Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions

Genomic and Phenotypic Adaptations of Rattus tanezumi to Cold Limit Its Further Northward Expansion and Range Overlap with R. norvegicus

Global climate change has led to shifts in the distribution ranges of many terrestrial species, promoting their migration from lower altitudes or latitudes to higher ones. Meanwhile, successful invaders have developed genetic adaptations enabling the colonization of new environments. Over the past 40 years, Rattus tanezumi (RT) has expanded into northern China (Northwest and North China) from its southern origins. We studied the cold adaptation of RT and its potential for northward expansion by comparing it with sympatric Rattus norvegicus (RN), which is well adapted to cold regions. Through population genomic analysis, we revealed that the invading RT rats have split into three distinct populations: the North, Northwest, and Tibetan populations. The first two populations exhibited high genetic diversity, while the latter population showed remarkably low genetic diversity. These rats have developed various genetic adaptations to cold, arid, hypoxic, and high-UV conditions. Cold acclimation tests revealed divergent thermoregulation between RT and RN. Specifically, RT exhibited higher brown adipose tissue activity and metabolic rates than did RN. Transcriptome analysis highlighted changes in genes regulating triglyceride catabolic processes in RT, including Apoa1 and Apoa4, which were upregulated, under selection and associated with local adaptation. In contrast, RN showed changes in carbohydrate metabolism genes. Despite the cold adaptation of RT, we observed genotypic and phenotypic constraints that may limit its ability to cope with severe low temperatures farther north. Consequently, it is less likely that RT rats will invade and overlap with RN rats in farther northern regions.

Finding genes and pathways that underlie coral adaptation

Mass coral bleaching is one of the clearest threats of climate change to the persistence of marine biodiversity. Despite the negative impacts of bleaching on coral health and survival, some corals may be able to rapidly adapt to warming ocean temperatures. Thus, a significant focus in coral research is identifying the genes and pathways underlying coral heat adaptation. Here, we review state-of-the-art methods that may enable the discovery of heat-adaptive loci in corals and identify four main knowledge gaps. To fill these gaps, we describe an experimental approach combining seascape genomics with CRISPR/Cas9 gene editing to discover and validate heat-adaptive loci. Finally, we discuss how information on adaptive genotypes could be used in coral reef conservation and management strategies.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Projection of current and future distribution of adaptive genetic units in an alpine ungulate

Climate projections predict major changes in alpine environments by the end of the 21st century. To avoid climate-induced maladaptation and extinction, many animal populations will either need to move to more suitable habitats or adapt in situ to novel conditions. Since populations of a species exhibit genetic variation related to local adaptation, it is important to incorporate this variation into predictive models to help assess the ability of the species to survive climate change. Here, we evaluate how the adaptive genetic variation of a mountain ungulate-the Northern chamois (Rupicapra rupicapra)-could be impacted by future global warming. Based on genotype-environment association analyses of 429 chamois using a ddRAD sequencing approach, we identified genetic variation associated with climatic gradients across the European Alps. We then delineated adaptive genetic units and projected the optimal distribution of these adaptive groups in the future. Our results suggest the presence of local adaptation to climate in Northern chamois with similar genetic adaptive responses in geographically distant but climatically similar populations. Furthermore, our results predict that future climatic changes will modify the Northern chamois adaptive landscape considerably, with various degrees of maladaptation risk.

Responses of population structure and genomic diversity to climate change and fishing pressure in a pelagic fish

The responses of marine species to environmental changes and anthropogenic pressures (e.g., fishing) interact with ecological and evolutionary processes that are not well understood. Knowledge of changes in the distribution range and genetic diversity of species and their populations into the future is essential for the conservation and sustainable management of resources. Almaco jack (Seriola rivoliana) is a pelagic fish with high importance to fisheries and aquaculture in the Pacific Ocean. In this study, we assessed contemporary genomic diversity and structure in loci that are putatively under selection (outlier loci) and determined their potential functions. Using a combination of genotype-environment association, spatial distribution models, and demogenetic simulations, we modeled the effects of climate change (under three different RCP scenarios) and fishing pressure on the species' geographic distribution and genomic diversity and structure to 2050 and 2100. Our results show that most of the outlier loci identified were related to biological and metabolic processes that may be associated with temperature and salinity. The contemporary genomic structure showed three populations-two in the Eastern Pacific (Cabo San Lucas and Eastern Pacific) and one in the Central Pacific (Hawaii). Future projections suggest a loss of suitable habitat and potential range contractions for most scenarios, while fishing pressure decreased population connectivity. Our results suggest that future climate change scenarios and fishing pressure will affect the genomic structure and genotypic composition of S. rivoliana and lead to loss of genomic diversity in populations distributed in the eastern-central Pacific Ocean, which could have profound effects on fisheries that depend on this resource.

Molecular ecology meets systematic conservation planning

Integrative and proactive conservation approaches are critical to the long-term persistence of biodiversity. Molecular data can provide important information on evolutionary processes necessary for conserving multiple levels of biodiversity (genes, populations, species, and ecosystems). However, molecular data are rarely used to guide spatial conservation decision-making. Here, we bridge the fields of molecular ecology (ME) and systematic conservation planning (SCP) (the 'why') to build a foundation for the inclusion of molecular data into spatial conservation planning tools (the 'how'), and provide a practical guide for implementing this integrative approach for both conservation planners and molecular ecologists. The proposed framework enhances interdisciplinary capacity, which is crucial to achieving the ambitious global conservation goals envisioned for the next decade.

Understanding Local Adaptation to Prepare Populations for Climate Change

Adaptation within species to local environments is widespread in nature. Better understanding this local adaptation is critical to conserving biodiversity. However, conservation practices can rely on species’ trait averages or can broadly assume homogeneity across the range to inform management. Recent methodological advances for studying local adaptation provide the opportunity to fine-tune efforts for managing and conserving species. The implementation of these advances will allow us to better identify populations at greatest risk of decline because of climate change, as well as highlighting possible strategies for improving the likelihood of population persistence amid climate change. In the present article, we review recent advances in the study of local adaptation and highlight ways these tools can be applied in conservation efforts. Cutting-edge tools are available to help better identify and characterize local adaptation. Indeed, increased incorporation of local adaptation in management decisions may help meet the imminent demands of managing species amid a rapidly changing world.

Population genomics of a forest fungus reveals high gene flow and climate adaptation signatures

Genome sequencing of spatially distributed individuals sheds light on how evolution structures genetic variation. Populations of Phellopilus nigrolimitatus, a red-listed wood-inhabiting fungus associated with old-growth coniferous forests, have decreased in size over the last century due to a loss of suitable habitats. We assessed the population genetic structure and investigated local adaptation in P. nigrolimitatus, by establishing a reference genome and genotyping 327 individuals sampled from 24 locations in Northern Europe by RAD sequencing. We revealed a shallow population genetic structure, indicating large historical population sizes and high levels of gene flow. Despite this weak sub-structuring, two genetic groups were recognized; a western group distributed mostly in Norway and an eastern group covering most of Finland, Poland and Russia. This sub-structuring may reflect co-immigration with the main host, Norway spruce (Picea abies), into Northern Europe after the last ice age. We found evidence of low levels of genetic diversity in southwestern Finland, which has a long history of intensive forestry and urbanization. Numerous loci were significantly associated with one or more environmental factors, indicating adaptation to specific environments. These loci clustered into two groups with different associations with temperature and precipitation. Overall, our findings indicate that the current population genetic structure of P. nigrolimitatus results from a combination of gene flow, genetic drift and selection. The acquisition of similar knowledge especially over broad geographic scales, linking signatures of adaptive genetic variation to evolutionary processes and environmental variation, for other fungal species will undoubtedly be useful for assessment of the combined effects of habitat fragmentation and climate change on fungi strongly bound to old-growth forests.

New developments in the field of genomic technologies and their relevance to conservation management

Recent technological advances in the field of genomics offer conservation managers and practitioners new tools to explore for conservation applications. Many of these tools are well developed and used by other life science fields, while others are still in development. Considering these technological possibilities, choosing the right tool(s) from the toolbox is crucial and can pose a challenging task. With this in mind, we strive to inspire, inform and illuminate managers and practitioners on how conservation efforts can benefit from the current genomic and biotechnological revolution. With inspirational case studies we show how new technologies can help resolve some of the main conservation challenges, while also informing how implementable the different technologies are. We here focus specifically on small population management, highlight the potential for genetic rescue, and discuss the opportunities in the field of gene editing to help with adaptation to changing environments. In addition, we delineate potential applications of gene drives for controlling invasive species. We illuminate that the genomic toolbox offers added benefit to conservation efforts, but also comes with limitations for the use of these novel emerging techniques.

Genetic signatures of divergent selection in European beech (Fagus sylvatica L.) are associated with the variation in temperature and precipitation across its distribution range

High genetic variation and extensive gene flow may help forest trees with adapting to ongoing climate change, yet the genetic bases underlying their adaptive potential remain largely unknown. We investigated range-wide patterns of potentially adaptive genetic variation in 64 populations of European beech (Fagus sylvatica L.) using 270 SNPs from 139 candidate genes involved either in phenology or in stress responses. We inferred neutral genetic structure and processes (drift and gene flow) and performed differentiation outlier analyses and gene-environment association (GEA) analyses to detect signatures of divergent selection. Beech range-wide genetic structure was consistent with the species' previously identified postglacial expansion scenario and recolonization routes. Populations showed high diversity and low differentiation along the major expansion routes. A total of 52 loci were found to be putatively under selection and 15 of them turned up in multiple GEA analyses. Temperature and precipitation related variables were equally represented in significant genotype-climate associations. Signatures of divergent selection were detected in the same proportion for stress response and phenology-related genes. The range-wide adaptive genetic structure of beech appears highly integrated, suggesting a balanced contribution of phenology and stress-related genes to local adaptation, and of temperature and precipitation regimes to genetic clines. Our results imply a best-case scenario for the maintenance of high genetic diversity during range shifts in beech (and putatively other forest trees) with a combination of gene flow maintaining within-population neutral diversity and selection maintaining between-population adaptive differentiation.

Maximizing the effectiveness of national commitments to protected area expansion for conserving biodiversity and ecosystem carbon under climate change

Global commitments to protected area expansion should prioritize opportunities to protect climate refugia and ecosystems which store high levels of irrecoverable carbon, as key components of an effective response to biodiversity loss and climate change. The United States and Canada are responsible for one-sixth of global greenhouse gas emissions but hold extensive natural ecosystems that store globally significant above- and below-ground carbon. Canada has initiated a process of protected area network expansion in concert with efforts at reconciliation with Indigenous Peoples, and acknowledged nature-based solutions as a key aspect of climate change mitigation. The US, although not a party to global biodiversity conventions, has recently committed to protecting 30% of its extent by 2030 and achieving the UNFCCC Paris Agreement's mitigation targets. The opportunities afforded by these dual biodiversity conservation and climate commitments require coordinated national and regional policies to ensure that new protected areas maximize biodiversity-focused adaptation and nature-based mitigation opportunities. We address how global commitments can best inform national policy initiatives which build on existing agency mandates for regional planning and species conservation. Previous analyses of global conservation priorities under climate change have been tenuously linked to policy contexts of individual nations and have lacked information on refugia due to limitations of globally available datasets. Comparison and synthesis of predictions from a range of recently developed refugia metrics allow such data to inform planning despite substantial uncertainty arising from contrasting model assumptions and inputs. A case study for endangered species planning for old-forest-associated species in the US Pacific Northwest demonstrates how regional planning can be nested hierarchically within national biodiversity-focused adaptation and nature-based mitigation strategies which integrate refugia, connectivity, and ecosystem carbon metrics to holistically evaluate the role of different land designations and where carbon mitigation and protection of biodiversity's resilience to climate change can be aligned.

AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change

Background

At any particular location, frequencies of alleles that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at the population level.

Methods

The prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). The RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). Because the RDA step or CCA approach sometimes predict negative allele frequencies, the GAM step ensures that allele frequencies are in the range of 0 to 1.

Results

AlleleShift provides data sets with predicted frequencies and several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These visualizations include 'dot plot' graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), 'waffle' diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these visualizations were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplemental videos.

Availability

AlleleShift is available as an open-source R package from https://cran.r-project.org/package=AlleleShift and https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.