Genomic assessment of local adaptation in dwarf birch to inform assisted gene flow

Conserving Evolutionary Potential: Combining Landscape Genomics with Established Methods to Inform Plant Conservation

Biodiversity conservation requires conserving evolutionary potential-the capacity for wild populations to adapt. Understanding genetic diversity and evolutionary dynamics is critical for informing conservation decisions that enhance adaptability and persistence under environmental change. We review how emerging landscape genomic methods provide plant conservation programs with insights into evolutionary dynamics, including local adaptation and its environmental drivers. Landscape genomic approaches that explore relationships between genomic variation and environments complement rather than replace established population genomic and common garden approaches for assessing adaptive phenotypic variation, population structure, gene flow, and demography. Collectively, these approaches inform conservation actions, including genetic rescue, maladaptation prediction, and assisted gene flow. The greatest on-the-ground impacts from such studies will be realized when conservation practitioners are actively engaged in research and monitoring. Understanding the evolutionary dynamics shaping the genetic diversity of wild plant populations will inform plant conservation decisions that enhance the adaptability and persistence of species in an uncertain future.

Patterns and effects of gene flow on adaptation across spatial scales: implications for management

Gene flow can have rapid effects on adaptation and is an important evolutionary tool available when undertaking biological conservation and restoration. This tool is underused partly because of the perceived risk of outbreeding depression and loss of mean fitness when different populations are crossed. In this article, we briefly review some theory and empirical findings on how genetic variation is distributed across species ranges, describe known patterns of gene flow in nature with respect to environmental gradients, and highlight the effects of gene flow on adaptation in small or stressed populations in challenging environments (e.g., at species range limits). We then present a case study involving crosses at varying spatial scales among mountain populations of a trigger plant (Stylidium armeria: Stylidiaceae) in the Australian Alps to highlight how some issues around gene flow effects can be evaluated. We found evidence of outbreeding depression in seed production at greater geographic distances. Nevertheless, we found no evidence of maladaptive gene flow effects in likelihood of germination, plant performance (size), and performance variance, suggesting that gene flow at all spatial scales produces offspring with high adaptive potential. This case study demonstrates a path to evaluating how increasing sources of gene flow in managed wild and restored populations could identify some offspring with high fitness that could bolster the ability of populations to adapt to future environmental changes. We suggest further ways in which managers and researchers can act to understand and consider adaptive gene flow in natural and conservation contexts under rapidly changing conditions.

Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability?

Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.

Populus cathayana genome and population resequencing provide insights into its evolution and adaptation

Populus cathayana Rehder, an indigenous poplar species of ecological and economic importance, is widely distributed in a high-elevation range from southwest to northeast China. Further development of this species as a sustainable poplar resource has been hindered by a lack of genome information the at the population level. Here, we produced a chromosome-level genome assembly of P. cathayana, covering 406.55 Mb (scaffold N50 = 20.86 Mb) and consisting of 19 chromosomes, with 35 977 protein-coding genes. Subsequently, we made a genomic variation atlas of 438 wild individuals covering 36 representative geographic areas of P. cathayana, which were divided into four geographic groups. It was inferred that the Northwest China regions served as the genetic diversity centers and a population bottleneck happened during the history of P. cathayana. By genotype-environment association analysis, 947 environment-association loci were significantly associated with temperature, solar radiation, precipitation, and altitude variables. We identified local adaptation genes involved in DNA repair and UV radiation response, among which UVR8, HY5, and CUL4 had key roles in high-altitude adaptation of P. cathayana. Predictions of adaptive potential under future climate conditions showed that P. cathayana populations in areas with drastic climate change were anticipated to have greater maladaptation risk. These results provide comprehensive insights for understanding wild poplar evolution and optimizing adaptive potential in molecular breeding.

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.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Genetic and environmental drivers of migratory behavior in western burrowing owls and implications for conservation and management

Migration is driven by a combination of environmental and genetic factors, but many questions remain about those drivers. Potential interactions between genetic and environmental variants associated with different migratory phenotypes are rarely the focus of study. We pair low coverage whole genome resequencing with a de novo genome assembly to examine population structure, inbreeding, and the environmental factors associated with genetic differentiation between migratory and resident breeding phenotypes in a species of conservation concern, the western burrowing owl (Athene cunicularia hypugaea). Our analyses reveal a dichotomy in gene flow depending on whether the population is resident or migratory, with the former being genetically structured and the latter exhibiting no signs of structure. Among resident populations, we observed significantly higher genetic differentiation, significant isolation-by-distance, and significantly elevated inbreeding. Among migratory breeding groups, on the other hand, we observed lower genetic differentiation, no isolation-by-distance, and substantially lower inbreeding. Using genotype-environment association analysis, we find significant evidence for relationships between migratory phenotypes (i.e., migrant versus resident) and environmental variation associated with cold temperatures during the winter and barren, open habitats. In the regions of the genome most differentiated between migrants and residents, we find significant enrichment for genes associated with the metabolism of fats. This may be linked to the increased pressure on migrants to process and store fats more efficiently in preparation for and during migration. Our results provide a significant contribution toward understanding the evolution of migratory behavior and vital insight into ongoing conservation and management efforts for the western burrowing owl.

Achieving zero extinction for land plants

Despite the importance of plants for humans and the threats to their future, plant conservation receives far less support compared with vertebrate conservation. Plants are much cheaper and easier to conserve than are animals, but, although there are no technical reasons why any plant species should become extinct, inadequate funding and the shortage of skilled people has created barriers to their conservation. These barriers include the incomplete inventory, the low proportion of species with conservation status assessments, partial online data accessibility, varied data quality, and insufficient investment in both in and ex situ conservation. Machine learning, citizen science (CS), and new technologies could mitigate these problems, but we need to set national and global targets of zero plant extinction to attract greater support.

Small-scale genetic structure of coral populations in Palau based on whole mitochondrial genomes: Implications for future coral resilience

The ability of local populations to adapt to future climate conditions is facilitated by a balance between short range dispersal allowing local buildup of adaptively beneficial alleles, and longer dispersal moving these alleles throughout the species range. Reef building corals have relatively low dispersal larvae, but most population genetic studies show differentiation only over 100s of km. Here, we report full mitochondrial genome sequences from 284 tabletop corals (Acropora hyacinthus) from 39 patch reefs in Palau, and show two signals of genetic structure across reef scales from 1 to 55 km. First, divergent mitochondrial DNA haplotypes exist in different proportions from reef to reef, causing Phi_ST values of 0.02 (p = 0.02). Second, closely related sequences of mitochondrial Haplogroups are more likely to be co-located on the same reefs than expected by chance alone. We also compared these sequences to prior data on 155 colonies from American Samoa. In these comparisons, many Haplogroups in Palau were disproportionately represented or absent in American Samoa, and inter-regional Phi_ST = 0.259. However, we saw three instances of identical mitochondrial genomes between locations. Together, these data sets suggest two features of coral dispersal revealed by occurrence patterns in highly similar mitochondrial genomes. First, the Palau-American Samoa data suggest that long distance dispersal in corals is rare, as expected, but that it is common enough to deliver identical mitochondrial genomes across the Pacific. Second, higher than expected co-occurrence of Haplogroups on the same Palau reefs suggests greater retention of coral larvae on local reefs than predicted by many current oceanographic models of larval movement. Increased attention to local scales of coral genetic structure, dispersal, and selection may help increase the accuracy of models of future adaptation of corals and of assisted migration as a reef resilience intervention.

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.

Genomic signals of local adaptation and hybridization in Asian white birch

Disentangling the numerous processes that affect patterns of genome-wide diversity in widespread tree species has important implications for taxonomy, conservation, and forestry. Here, we investigate the population genomic structure of Asian white birch (Betula platyphylla) in China and seek to explain it in terms of hybridization, demography and adaptation. We generate whole genome sequence data from 83 individuals across the species range in China. Combining this with an existing data set for 79 European and Russian white birches, we show a clear distinction between B. pendula and B. platyphylla, which have sometimes been lumped taxonomically. Genomic diversity of B. platyphylla in north-western China and Central Russia is affected greatly by hybridization with B. pendula. Excluding these hybridized populations, B. platyphylla in China has a linear distribution from north-eastern to south-western China, along the edge of the inland mountainous region. Within this distribution, three genetic clusters are found, which we model as long diverged with subsequent episodes of gene flow. Patterns of covariation between allele frequencies and environmental variables in B. platyphylla suggest the role of natural selection in the distribution of diversity at 7609 SNPs of which 3767 were significantly differentiated among the genetic clusters. The putative adaptive SNPs are distributed throughout the genome and span 1633 genic regions. Of these genic regions, 87 were previously identified as candidates for selective sweeps in Eurasian B. pendula. We use the 7609 environmentally associated SNPs to estimate the risk of nonadaptedness for each sequenced B. platyphylla individual under a scenario of future climate change, highlighting areas where populations may be under future threat from rising temperatures.

Climate adaptation and vulnerability of foundation species in a global change hotspot

Climate change is altering species ranges, and relative abundances within ranges, as populations become differentially adapted and vulnerable to the climates they face. Understanding present species ranges, whether species harbour and exchange adaptive variants, and how variants are distributed across landscapes undergoing rapid change, is therefore crucial to predicting responses to future climates and informing conservation strategies. Such insights are nonetheless lacking for most species of conservation concern. We assess genomic patterns of neutral variation, climate adaptation and climate vulnerability (offsets in predicted distributions of putatively adaptive variants across present and future landscapes) for sister foundation species, the marine tubeworms Galeolaria caespitosa and Galeolaria gemineoa, in a sentinel region for climate change impacts. We find that species are genetically isolated despite uncovering sympatry in their ranges, show parallel and nonparallel signals of thermal adaptation on spatial scales smaller than gene flow across their ranges, and are predicted to face different risks of maladaptation under future temperatures across their ranges. Our findings have implications for understanding local adaptation in the face of gene flow, and generate spatially explicit predictions for climatic disruption of adaptation and species distributions in coastal ecosystems that could guide experimental validation and conservation planning.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Genome-Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome-environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat-based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change. "I shall endeavor to find out how nature's forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature" Alexander von Humboldt-Letter to Karl Freiesleben, June 1799.

Assessing ex situ genetic and ecogeographic conservation in a threatened but widespread oak after range-wide collecting effort

Although the genetic diversity and structure of in situ populations has been investigated in thousands of studies, the genetic composition of ex situ plant populations has rarely been studied. A better understanding of how much genetic diversity is conserved ex situ, how it is distributed among locations (e.g., botanic gardens), and what minimum sample sizes are needed is necessary to improve conservation outcomes. Here we address these issues in a threatened desert oak species, Quercus havardii Rydb. We assess the genetic, geographic, and ecological representation of 290 plants from eight ex situ locations, relative to 667 wild individuals from 35 in situ locations. We also leverage a recent dataset of >3000 samples from 11 other threatened plants to directly compare the degree of genetic conservation for species that differ in geographic range size. We found that a majority of Q. havardii genetic diversity is conserved; one of its geographic regions is significantly better conserved than the other; genetic diversity conservation of this widespread species is lower than documented for the 11 rarer taxa; genetic diversity within each garden is strongly correlated to the number of plants and number of source populations; and measures of geographic and ecological conservation (i.e., percent area and percent of ecoregions represented) were typically lower than the direct assessment of genetic diversity (i.e., percent alleles). This information will inform future seed sampling expeditions to ensure that the intraspecific diversity of threatened plants can be effectively conserved.

Plant collections for conservation and restoration: can they be adapted and adaptable?

Plant collections are important for the conservation of threatened species, and can provide material for ecological restoration. Typically we want collections to have high genetic diversity so populations founded from it are adaptable to future challenges. Sometimes, we have additional objectives for collections, such as enrichment for desirable traits controlled by adaptive alleles. We used landscape genomic datasets for two plants, Westringia fruticosa and Wilkiea huegeliana, to design collections that are genetically diverse, and that are adapted to warming climates. We characterized temperature adaptation by: (i) using the mean annual temperature of the sites of origin of the plants, and (ii) using the representation of alleles that are associated with warm temperatures. In Westringia fruticosa, there was a negative correlation, or tradeoff, between designing a collection that was both genetically diverse and adapted to warm temperatures. This tradeoff was weaker in Wilkiea huegeliana. We hypothesized this was because neutral genetic variation was strongly correlated with temperature in Westringia fruticosa, and not in Wilkiea huegeliana. Accordingly, when we shuffled the temperature data, breaking up the covariance between Westringia fruticosa genetic variation and temperature, there was a relaxation of the observed tradeoff. In sum, we explore tradeoffs between promoting genetic diversity and selecting for a specific trait in plant collections, and show that the strength of this tradeoff varies between two species. This represents a useful step towards understanding when selection will have a large cost in genetic diversity, and when it will be possible to design a collection that is both adapted and adaptable.

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.

Assessing Population Genetic Status for Designing Plant Translocations

Assisted gene flow interventions such as plant translocations are valuable complementary techniques to habitat restoration. Bringing new genetic variants can contribute to increasing genetic diversity and evolutionary resilience, counteract inbreeding depression and improve plant fitness through heterosis. Large, highly genetically variable populations are usually recommended as sources for translocation. Unfortunately, many critically endangered species only occur as small populations, which are expected to show low genetic variation, high inbreeding level, paucity of compatible mates in self-incompatible species, and increased genetic divergence. Therefore, assessment of population genetic status is required for an appropriate choice of the source populations. In this paper, we exemplify the different analyses relevant for genetic evaluation of populations combining both molecular (plastid and nuclear) markers and fitness-related quantitative traits. We assessed the genetic status of the adult generation and their seed progeny (the potential translocation founders) of small populations of Campanula glomerata (Campanulaceae), a self-incompatible insect-pollinated herbaceous species critically endangered in Belgium. Only a few small populations remain, so that the species has been part of a restoration project of calcareous grasslands implementing plant translocations. In particular, we estimated genetic diversity, inbreeding levels, genetic structure in adults and their seed progeny, recent bottlenecks, clonal extent in adults, contemporary gene flow, effective population size (Ne), and parentage, sibship and seed progeny fitness variation. Small populations of C. glomerata presented high genetic diversity, and extensive contemporary pollen flow within populations, with multiple parentage among seed progenies, and so could be good seed source candidates for translocations. As populations are differentiated from each other, mixing the sources will not only optimize the number of variants and of compatible mates in translocated populations, but also representativeness of species regional genetic diversity. Genetic diversity is no immediate threat to population persistence, but small Ne, restricted among-population gene flow, and evidence of processes leading to genetic erosion, inbreeding and inbreeding depression in the seed progeny require management measures to counteract these trends and stochastic vulnerability. Habitat restoration facilitating recruitment, flowering and pollination, reconnecting populations by biological corridors or stepping stones, and creating new populations through translocations in protected areas are particularly recommended.

Landscape Genomics in Tree Conservation Under a Changing Environment

Understanding the genetic basis of how species respond to changing environments is essential to the conservation of species. However, the molecular mechanisms of adaptation remain largely unknown for long-lived tree species which always have large population sizes, long generation time, and extensive gene flow. Recent advances in landscape genomics can reveal the signals of adaptive selection linking genetic variations and landscape characteristics and therefore have created novel insights into tree conservation strategies. In this review article, we first summarized the methods of landscape genomics used in tree conservation and elucidated the advantages and disadvantages of these methods. We then highlighted the newly developed method "Risk of Non-adaptedness," which can predict the genetic offset or genomic vulnerability of species via allele frequency change under multiple scenarios of climate change. Finally, we provided prospects concerning how our introduced approaches of landscape genomics can assist policymaking and improve the existing conservation strategies for tree species under the ongoing global changes.

Finding common ground: Toward comparable indicators of adaptive capacity of tree species to a changing climate

Adaptive capacity, one of the three determinants of vulnerability to climate change, is defined as the capacity of species to persist in their current location by coping with novel environmental conditions through acclimation and/or evolution. Although studies have identified indicators of adaptive capacity, few have assessed this capacity in a quantitative way that is comparable across tree species. Yet, such multispecies assessments are needed by forest management and conservation programs to refine vulnerability assessments and to guide the choice of adaptation measures. In this paper, we propose a framework to quantitatively evaluate five key components of tree adaptive capacity to climate change: individual adaptation through phenotypic plasticity, population phenotypic diversity as influenced by genetic diversity, genetic exchange within populations, genetic exchange between populations, and genetic exchange between species. For each component, we define the main mechanisms that underlie adaptive capacity and present associated metrics that can be used as indices. To illustrate the use of this framework, we evaluate the relative adaptive capacity of 26 northeastern North American tree species using values reported in the literature. Our results show adaptive capacity to be highly variable among species and between components of adaptive capacity, such that no one species ranks consistently across all components. On average, the conifer Picea glauca and the broadleaves Acer rubrum and A. saccharinum show the greatest adaptive capacity among the 26 species we documented, whereas the conifers Picea rubens and Thuja occidentalis, and the broadleaf Ostrya virginiana possess the lowest. We discuss limitations that arise when comparing adaptive capacity among species, including poor data availability and comparability issues in metrics derived from different methods or studies. The breadth of data required for such an assessment exemplifies the multidisciplinary nature of adaptive capacity and the necessity of continued cross-collaboration to better anticipate the impacts of a changing climate.

Prospects and limitations of genomic offset in conservation management

In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population can be self-sustaining under future alterations of its habitat or whether it may require human intervention such as protection, restoration, or assisted migration. An increasingly popular approach in this respect is the concept of genomic offset, which combines genomic and environmental data from different time points and/or locations to assess the degree of possible maladaptation to new environmental conditions. Here, we argue that the concept of genomic offset holds great potential, but an exploration of its risks and limitations is needed to use it for recommendations in conservation or assisted migration. After briefly describing the concept, we list important issues to consider (e.g., statistical frameworks, population genetic structure, migration, independent evidence) when using genomic offset or developing these methods further. We conclude that genomic offset is an area of development that still lacks some important features and should be used in combination with other approaches to inform conservation measures.

Genomic vulnerability to rapid climate warming in a tree species with a long generation time

The ongoing increase in global temperature affects biodiversity, especially in mountain regions where climate change is exacerbated. As sessile, long-lived organisms, trees are especially challenged in terms of adapting to rapid climate change. Here, we show that low rates of allele frequency shifts in Swiss stone pine (Pinus cembra) occurring near the treeline result in high genomic vulnerability to future climate warming, presumably due to the species' long generation time. Using exome sequencing data from adult and juvenile cohorts in the Swiss Alps, we found an average rate of allele frequency shift of 1.23 × 10^-2 /generation (i.e. 40 years) at presumably neutral loci, with similar rates for putatively adaptive loci associated with temperature (0.96 × 10^-2 /generation) and precipitation (0.91 × 10^-2 /generation). These recent shifts were corroborated by forward-in-time simulations at neutral and adaptive loci. Additionally, in juvenile trees at the colonisation front we detected alleles putatively beneficial under a future warmer and drier climate. Notably, the observed past rate of allele frequency shift in temperature-associated loci was decidedly lower than the estimated average rate of 6.29 × 10^-2 /generation needed to match a moderate future climate scenario (RCP4.5). Our findings suggest that species with long generation times may have difficulty keeping up with the rapid climate change occurring in high mountain areas and thus are prone to local extinction in their current main elevation range.

Revisiting the Functional Zoning Concept under Climate Change to Expand the Portfolio of Adaptation Options

Climate change is threatening our ability to manage forest ecosystems sustainably. Despite strong consensus on the need for a broad portfolio of options to face this challenge, diversified management options have yet to be widely implemented. Inspired by functional zoning, a concept aimed at optimizing biodiversity conservation and wood production in multiple-use forest landscapes, we present a portfolio of management options that intersects management objectives with forest vulnerability to better address the wide range of goals inherent to forest management under climate change. Using this approach, we illustrate how different adaptation options could be implemented when faced with impacts related to climate change and its uncertainty. These options range from establishing ecological reserves in climatic refuges, where self-organizing ecological processes can result in resilient forests, to intensive plantation silviculture that could ensure a stable wood supply in an uncertain future. While adaptation measures in forests that are less vulnerable correspond to the traditional functional zoning management objectives, forests with higher vulnerability might be candidates for transformative measures as they may be more susceptible to abrupt changes in structure and composition. To illustrate how this portfolio of management options could be applied, we present a theoretical case study for the eastern boreal forest of Canada. Even if these options are supported by solid evidence, their implementation across the landscape may present some challenges and will require good communication among stakeholders and with the public.

Disentangling the effects of geographic peripherality and habitat suitability on neutral and adaptive genetic variation in Swiss stone pine

It is generally accepted that the spatial distribution of neutral genetic diversity within a species' native range mostly depends on effective population size, demographic history, and geographic position. However, it is unclear how genetic diversity at adaptive loci correlates with geographic peripherality or with habitat suitability within the ecological niche. Using exome-wide genomic data and distribution maps of the Alpine range, we first tested whether geographic peripherality correlates with four measures of population genetic diversity at > 17,000 SNP loci in 24 Alpine populations (480 individuals) of Swiss stone pine (Pinus cembra) from Switzerland. To distinguish between neutral and adaptive SNP sets, we used four approaches (two gene diversity estimates, F_ST outlier test, and environmental association analysis) that search for signatures of selection. Second, we established ecological niche models for P. cembra in the study range and investigated how habitat suitability correlates with genetic diversity at neutral and adaptive loci. All estimates of neutral genetic diversity decreased with geographic peripherality, but were uncorrelated with habitat suitability. However, heterozygosity (H_e ) at adaptive loci based on Tajima's D declined significantly with increasingly suitable conditions. No other diversity estimates at adaptive loci were correlated with habitat suitability. Our findings suggest that populations at the edge of a species' geographic distribution harbour limited neutral genetic diversity due to demographic properties. Moreover, we argue that populations from suitable habitats went through strong selection processes, are thus well adapted to local conditions, and therefore exhibit reduced genetic diversity at adaptive loci compared to populations at niche margins.

Range-wide neutral and adaptive genetic structure of an endemic herb from Amazonian Savannas

Conserving genetic diversity in rare and narrowly distributed endemic species is essential to maintain their evolutionary potential and minimize extinction risk under future environmental change. In this study we assess neutral and adaptive genetic structure and genetic diversity in Brasilianthus carajensis (Melastomataceae), an endemic herb from Amazonian Savannas. Using RAD sequencing we identified a total of 9365 SNPs in 150 individuals collected across the species' entire distribution range. Relying on assumption-free genetic clustering methods and environmental association tests we then compared neutral with adaptive genetic structure. We found three neutral and six adaptive genetic clusters, which could be considered management units (MU) and adaptive units (AU), respectively. Pairwise genetic differentiation (F _ST) ranged between 0.024 and 0.048, and even though effective population sizes were below 100, no significant inbreeding was found in any inferred cluster. Nearly 10 % of all analysed sequences contained loci associated with temperature and precipitation, from which only 25 sequences contained annotated proteins, with some of them being very relevant for physiological processes in plants. Our findings provide a detailed insight into genetic diversity, neutral and adaptive genetic structure in a rare endemic herb, which can help guide conservation and management actions to avoid the loss of unique genetic variation.

Forest genomics: Advancing climate adaptation, forest health, productivity, and conservation

Forest ecosystems provide important ecological services and resources, from habitat for biodiversity to the production of environmentally friendly products, and play a key role in the global carbon cycle. Humanity is counting on forests to sequester and store a substantial portion of the anthropogenic carbon dioxide produced globally. However, the unprecedented rate of climate change, deforestation, and accidental importation of invasive insects and diseases are threatening the health and productivity of forests, and their capacity to provide these services. Knowledge of genetic diversity, local adaptation, and genetic control of key traits is required to predict the adaptive capacity of tree populations, inform forest management and conservation decisions, and improve breeding for productive trees that will withstand the challenges of the 21st century. Genomic approaches have well accelerated the generation of knowledge of the genetic and evolutionary underpinnings of nonmodel tree species, and advanced their applications to address these challenges. This special issue of Evolutionary Applications features 14 papers that demonstrate the value of a wide range of genomic approaches that can be used to better understand the biology of forest trees, including species that are widespread and managed for timber production, and others that are threatened or endangered, or serve important ecological roles. We highlight some of the major advances, ranging from understanding the evolution of genomes since the period when gymnosperms separated from angiosperms 300 million years ago to using genomic selection to accelerate breeding for tree health and productivity. We also discuss some of the challenges and future directions for applying genomic tools to address long-standing questions about forest trees.