An integrated framework to identify wildlife populations under threat from climate change

Climate change will lead to range shifts and genetic diversity losses of dung beetles in the Gobi Desert and Mongolian Steppe

Desertification is known to be a major threat to biodiversity, yet our understanding of the consequent decline in biodiversity remains insufficient. Here, we predicted climate change-induced range shifts and genetic diversity losses in three model dung beetles: Colobopterus erraticus, Cheironitis eumenes, and Gymnopleurus mopsus, distributed across the Gobi Desert and Mongolian Steppe, areas known for desertification. Phylogeographic analyses of mitochondrial COI sequences and species distribution modeling, based on extensive field investigations spanning 14 years, were performed. Species confined to a single biome were predicted to contract and shift their distribution in response to climate change, whereas widespread species was predicted to expand even if affected by range shifts. We indicated that all species are expected to experience significant haplotype losses, yet the presence of high singleton frequencies and low genetic divergence across geographic configurations and lineages mitigate loss of genetic diversity. Notably, Cheironitis eumenes, a desert species with low genetic diversity, appears to be the most vulnerable to climate change due to the extensive degradation in the Gobi Desert. This is the first study to predict the response of insects to desertification in the Gobi Desert. Our findings highlight that dung beetles in the Gobi Desert and Mongolian Steppe might experience high rates of occupancy turnover and genetic loss, which could reshuffle the species composition.

Evaluation of species thermal sensitivity with individual-based physiological performance

Ignoring intraspecific variations can prevent us from accurately assessing species' thermal sensitivity to global warming. Individual-based physiological performance provides a feasible solution to depict species' thermal sensitivity using a bottom-up approach. We measured the cardiac performance of intertidal bivalves (1159 individuals from multiple populations of six bivalves), determined the upper thermal limit of each individual, calculated the proportions of individuals suffering sublethal/lethal heat stress, and mapped sensitive regions to high temperatures. Results showed that high inter-individual variations of physiological performance existed in levels of populations and species, and species' thermal sensitivity was positively related to the intraspecific variations of heat tolerance. This bottom-up approach scaled up from individual, population to species emphasizes the importance of individual-based physiology performance in assessing thermal sensitivity across different hierarchical levels and enables better evaluating and forecasting of species responses to global warming.

Ecological impacts of climate change on Arctic marine megafauna

Global warming affects the Arctic more than any other region. Mass media constantly relay apocalyptic visions of climate change threatening Arctic wildlife, especially emblematic megafauna such as polar bears, whales, and seabirds. Yet, we are just beginning to understand such ecological impacts on marine megafauna at the scale of the Arctic. This knowledge is geographically and taxonomically biased, with striking deficiencies in the Russian Arctic and strong focus on exploited species such as cod. Beyond a synthesis of scientific advances in the past 5 years, we provide ten key questions to be addressed by future work and outline the requested methodology. This framework builds upon long-term Arctic monitoring inclusive of local communities whilst capitalising on high-tech and big data approaches.

Bat responses to climate change: a systematic review

Understanding how species respond to climate change is key to informing vulnerability assessments and designing effective conservation strategies, yet research efforts on wildlife responses to climate change fail to deliver a representative overview due to inherent biases. Bats are a species-rich, globally distributed group of organisms that are thought to be particularly sensitive to the effects of climate change because of their high surface-to-volume ratios and low reproductive rates. We systematically reviewed the literature on bat responses to climate change to provide an overview of the current state of knowledge, identify research gaps and biases and highlight future research needs. We found that studies are geographically biased towards Europe, North America and Australia, and temperate and Mediterranean biomes, thus missing a substantial proportion of bat diversity and thermal responses. Less than half of the published studies provide concrete evidence for bat responses to climate change. For over a third of studied bat species, response evidence is only based on predictive species distribution models. Consequently, the most frequently reported responses involve range shifts (57% of species) and changes in patterns of species diversity (26%). Bats showed a variety of responses, including both positive (e.g. range expansion and population increase) and negative responses (range contraction and population decrease), although responses to extreme events were always negative or neutral. Spatial responses varied in their outcome and across families, with almost all taxonomic groups featuring both range expansions and contractions, while demographic responses were strongly biased towards negative outcomes, particularly among Pteropodidae and Molossidae. The commonly used correlative modelling approaches can be applied to many species, but do not provide mechanistic insight into behavioural, physiological, phenological or genetic responses. There was a paucity of experimental studies (26%), and only a small proportion of the 396 bat species covered in the examined studies were studied using long-term and/or experimental approaches (11%), even though they are more informative about the effects of climate change. We emphasise the need for more empirical studies to unravel the multifaceted nature of bats' responses to climate change and the need for standardised study designs that will enable synthesis and meta-analysis of the literature. Finally, we stress the importance of overcoming geographic and taxonomic disparities through strengthening research capacity in the Global South to provide a more comprehensive view of terrestrial biodiversity responses to climate change.

Genomic analysis of indigenous goats in Southwest Asia reveals evidence of ancient adaptive introgression related to desert climate

Understanding how evolutionary pressures related to climate change have shaped the current genetic background of domestic animals is a fundamental pursuit of biology. Here, we generated whole-genome sequencing data from native goat populations in Iraq and Pakistan. Combined with previously published data on modern, ancient (Late Neolithic to Medieval periods), and wild Capra species worldwide, we explored the genetic population structure, ancestry components, and signatures of natural positive selection in native goat populations in Southwest Asia (SWA). Results revealed that the genetic structure of SWA goats was deeply influenced by gene flow from the eastern Mediterranean during the Chalcolithic period, which may reflect adaptation to gradual warming and aridity in the region. Furthermore, comparative genomic analysis revealed adaptive introgression of the KITLG locus from the Nubian ibex ( C. nubiana) into African and SWA goats. The frequency of the selected allele at this locus was significantly higher among goat populations located near northeastern Africa. These results provide new insights into the genetic composition and history of goat populations in the SWA region.

Genic distribution modelling predicts adaptation of the bank vole to climate change

The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geographical and temporal variation in climate. Projections to future climatic conditions suggest a change in relative climatic suitability that would result in HbS being displaced by HbF in northern Britain. This would facilitate local adaptation to future climate—without Hb displacement, populations in northern Britain would likely be suboptimally adapted because their Hb would not match local climatic conditions. Our study shows how pre-existing physiological differences can influence the adaptive capacity of species to climate change.

Haemoglobin variation in British bank voles combined with climate models predict future regional allelic replacement reflecting capacity for adaptation to climate change.

Applying novel connectivity networks to wood turtle populations to provide comprehensive conservation management strategies for species at risk

Genetic diversity within and among populations is frequently used in prioritization processes to rank populations based on their vulnerability or distinctiveness, however, connectivity and gene flow are rarely considered within these frameworks. Using a wood turtle (Glyptemys insculpta) population graph, we introduce BRIDES as a new tool to evaluate populations for conservation purpose without focusing solely on individual nodes. BRIDES characterizes different types of shortest paths among the nodes of a subgraph and compares the shortest paths among the same nodes in a complete network. The main objectives of this study were to (1) introduce a BRIDES selection process to assist conservation biologists in the prioritization of populations, and (2) use different centrality indices and node removal statistics to compare BRIDES results and assess gene flow among wood turtle populations. We constructed six population subgraphs and used a stepwise selection algorithm to choose the optimal number of additional nodes, representing different populations, required to maximize network connectivity under different weighting schemes. Our results demonstrate the robustness of the BRIDES selection process for a given scenario, while inconsistencies were observed among node-based metrics. Results showed repeated selection of certain wood turtle populations, which could have not been predicted following only genetic diversity and distinctiveness estimation, node-based metrics and node removal analysis. Contrary to centrality measures focusing on static networks, BRIDES allowed for the analysis of evolving networks. To our knowledge, this study is the first to apply graph theory for turtle conservation genetics. We show that population graphs can reveal complex gene flow dynamics and population resiliency to local extinction. As such, BRIDES offers an interesting complement to node-based metrics and node removal to better understand the global processes at play when addressing population prioritization frameworks.

Modelling Genetic Benefits and Financial Costs of Integrating Biobanking into the Captive Management of Koalas

Simple Summary

Managed wildlife breeding faces high costs and genetic diversity challenges associated with caring for small populations. Biobanking (freezing of sex cells and tissues for use in assisted breeding) and associated reproductive technologies could help alleviate these issues in koala captive management by enhancing retention of genetic diversity in captive-bred animals and lowering program costs through reductions in the size of the required live captive colonies. Australia’s zoos and wildlife hospitals provide rare opportunities to refine and cost-effectively integrate these tools into conservation outcomes for koalas due to extensive already-existing infrastructure, technical expertise, and captive animals.

Abstract

Zoo and wildlife hospital networks are set to become a vital component of Australia’s contemporary efforts to conserve the iconic and imperiled koala (Phascolarctos cinereus). Managed breeding programs held across zoo-based networks typically face high economic costs and can be at risk of adverse genetic effects typical of unavoidably small captive colonies. Emerging evidence suggests that biobanking and associated assisted reproductive technologies could address these economic and genetic challenges. We present a modelled scenario, supported by detailed costings, where these technologies are optimized and could be integrated into conservation breeding programs of koalas across the established zoo and wildlife hospital network. Genetic and economic modelling comparing closed captive koala populations suggest that supplementing them with cryopreserved founder sperm using artificial insemination or intracytoplasmic sperm injection could substantially reduce inbreeding, lower the required colony sizes of conservation breeding programs, and greatly reduce program costs. Ambitious genetic retention targets (maintaining 90%, 95% and 99% of source population heterozygosity for 100 years) could be possible within realistic cost frameworks, with output koalas suited for wild release. Integrating biobanking into the zoo and wildlife hospital network presents a cost-effective and financially feasible model for the uptake of these tools due to the technical and research expertise, captive koala colonies, and ex situ facilities that already exist across these networks.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (N_e). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Delineating Functional Corridors Linking Leopard Habitat in the Eastern and Western Cape, South Africa

Natural landscapes are increasingly fragmented due to human activity. This contributes to isolation and inadequate gene flow among wildlife populations. These threats intensify where populations are already low, and gene flow is compromised. Ensuring habitat connectivity despite transformed landscapes can mitigate these risks. Leopards are associated with high levels of biodiversity and are the last widely occurring, free-roaming apex predator in South Africa. Although highly adaptable, leopard survival is reduced by human-caused mortality and habitat destruction. We aimed to assess the connectivity of leopard habitat in the Eastern Cape and Western Cape, South Africa. We predicted leopard habitat by correlating GPS data from 31 leopards to environmental features that included human-associated and natural landscapes. We used circuit theory to delineate corridors linking known leopard populations. Finally, using camera traps, we tested whether five predicted corridors were used by leopards. Leopard habitat was strongly correlated to moderate slopes and areas of natural land-cover and plantations, highlighting mountainous areas as important habitat with high connectivity probability. While most habitat patches showed some level of connectivity, leopards avoided highly transformed landscapes, potentially isolating some populations. Where corridors are not functional, active conservation measures for species connectivity becomes important.

Seeing the Forest for the trees: Assessing genetic offset predictions from Gradient Forest

Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF‐predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic “population genetic” model with a single environmentally adapted locus; and (3) a polygenic “quantitative genetic” model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.

Land use and life history constrain adaptive genetic variation and reduce the capacity for climate change adaptation in turtles

BACKGROUND

Rapid anthropogenic climate change will require species to adapt to shifting environmental conditions, with successful adaptation dependent upon current patterns of genetic variation. While landscape genomic approaches allow for exploration of local adaptation in non-model systems, most landscape genomics studies of adaptive capacity are limited to exploratory identification of potentially important functional genes, often without a priori expectations as to the gene functions that may be most important for climate change responses. In this study, we integrated targeted sequencing of genes of known function and genotyping of single-nucleotide polymorphisms to examine spatial, environmental, and species-specific patterns of potential local adaptation in two co-occuring turtle species: the Blanding's turtle (Emydoidea blandingii) and the snapping turtle (Chelydra serpentina).

RESULTS

We documented divergent patterns of spatial clustering between neutral and putatively adaptive genetic variation in both species. Environmental associations varied among gene regions and between species, with stronger environmental associations detected for genes involved in stress response and for the more specialized Blanding's turtle. Land cover appeared to be more important than climate in shaping spatial variation in functional genes, indicating that human landscape alterations may affect adaptive capacity important for climate change responses.

CONCLUSIONS

Our study provides evidence that responses to climate change will be contingent on species-specific adaptive capacity and past history of exposure to human land cover change.

Genome-wide analysis reveals associations between climate and regional patterns of adaptive divergence and dispersal in American pikas

Understanding the role of adaptation in species' responses to climate change is important for evaluating the evolutionary potential of populations and informing conservation efforts. Population genomics provides a useful approach for identifying putative signatures of selection and the underlying environmental factors or biological processes that may be involved. Here, we employed a population genomic approach within a space-for-time study design to investigate the genetic basis of local adaptation and reconstruct patterns of movement across rapidly changing environments in a thermally sensitive mammal, the American pika (Ochotona princeps). Using genotypic data at 49,074 single-nucleotide polymorphisms (SNPs), we analyzed patterns of genome-wide diversity, structure, and migration along three independent elevational transects located at the northern extent (Tweedsmuir South Provincial Park, British Columbia, Canada) and core (North Cascades National Park, Washington, USA) of the Cascades lineage. We identified 899 robust outlier SNPs within- and among-transects. Of those annotated to genes with known function, many were linked with cellular processes related to climate stress including ATP-binding, ATP citrate synthase activity, ATPase activity, hormone activity, metal ion-binding, and protein-binding. Moreover, we detected evidence for contrasting patterns of directional migration along transects across geographic regions that suggest an increased propensity for American pikas to disperse among lower elevation populations at higher latitudes where environments are generally cooler. Ultimately, our data indicate that fine-scale demographic patterns and adaptive processes may vary among populations of American pikas, providing an important context for evaluating biotic responses to climate change in this species and other alpine-adapted mammals.

The evolutionary genomics of species' responses to climate change

Climate change is a threat to biodiversity. One way that this threat manifests is through pronounced shifts in the geographical range of species over time. To predict these shifts, researchers have primarily used species distribution models. However, these models are based on assumptions of niche conservatism and do not consider evolutionary processes, potentially limiting their accuracy and value. To incorporate evolution into the prediction of species' responses to climate change, researchers have turned to landscape genomic data and examined information about local genetic adaptation using climate models. Although this is an important advancement, this approach currently does not include other evolutionary processes-such as gene flow, population dispersal and genomic load-that are critical for predicting the fate of species across the landscape. Here, we briefly review the current practices for the use of species distribution models and for incorporating local adaptation. We next discuss the rationale and theory for considering additional processes, reviewing how they can be incorporated into studies of species' responses to climate change. We summarize with a conceptual framework of how manifold layers of information can be combined to predict the potential response of specific populations to climate change. We illustrate all of the topics using an exemplar dataset and provide the source code as potential tutorials. This Perspective is intended to be a step towards a more comprehensive integration of population genomics with climate change science.

Distinct interspecific and intraspecific vulnerability of coastal species to global change

Characterising and predicting species responses to anthropogenic global change is one of the key challenges in contemporary ecology and conservation. The sensitivity of marine species to climate change is increasingly being described with forecasted species distributions, yet these rarely account for population level processes such as genomic variation and local adaptation. This study compares inter- and intraspecific patterns of biological composition to determine how vulnerability to climate change, and its environmental drivers, vary across species and populations. We compare species trajectories for three ecologically important southern African marine invertebrates at two time points in the future, both at the species level, with correlative species distribution models, and at the population level, with gradient forest models. Reported range shifts are species-specific and include both predicted range gains and losses. Forecasted species responses to climate change are strongly influenced by changes in a suite of environmental variables, from sea surface salinity and sea surface temperature, to minimum air temperature. Our results further suggest a mismatch between future habitat suitability (where species can remain in their ecological niche) and genomic vulnerability (where populations retain their genomic composition), highlighting the inter- and intraspecific variability in species' sensitivity to global change. Overall, this study demonstrates the importance of considering species and population level climatic vulnerability when proactively managing coastal marine ecosystems in the Anthropocene.

The role of neutral and adaptive genomic variation in population diversification and speciation in two ground squirrel species of conservation concern

Understanding the neutral (demographic) and adaptive processes leading to the differentiation of species and populations is a critical component of evolutionary and conservation biology. In this context, recently diverged taxa represent a unique opportunity to study the process of genetic differentiation. Northern and southern Idaho ground squirrels (Urocitellus brunneus - NIDGS, and U. endemicus - SIDGS, respectively) are a recently diverged pair of sister species that have undergone dramatic declines in the last 50 years and are currently found in metapopulations across restricted spatial areas with distinct environmental pressures. Here we genotyped single-nucleotide polymorphisms (SNPs) from buccal swabs with restriction site-associated DNA sequencing (RADseq). With these data we evaluated neutral genetic structure at both theinter- and intraspecific level, and identified putatively adaptive SNPs using population structure outlier detection and genotype-environment association (GEA) analyses. At the interspecific level, we detected a clear separation between NIDGS and SIDGS, and evidence for adaptive differentiation putatively linked to torpor patterns. At the intraspecific level, we found evidence of both neutral and adaptive differentiation. For NIDGS, elevation appears to be the main driver of adaptive differentiation, while neutral variation patterns match and expand information on the low connectivity between some populations identified in previous studies using microsatellite markers. For SIDGS, neutral substructure generally reflected natural geographic barriers, while adaptive variation reflected differences in land cover and temperature, as well as elevation. These results clearly highlight the roles of neutral and adaptive processes for understanding the complexity of the processes leading to species and population differentiation, which can have important conservation implications in susceptible and threatened species.

Building a bridge between adaptive capacity and adaptive potential to understand responses to environmental change

Adaptive capacity is a topic at the forefront of environmental change research with roots in both social, ecological, and evolutionary science. It is closely related to the evolutionary biology concept of adaptive potential. In this systematic literature review, we: (1) summarize the history of these topics and related fields; (2) assess relationship(s) between the concepts among disciplines and the use of the terms in climate change research, and evaluate methodologies, metrics, taxa biases, and the geographic scale of studies; and (3) provide a synthetic conceptual framework to clarify concepts. Bibliometric analyses revealed the terms have been used most frequently in conservation and evolutionary biology journals, respectively. There has been a greater growth in studies of adaptive potential than adaptive capacity since 2001, but a greater geographical extent of adaptive capacity studies. Few studies include both, and use is often superficial. Our synthesis considers adaptive potential as one process contributing to adaptive capacity of complex systems, notes "sociological" adaptive capacity definitions include actions aimed at desired outcome (i.e., policies) as a system driver whereas "biological" definitions exclude such drivers, and suggests models of adaptive capacity require integration of evolutionary and social-ecological system components.

Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment

The conservation field is experiencing a rapid increase in the amount, variety, and quality of spatial data that can help us understand species movement and landscape connectivity patterns. As interest grows in more dynamic representations of movement potential, modelers are often limited by the capacity of their analytic tools to handle these datasets. Technology developments in software and high-performance computing are rapidly emerging in many fields, but uptake within conservation may lag, as our tools or our choice of computing language can constrain our ability to keep pace. We recently updated Circuitscape, a widely used connectivity analysis tool developed by Brad McRae and Viral Shah, by implementing it in Julia, a high-performance computing language. In this initial re-code (Circuitscape 5.0) and later updates, we improved computational efficiency and parallelism, achieving major speed improvements, and enabling assessments across larger extents or with higher resolution data. Here, we reflect on the benefits to conservation of strengthening collaborations with computer scientists, and extract examples from a collection of 572 Circuitscape applications to illustrate how through a decade of repeated investment in the software, applications have been many, varied, and increasingly dynamic. Beyond empowering continued innovations in dynamic connectivity, we expect that faster run times will play an important role in facilitating co-production of connectivity assessments with stakeholders, increasing the likelihood that connectivity science will be incorporated in land use decisions.

Toward reliable habitat suitability and accessibility models in an era of multiple environmental stressors

Global biodiversity declines, largely driven by climate and land-use changes, urge the development of transparent guidelines for effective conservation strategies. Species distribution modeling (SDM) is a widely used approach for predicting potential shifts in species distributions, which can in turn support ecological conservation where environmental change is expected to impact population and community dynamics. Improvements in SDM accuracy through incorporating intra- and interspecific processes have boosted the SDM field forward, but simultaneously urge harmonizing the vast array of SDM approaches into an overarching, widely adoptable, and scientifically justified SDM framework. In this review, we first discuss how climate warming and land-use change interact to govern population dynamics and species' distributions, depending on species' dispersal and evolutionary abilities. We particularly emphasize that both land-use and climate change can reduce the accessibility to suitable habitat for many species, rendering the ability of species to colonize new habitat and to exchange genetic variation a crucial yet poorly implemented component of SDM. We then unite existing methodological SDM practices that aim to increase model accuracy through accounting for multiple global change stressors, dispersal, or evolution, while shifting our focus to model feasibility. We finally propose a roadmap harmonizing model accuracy and feasibility, applicable to both common and rare species, particularly those with poor dispersal abilities. This roadmap (a) paves the way for an overarching SDM framework allowing comparison and synthesis of different SDM studies and (b) could advance SDM to a level that allows systematic integration of SDM outcomes into effective conservation plans.

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

BACKGROUND

As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species' potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare putative environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis).

RESULTS

Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus. Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus, but not for C. punctatus.

CONCLUSION

The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses may be better predictors of evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change.

A comprehensive landscape genomics approach for seed sourcing strategies in landscapes under varying degrees of habitat disturbance

As most ecosystems around the world are threatened by anthropogenic degradation and climate change, there is an increasing urgency to implement restoration strategies aiming at ensuring ecosystem self-sustainability and resilience. An initial step towards that goal relies on selecting the most suitable seed sources for a successful revegetation, which can be extremely challenging in highly degraded landscapes. The most common seed sourcing strategy is to select local seeds because it is assumed that plants experience strong adaptations to their natal sites. An alternative strategy is the selection of climate-adapted genotypes to future conditions. While considering future climatic projections is important to account for spatial shifts in climate to inform assisted gene flow and translocations, to restore highly degraded landscapes we need a comprehensive approach that first accounts for species adaptations to current at-site environmental conditions. In this issue of Molecular Ecology Resources, Carvalho et al. present a novel landscape genomics framework to identify the most appropriate seed sourcing strategy for moderately and highly degraded sites by integrating genotype, phenotype and environmental data in a spatially explicit context for two native plant species with potential to help restore iron-rich Amazonian savannas. This framework is amenable to be applicable and adapted to a broad range of restoration initiatives, as the dichotomy between focusing on the current or future climatic conditions should depend on the goals and environmental circumstances of each restoration site.

Signatures of local adaptation in the spatial genetic structure of the ascidian Pyura chilensis along the southeast Pacific coast

The highly heterogeneous Humboldt Current System (HCS) and the 30°S transition zone on the southeast Pacific coast, represent an ideal scenario to test the influence of the environment on the spatial genomic structure in marine near-shore benthic organisms. In this study, we used seascape genomic tools to evaluate the genetic structure of the commercially important ascidian Pyura chilensis, a species that exhibits a low larval transport potential but high anthropogenic dispersal. A recent study in this species recorded significant genetic differentiation across a transition zone around 30°S in putatively adaptive SNPs, but not in neutral ones, suggesting an important role of environmental heterogeneity in driving genetic structure. Here, we aim to understand genomic-oceanographic associations in P. chilensis along the Southeastern Pacific coast using two combined seascape genomic approaches. Using 149 individuals from five locations along the HCS, a total of 2,902 SNPs were obtained by Genotyping-By-Sequencing, of which 29–585 were putatively adaptive loci, depending on the method used for detection. In adaptive loci, spatial genetic structure was better correlated with environmental differences along the study area (mainly to Sea Surface Temperature, upwelling-associated variables and productivity) than to the geographic distance between sites. Additionally, results consistently showed the presence of two groups, located north and south of 30°S, which suggest that local adaptation processes seem to allow the maintenance of genomic differentiation and the spatial genomic structure of the species across the 30°S biogeographic transition zone of the Humboldt Current System, overriding the homogenizing effects of gene flow.

Conserving on the edge: genetic variation and structure in northern populations of the endangered plant Dracocephalum ruyschiana L. (Lamiaceae)

Loss of biodiversity is accelerating, including the loss of genetic diversity. Conservation of small, isolated populations may be important, as they can provide valuable contributions to overall genetic variation and long-term viability of species. Furthermore, such populations may play an essential role in adaptation to new environments following changes in e.g. land-use and climate. Dracocephalum ruyschiana is a threatened plant species throughout its European distribution, but 25% of the European populations are situated within Norway. Therefore, the species has its own action plan in Norway, which includes demographic monitoring. However, this monitoring does not cover genetic variation nor is the selection of monitored populations based on genetic differentiation, therefore this fundamental level of biodiversity is overlooked. We analyzed 43 sites using 96 SNPs developed for D. ruyschiana, to investigate whether the monitored populations cover the genetic variation and differentiation found within the Norwegian distribution. The results show structuring and differentiation between populations and indicate that there are at least four distinct genetic groups, of which only two are covered extensively by current demographic monitoring. We suggest that two sites representing the two other genetic groups should be included in the national monitoring program to better conserve the genetic variation found in the Norwegian population of D. ruyschiana. Overall, our results highlight the importance of an integrated, interdisciplinary framework to better monitor and conserve biodiversity at several levels.

Local thermal adaptation and limited gene flow constrain future climate responses of a marine ecosystem engineer

Rising ocean temperatures and extreme temperature events have precipitated declines and local extinctions in many marine species globally, but patterns of loss are often uneven across species ranges for reasons that are poorly understood. Knowledge of the extent of local adaptation and gene flow may explain such patterns and help predict future trajectories under scenarios of climate change. We test the extent to which local differentiation in thermal tolerance is influenced by gene flow and local adaptation using a widely distributed intertidal seaweed (Hormosira banksii) from temperate Australia. Population surveys across ~2,000 km of the species range revealed strong genetic structuring at regional and local scales (global F ST = 0.243) reflecting extremely limited gene flow, while common garden experiments (14-day exposures to 15, 18, 21°C) revealed strong site differences in early development and mortality in response to elevated temperature. Embryos from many sites spanning a longitudinal thermal gradient showed suppressed development and increased mortality to elevated water temperatures, but populations originating from warmer and more variable thermal environments tended to be less susceptible to warming. Notably, there was significant local-scale variation in the thermal responses of embryos within regions which was corroborated by the finding of small-scale genetic differences. We expect the observed genetic and phenotypic differentiation to lead to uneven responses to warming sea surface temperatures in this important marine foundation species. The study highlights the challenges of predicting species responses to thermal stress and the importance of management strategies that incorporate evolutionary potential for "climate-proofing" marine ecosystems.

Climate-associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps

Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming is predicted to induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could impede the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a double-digest restriction-site-associated DNA (ddRAD) sequencing approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. A redundancy analysis (RDA)-derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north-western and south-eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings allowed identifying populations at risk for F. sylvatica in the Alps, which could be helpful for future management plans.

Dramatic decline of northern bat Eptesicus nilssonii in Sweden over 30 years

We monitored northern bat Eptesicus nilssonii (Keyserling & Blasius, 1839) acoustically along a 27 km road transect at weekly intervals in 1988, 1989 and 1990, and again in 2016 and 2017. The methodology of data collection and the transect were the same throughout, except that the insect-attracting mercury-vapour street-lights along parts of the road were replaced by sodium lights between the two survey periods. Counts along sections of the transect with and without street-lights were analysed separately. The frequency of bat encounters in unlit sections showed an average decline of 3.0% per year, corresponding to a reduction of 59% between 1988 and 2017. Sections with street-lights showed an 85% decline over the same period (6.3% per year). The decline represents a real reduction in the abundance of bats rather than an artefact of changed distribution of bats away from roads. Our study conforms with another long-term survey of the same species on the Baltic island of Gotland. Our results agree with predictions based on climate change models. They also indicate that the decline was caused directly by the disuse of the insect-attracting mercury-vapour street-lights, which may have resulted in lower availability of preferred prey (moths). In the 1980s, E. nilssonii was considered the most common bat in Sweden, but the subsequent decline would rather qualify it for vulnerable or endangered status in the national Red List of Threatened Species.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

Distribution and Management of Nutria (Myocastor coypus) Populations in South Korea

In 2014, the South Korean government initiated the “Nutria Eradication Project” to actively manage and control populations of nutria, an invasive alien species that threatens national biodiversity. In the present study, we examined domestic nutria habitats in 2014 to 2018 and analyzed spatial shifts in habitat distribution to develop management policies and eradication strategies for the South Korean Ministry of Environment. A total of 27,487 nutria individuals were captured over five years upon the initiation of the eradication project. We found that the number of habitat tracks decreased from 1510 in 19 administrative districts in 2014 to 176 in 14 districts in 2018. We examined the distribution of nutria habitat tracks and found a northwestward shift at an average angle of 313.9° and 46,656.9 m. This distribution shift prompted improvements in control policies focused on nutria capture to suppress rodent movement and shifting distributions. We redefined the spatial scope of our control regions accordingly and established isolated environments in each region to prevent further spread. Additionally, resource management was focused in areas showing habitat expansion. Overall, we observed an estimated 54% decrease in nutria habitat tracks from 2016 to 2017. Our results have since been enacted in government policies and provide a basis for establishing flexible strategies for effectively controlling nutria habitats and populations. In 2017, the South Korean government allocated additional funds for research and for the development of further control strategies working toward the project’s goals.

Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections

Forecasts of species vulnerability and extinction risk under future climate change commonly ignore local adaptations despite their importance for determining the potential of populations to respond to future changes. We present an approach to assess the impacts of global climate change on biodiversity that takes into account adaptive genetic variation and evolutionary potential. We show that considering local climatic adaptations reduces range loss projections but increases the potential for competition between species. Our findings suggest that failure to account for within-species variability can result in overestimation of future biodiversity losses. Therefore, it is important to identify the climate-adaptive potential of populations and to increase landscape connectivity between populations to enable the spread of adaptive genetic variation.

Local adaptations can determine the potential of populations to respond to environmental changes, yet adaptive genetic variation is commonly ignored in models forecasting species vulnerability and biogeographical shifts under future climate change. Here we integrate genomic and ecological modeling approaches to identify genetic adaptations associated with climate in two cryptic forest bats. We then incorporate this information directly into forecasts of range changes under future climate change and assessment of population persistence through the spread of climate-adaptive genetic variation (evolutionary rescue potential). Considering climate-adaptive potential reduced range loss projections, suggesting that failure to account for intraspecific variability can result in overestimation of future losses. On the other hand, range overlap between species was projected to increase, indicating that interspecific competition is likely to play an important role in limiting species’ future ranges. We show that although evolutionary rescue is possible, it depends on a population’s adaptive capacity and connectivity. Hence, we stress the importance of incorporating genomic data and landscape connectivity in climate change vulnerability assessments and conservation management.

A review of the major threats and challenges to global bat conservation

Bats are an ecologically and taxonomically diverse group accounting for roughly a fifth of mammalian diversity worldwide. Many of the threats bats face (e.g., habitat loss, bushmeat hunting, and climate change) reflect the conservation challenges of our era. However, compared to other mammals and birds, we know significantly less about the population status of most bat species, which makes prioritizing and planning conservation actions challenging. Over a third of bat species assessed by the International Union for Conservation of Nature (IUCN) are considered threatened or data deficient, and well over half of the species have unknown or decreasing population trends. That equals 988 species, or 80% of bats assessed by IUCN, needing conservation or research attention. Delivering conservation to bat species will require sustained efforts to assess population status and trends and address data deficiencies. Successful bat conservation must integrate research and conservation to identify stressors and their solutions and to test the efficacy of actions to stabilize or increase populations. Global and regional networks that connect researchers, conservation practitioners, and local stakeholders to share knowledge, build capacity, and prioritize and coordinate research and conservation efforts, are vital to ensuring sustainable bat populations worldwide.

Porous barriers? Assessment of gene flow within and among sympatric long-eared bat species

Species are the basic units for measuring biodiversity and for comprehending biological interactions. Yet, their delineation is often contentious, especially in groups that are both diverse and phenotypically conservative. Three cryptic species of long-eared bats, Plecotus auritus, P. austriacus, and P. macrobullaris, co-occur over extensive areas of Western Europe. The latter is a fairly recent discovery, questioning the overall diversity of the entire Plecotus complex. Yet, high morphological and acoustic similarities compromise the reliable identification of long-eared bats in the field. We postulate that such extensive phenotypic overlap, along with the recurrent observation of morphologically intermediate individuals, may hide rampant interspecific hybridization. Based on a geographic sampling centered on areas of sympatry in the Alps and Corsica, we assessed the level of reproductive isolation of these three Plecotus species with mitochondrial and nuclear markers, looking at both inter- and intraspecific genetic population structuring. No sign of hybridization was detected between these three species that appear well separated biologically. Genetic structuring of populations, however, reflected different species-specific responses to environmental connectivity, that is, to the presence of orographic or sea barriers. While the Alpine range and the Ligurian Sea coincided with sharp genetic discontinuities in P. macrobullaris and P. austriacus, the more ubiquitous P. auritus showed no significant population structuration. There were clear phylogeographic discrepancies between microsatellite and mitochondrial markers at the intraspecific level, however, which challenges the reliance on simple barcoding approaches for the delineation of sound conservation units.

Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa

Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 F ST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.

An integrated framework to identify wildlife populations under threat from climate change

Climate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population-level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype-environment association analysis, we identify potential climate-adaptive SNPs in our genomic data set and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore, a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.