Demography and environment modulate the effects of genetic diversity on extinction risk in a butterfly metapopulation

Linking genetic diversity to extinction is a common goal in genomic studies. Recently, a debate has arisen regarding the importance of genetic variation in conservation as some studies have failed to find associations between genome-wide genetic diversity and extinction risk. However, only rarely are genetic diversity and fitness measured together in the wild, and typically demographic history and environment are ignored. It is therefore difficult to infer whether a lack of an association is real or obscured by confounding factors. To address these shortcomings, we analyzed genetic data from 7,501 individuals with extinction data from 279 meadows and mortality of 1,742 larval nests in a butterfly metapopulation. We found a strong negative association between genetic diversity and extinction when considering only heterozygosity in models. However, this association disappeared when accounting for ecological covariates, suggesting a confounding between demography and genetics and a more complex role for heterozygosity in extinction risk. Modeling interactions between heterozygosity and demographic variables revealed that associations between extinction and heterozygosity were context-dependent. For example, extinction declined with increasing heterozygosity in large, but not currently small populations, although negative associations between heterozygosity, extinction, and mortality were detected in small populations with a recent history of decline. We conclude that low genetic diversity is an important predictor of extinction, predicting >25% increase in extinction beyond ecological factors in certain contexts. These results highlight that inferences about the importance of genetic diversity for population viability should not rely on genomic data alone but require investments in obtaining demographic and environmental data from natural populations.

Competitive interactions affect introgression and population viability amidst maladaptive hybridization

The deliberate release of captive-bred individuals, the accidental escape of domesticated strains, or the invasion of closely related conspecifics into wild populations can all lead to introgressive hybridization, which poses a challenge for conservation and wildlife management. Rates of introgression and the magnitude of associated demographic impacts vary widely across ecological contexts. However, the reasons for this variation remain poorly understood. One rarely considered phenomenon in this context is soft selection, wherein relative trait values determine success in intraspecific competition for a limiting resource. Here we develop an eco-genetic model explicitly focussed on understanding the influence of such competitive interactions on the eco-evolutionary dynamics of wild populations experiencing an influx of foreign/domesticated individuals. The model is applicable to any taxon that experiences natural or human-mediated inputs of locally maladapted genotypes ('intrusion'), in addition to phenotype-dependent competition for a limiting resource (e.g. breeding sites, feeding territories). The effects of both acute and chronic intrusion depended strongly on the relative competitiveness of intruders versus locals. When intruders were competitively inferior, density-dependent regulation limited their reproductive success (ability to compete for limited spawning sites), which prevented strong introgression or population declines from occurring. In contrast, when intruders were competitively superior, this amplified introgression and led to increased maladaptation of the admixed population. This had negative consequences for population size and population viability. The results were sensitive to the intrusion level, the magnitude of reproductive excess, trait heritability and the extent to which intruders were maladapted relative to locals. Our findings draw attention to under-appreciated interactions between phenotype-dependent competitive interactions and maladaptive hybridization, which may be critical to determining the impact captive breeding programmes and domesticated escapees can have on otherwise self-sustaining wild populations.

Genomics and conservation: Guidance from training to analyses and applications

Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here.

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.

Admixture mapping and selection scans identify genomic regions associated with stomatal patterning and disease resistance in hybrid poplars

Variation in fitness components can be linked in some cases to variation in key traits. Metric traits that lie at the intersection of development, defense, and ecological interactions may be expected to experience environmental selection, informing our understanding of evolutionary and ecological processes. Here, we use quantitative genetic and population genomic methods to investigate disease dynamics in hybrid and non-hybrid populations. We focus our investigation on morphological and ecophysiological traits which inform our understanding of physiology, growth, and defense against a pathogen. In particular, we investigate stomata, microscopic pores on the surface of a leaf that regulate gas exchange during photosynthesis and are sites of entry for various plant pathogens. Stomatal patterning traits were highly predictive of disease risk. Admixture mapping identified a polygenic basis of disease resistance. Candidate genes for stomatal and disease resistance map to the same genomic regions and experienced positive selection. Genes with functions to guard cell homeostasis, the plant immune system, components of constitutive defenses, and growth-related transcription factors were identified. Our results indicate positive selection acted on candidate genes for stomatal patterning and disease resistance, potentially acting in concert to structure their variation in naturally formed backcrossing hybrid populations.

A polygenic basis for birth weight in a wild population of red deer (Cervus elaphus)

The genetic architecture of traits under selection has important consequences for the response to selection and potentially for population viability. Early QTL mapping studies in wild populations have reported loci with large effect on trait variation. However, these results are contradicted by more recent genome-wide association analyses, which strongly support the idea that most quantitative traits have a polygenic basis. This study aims to re-evaluate the genetic architecture of a key morphological trait, birth weight, in a wild population of red deer (Cervus elaphus), using genomic approaches. A previous study using 93 microsatellite and allozyme markers and linkage mapping on a kindred of 364 deer detected a pronounced QTL on chromosome 21 explaining 29% of the variance in birth weight, suggesting that this trait is partly controlled by genes with large effects. Here, we used data for more than 2,300 calves genotyped at >39,000 SNP markers and two approaches to characterise the genetic architecture of birth weight. First, we performed a genome-wide association (GWA) analysis, using a genomic relatedness matrix to account for population structure. We found no SNPs significantly associated with birth weight. Second, we used genomic prediction to estimate the proportion of variance explained by each SNP and chromosome. This analysis confirmed that most genetic variance in birth weight was explained by loci with very small effect sizes. Third, we found that the proportion of variance explained by each chromosome was slightly positively correlated with its size. These three findings highlight a highly polygenic architecture for birth weight, which contradicts the previous QTL study. These results are probably explained by the differences in how associations are modelled between QTL mapping and GWA. Our study suggests that models of polygenic adaptation are the most appropriate to study the evolutionary trajectory of this trait.

The evolution of white-tailed jackrabbit camouflage in response to past and future seasonal climates

The genetic basis of adaptive traits has rarely been used to predict future vulnerability of populations to climate change. We show that light versus dark seasonal pelage in white-tailed jackrabbits (Lepus townsendii) tracks snow cover and is primarily determined by genetic variation at endothelin receptor type B (EDNRB), corin serine peptidase (CORIN), and agouti signaling protein (ASIP). Winter color variation was associated with deeply divergent alleles at these genes, reflecting selection on both ancestral and introgressed variation. Forecasted reductions in snow cover are likely to induce widespread camouflage mismatch. However, simulated populations with variation for darker winter pelage are predicted to adapt rapidly, providing a trait-based genetic framework to facilitate evolutionary rescue. These discoveries demonstrate how the genetic basis of climate change adaptation can inform conservation.

Inbreeding depression explains killer whale population dynamics

Understanding the factors that cause endangered populations to either grow or decline is crucial for preserving biodiversity. Conservation efforts often address extrinsic threats, such as environmental degradation and overexploitation, that can limit the recovery of endangered populations. Genetic factors such as inbreeding depression can also affect population dynamics but these effects are rarely measured in the wild and thus often neglected in conservation efforts. Here we show that inbreeding depression strongly influences the population dynamics of an endangered killer whale population, despite genomic signatures of purging of deleterious alleles via natural selection. We find that the 'Southern Residents', which are currently endangered despite nearly 50 years of conservation efforts, exhibit strong inbreeding depression for survival. Our population models suggest that this inbreeding depression limits population growth and predict further decline if the population remains genetically isolated and typical environmental conditions continue. The Southern Residents also had more inferred homozygous deleterious alleles than three other, growing, populations, further suggesting that inbreeding depression affects population fitness. These results demonstrate that inbreeding depression can substantially limit the recovery of endangered populations. Conservation actions focused only on extrinsic threats may therefore fail to account for key intrinsic genetic factors that also limit population growth.

Dissecting the loci underlying maturation timing in Atlantic salmon using haplotype and multi-SNP based association methods

Characterizing the role of different mutational effect sizes in the evolution of fitness-related traits has been a major goal in evolutionary biology for a century. Such characterization in a diversity of systems, both model and non-model, will help to understand the genetic processes underlying fitness variation. However, well-characterized genetic architectures of such traits in wild populations remain uncommon. In this study, we used haplotype-based and multi-SNP Bayesian association methods with sequencing data for 313 individuals from wild populations to test the mutational composition of known candidate regions for sea age at maturation in Atlantic salmon (Salmo salar). We detected an association at five loci out of 116 candidates previously identified in an aquaculture strain with maturation timing in wild Atlantic salmon. We found that at four of these five loci, variation explained by the locus was predominantly driven by a single SNP suggesting the genetic architecture of this trait includes multiple loci with simple, non-clustered alleles and a locus with potentially more complex alleles. This highlights the diversity of genetic architectures that can exist for fitness-related traits. Furthermore, this study provides a useful multi-SNP framework for future work using sequencing data to characterize genetic variation underlying phenotypes in wild populations.

Modeling minimum viable population size with multiple genetic problems of small populations

An important goal for conservation is to define minimum viable population (MVP) sizes for long-term persistence of a species. There is increasing evidence of the role of genetics in population extinction; thus, conservation practitioners are starting to consider the effects of deleterious mutations (DM), in particular the effects of inbreeding depression on fitness. We sought to develop methods to account for genetic problems other than inbreeding depression in MVP estimates, quantify the effect of the interaction of multiple genetic problems on MVP sizes, and find ways to reduce the arbitrariness of time and persistence probability thresholds in MVP analyses. To do so, we developed ecoevolutionary quantitative models to track population size and levels of genetic diversity. We assumed a biallelic multilocus genome with loci under single or multiple, interacting genetic forces. We included mutation-selection-drift balance (for loci with DM) and 3 forms of balancing selection for loci for which variation is lost through genetic drift. We defined MVP size as the lowest population size that avoids an ecoevolutionary extinction vortex. For populations affected by only balancing selection, MVP size decreased rapidly as mutation rates increased. For populations affected by mutation-selection-drift balance, the MVP size increased rapidly. In addition, MVP sizes increased rapidly as the number of loci increased under the same or different selection mechanisms until even arbitrarily large populations could not survive. In the case of fixed number of loci under selection, interaction of genetic problems did not always increase MVP sizes. To further enhance understanding about interaction of genetic problems, there is need for more empirical studies to reveal how different genetic processes interact in the genome.

Genomics facilitates evaluation and monitoring of McCloud River Redband Trout (Oncorhynchus mykiss stonei)

The McCloud River Redband Trout (MRRT; Oncorhynchus mykiss stonei) is a unique subspecies of rainbow trout that inhabits the isolated Upper McCloud River of Northern California. A major threat to MRRT is introgressive hybridization with non-native rainbow trout from historical stocking and contemporary unauthorized introductions. To help address this concern, we collected RAD-sequencing data on 308 total individuals from MRRT and other California O. mykiss populations and examined population structure using Principal Component and admixture analyses. Our results are consistent with previous studies; we found that populations of MRRT in Sheepheaven, Swamp, Edson, and Moosehead creeks are nonintrogressed. Additionally, we saw no evidence of introgression in Dry Creek, and suggest further investigation to determine if it can be considered a core MRRT conservation population. Sheepheaven Creek was previously thought to be the sole historical lineage of MRRT, but our analysis identified three: Sheepheaven, Edson, and Dry creeks, all of which should be preserved. Finally, we discovered diagnostic and polymorphic SNP markers for monitoring introgression and genetic diversity in MRRT. Collectively, our results provide a valuable resource for the conservation and management of MRRT.

How does genetic architecture affect eco-evolutionary dynamics? A theoretical perspective

Recent studies have revealed the importance of feedbacks between contemporary rapid evolution (i.e. evolution that occurs through changes in allele frequencies) and ecological dynamics. Despite its inherent interdisciplinary nature, however, studies on eco-evolutionary feedbacks have been mostly ecological and tended to focus on adaptation at the phenotypic level without considering the genetic architecture of evolutionary processes. In empirical studies, researchers have often compared ecological dynamics when the focal species under selection has a single genotype with dynamics when it has multiple genotypes. In theoretical studies, common approaches are models of quantitative traits where mean trait values change adaptively along the fitness gradient and Mendelian traits with two alleles at a single locus. On the other hand, it is well known that genetic architecture can affect short-term evolutionary dynamics in population genetics. Indeed, recent theoretical studies have demonstrated that genetic architecture (e.g. the number of loci, linkage disequilibrium and ploidy) matters in eco-evolutionary dynamics (e.g. evolutionary rescue where rapid evolution prevents extinction and population cycles driven by (co)evolution). I propose that theoretical approaches will promote the synthesis of functional genomics and eco-evolutionary dynamics through models that combine population genetics and ecology as well as nonlinear time-series analyses using emerging big data.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Implications of Large-Effect Loci for Conservation: A Review and Case Study with Pacific Salmon

The increasing feasibility of assembling large genomic datasets for non-model species presents both opportunities and challenges for applied conservation and management. A popular theme in recent studies is the search for large-effect loci that explain substantial portions of phenotypic variance for a key trait(s). If such loci can be linked to adaptations, 2 important questions arise: 1) Should information from these loci be used to reconfigure conservation units (CUs), even if this conflicts with overall patterns of genetic differentiation? 2) How should this information be used in viability assessments of populations and larger CUs? In this review, we address these questions in the context of recent studies of Chinook salmon and steelhead (anadromous form of rainbow trout) that show strong associations between adult migration timing and specific alleles in one small genomic region. Based on the polygenic paradigm (most traits are controlled by many genes of small effect) and genetic data available at the time showing that early-migrating populations are most closely related to nearby late-migrating populations, adult migration differences in Pacific salmon and steelhead were considered to reflect diversity within CUs rather than separate CUs. Recent data, however, suggest that specific alleles are required for early migration, and that these alleles are lost in populations where conditions do not support early-migrating phenotypes. Contrasting determinations under the US Endangered Species Act and the State of California's equivalent legislation illustrate the complexities of incorporating genomics data into CU configuration decisions. Regardless how CUs are defined, viability assessments should consider that 1) early-migrating phenotypes experience disproportionate risks across large geographic areas, so it becomes important to identify early-migrating populations that can serve as reliable sources for these valuable genetic resources; and 2) genetic architecture, especially the existence of large-effect loci, can affect evolutionary potential and adaptability.

Escalating the conflict? Intersex genetic correlations influence adaptation to environmental change in facultatively migratory populations

Males and females are often subject to different and even opposing selection pressures. When a given trait has a shared genetic basis between the sexes, sexual conflict (antagonism) can arise. This can result in significant individual-level fitness consequences that might also affect population performance, whilst anthropogenic environmental change can further exacerbate maladaptation in one or both sexes driven by sexual antagonism. Here, we develop a genetically explicit eco-evolutionary model using an agent-based framework to explore how a population of a facultatively migratory fish species (brown trout Salmo trutta) adapts to environmental change across a range of intersex genetic correlations for migration propensity, which influence the magnitude of sexual conflict. Our modelled focal trait represents a condition threshold governing whether individuals adopt a resident or anadromous (sea migration) tactic. Anadromy affords potential size-mediated reproductive advantages to both males and females due to improved feeding opportunities at sea, but these can be undermined by high background marine mortality and survival/growth costs imposed by marine parasites (sea lice). We show that migration tactic frequency for a given set of environmental conditions is strongly influenced by the intersex genetic correlation, such that one sex can be dragged off its optimum more than the other. When this occurred in females in our model, population productivity was substantially reduced, but eco-evolutionary outcomes were altered by allowing for sneaking behaviour in males. We discuss real-world implications of our work given that anadromous salmonids are regularly challenged by sea lice infestations, which might act synergistically with other stressors such as climate change or fishing that impact marine performance, driving populations towards residency and potentially reduced resilience.

Genomic reaction norms inform predictions of plastic and adaptive responses to climate change

Genomic reaction norms represent the range of gene expression phenotypes (usually mRNA transcript levels) expressed by a genotype along an environmental gradient. Reaction norms derived from common‐garden experiments are powerful approaches for disentangling plastic and adaptive responses to environmental change in natural populations. By treating gene expression as a phenotype in itself, genomic reaction norms represent invaluable tools for exploring causal mechanisms underlying organismal responses to climate change across multiple levels of biodiversity.

Our goal is to provide the context, framework and motivation for applying genomic reaction norms to study the responses of natural populations to climate change.

Here, we describe the utility of integrating genomics with common‐garden‐gradient experiments under a reaction norm analytical framework to answer fundamental questions about phenotypic plasticity, local adaptation, their interaction (i.e. genetic variation in plasticity) and future adaptive potential.

An experimental and analytical framework for constructing and analysing genomic reaction norms is presented within the context of polygenic climate change responses of structured populations with gene flow. Intended for a broad eco‐evo readership, we first briefly review adaptation with gene flow and the importance of understanding the genomic basis and spatial scale of adaptation for conservation and management of structured populations under anthropogenic change. Then, within a high‐dimensional reaction norm framework, we illustrate how to distinguish plastic, differentially expressed (difference in reaction norm intercepts) and differentially plastic (difference in reaction norm slopes) genes, highlighting the areas of opportunity for applying these concepts.

We conclude by discussing how genomic reaction norms can be incorporated into a holistic framework to understand the eco‐evolutionary dynamics of climate change responses from molecules to ecosystems. We aim to inspire researchers to integrate gene expression measurements into common‐garden experimental designs to investigate the genomics of climate change responses as sequencing costs become increasingly accessible.

On the genetic architecture of rapidly adapting and convergent life history traits in guppies

The genetic basis of traits shapes and constrains how adaptation proceeds in nature; rapid adaptation can proceed using stores of polygenic standing genetic variation or hard selective sweeps, and increasing polygenicity fuels genetic redundancy, reducing gene re-use (genetic convergence). Guppy life history traits evolve rapidly and convergently among natural high- and low-predation environments in northern Trinidad. This system has been studied extensively at the phenotypic level, but little is known about the underlying genetic architecture. Here, we use four independent F2 QTL crosses to examine the genetic basis of seven (five female, two male) guppy life history phenotypes and discuss how these genetic architectures may facilitate or constrain rapid adaptation and convergence. We use RAD-sequencing data (16,539 SNPs) from 370 male and 267 female F2 individuals. We perform linkage mapping, estimates of genome-wide and per-chromosome heritability (multi-locus associations), and QTL mapping (single-locus associations). Our results are consistent with architectures of many loci of small-effect for male age and size at maturity and female interbrood period. Male trait associations are clustered on specific chromosomes, but female interbrood period exhibits a weak genome-wide signal suggesting a potentially highly polygenic component. Offspring weight and female size at maturity are also associated with a single significant QTL each. These results suggest rapid, repeatable phenotypic evolution of guppies may be facilitated by polygenic trait architectures, but subsequent genetic redundancy may limit gene re-use across populations, in agreement with an absence of strong signatures of genetic convergence from recent analyses of wild guppies.

The pace of modern life, revisited

Wild populations must continuously respond to environmental changes or they risk extinction. Those responses can be measured as phenotypic rates of change, which can allow us to predict contemporary adaptive responses, some of which are evolutionary. About two decades ago, a database of phenotypic rates of change in wild populations was compiled. Since then, researchers have used (and expanded) this database to examine phenotypic responses to specific types of human disturbance. Here, we update the database by adding 5675 new estimates of phenotypic change. Using this newer version of the data base, now containing 7338 estimates of phenotypic change, we revisit the conclusions of four published articles. We then synthesize the expanded database to compare rates of change across different types of human disturbance. Analyses of this expanded database suggest that: (i) a small absolute difference in rates of change exists between human disturbed and natural populations, (ii) harvesting by humans results in higher rates of change than other types of disturbance, (iii) introduced populations have increased rates of change, and (iv) body size does not increase through time. Thus, findings from earlier analyses have largely held-up in analyses of our new database that encompass a much larger breadth of species, traits, and human disturbances. Lastly, we use new analyses to explore how various types of human disturbances affect rates of phenotypic change, and we call for this database to serve as a steppingstone for further analyses to understand patterns of contemporary phenotypic change.

The crucial role of genome-wide genetic variation in conservation

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

Individual-based eco-evolutionary models for understanding adaptation in changing seas

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field

A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors-and beyond-to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.

The inflated significance of neutral genetic diversity in conservation genetics

The current rate of species extinction is rapidly approaching unprecedented highs, and life on Earth presently faces a sixth mass extinction event driven by anthropogenic activity, climate change, and ecological collapse. The field of conservation genetics aims at preserving species by using their levels of genetic diversity, usually measured as neutral genome-wide diversity, as a barometer for evaluating population health and extinction risk. A fundamental assumption is that higher levels of genetic diversity lead to an increase in fitness and long-term survival of a species. Here, we argue against the perceived importance of neutral genetic diversity for the conservation of wild populations and species. We demonstrate that no simple general relationship exists between neutral genetic diversity and the risk of species extinction. Instead, a better understanding of the properties of functional genetic diversity, demographic history, and ecological relationships is necessary for developing and implementing effective conservation genetic strategies.