Applications of landscape genetics in conservation biology: concepts and challenges

Landscape genetics plays an increasingly important role in the management and conservation of species. Here, we highlight some of the opportunities and challenges in using landscape genetic approaches in conservation biology. We first discuss challenges related to sampling design and introduce several recent methodological developments in landscape genetics (analyses based on pairwise relatedness, the application of Bayesian methods, inference from landscape resistance and a shift from population-based to individual-based analyses). We then show how simulations can foster the field of landscape genetics and, finally, elaborate on technical developments in sequencing techniques that will dramatically improve our ability to study genetic variation in wild species, opening up new and unprecedented avenues for genetic analysis in conservation biology.     

The integration of 'omic' disciplines and systems biology in cattle breeding

Enormous progress has been made in the selection of animals, including cattle, for specific traits using traditional quantitative genetics approaches. Nevertheless, considerable variation in phenotypes remains unexplained, and therefore represents potential additional gain for animal production. In addition, the paradigm shift in new disciplines now being applied to animal breeding represents a powerful opportunity to prise open the 'black box' underlying the response to selection and fully understand the genetic architecture controlling the traits of interest. A move away from traditional approaches of animal breeding toward systems approaches using integrative analysis of data from the 'omic' disciplines represents a multitude of exciting opportunities for animal breeding going forward as well as providing alternatives for overcoming some of the limitations of traditional approaches such as the expressed phenotype being an imperfect predictor of the individual's true genetic merit, or the phenotype being only expressed in one gender or late in the lifetime of an animal. This review aims to discuss these opportunities from the perspective of their potential application and contribution to cattle breeding. Harnessing the potential of this paradigm shift also poses some new challenges for animal scientists - and they will also be discussed.     

Applying landscape genetics to the microbial world

Landscape genetics, which explicitly quantifies landscape effects on gene flow and adaptation, has largely focused on macroorganisms, with little attention given to microorganisms. This is despite overwhelming evidence that microorganisms exhibit spatial genetic structuring in relation to environmental variables. The increasing accessibility of genomic data has opened up the opportunity for landscape genetics to embrace the world of microorganisms, which may be thought of as ‘the invisible regulators’ of the macroecological world. Recent developments in bioinformatics and increased data accessibility have accelerated our ability to identify microbial taxa and characterize their genetic diversity. However, the influence of the landscape matrix and dynamic environmental factors on microorganism genetic dispersal and adaptation has been little explored. Also, because many microorganisms coinhabit or codisperse with macroorganisms, landscape genomic approaches may improve insights into how micro‐ and macroorganisms reciprocally interact to create spatial genetic structure. Conducting landscape genetic analyses on microorganisms requires that we accommodate shifts in spatial and temporal scales, presenting new conceptual and methodological challenges not yet explored in ‘macro’‐landscape genetics. We argue that there is much value to be gained for microbial ecologists from embracing landscape genetic approaches. We provide a case for integrating landscape genetic methods into microecological studies and discuss specific considerations associated with the novel challenges this brings. We anticipate that microorganism landscape genetic studies will provide new insights into both micro‐ and macroecological processes and expand our knowledge of species’ distributions, adaptive mechanisms and species’ interactions in changing environments.     

Conservation genetics and genomics of threatened vertebrates in China

Conservation genetics and genomics are two independent disciplines that focus on using new techniques in genetics and genomics to solve problems in conservation biology. During the past two decades, conservation genetics and genomics have experienced rapid progress. Here, we summarize the research advances in the conservation genetics and genomics of threatened vertebrates (e.g., carnivorans, primates, ungulates, cetaceans, avians, amphibians and reptiles) in China. First, we introduce the concepts of conservation genetics and genomics and their development. Second, we review the recent advances in conservation genetics research, including noninvasive genetics and landscape genetics. Third, we summarize the progress in conservation genomics research, which mainly focuses on resolving genetic problems relevant to conservation such as genetic diversity, genetic structure, demographic history, and genomic evolution and adaptation. Finally, we discuss the future directions of conservation genetics and genomics.     

Analysis of genetic diversity in a peatland specialist butterfly suggests an important role for habitat quality and small habitat patches

Understanding effects of habitat and landscape features on genetic variation is a prerequisite for the development of habitat and landscape management strategies aimed at conserving genetic diversity. While there has been considerable research on the effects of landscape structure on the genetics of populations, a recent review identified key biases in this body of work. The majority of landscape genetic studies investigate the intervening matrix’s influence on differentiation and gene flow among populations. Although characteristics of local habitat patches may be important determinants of genetic diversity, fewer studies have examined these relationships. Here we use node- and neighbourhood-based approaches to analyze correlates of genetic diversity in the bog copper (Lycaena epixanthe), a specialist butterfly endemic to temperate Nearctic peatlands that is threatened in parts of its range. Based on 190 repeatable and polymorphic amplified fragment length polymorphism loci, we found that genetic diversity was higher in habitat patches that were smaller and surrounded by more open water. Our results indicate that valuing small peatlands and preserving the surrounding water table may be important for conservation of genetic diversity in this highly specialized species. Our study highlights the importance of variables affecting habitat quality for conservation genetics.     

Perspectives of genomics for genetic conservation of livestock

Genomics provides new opportunities for conservation genetics. Conservation genetics in livestock is based on estimating diversity by pedigree relatedness and managing diversity by choosing those animals that maximize genetic diversity. Animals can be chosen as parents for the next generation, as donors of material to a gene bank, or as breeds for targeting conservation efforts. Genomics provides opportunities to estimate diversity for specific parts of the genome, such as neutral and adaptive diversity and genetic diversity underlying specific traits. This enables us to choose candidates for conservation based on specific genetic diversity (e.g. diversity of traits or adaptive diversity) or to monitor the loss of diversity without conservation. In wild animals direct genetic management, by choosing candidates for conservation as in livestock, is generally not practiced. With dense marker maps opportunities exist for monitoring relatedness and genetic diversity in wild populations, thus enabling a more active management of diversity.     

Spatiotemporal landscape genetics: Investigating ecology and evolution through space and time

Genetic time‐series data from historical samples greatly facilitate inference of past population dynamics and species evolution. Yet, although climate and landscape change are often touted as post‐hoc explanations of biological change, our understanding of past climate and landscape change influences on evolutionary processes is severely hindered by the limited application of methods that directly relate environmental change to species dynamics through time. Increased integration of spatiotemporal environmental and genetic data will revolutionize the interpretation of environmental influences on past population processes and the quantification of recent anthropogenic impacts on species, and vastly improve prediction of species responses under future climate change scenarios, yielding widespread revelations across evolutionary biology, landscape ecology and conservation genetics. This review encourages greater use of spatiotemporal landscape genetic analyses that explicitly link landscape, climate and genetic data through time by providing an overview of analytical approaches for integrating historical genetic and environmental data in five key research areas: population genetic structure, demography, phylogeography, metapopulation connectivity and adaptation. We also include a tabular summary of key methodological information, suggest approaches for mitigating the particular difficulties in applying these techniques to ancient DNA and palaeoclimate data, and highlight areas for future methodological development.     

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.     

Dealing with uncertainty in landscape genetic resistance models: a case of three co‐occurring marsupials

Landscape genetics lacks explicit methods for dealing with the uncertainty in landscape resistance estimation, which is particularly problematic when sample sizes of individuals are small. Unless uncertainty can be quantified, valuable but small data sets may be rendered unusable for conservation purposes. We offer a method to quantify uncertainty in landscape resistance estimates using multimodel inference as an improvement over single model‐based inference. We illustrate the approach empirically using co‐occurring, woodland‐preferring Australian marsupials within a common study area: two arboreal gliders (Petaurus breviceps, and Petaurus norfolcensis) and one ground‐dwelling antechinus (Antechinus flavipes). First, we use maximum‐likelihood and a bootstrap procedure to identify the best‐supported isolation‐by‐resistance model out of 56 models defined by linear and non‐linear resistance functions. We then quantify uncertainty in resistance estimates by examining parameter selection probabilities from the bootstrapped data. The selection probabilities provide estimates of uncertainty in the parameters that drive the relationships between landscape features and resistance. We then validate our method for quantifying uncertainty using simulated genetic and landscape data showing that for most parameter combinations it provides sensible estimates of uncertainty. We conclude that small data sets can be informative in landscape genetic analyses provided uncertainty can be explicitly quantified. Being explicit about uncertainty in landscape genetic models will make results more interpretable and useful for conservation decision‐making, where dealing with uncertainty is critical.     

景观遗传学：概念与方法

全球变化下的物种栖息地丧失和破碎化给生物多样性保护带来了新的问题和挑战,生物多样性保护必须由单纯的物种保护上升到栖息地景观的保护。景观遗传学是定量确定栖息地景观特征对种群遗传结构影响的一门交叉学科,在生物保护及自然保护区管理方面有巨大的潜力。从生物多样性保护的角度评述了景观结构与遗传多样性的关系,介绍了景观遗传学的基本概念,研究尺度和方法,并对景观遗传学当前的研究焦点及面临的挑战做了总结。     

鹿科动物MHC的基因组学、多态性及与性状的相关性

近年来主要组织相容性复合体(MHC)基因已经成为保护遗传学和分子生态学重要的遗传标记.鹿科动物是很多生态系统中的关键物种,也包含很多重要的经济物种和濒危物种.因此,鹿科动物的MHC研究可为种群遗传结构、进化、遗传多样性和种群生存力评估、疾病风险评估、抗病力的定向选育等领域的研究提供新的视角.本文从MHC的基因组结构、多态性,与抗病、抗寄生虫的关系,与鹿角生长的关系等方面,综述了20年来鹿科动物MHC的研究成果,并为今后的研究提出了思路.     

Breaking out of the echo chamber: missed opportunities for genetics at conservation conferences

Genetic approaches have proven useful for addressing various conservation problems, but genetics remains poorly integrated into conservation practice. Multidisciplinary conservation conferences present excellent opportunities for bridging the conservation-genetics gap and facilitating cross-disciplinary projects. We hypothesize that there is a tendency for presentations featuring genetic approaches to be siloed into approach specific sessions, creating an “echo chamber”; geneticists are left talking amongst themselves, hindering collaboration across disciplines. To test this, we reviewed abstracts from the past six Society for Conservation Biology conferences and assessed how presentations featuring genetics/genomics were distributed throughout the respective programs. We found that: the segregation of presentations featuring genetics varied widely between conferences (22–78 %); that no other method or approach was segregated to the same degree; and that the vast majority (99 %) of presentations featuring genetics had broader applications that made them appropriate for other sessions. We argue that segregating genetics at conservation conferences in this way is unhelpful and serves to strengthen the idea that genetics is not relevant to a wider conservation audience. We recommend that; (1) conference organisers endeavour to facilitate the integration of genetics into sessions based on the conservation questions addressed, rather than the methods used to address them; and (2) geneticists make the practical application of their work clear at abstract submission and during presentations. These recommendations are not novel, but our data illustrate a clear need for them to be implemented to better facilitate integration of genetic research that will benefit conservation outcomes.     

Advancing ecological understandings through technological transformations in noninvasive genetics

Noninvasive genetic approaches continue to improve studies in molecular ecology, conservation genetics and related disciplines such as forensics and epidemiology. Noninvasive sampling allows genetic studies without disturbing or even seeing the target individuals. Although noninvasive genetic sampling has been used for wildlife studies since the 1990s, technological advances continue to make noninvasive approaches among the most used and rapidly advancing areas in genetics. Here, we review recent advances in noninvasive genetics and how they allow us to address important research and management questions thanks to improved techniques for DNA extraction, preservation, amplification and data analysis. We show that many advances come from the fields of forensics, human health and domestic animal health science, and suggest that molecular ecologists explore literature from these fields. Finally, we discuss how the combination of advances in each step of a noninvasive genetics study, along with fruitful areas for future research, will continually increase the power and role of noninvasive genetics in molecular ecology and conservation genetics.     

Quantitative genetic analyses of complex behaviours in Drosophila

Behaviours are exceptionally complex quantitative traits. Sensitivity to environmental variation and genetic background, the presence of sexual dimorphism, and the widespread functional pleiotropy that is inherent in behavioural phenotypes pose daunting challenges for unravelling their underlying genetics. Drosophila melanogaster provides an attractive system for elucidating the unifying principles of the genetic architectures that drive behaviours, as genetically identical individuals can be reared rapidly in controlled environments and extensive publicly accessible genetic resources are available. Recent advances in quantitative genetic and functional genomic approaches now enable the extensive characterization of complex genetic networks that mediate behaviours in this important model organism.     

Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data

The goal of landscape genetics is to detect and explain landscape effects on genetic diversity and structure. Despite the increasing popularity of landscape genetic approaches, the statistical methods for linking genetic and landscape data remain largely untested. This lack of method evaluation makes it difficult to compare studies utilizing different statistics, and compromises the future development and application of the field. To investigate the suitability and comparability of various statistical approaches used in landscape genetics, we simulated data sets corresponding to five landscape-genetic scenarios. We then analyzed these data with eleven methods, and compared the methods based on their statistical power, type-1 error rates, and their overall ability to lead researchers to accurate conclusions about landscape-genetic relationships. Results suggest that some of the most commonly applied techniques (e.g. Mantel and partial Mantel tests) have high type-1 error rates, and that multivariate, non-linear methods are better suited for landscape genetic data analysis. Furthermore, different methods generally show only moderate levels of agreement. Thus, analyzing a data set with only one method could yield method-dependent results, potentially leading to erroneous conclusions. Based on these findings, we give recommendations for choosing optimal combinations of statistical methods, and identify future research needs for landscape genetic data analyses.     

植物景观遗传学研究进展

植物景观遗传学是新兴的景观遗传学交叉学科的一个重要研究方向。目前植物景观遗传学的研究虽落后于动物,但其在生物多样性保护方面具有的巨大潜力不可忽视。从景观特征对遗传结构、环境因素对适应性遗传变异影响两个方面,系统综述了近十年来国际上植物景观遗传学的研究焦点和研究进展,比较了植物景观遗传学与动物景观遗传学研究在研究设计和研究方法上的异同,并基于将来植物景观遗传学由对空间遗传结构的描述发展为对景观遗传效应的量化分析及预测的发展框架,具体针对目前景观特征与遗传结构研究设计的系统性差、遗传结构与景观格局在时间上的误配、适应性位点与环境变量的模糊匹配、中性遗传变异与适应性遗传变异研究的分隔、景观与遗传关系分析方法的局限等五个方面提出了研究对策。     

基于景观遗传学的滇金丝猴栖息地连接度分析

结合景观遗传学,应用最小费用距离模型对物种栖息地进行连接度分析,能够为生物多样性保护和自然保护区管理提供更加真实准确及可实践操作的指导。选取滇金丝猴这一珍稀濒危物种,结合景观遗传学,应用最小费用距离模型对其栖息地进行了连接度和潜在扩散廊道分析。并且通过连接度的分析和制图绘制出了更为准确的种群间潜在扩散廊道,确定了受人工障碍影响的廊道及敏感区域。结果表明,研究区内的5个亚群中,仅S3亚群内的5个猴群保持着较好的连接度,总体来说,各亚群内的连接度相对于各亚群间连接度保持的较好。除S3亚群中猴群间的潜在扩散廊道较为理想外,其余种群间的潜在扩散廊道均受人工斑块的影响,多数廊道被人工障碍阻断,或面临即将被阻断的情况,对于滇金丝猴的扩散交流影响较大。敏感区域多集中在中南部的3个亚群间,这些敏感区域应作为景观恢复及保护区规划的重要优先区域。