Landscape Genetics Approach Research Articles

The effect of terrain on the fine-scale genetic diversity of sub-Antarctic Collembola: A landscape genetics approach.

Biodiversity patterns are shaped by the interplay between geodiversity and organismal characteristics. Superimposing genetic structure onto landscape heterogeneity (i.e., landscape genetics) can help to disentangle their interactions and better understand population dynamics. Previous studies on the sub-Antarctic Prince Edward Islands (located midway between Antarctica and Africa) have highlighted the importance of landscape and climatic barriers in shaping spatial genetic patterns and have drawn attention to the value of these islands as natural laboratories for studying fundamental concepts in biology. Here, we assessed the fine-scale spatial genetic structure of the springtail, Cryptopygus antarcticus travei, which is endemic to Marion Island, in tandem with high-resolution geological data. Using a species-specific suite of microsatellite markers, a fine-scale sampling design incorporating landscape complexity and generalised linear models (GLMs), we examined genetic patterns overlaid onto high-resolution digital surface models and surface geology data across two 1-km sampling transects. The GLMs revealed that genetic patterns across the landscape closely track landscape resistance data in concert with landscape discontinuities and barriers to gene flow identified at a scale of a few metres. These results show that the island's geodiversity plays an important role in shaping biodiversity patterns and intraspecific genetic diversity. This study illustrates that fine-scale genetic patterns in soil arthropods are markedly more structured than anticipated, given that previous studies have reported high levels of genetic diversity and evidence of genetic structing linked to landscape changes for springtail species and considering the homogeneity of the vegetation complexes characteristic of the island at the scale of tens to hundreds of metres. By incorporating fine-scale and high-resolution landscape features into our study, we were able to explain much of the observed spatial genetic patterns. Our study highlights geodiversity as a driver of spatial complexity. More widely, it holds important implications for the conservation and management of the sub-Antarctic islands.

Landscape features influencing gene flow and connectivity of an endangered passerine.

Dispersal of individuals and gene flow are crucial aspects to maintain genetic diversity and viability of populations, especially in the case of threatened species. Landscape composition and structure may facilitate or limit individual movement within and among populations. We used a landscape genetics approach to assess the connectivity patterns of the threatened Dupont's lark (Chersophilus duponti subsp. duponti), considering their genetic patterns and the landscape features associated with its gene flow in Spain. We analysed the genetic relatedness based on 11 species-specific polymorphic microsatellites on 416 Dupont's lark individuals sampled across peninsular Spain between 2017 and 2019, covering most of the European distribution of the species. To assess the relationship between the landscape composition and the species gene flow, we estimated genetic distance at the individual level (Dps). Next, we built a set of environmental surfaces from two time periods (years 1990 and 2018), based on factors such as land use and topography, influencing individuals' movement. We then obtained resistance surfaces from an optimization process on landscape variables. Landscape genetics analyses were done for single and composite surface models for each year separately. Our findings from both time points show that scatter or mosaic-structured vegetation composed by low agricultural and tree cover and high presence of sclerophyllous shrubs favoured Dupont's lark dispersal, while dense and continuous tree cover, as well as areas of intensive agriculture, were limiting factors. Our results suggest the importance of steppe habitat patches for the species' establishment and dispersal. In addition, our results provide key information to develop conservation measures, including conserving and restoring steppe habitats as scattered and/or mosaic-structured vegetation that could warrant the connectivity and persistence of Dupont's lark populations.

Landscape Heterogeneity Explains the Genetic Differentiation of a Forest Bird across the Sino-Himalayan Mountains.

Mountains are the world's most important centers of biodiversity. The Sino-Himalayan Mountains are global biodiversity hotspot due to their extremely high species richness and endemicity. Ample research investigated the impact of the Qinghai-Tibet Plateau uplift and Quaternary glaciations in driving species diversification in plants and animals across the Sino-Himalayan Mountains. However, little is known about the role of landscape heterogeneity and other environmental features in driving diversification in this region. We utilized whole genomes and phenotypic data in combination with landscape genetic approaches to investigate population structure, demography, and genetic diversity in a forest songbird species native to the Sino-Himalayan Mountains, the red-billed leiothrix (Leiothrix lutea). We identified 5 phylogeographic clades, including 1 in the East of China, 1 in Yunnan, and 3 in Tibet, roughly consistent with differences in song and plumage coloration but incongruent with traditional subspecies boundaries. Isolation-by-resistance model best explained population differentiation within L. lutea, with extensive secondary contact after allopatric isolation leading to admixture among clades. Ecological niche modeling indicated relative stability in the extent of suitable distribution areas of the species across Quaternary glacial cycles. Our results underscore the importance of mountains in the diversification of this species, given that most of the distinct genetic clades are concentrated in a relatively small area in the Sino-Himalayan Mountain region, while a single shallow clade populates vast lower-lying areas to the east. This study highlights the crucial role of landscape heterogeneity in promoting differentiation and provides a deep genomic perspective on the mechanisms through which diversity hotspots form.

Influence of climate and landscape on genetic differentiation of aardvarks (Orycteropus afer)

AbstractAimAs climate change accelerates, assessing how climate shapes gene flow and neutral and adaptive genetic differentiation on landscapes is increasingly important. Aardvarks (Orycteropus afer) are ecologically important in sub‐Saharan Africa but are sensitive to human pressures and increasing aridity. We used individual, population and landscape genetic approaches to infer the influence of landscape, climate and potential adaptive differences on gene flow.LocationWe surveyed 8 protected and 4 privately owned areas in South Africa, 2 protected areas in Eswatini and one location in Kenya during 2016–2018.MethodsWe developed microsatellite markers and methods for DNA extraction from faeces, collected and genotyped faecal samples from focal areas and estimated genetic structure. We inferred space use from individual redetections, tested for close relatives and estimated genetic neighbourhood distance. We applied individual‐based landscape genetic analyses at multiple scales to test hypotheses about genetic differentiation by landscape resistance and potential adaptive differences.ResultsWe developed 19 variable microsatellite loci and collected 253 faecal samples from 13 focal areas. We genotyped 104 samples successfully at ≥8 loci as needed for individual identification. The genetic structure suggested 3 regional divisions in South Africa. We detected individuals at locations ≤7.3 km distant and closely related individuals at ≤44 km; genetic neighbourhood distance was <55 km. Lower precipitation increased landscape resistance and strongly predicted genetic differentiation at most spatial scales. Temperature differences at sampling sites also influenced structure, suggesting climate‐associated adaptive differences.Main ConclusionsThe genetic structure of aardvarks is strongly shaped by climate, with arid areas limiting gene flow and reflects apparent isolation by adaptation associated with temperature. Dispersal distances likely are <55 km. The markers we developed will facilitate studies of space use, dispersal, population density or survival. Aridification will increase fragmentation and we recommend monitoring aardvark presence as an indicator of ecosystem change associated with aridification.

Multiscale landscape genetic analysis identifies major waterways as a barrier to dispersal of feral pigs in north Queensland, Australia.

Feral pigs (Sus scrofa) are a destructive and widespread invasive pest in Australia. An understanding of feral pig movement is required to develop management strategies to control feral pigs in Australia. Because landscape structure can have a strong influence on animal movement, it is important to determine how landscape features facilitate or impede the movement of feral pigs. Consequently, we conducted a landscape genetic analysis of feral pig populations in the Herbert region of far north Queensland, Australia, to determine management units and provide recommendations to better inform feral pig population control strategies. Using microsatellite data obtained from 256 feral pig samples from 44 sites, we examined feral pig population structure at multiple spatial scales for univariate and multivariate landscape resistance surfaces to determine the optimal spatial scale and to identify which of the nine landscape features tested impede or facilitate feral pig gene flow. Only weak genetic structure was found among the 44 sampling sites, but major waterways were identified as a minor barrier to gene flow, and an isolation by distance model was supported. We also found that highways facilitated gene flow across the study area, and this suggests that they may act as movement corridors or indicate translocation of feral pigs. Additionally, incorporating a second spatial scale enhanced the ability of our landscape genetics analysis to detect the influence of landscape structure on gene flow. We identified three management units based on natural barriers to gene flow and future targeted control should be undertaken in these management units to deliver sustained reduction of feral pig populations in the Herbert region. This study demonstrates how a landscape genetic approach can be used to gain insight into the ecology of an invasive pest species and be used to develop population control strategies which utilise natural barriers to movement.

Barriers to chimpanzee gene flow at the south-east edge of their distribution.

Populations on the edge of a species' distribution may represent an important source of adaptive diversity, yet these populations tend to be more fragmented and are more likely to be geographically isolated. Lack of genetic exchanges between such populations, due to barriers to animal movement, can not only compromise adaptive potential but also lead to the fixation of deleterious alleles. The south-eastern edge of chimpanzee distribution is particularly fragmented, and conflicting hypotheses have been proposed about population connectivity and viability. To address this uncertainty, we generated both mitochondrial and MiSeq-based microsatellite genotypes for 290 individuals ranging across western Tanzania. While shared mitochondrial haplotypes confirmed historical gene flow, our microsatellite analyses revealed two distinct clusters, suggesting two populations currently isolated from one another. However, we found evidence of high levels of gene flow maintained within each of these clusters, one of which covers an 18,000 km2 ecosystem. Landscape genetic analyses confirmed the presence of barriers to gene flow with rivers and bare habitats highly restricting chimpanzee movement. Our study demonstrates how advances in sequencing technologies, combined with the development of landscape genetics approaches, can resolve ambiguities in the genetic history of critical populations and better inform conservation efforts of endangered species.

Landscape genetics of the Southern Flying Squirrel (Glaucomys volans) in the northeastern United States

Abstract Understanding how changes in landscape properties influence common species is relevant as it allows us to identify patterns that could be shared with co-distributed species that occupy the same landscapes. The northeastern United States (NE-USA: New York state and the six states of New England) is heavily urbanized and affected by continuous and prolonged anthropogenic activities, leading to intensive landscape fragmentation and loss of natural forests. Here, we used a landscape genetics approach to explore the genetic diversity and structure of the Southern Flying Squirrel, Glaucomys volans, and how resulting patterns may be related to landscape fragmentation and forest loss in the NE-USA. To study G. volans genetic variation and population structure, we amplified and genotyped 10 microsatellites loci from DNA extracted from tissue samples stored in biological collections and natural history museums. To assess the influence of landscape on gene flow and connectivity, we used two genetic distances metrics–proportion of shared alleles and codominant marker, and tested two landscape cost models approaches–least cost path and isolation by resistance. We identified three genetic clusters, with low but significant genetic differentiation between them. We did not find correlation between geographic distance and genetic variation in these populations. According to landscape models, land cover and elevation were the best predictors of genetic connectivity of G. volans, although were poorly related to genetic distances. Our results suggest that gene flow occurs between G. volans populations across the NE-USA despite the changed landscape configuration, implying potential dispersal of individuals between patches. Nonetheless, individuals from the eastern periphery of the distribution may have been temporarily isolated in the past due to historical deforestation. The current regeneration of hardwood forests represents a positive outlook for the genetic integrity of G. volans populations in the NE-USA because more possibilities for corridors and patches of habitable forests emerge. These changes would improve the connectivity of the species in the region and avoid possible local extinction events.

Terrain Ruggedness and Canopy Height Predict Short-Range Dispersal in the Critically Endangered Black-and-White Ruffed Lemur.

Dispersal is a fundamental aspect of primates' lives and influences both population and community structuring, as well as species evolution. Primates disperse within an environmental context, where both local and intervening environmental factors affect all phases of dispersal. To date, research has primarily focused on how the intervening landscape influences primate dispersal, with few assessing the effects of local habitat characteristics. Here, we use a landscape genetics approach to examine between- and within-site environmental drivers of short-range black-and-white ruffed lemur (Varecia variegata) dispersal in the Ranomafana region of southeastern Madagascar. We identified the most influential drivers of short-range ruffed lemur dispersal as being between-site terrain ruggedness and canopy height, more so than any within-site habitat characteristic evaluated. Our results suggest that ruffed lemurs disperse through the least rugged terrain that enables them to remain within their preferred tall-canopied forest habitat. Furthermore, we noted a scale-dependent environmental effect when comparing our results to earlier landscape characteristics identified as driving long-range ruffed lemur dispersal. We found that forest structure drives short-range dispersal events, whereas forest presence facilitates long-range dispersal and multigenerational gene flow. Together, our findings highlight the importance of retaining high-quality forests and forest continuity to facilitate dispersal and maintain functional connectivity in ruffed lemurs.

Lahaul-Zanskar-Sham Valley Corridor in Indian Trans Himalayan Region Facilitates Dispersal and Gene Flow in Himalayan Ibex.

Wildlife corridors that connect mosaic habitats in heterogeneous mountainous landscapes can be of high significance as they facilitate the genetic and demographic stability of free-ranging populations. Peripheral populations of widespread species are usually ignored in conservation planning. However, these populations retain locally common alleles and are genetic reservoir under the changing climatic conditions. Capra sibirica has widespread distribution, and its southern peripheral population is distributed in the Indian trans-Himalayan region (ITR). In the present study, we studied the spatial distribution and genetic make-up of Himalayan ibex from the ITR following the landscape genetics approach. We obtained 16 haplotypes at the mitochondrial d-loop region and found a stable demography in the past with a recent decline. With 10 nuclear microsatellites, we ascertained 111 unique individuals assigned into two clusters following Bayesian and non-Bayesian clustering analysis with several admixed individuals. We also recorded 25 first-generation migrants that reflected relatively high dispersal and gene-flow across the range. We identified a 19,835 sq.km suitable area with 13,311 sq.km in Ladakh and 6524 sq.km in Lahaul-Spiti. We identified a novel movement corridor for Himalayan ibex across the Lahaul-Zanskar-Sham valley (L-Z-SV) that displayed a fairly good conductance with low genetic divergence among the samples collected on the L-Z-SV corridor. We propose declaring a protected area in the Lahaul and Kargil districts to prioritize dedicated conservation efforts for the Himalayan ibex and other sympatric ungulates that impart a major role in the diet of large carnivore and balancing ecosystem services in the trans-Himalayan region.

Genetic diversity pattern reveals the primary determinant of burcucumber (Sicyos angulatus L.) invasion in Korea.

Biological invasion is a complex process associated with propagule pressure, dispersal ability, environmental constraints, and human interventions, which leave genetic signatures. The population genetics of an invasive species thus provides invaluable insights into the patterns of invasion. Burcucumber, one of the most detrimental weeds for soybean production in US, has recently colonized Korea and rapidly spread posing a great threat to the natural ecosystem. We aim to infer the determinants of the rapid burcucumber invasion by examining the genetic diversity, demography, and spread pattern with advanced genomic tools. We employed 2,696 genome-wide single-nucleotide polymorphisms to assess the level of diversity and the spatial pattern associated with the landscape factors and to infer the demographic changes of 24 populations (364 genotypes) across four major river basins with the east coastal streams in South Korea. Through the approximate Bayesian computation, we inferred the likely invasion scenario of burcucumber in Korea. The landscape genetics approach adopting the circuit theory and MaxEnt model was applied to determine the landscape contributors. Our data suggested that most populations have experienced population bottlenecks, which led to lowered within-population genetic diversity and inflated population divergences. Burcucumber colonization in Korea has strongly been affected by demographic bottlenecks and multiple introductions, whereas environmental factors were not the primary determinant of the invasion. Our work highlighted the significance of preventing secondary introductions, particularly for aggressive weedy plants such as the burcucumber.

Scale‐dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage‐grouse

Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision‐making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage‐grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations. Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage‐grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.

Host, Microbiome, and Complex Space: Applying Population and Landscape Genetic Approaches to Gut Microbiome Research in Wild Populations.

In recent years, emerging sequencing technologies and computational tools have driven a tidal wave of research on host-associated microbiomes, particularly the gut microbiome. These studies demonstrate numerous connections between the gut microbiome and vital host functions, primarily in humans, model organisms, and domestic animals. As the adaptive importance of the gut microbiome becomes clearer, interest in studying the gut microbiomes of wild populations has increased, in part due to the potential for discovering conservation applications. The study of wildlife gut microbiomes holds many new challenges and opportunities due to the complex genetic, spatial, and environmental structure of wild host populations, and the potential for these factors to interact with the microbiome. The emerging picture of adaptive coevolution in host-microbiome relationships highlights the importance of understanding microbiome variation in the context of host population genetics and landscape heterogeneity across a wide range of host populations. We propose a conceptual framework for understanding wildlife gut microbiomes in relation to landscape variables and host population genetics, including the potential of approaches derived from landscape genetics. We use this framework to review current research, synthesize important trends, highlight implications for conservation, and recommend future directions for research. Specifically, we focus on how spatial structure and environmental variation interact with host population genetics and microbiome variation in natural populations, and what we can learn from how these patterns of covariation differ depending on host ecological and evolutionary traits.

Quantifying and predicting population connectivity of an outbreaking forest insect pest

ContextDispersal has a key role in the population dynamics of outbreaking species such as the spruce budworm (Choristoneura fumiferana) as it can synchronize the demography of distant populations and favor the transition from endemic to epidemic states. However, we know very little about how landscape structure influences dispersal in such systems while such knowledge is essential for better forecasting of spatially synchronous population dynamics and to guide management strategies.ObjectivesWe aimed to characterize the spatial environmental determinants of spruce budworm dispersal to determine how these features affect outbreak spread in Quebec (Canada). We then apply our findings to predict expected future landscape connectivity and explore its potential consequences on future outbreaks.MethodsWe used a machine-learning landscape genetics approach on 447 larvae covering most of the outbreak area and genotyped at 3562 SNP loci to identify the main variables affecting connectivity.ResultsWe found that the connectivity between outbreak populations was driven by the combination of precipitation and host cover. Our forecasting suggests that between the current and next outbreaks, connectivity may increase between Ontario and Quebec, and might decrease in the eastern part, which could have the effect of limiting outbreak spread from Ontario and Quebec to the eastern provinces.ConclusionsAlthough we did not identify any discrete barriers, low connectivity areas might constrain dispersal in the current and future outbreaks and should in turn, be intensively monitored. However, continued sampling as the outbreak progresses is needed to confirm the temporal stability of the observed patterns.

Environmental resistance and habitat quality influence dispersal of the saltwater crocodile.

Landscape genetics commonly focuses on the effects of environmental resistance on animal dispersal patterns, but there is an emerging focus on testing environmental effects on emigration and settlement choices. In this study, we used landscape genetics approaches to quantify dispersal patterns in the world's largest crocodilian, the saltwater crocodile (Crocodylus porosus), and demonstrated environmental influences on three processes that comprise dispersal: emigration, movement and settlement. We found that both environmental resistance and properties of the source and destination catchments (proportion of breeding habitat) were important factors influencing observed dispersal events. Our habitat quality variables related to hypotheses about resource competition and represented the ratio of breeding habitat (which limits carrying capacity), suggesting that competition for habitat influences emigration and settlement choices, together with the strong effect of environmental resistance to movement (where high‐quality habitat was associated with greatest environmental permeability). Approximately 42% of crocodiles were migrants from populations other than their sampling locations and some outstandingly productive populations had a much higher proportion of emigration rather than immigration. The distance most commonly travelled between source and destination was 150–200 km although a few travelled much longer distances, up to 600–700 km. Given the extensive dispersal range, individual catchments or hydrographic regions that combine two or three adjacent catchments are an appropriate scale for population management.

Genomic analysis of red snapper, Lutjanus campechanus, population structure in the U.S. Atlantic and Gulf of Mexico

Abstract Red snapper, Lutjanus campechanus, supports one of the more important fisheries in marine waters of the United States. Consequently, it has been the focus of intensive fisheries research for more than 20 years. Here, we present a genomic analysis of population structure that uses a landscape genetics approach to characterize patterns of variation in adult red snapper in the Gulf of Mexico (GOM) alongside a synoptic view of decades of stock-structure research. The results support Atlantic and GOM stocks and indicate weak heterogeneity within the GOM. Furthermore, redundancy analysis using Moran Eigenvector Maps based on physical distance, larval dispersal probability, and adult dispersal probability reveal heterogeneity on various spatial scales, with adult movement explaining a larger component of variation than spatial position or larval dispersal. Results of this study support the idea that red snapper in the GOM display metapopulation structure, but also suggest a potential genetic discontinuity along the West Florida Shelf not previously described. The approach of using landscape genomics and dispersal data (larval and/or adult) to better understand metapopulation dynamics is promising for not only red snapper, but also for other marine species that occupy a diversity of habitats and are seemingly distributed continuously.

Genetic diversity and functional connectivity of a critically endangered salamander

AbstractHabitat loss and fragmentation are among the greatest threats to biodiversity since unsuitable habitat can be a significant barrier to gene flow, disrupting the connectivity of populations. In this scenario, landscape genetic approaches have been applied as invaluable tools to demonstrate how contemporary habitat alterations affect gene flow. In this study, we used nine microsatellite genotypes to determine the landscape features driving genetic diversity, structure, and functional connectivity among eleven sampling sites of a micro‐endemic, and critically endangered salamander (Pseudoeurycea robertsi) in the Nevado de Toluca Volcano. We also modelled the ecological niche of P. robertsi to assess the most important habitat features associated with its probability of presence and analyzed the corridor network to identify important core areas and corridors to keep the network connected, as well as points where the network connection is lost or tightened. Moreover, we performed a redundancy analysis to assess the effect of genetic distance and habitat resistances on gene flow. We found the highest levels of genetic diversity and connectivity at the northwestern part of the Volcano. Meson Viejo sampling site was of especial importance to overall network connectivity. We found low levels of migration rates and low levels of genetic structure. The most important habitat feature associated with probability of presence of Pseudoeurycea robertsi was the Abies forest, and two models were significant under the RDA analysis: Abies forest and Abies forest+Grasslands. We recommend prioritizing the areas of the northwestern and central parts of the volcano in conservation programs.Abstract in Spanish is available with online material.

MrIML: Multi-response interpretable machine learning to model genomic landscapes.

We introduce a new R package "MrIML" ("Mister iml"; Multi-response Interpretable Machine Learning). MrIML provides a powerful and interpretable framework that enables users to harness recent advances in machine learning to quantify multilocus genomic relationships, to identify loci of interest for future landscape genetics studies, and to gain new insights into adaptation across environmental gradients. Relationships between genetic variation and environment are often nonlinear and interactive; these characteristics have been challenging to address using traditional landscape genetic approaches. Our package helps capture this complexity and offers functions that fit and interpret a wide range of highly flexible models that are routinely used for single-locus landscape genetics studies but are rarely extended to estimate response functions for multiple loci. To demonstrate the package's broad functionality, we test its ability to recover landscape relationships from simulated genomic data. We also apply the package to two empirical case studies. In the first, we model genetic variation of North American balsam poplar (Populus balsamifera, Salicaceae) populations across environmental gradients. In the second case study, we recover the landscape and host drivers of feline immunodeficiency virus genetic variation in bobcats (Lynx rufus). The ability to model thousands of loci collectively and compare models from linear regression to extreme gradient boosting, within the same analytical framework, has the potential to be transformative. The MrIML framework is also extendable and not limited to modelling genetic variation; for example, it can quantify the environmental drivers of microbiomes and coinfection dynamics.

Landscape Features Fail to Explain Spatial Genetic Structure in White‐Tailed Deer Across Ohio, USA

ABSTRACTLandscape features influence wildlife movements across spatial scales and have the potential to influence the spread of disease. Chronic wasting disease (CWD) is a fatal prion disease affecting members of the family Cervidae, particularly white‐tailed deer (Odocoileus virginianus), and the first positive CWD case in a wild deer in Ohio, USA, was recorded in 2020. Landscape genetics approaches are increasingly used to better understand potential pathways for CWD spread in white‐tailed deer, but little is known about genetic structure of white‐tailed deer in Ohio. The objectives of our study were to evaluate spatial genetic structure in white‐tailed deer across Ohio and compare the support for isolation by distance (IBD) and isolation by landscape resistance (IBR) models in explaining this structure. We collected genetic data from 619 individual deer from 24 counties across Ohio during 2007–2009. We used microsatellite genotypes from 619 individuals genotyped at 11 loci and haplotypes from a 547‐base pair fragment of the mitochondrial DNA control region. We used spatial and non‐spatial genetic clustering tests to evaluate genetic structure in both types of genetic data and empirically optimized landscape resistance surfaces to compare IBD and IBR using microsatellite data. Non‐spatial genetic clustering tests failed to detect spatial genetic structure, whereas spatial genetic clustering tests indicated subtle spatial genetic structure. The IBD model consistently outperformed IBR models that included land cover, traffic volume, and streams. Our results indicated widespread genetic connectivity of white‐tailed deer across Ohio and negligible effects of landscape features. These patterns likely reflect some combination of minimal resistive effects of landscape features on white‐tail deer movement in Ohio and the effects of regional recolonization or translocation. We encourage continued CWD surveillance in Ohio, particularly in the proximity of confirmed cases. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Landscape Genetics of American Beaver in Coastal Oregon

ABSTRACTAmerican beaver (Castor canadensis) have been translocated for population restoration, reduction of human‐wildlife conflict, and enhancement of ecosystem function. Yet few studies have assessed dispersal of beaver, making it difficult to determine at what scale translocations are appropriate. Genetic studies can provide inferences about gene flow, and thus dispersal. We used a landscape genetic approach to evaluate whether landscape features influenced gene flow among beaver in the Coast Range of western Oregon, USA, using samples collected April–September 2014. We collected genetic samples from live‐captured (n = 232), road‐killed (n = 2) and trapper‐provided (n = 58) tissue samples and genotyped them at 10 microsatellite loci. We mapped records of beaver translocations into or within the study area during the twentieth century to consider the effect of those movements on genetic structure. We used population assignment tests to delimit genetic clusters, evaluated correspondence of those clusters with watershed boundaries and translocation history, and then estimated differentiation between clusters and between watersheds using model‐based and model‐free approaches. We evaluated how individual genetic differences varied with geographic distance, and investigated related pairs within clusters. We developed landscape resistance models incorporating slope, distance to water, and watershed boundaries at 2 scales, and estimated effective distances between sample locations with least cost path and circuit theoretic analyses. We evaluated the correlation of individual genetic distances with effective distances using a pseudo‐bootstrapping approach. Landscape genetic models did not explain spatial variation in genetic structure better than geographic distance, but hierarchical genetic structure corresponded with watershed boundaries and suggested influences from historical translocations. Pairwise individual genetic distances were positively correlated with geographic distances to 61 km; highly‐related pairs mostly were detected <1 km apart (median = 1.0 km, = 14.6 ± 2.3 [SE] km, n = 77). We concluded that slope and distance to water did not strongly limit dispersal and gene flow by beaver in this system, but concordance of genetic structure with watershed boundaries suggests that dispersal is more common within than between watersheds. Genetic differentiation of beaver within this topographically complex system was much greater than reported in a study at similar spatial scales in relatively flat topography. We recommend that translocation efforts of American beaver in topographically complex landscapes occur within watersheds when possible but conclude that dispersal can occur across watersheds. © 2021 The Wildlife Society. This article is a U.S. Government work and is in the public domain in the USA.

Title: priority areas for genetic conservation of Eremanthus erythropappus (DC.) MacLeish in Brazil

Eremanthus erythropappus (DC.) MacLeish, commonly known as candeia, is a threatened tree species that occurs in Seasonal Semideciduous Forests in Brazil. The tree is valued for the durability of its wood and essential oil production, from which the active agent (alpha-bisabolol) is used in pharmaceutical and cosmetic industries. Due to its high economic value, E. erythropappus has been exploited for several decades. Natural populations have been reduced, with the subsequent ecological and genetic negative impacts. We aimed to use a landscape genetics approach to identify if natural features influence the genetic diversity of E. erythropappus. In order to assess the genetic variability and provide information for the conservation of the species, genetics analyses were carried out for 200 individuals from ten natural populations of E. erythropappus. Nine ISSR primers produced 72 bands, of which 57 (79%) were polymorphic. Genetic diversity ( $${H}_{E}$$ ) was 0.30 and gene flow was 1.4 migrants per population. The Bayesian clustering model indicated the occurrence of four genetically distinct populations (K = 4). Results of AMOVA showed high genetic differentiation between populations (30.8 %) and there was positive correlation between genetic and geographic distances (r = 0.632, P = 0.001). Based on a Mantel correlation and the genetic discontinuity among populations, we recommend the implementation of four operational units to support the conservation of this species.