metapopulation in a threatened landscape

It is well documented that hydropower plants can affect the dynamics of fish populations through landscape alterations and the creation of new barriers. Less emphasis has been placed on the examination of the genetic consequences for fish populations of the construction of dams. The relatively few studies that focus on genetics often do not consider colonization history and even fewer tend to use this information for conservation purposes. As a case study, we used a 3-pronged approach to study the influence of historical processes, contemporary landscape features, and potential future anthropogenic changes in landscape on the genetic diversity of a fish metapopulation. Our goal was to identify the metapopulation's main attributes, detect priority areas for conservation, and assess the consequences of the construction of hydropower plants for the persistence of the metapopulation. We used microsatellite markers and coalescent approaches to examine historical colonization processes, traditional population genetics, and simulations of future populations under alternate scenarios of population size reduction and gene flow. Historical gene flow appeared to have declined relatively recently and contemporary populations appeared highly susceptible to changes in landscape. Gene flow is critical for population persistence. We found that hydropower plants could lead to a rapid reduction in number of alleles and to population extirpation 50-80 years after their construction. More generally, our 3-pronged approach for the analyses of empirical genetic data can provide policy makers with information on the potential impacts of landscape changes and thus lead to more robust conservation efforts.

Evidence for human-mediated range expansion and gene flow in an invasive grass

Cities and adjacent regions represent foci of intense human activity and provide unique opportunities for studying human-mediated dispersal and gene flow. We examined the effect of landscape features on gene flow in the invasive grass Brachypodium sylvaticum across an urban-rural interface at the edge of its expanding range. We used genome-wide single-nucleotide polymorphism surveys of individuals from 22 locations. Resistance surfaces were created for each landscape feature, using ResistanceGA to optimize resistance parameters. Our Structure analysis identified three distinct clusters, and diversity analyses support the existence of at least three local introductions. Multiple regression on distance matrices showed no evidence that development, roads, canopy cover or agriculture had a significant influence on genetic distance in B. sylvaticum Geographical distance was a mediocre predictor of genetic distance and reflected geographical clustering. The model of rivers acting as a conduit explained a large portion of variation in genetic distance, but the lack of evidence of directional gene flow eliminated hydrochory as a dispersal mechanism. These results and observations of the distribution of populations in disturbed sites indicate that the influence of rivers on patterns of dispersal of B. sylvaticum probably reflects seed dispersal due to human recreational activity.

These aren't the loci you'e looking for: Principles of effective SNP filtering for molecular ecologists

Sequencing reduced-representation libraries of restriction site-associated DNA (RADseq) to identify single nucleotide polymorphisms (SNPs) is quickly becoming a standard methodology for molecular ecologists. Because of the scale of RADseq data sets, putative loci cannot be assessed individually, making the process of filtering noise and correctly identifying biologically meaningful signal more difficult. Artefacts introduced during library preparation and/or bioinformatic processing of SNP data can create patterns that are incorrectly interpreted as indicative of population structure or natural selection. Therefore, it is crucial to carefully consider types of errors that may be introduced during laboratory work and data processing, and how to minimize, detect and remove these errors. Here, we discuss issues inherent to RADseq methodologies that can result in artefacts during library preparation and locus reconstruction resulting in erroneous SNP calls and, ultimately, genotyping error. Further, we describe steps that can be implemented to create a rigorously filtered data set consisting of markers accurately representing independent loci and compare the effect of different combinations of filters on four RAD data sets. At last, we stress the importance of publishing raw sequence data along with final filtered data sets in addition to detailed documentation of filtering steps and quality control measures.

Spatial genetic patterns indicate mechanism and consequences of large carnivore cohabitation within development

Patterns of human development are shifting from concentrated housing toward sprawled housing intermixed with natural land cover, and wildlife species increasingly persist in close proximity to housing, roads, and other anthropogenic features. These associations can alter population dynamics and evolutionary trajectories. Large carnivores increasingly occupy urban peripheries, yet the ecological consequences for populations established entirely within urban and exurban landscapes are largely unknown. We applied a spatial and landscape genetics approach, using noninvasively collected genetic data, to identify differences in black bear spatial genetic patterns across a rural‐to‐urban gradient and quantify how development affects spatial genetic processes. We quantified differences in black bear dispersal, spatial genetic structure, and migration between differing levels of development within a population primarily occupying areas with >6 houses/km² in western Connecticut. Increased development disrupted spatial genetic structure, and we found an association between increased housing densities and longer dispersal. We also found evidence that roads limited gene flow among bears in more rural areas, yet had no effect among bears in more developed ones. These results suggest dispersal behavior is condition‐dependent and indicate the potential for landscapes intermixing development and natural land cover to facilitate shifts toward increased dispersal. These changes can affect patterns of range expansion and the phenotypic and genetic composition of surrounding populations. We found evidence that subpopulations occupying more developed landscapes may be sustained by male‐biased immigration, creating potentially detrimental demographic shifts.

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

Tsetse flies (genus Glossina) are the only vector for the parasitic trypanosomes responsible for sleeping sickness and nagana across sub-Saharan Africa. In Uganda, the tsetse fly Glossina fuscipes fuscipes is responsible for transmission of the parasite in 90% of sleeping sickness cases, and co-occurrence of both forms of human-infective trypanosomes makes vector control a priority. We use population genetic data from 38 samples from northern Uganda in a novel methodological pipeline that integrates genetic data, remotely sensed environmental data, and hundreds of field-survey observations. This methodological pipeline identifies isolated habitat by first identifying environmental parameters correlated with genetic differentiation, second, predicting spatial connectivity using field-survey observations and the most predictive environmental parameter(s), and third, overlaying the connectivity surface onto a habitat suitability map. Results from this pipeline indicated that net photosynthesis was the strongest predictor of genetic differentiation in G. f. fuscipes in northern Uganda. The resulting connectivity surface identified a large area of well-connected habitat in northwestern Uganda, and twenty-four isolated patches on the northeastern margin of the G. f. fuscipes distribution. We tested this novel methodological pipeline by completing an ad hoc sample and genetic screen of G. f. fuscipes samples from a model-predicted isolated patch, and evaluated whether the ad hoc sample was in fact as genetically isolated as predicted. Results indicated that genetic isolation of the ad hoc sample was as genetically isolated as predicted, with differentiation well above estimates made in samples from within well-connected habitat separated by similar geographic distances. This work has important practical implications for the control of tsetse and other disease vectors, because it provides a way to identify isolated populations where it will be safer and easier to implement vector control and that should be prioritized as study sites during the development and improvement of vector control methods.