Landscape Genetic Studies Research Articles

Desert landscape features influencing the microgeographic genetic structure of Nelson's pocket mouse Chaetodipus nelsoni.

Elucidating the factors that drive the genetic patterns of natural populations is key in evolutionary biology, ecology and conservation. Hence, it is crucial to understand the role that environmental features play in species genetic diversity and structure. Landscape genetics measures functional connectivity and evaluates the effects of landscape composition, configuration, and heterogeneity on microevolutionary processes. Deserts constitute one of the world's most widespread biomes and exhibit a striking heterogeneity of microhabitats, yet few landscape genetics studies have been performed with rodents in deserts. We evaluated the relationship between landscape and functional connectivity, at a microgeographic scale, of the Nelson's pocket mouse Chaetodipus nelsoni in the Mapimí Biosphere Reserve (Chihuahuan desert). We used single-nucleotide polymorphisms and characterized the landscape based on on-site environmental data and from Landsat satellite images. We identified two distinct genetic clusters shaped by elevation, vegetation and soil. High elevation group showed higher connectivity in the elevated zones (1250-1350 m), with scarce vegetation and predominantly rocky soils; whereas that of Low elevation group was at <1200 m, with denser vegetation and sandy soils. These genetic patterns are likely associated with the species' locomotion type, feeding strategy and building of burrows. Interestingly, we also identified morphological differences, where hind foot size was significantly smaller in individuals from High elevation compared to Low elevation, suggesting the possibility of ecomorphs associated with habitat differences and potential local adaptation processes, which should be explored further. These findings improve our understanding of the genetics and ecology of C. nelsoni and other desert rodents.

Same landscape, different connectivity: contrasting patterns of gene flow in two sympatric ungulates in a mountain area

Comparative landscape genetics studies provide insights on the impact of landscape elements on gene flow patterns of different species inhabiting the same geographic area. We investigated the population genetic structure of two sympatric ungulates, roe deer Capreolus capreolus and Northern chamois Rupicapra rupicapra, in a mountain area of the central Italian Alps (Trentino, northern Italy). A total of 122 chamois and 72 roe deer samples were genotyped by two species-specific panels of 11 polymorphic microsatellite loci and analyzed by aspatial and spatially explicit analyses. While the roe deer population resulted unstructured, a clear population structure was detected in chamois, with two main groups, one inhabiting the eastern and the other spread in the western part of the study area. Landscape genetics analysis confirmed these scenarios and revealed a different effect of landscape on gene flow. An IBD (Isolation-By-Distance) model best explained genetic variation in roe deer, while IBR (Isolation-By-Resistance) was found as the process underlying genetic variation patterns in chamois, suggesting arable lands, coniferous forests, watercourses, and main roads as potential barriers. Species distribution and landscape use might explain these results: roe deer mostly occupy valley floors relatively connected to each other, and their spatial behavior may promote gene flow across areas. On the other hand, chamois prefer higher elevations and their movements may be hindered by valleys, rivers, and road networks. This study highlights the different impacts of natural and anthropic landscape elements on gene flow in two sympatric species, resulting from their different ecological requirements.

Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae)

One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis (Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.

Population and landscape genetic studies in Citrus tangerina Tanaka

Population and landscape genetic studies in Citrus tangerina Tanaka

Spatial PCA and Random Forest Analyses of Spatial Patterns in Genetic Diversity of Calotropis procera

Landscape genetic study can provide data on spatial effects on the genetic structure of plants. Calotropis procera is an economically and medicinally important plant species that grows in limited regions of southern parts of Iran. Identifying genetic variability and corridor of gene flow may be used in the conservation of this valuable plant. For this reason, we used a multivariate spatial PCA (sPCA) and a machine learning approach of random forest (RF), to reveal the genetic divergence of twelve populations in Calotropis procera with respect to spatial and geographical features. sPCA analyses revealed significant isolation by distance and spatial genetic structuring at both global and local levels. RF analysis identified temperature and altitude as major spatial features affecting the genetic differentiation of these populations based on the Fst value. We also noticed the genetic differentiation of populations within a single area due to local spatial effects. However, these populations did not force a separate infraspecific taxonomic entity. The genetic connectivity graph is constructed and a gene flow corridor is suggested for these populations. Similarly, resistance surface including temperature, latitude, and soil type has been proposed for these plant species.

Landscape Genetic Analysis for the Japanese Wild Boar in the Early Expanding Stage in the Hokuriku Region of Japan.

As a contribution to improving management of the Japanese wild boar (Sus scrofa leucomystax), which has recently expanded its range and is having some negative effects on the ecosystem, we conducted a landscape genetic study using individual-based genetic analysis and multiple landscape elements to elucidate its dispersal patterns in the early stage of its expansion. Microsatellite DNA analysis of Japanese wild boars in the Hokuriku region of Japan revealed the existence of two ancestral genetic clusters, that they had migrated via different pathways, and that they were inadequately admixed. We also inferred the most suitable habitats for Japanese wild boar using MaxEnt and concluded that lower elevation and snowfall may favor the occurrence of wild boar individuals. Landscape genetic analysis indicated regional differences in Japanese wild boar dispersal patterns, according to the spatial heterogeneity of genetic features and landscape elements. On the western side of the study area, where individuals with a high frequency of one of two ancestral clusters were more abundant, significant effects of isolation by distance and resistance due to the above two landscape factors were detected, suggesting unidirectional dispersion influenced by the alpine landscape. In contrast, on the eastern side, there was indication of resistance to dispersal of individuals predominantly possessing another ancestral cluster, suggesting the influence of irregularly arranged suitable habitats due to the complexity of the mountainous terrain. Based on our findings, we conclude that Japanese wild boar dispersal patterns may be influenced by landscape elements, such as alpine mountains.

Biogeographic inferences across spatial and evolutionary scales.

The field of biogeography unites landscape genetics and phylogeography under a common conceptual framework. Landscape genetics traditionally focuses on recent-time, population-based, spatial genetics processes at small geographical scales, while phylogeography typically investigates deep past, lineage- and species-based processes at large geographical scales. Here, we evaluate the link between landscape genetics and phylogeographical methods using the western fence lizard (Sceloporus occidentalis) as a model species. First, we conducted replicated landscape genetics studies across several geographical scales to investigate how population genetics inferences change depending on the spatial extent of the study area. Then, we carried out a phylogeographical study of population structure at two evolutionary scales informed by inferences derived from landscape genetics results to identify concordance and conflict between these sets of methods. We found significant concordance in landscape genetics processes at all but the largest geographical scale. Phylogeographical results indicate major clades are restricted to distinct river drainages or distinct hydrological regions. At a more recent timescale, we find minor clades are restricted to single river canyons in the majority of cases, while the remainder of river canyons include samples from at most two clades. Overall, the broad-scale pattern implicating stream and river valleys as key features linking populations in the landscape genetics results, and high degree of clade specificity within major topographic subdivisions in the phylogeographical results, is consistent. As landscape genetics and phylogeography share many of the same objectives, synthesizing theory, models and methods between these fields will help bring about a better understanding of ecological and evolutionary processes structuring genetic variation across space and time.

Defining environmentally heterogeneous sites when faced with conservation urgency and scarce in situ data

We apply an environmental domains approach to identify environmentally heterogeneous characteristics defining a landscape matrix. We built environmental layers for national, regional, and local scales, considering the different scales studies can have. We used a numerical classification of explicit spatial layers and performed a multivariate classification. Based on the domains obtained, we mapped the landscape’s climatic heterogeneity and identified a comprehensive set of environmental variables that defined the landscape matrix at each scale. We specifically tested our approach for its suitability to define a sampling strategy for a landscape genetics study, using as focal species the rodent Heteromys pictus. Namely, from the domains obtained at the local scale, we selected sampling localities that comprised the broadest habitat heterogeneity, which we corroborated in the field. The landscape matrix thus generated was used with genetic data previously obtained for H. pictus. Our approach allowed identification of environmental variables significantly associated with dispersal (gene flow) of H. pictus individuals in their natural habitat. We demonstrate its adequacy to efficiently determine sampling localities —or landscape sites— that encompass the highest environmental heterogeneity, in explored and unexplored landscapes, enabling rapid identification of localities and their environmental characteristics where in situ information is scarce.

Landscape genetics of an endangered salt marsh endemic: Identifying population continuity and barriers to dispersal

Preserving the genetic diversity of endangered species is fundamental to their conservation and requires an understanding of genetic structure. In turn, identification of landscape features that impede gene flow can facilitate management to mitigate such obstacles and help with identifying isolated populations. We conducted a landscape genetic study of the endangered salt marsh harvest mouse (Reithrodontomys raviventris), a species endemic to the coastal marshes of the San Francisco Estuary of California. We collected and genotyped > 500 samples from across the marshes of Suisun Bay which contain the largest remaining tracts of habitat for the species. Cluster analyses and a population tree identified three geographically discrete populations. Next, we conducted landscape genetic analyses at two scales (the entire study area and across the Northern Marshes) where we tested 65 univariate models of landscape features and used the best supported to test multivariable analyses. Our analysis of the entire study area indicated that open water and elevation (> 2 m) constrained gene flow. Analysis of the Northern Marshes, where low elevation marsh habitat is more continuous, indicated that geographic distance was the only significant predictor of genetic distance at this scale. The identification of a large, connected population across Northern Marshes achieves a number of recovery targets for this stronghold of the species. The identification of landscape features that act as barriers to dispersal enables the identification of isolated and vulnerable populations more broadly across the species range, thus aiding conservation prioritization.

山地景观遗传学研究文献综述

PDF HTML阅读 XML下载 导出引用 引用提醒 山地景观遗传学研究文献综述 DOI: 10.5846/stxb202106191631 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金面上项目31970431；生态环境部生物多样性调查、观测与评估项目（2019HJ2096001006） Research progress and future outlook of mountain landscape genetics studies Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:山地生态系统是生物多样性分布与保护的热点。山地景观遗传学（Mountain Landscape Genetics）研究在山地景观尺度上野生生物的种群遗传格局及其驱动机制和影响因素，是景观遗传学（Landscape Genetics）的重要分支。山地景观遗传学研究对于深入理解物种的空间遗传结构、形成过程、物种形成与分化机制具有重要意义与价值，同时可以为珍稀濒危物种和山地生物多样性的有效保护与管理提供科学指导。为了更好地掌握目前山地景观遗传学的发展趋势与重点研究问题，为未来生物多样性与山地生态系统的保护管理提供科学参考，基于对Web of Science核心数据库和中国知网数据库的系统检索，全面汇总分析了1999-2020年山地景观遗传学领域发表的192篇英文文献与31篇中文文献。结果显示，该领域自2008年起迅速发展，截至2020年共有46个国家的研究机构发表了山地景观遗传相关研究，研究热点地区包括北美洲的落基山脉、内华达山脉、阿巴拉契亚山脉，欧洲的阿尔卑斯山脉、比利牛斯山脉，以及亚洲的喜马拉雅-横断山脉。研究对象类群涵盖真菌、植物、节肢动物、脊椎动物，其中脊椎动物是研究发表最多的类群，占发表文献总数的62.0%；脊椎动物中，又以对哺乳类（占脊椎动物发表文献总数的52.9%）与两栖类（23.5%）的研究最多。目前主要的研究方向包括：（1）识别山地景观中的基因流路径或阻碍；（2）量化山地景观特征对种群遗传结构时空变化的影响。中国是发表山地景观遗传学文章数量最多的亚洲国家，近十年来相关研究发展迅速，研究类群以植物（占在中国发表文献总数的62.3%）与脊椎动物（35.8%）为主，对脊椎动物的研究中以两栖动物为最多（占所有脊椎动物发文数量的52.6%），研究区域主要集中在喜马拉雅-横断山脉与秦岭。本文进一步对目前山地景观遗传学研究中存在的空缺及未来重点关注问题提出建议。 Abstract:Mountain ecosystems are hotspots of biodiversity distribution and conservation. Mountain landscape genetics is an important branch of the subject Landscape Genetics, which studies the genetic patterns of wild populations, their underlining mechanisms and influencing factors at the mountain landscape scale. Mountain landscape genetics research is of great significance for in-depth understanding of the formation of species’ spatial genetic structure, speciation and differentiation mechanism, and can provide important guidance for the effective conservation and management of rare and endangered species and mountain biodiversity. To better understand the development trend and key research issues in the field of mountain landscape genetics, and to provide scientific reference for protection and management of biodiversity and mountain ecosystems in the future, we systematically reviewed relevant studies retrieved from the core database of Web of Science and China National Knowledge Infrastructure (CNKI). A total of 192 English and 31 Chinese literatures in the field of mountain landscape genetics published from 1999 to 2020 were summarized and analyzed. The results showed that the field has been developing rapidly since 2008, with numerous research institutions from 46 nations involved in these published studies. The geographical research hotspots included the Rockies, Sierra Nevada, and Appalachians in North America, the Alps and Pyrenees in Europe, and the Himalaya-Hengduan Mountains in Asia. The studied taxa included fungi, plants, arthropods and vertebrates, where vertebrates were the most studied taxon accounting for 62.0% of the total number of published English articles. Among the vertebrates, mammals (accounting for 52.9% the total number of vertebrate articles) and amphibians (23.5%) were the most studied taxa. Current research directions of mountain landscape genetics mainly include: (1) identifying paths or barriers of gene flow in the mountain landscapes; and (2) quantifying the effects of mountain landscape characteristics on the temporal and spatial variations of population genetic structure. Of all Asian countries, China has published the largest number of articles on mountain landscape genetics. Research on mountain landscape genetics in China has been rapidly advancing in the past decade, with plants (accounting for 62.3% the total number of Chinese studies) and vertebrates (35.8%) being the focal taxa. The largest number of vertebrate studies were conducted on amphibians (accounting for 52.6% the total number of vertebrate publications). Himalayas and Qinling Mountains were the focal mountainous regions in China. In this review, we also provide suggestions about the gaps existing in mountain landscape genetics and the key research issues to be addressed for current and future studies. 参考文献 相似文献 引证文献

Species-landscape interactions drive divergent population trajectories in four forest-dependent Afromontane forest songbird species within a biodiversity hotspot in South Africa.

Species confined to naturally fragmented habitats may exhibit intrinsic population complexity which may challenge interpretations of species response to anthropogenic landscape transformation. In South Africa, where native forests are naturally fragmented, forest‐dependent birds have undergone range declines since 1992, most notably among insectivores. These insectivores appear sensitive to the quality of natural matrix habitats, and it is unknown whether transformation of the landscape matrix has disrupted gene flow in these species. We undertook a landscape genetics study of four forest‐dependent insectivorous songbirds across southeast South Africa. Microsatellite data were used to conduct a priori optimization of landscape resistance surfaces (land cover, rivers and dams, and elevation) using cost‐distances along least‐cost pathway (LCP), and resistance distances (IBR). We detected pronounced declines in effective population sizes over the past two centuries for the endemic forest specialist Cossypha dichroa and Batis capensis, alongside recent gene flow disruption in B. capensis, C. dichroa and Pogonocichla stellata. Landscape resistance modelling showed both native forest and dense thicket configuration facilitates gene flow in P. stellata, B. capensis and C. dichroa. Facultative dispersal of P. stellata through dense thicket likely aided resilience against historic landscape transformation, whereas combined forest‐thicket degradation adversely affected the forest generalist B. capensis. By contrast, Phylloscopus ruficapilla appears least reliant upon landscape features to maintain gene flow and was least impacted by anthropogenic landscape transformation. Collectively, gene flow in all four species is improved at lower elevations, along river valleys, and riparian corridors— where native forest and dense thicket better persist. Consistent outperformance of LCP over IBR land‐cover models for P. stellata, B. capensis and C. dichroa demonstrates the benefits of wildlife corridors for South African forest‐dependent bird conservation, to ameliorate the extinction debts from past and present anthropogenic forest exploitation.

Effect of the landscape on functional and spatial connectivity in Magnolia cubensis (Magnoliaceae) in two mountain massifs of Cuba

Landscape features impact gene flow and the spatial patterns of genetic variation between populations of a species. Because many Magnoliaceae species occur in fragmented and highly disturbed landscapes, the family provide an excellent model for landscape genetic studies. This research focuses on the subspecies and subpopulations of Magnolia cubensis and aims to: (1) compare the genetic diversity between the different subspecies and their subpopulations, (2) search for patterns between the spatial and genetic distance, (3) quantify the functional connectivity and (4) assess the structural connectivity of the landscape. This study employs 21 microsatellite markers to quantify the genetic diversity, complemented with seven landscape characteristics of the Guamuhaya and Sierra Maestra massifs in Cuba. Magnolia cubensis subsp. acunae does not have a well-defined spatial genetic pattern: there is no evidence of isolation by distance or spatial autocorrelation and the little genetic differentiation between the two subpopulations does not reflect the characteristics of the landscape that separates them or the cost values to cross it. Magnolia cubensis subsp. cubensis presents evidence of isolation by distance and the autocorrelation analyses indicate that the approximate scale of the genetic neighborhood is between 35 and 40 km. There is a marked genetic structure with probability values that indicate the existence of three genetic groups. Large genetic differentiation was only found between Gran Piedra and the other subpopulations, which reflects low gene flow. Our results support the recognition of these subspecies at the species level. We define one evolutionary significant unit in Magnolia cubensis subsp. acunae and two evolutionary significant units in Magnolia cubensis subsp. cubensis. These results must be combined with ecological, social and distribution data, in order to obtain a more accurate and realistic perspective of the conservation management strategies for these taxa.

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.

Genomic Sequence Analysis of Methicillin- and Carbapenem-Resistant Bacteria Isolated from Raw Sewage.

ABSTRACTAntibiotic resistance is one of the largest threats facing global health. Wastewater treatment plants are well-known hot spots for interaction between diverse bacteria, genetic exchange, and antibiotic resistance. Nonpathogenic bacteria theoretically act as reservoirs of antibiotic resistance subsequently transferring antibiotic resistance genes to pathogens, indicating that evolutionary processes occur outside clinical settings and may drive patterns of drug-resistant infections. We isolated and sequenced 100 bacterial strains from five wastewater treatment plants to analyze regional dynamics of antibiotic resistance in the California Central Valley. The results demonstrate the presence of a wide diversity of pathogenic and nonpathogenic bacteria, with an arithmetic mean of 5.1 resistance genes per isolate. Forty-three percent of resistance genes were located on plasmids, suggesting that large levels of gene transfer between bacteria that otherwise may not co-occur are facilitated by wastewater treatment. One of the strains detected was a Bacillus carrying pX01 and pX02 anthrax-like plasmids and multiple drug resistance genes. A correlation between resistance genes and taxonomy indicates that taxon-specific evolutionary studies may be useful in determining and predicting patterns of antibiotic resistance. Conversely, a lack of geographic correlation may indicate that landscape genetic studies to understand the spread of antibiotic resistance genes should be carried out at broader scales. This large data set provides insights into how pathogenic and nonpathogenic bacteria interact in wastewater environments and the resistance genes which may be horizontally transferred between them. This can help in determining the mechanisms leading to the increasing prevalence of drug-resistant infections observed in clinical settings.IMPORTANCE The reasons for the increasing prevalence of antibiotic-resistant infections are complex and associated with myriad clinical and environmental processes. Wastewater treatment plants operate as nexuses of bacterial interaction and are known hot spots for genetic exchange between bacteria, including antibiotic resistance genes. We isolated and sequenced 100 drug-resistant bacteria from five wastewater treatment plants in California’s Central Valley, characterizing widespread gene sharing between pathogens and nonpathogens. We identified a novel, multiresistant Bacillus carrying anthrax-like plasmids. This empirical study supports the likelihood of evolutionary and population processes in the broader environment affecting the prevalence of clinical drug-resistant infections and identifies several taxa that may operate as reservoirs and vectors of antibiotic resistance genes.

Can We Compare Effect Size of Spatial Genetic Structure Between Studies and Species Using Moran Eigenvector Maps?

As the field of landscape genetics is progressing toward comparative empirical studies and meta-analysis, it is important to know how best to compare the strength of spatial genetic structure between studies and species. Moran’s Eigenvector Maps are a promising method that does not make an assumption of isolation-by-distance in a homogeneous environment but can discern cryptic structure that may result from multiple processes operating in heterogeneous landscapes. MEMgene uses spatial filters from Moran’s Eigenvector Maps as predictor variables to explain variation in a genetic distance matrix, and it returns adjusted R2 as a measure of the amount of genetic variation that is spatially structured. However, it is unclear whether, and under which conditions, this value can be used to compare the degree of spatial genetic structure (effect size) between studies. This study addresses the fundamental question of comparability at two levels: between independent studies (meta-analysis mode) and between species sampled at the same locations (comparative mode). We used published datasets containing 9,900 haploid, biallelic, neutral loci simulated on a quasi-continuous, square landscape under four demographic scenarios (island model, isolation-by-distance, expansion from one or two refugia). We varied the genetic resolution (number of individuals and loci) and the number of random sampling locations. We considered two measures of effect size, the MEMgene adjusted R2 and multivariate Moran’s I, which is related to Moran’s Eigenvector Maps. Both metrics were highly sensitive to the number of locations, even when using standardized effect sizes, SES, and the number of individuals sampled per location, but not to the number of loci. In comparative mode, using the same Moran Eigenvector Maps for all species, even those with missing values at some sampling locations, reduced bias due to the number of locations under isolation-by-distance (stationary process) but increased it under expansion from one or two refugia (non-stationary process). More robust measures of effect size need to be developed before the strength of spatial genetic structure can be accurately compared, either in a meta-analysis of independent empirical studies or within a comparative, multispecies landscape genetic study.

Primate landscape genetics: A review and practical guide.

Landscape genetics is an emerging field that integrates population genetics, landscape ecology, and spatial statistics to investigate how geographical and environmental features and evolutionary processes such as gene flow, genetic drift, and selection structure genetic variation at both the population and individual levels, with implications for ecology, evolution, and conservation biology. Despite being particularly well suited for primatologists, this method is currently underutilized. Here, we synthesize the current state of research on landscape genetics in primates. We begin by outlining how landscape genetics has been used to disentangle the drivers of diversity, followed by a review of how landscape genetic methods have been applied to primates. This is followed by a section highlighting special considerations when applying the methods to primates, and a practical guide to facilitate further landscape genetics studies using both existing and de novo datasets. We conclude by exploring future avenues of inquiry that could be facilitated by recent developments as well as underdeveloped applications of landscape genetics to primates.

Spatial genetic structure and landscape connectivity in black bears: Investigating the significance of using different land cover datasets and classifications in landscape genetics analyses.

Landscape genetic analyses allow detection of fine‐scale spatial genetic structure (SGS) and quantification of effects of landscape features on gene flow and connectivity. Typically, analyses require generation of resistance surfaces. These surfaces characteristically take the form of a grid with cells that are coded to represent the degree to which landscape or environmental features promote or inhibit animal movement. How accurately resistance surfaces predict association between the landscape and movement is determined in large part by (a) the landscape features used, (b) the resistance values assigned to features, and (c) how accurately resistance surfaces represent landscape permeability. Our objective was to evaluate the performance of resistance surfaces generated using two publicly available land cover datasets that varied in how accurately they represent the actual landscape. We genotyped 365 individuals from a large black bear population (Ursus americanus) in the Northern Lower Peninsula (NLP) of Michigan, USA at 12 microsatellite loci, and evaluated the relationship between gene flow and landscape features using two different land cover datasets. We investigated the relative importance of land cover classification and accuracy on landscape resistance model performance. We detected local spatial genetic structure in Michigan's NLP black bears and found roads and land cover were significantly correlated with genetic distance. We observed similarities in model performance when different land cover datasets were used despite 21% dissimilarity in classification between the two land cover datasets. However, we did find the performance of land cover models to predict genetic distance was dependent on the way the land cover was defined. Models in which land cover was finely defined (i.e., eight land cover classes) outperformed models where land cover was defined more coarsely (i.e., habitat/non‐habitat or forest/non‐forest). Our results show that landscape genetic researchers should carefully consider how land cover classification changes inference in landscape genetic studies.

Effects of natural and anthropogenic features on functional connectivity of anurans: a review of landscape genetics studies in temperate, subtropical and tropical species

AbstractHabitat loss, overexploitation, the presence of invasive species, climate change and the proliferation of diseases continue to put at risk anuran species that represent 90% of all amphibians. Biphasic life cycle, habitat specialization to oviposit and forage, low dispersal abilities, and permeable skin make anurans particularly susceptible to the effect of landscape composition and configuration on their capacity to move through the landscape (connectivity). Limited connectivity can result in reduced gene flow, low genetic variation and high genetic structuring. Therefore, identifying landscape elements that promote or limit the dispersal of anurans is fundamental to propose conservation plans that allow maintaining areas that enhance connectivity to assure the evolutionary potential of the species by preserving genetic diversity. Here, we reviewed studies evaluating the effect of natural and anthropogenic elements of the landscape on gene flow across temperate, tropical and subtropical landscapes. Our results suggest that roads have the strongest negative effect on connectivity resistance in anurans from temperate regions. Urbanization, fragmentation, and land cover change into agriculture and grasslands are other anthropogenic landscape elements that provide resistance to connectivity in anurans worldwide. In temperate and tropical regions, rivers are the most important natural element negatively affecting connectivity, having a stronger effect in the tropics. Contrary, streams and forests cover promote connectivity in all regions. We provide a review of the growing progress of landscape genetics in this group of vulnerable organisms and highlight the importance of considering this research field for the conservation of the threatened ecosystems that anurans inhabit.

A Conceptual Framework for Designing Phylogeography and Landscape Genetic Studies

Phylogeography and landscape genetics combines molecular genetics with geography, ecology, and evolutionary biology to develop an understanding of patterns in the spatial distributions of biological diversity. The two disciplines bring together advanced molecular and geospatial tools providing a critical insight on issues that are vital to the field of biogeography, including how and where biodiversity arises, how species respond to changing climates, and how and where conservation efforts should be focused. Although two fields can be considered as merely the fusion of classic biogeography with genetics and genomics, yet both differ in their level of spatial, temporal and system scales along with analytical tools utilized. At the same time, the unique combination of different scientific disciplines and methodical approaches pose a challenge to many researchers who wish to conduct a study at the interface of phylogeography and landscape genetics. A synthesis of the phylogeographic literature presented in this review solely based on the examination of studies that deals with Quaternary climatic oscillations and species’ range dynamics across the Palearctic. This review provides a comprehensive overview of the conceptual framework and recent methodological advances in two disciplines and highlights main points to be taken into account while designing a study that represents a window to the past and an opportunity to predict the fate of species due to ongoing climatic and landscape change.

Different processes shape the patterns of divergence in the nuclear and chloroplast genomes of a relict tree species in East Asia.

Isolation by spatial distance (IBD), environment (IBE), and historical climatic instability (IBI) are three common processes assessed in phylogeographic and/or landscape genetic studies. However, the relative contributions of these three processes with respect to spatial genetic patterns have seldom been compared. Moreover, whether the relative contribution differs in different regions or when assessed using different genetic markers has rarely been reported. Lindera obtusiloba has been found to have two sister genetic clades of chloroplast (cpDNA) and nuclear microsatellite (nSSR), both of which show discontinuous distribution in northern and southern East Asia. In this study, we used the Mantel test and multiple matrix regression with randomization (MMRR) to determine the relative contributions of IBD, IBE, and IBI with respect to L. obtusiloba populations. Independent Mantel tests and MMRR calculations were conducted for two genetic data sets (cpDNA and nSSR) and for different regions (the overall species range, and northern and southern subregions of the range). We found a significant IBI pattern in nSSR divergence for all assessed regions, whereas no clear IBI pattern was detected with respect to cpDNA. In contrast, significant (or marginal) divergent IBD patterns were detected for cpDNA in all regions, whereas although a significant IBE was apparent with respect to the overall range, the effect was not detected in the two subregions. The differences identified in nSSR and cpDNA population divergence may be related to differences in the heredity and ploidy of the markers. Compared with the southern region, the northern region showed less significant correlation patterns, which may be related to the shorter population history and restricted population range. The findings of this study serve to illustrate that comparing between markers or regions can contribute to gaining a better understanding the population histories of different genomes or within different regions of a species' range.