Development and validation of a GT-seq panel for genetic monitoring in a threatened species using minimally invasive sampling.

Minimally invasive samples are often the best option for collecting genetic material from species of conservation concern, but they perform poorly in many genomic sequencing methods due to their tendency to yield low DNA quality and quantity. Genotyping-in-thousands by sequencing (GT-seq) is a powerful amplicon sequencing method that can genotype large numbers of variable-quality samples at a standardized set of single nucleotide polymorphism (SNP) loci. Here, we develop, optimize, and validate a GT-seq panel for the federally threatened northern Idaho ground squirrel (Urocitellus brunneus) to provide a standardized approach for future genetic monitoring and assessment of recovery goals using minimally invasive samples. The optimized panel consists of 224 neutral and 81 putatively adaptive SNPs. DNA collected from buccal swabs from 2016 to 2020 had 73% genotyping success, while samples collected from hair from 2002 to 2006 had little to no DNA remaining and did not genotype successfully. We evaluated our GT-seq panel by measuring genotype discordance rates compared to RADseq and whole-genome sequencing. GT-seq and other sequencing methods had similar population diversity and F ST estimates, but GT-seq consistently called more heterozygotes than expected, resulting in negative F IS values at the population level. Genetic ancestry assignment was consistent when estimated with different sequencing methods and numbers of loci. Our GT-seq panel is an effective and efficient genotyping tool that will aid in the monitoring and recovery of this threatened species, and our results provide insights for applying GT-seq for minimally invasive DNA sampling techniques in other rare animals.

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore.

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and GST″) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and GST″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

Sources of bias in applying close-kin mark-recapture to terrestrial game species with different life histories.

Close-kin mark-recapture (CKMR) is a method analogous to traditional mark-recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species' and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent-offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Range-wide evolutionary relationships and historical demography of brown bears (Ursus arctos) revealed by whole-genome sequencing of isolated central Asian populations.

Phylogeographic studies uncover hidden pathways of divergence and inform conservation. Brown bears (Ursus arctos) have one of the broadest distributions of all land mammals, ranging from Eurasia to North America, and are an important model for evolutionary studies. Although several whole genomes were available for individuals from North America, Europe and Asia, limited whole-genome data were available from Central Asia, including the highly imperilled brown bears in the Gobi Desert. To fill this knowledge gap, we sequenced whole genomes from nine Asian brown bears from the Gobi Desert of Mongolia, Northern Mongolia and the Himalayas of Pakistan. We combined these data with published brown bear sequences from Europe, Asia and North America, as well as other bear species. Our goals were to determine the evolutionary relationships among brown bear populations worldwide, their genetic diversity and their historical demography. Our analyses revealed five major lineages of brown bears based on a filtered set of 684,081 single nucleotide polymorphisms. We found distinct evolutionary lineages of brown bears in the Gobi, Himalayas, northern Mongolia, Europe and North America. The lowest level of genetic diversity and the highest level of inbreeding were found in Pakistan, the Gobi Desert and Central Italy. Furthermore, the effective population size (Ne ) for all brown bears decreased over the last 70,000 years. Our results confirm the genetic distinctiveness and ancient lineage of brown bear subspecies in the Gobi Desert of Mongolia and the Himalayas of Pakistan and highlight their importance for conservation.

Population structure and hybridization under contemporary and future climates in a heteroploid foundational shrub species (Artemisia tridentata).

Current and past climatic changes can shift plant climatic niches, which may cause spatial overlap or separation between related taxa. The former often leads to hybridization and introgression, which may generate novel variation and influence the adaptive capacity of plants. An additional mechanism facilitating adaptations to novel environments and an important evolutionary driver in plants is polyploidy as the result of whole genome duplication. Artemisia tridentata (big sagebrush) is a landscape-dominating foundational shrub in the western United States which occupies distinct ecological niches, exhibiting diploid and tetraploid cytotypes. Tetraploids have a large impact on the species' landscape dominance as they occupy a preponderance of the arid spectrum of A. tridentata range. Three distinct subspecies are recognized, which co-occur in ecotones - the transition zone between two or more distinct ecological niches - allowing for hybridization and introgression. Here we assess the genomic distinctiveness and extent of hybridization among subspecies at different ploidies under both contemporary and predicted future climates. We sampled five transects throughout the western United States where a subspecies overlap was predicted using subspecies-specific climate niche models. Along each transect, we sampled multiple plots representing the parental and the potential hybrid habitats. We performed reduced representation sequencing and processed the data using a ploidy-informed genotyping approach. Population genomic analyses revealed distinct diploid subspecies and at least two distinct tetraploid gene pools, indicating independent origins of the tetraploid populations. We detected low levels of hybridization (2.5%) between the diploid subspecies, while we found evidence for increased admixture between ploidy levels (18%), indicating hybridization has an important role in the formation of tetraploids. Our analyses highlight the importance of subspecies co-occurrence within these ecotones to maintain gene exchange and potential formation of tetraploid populations. Genomic confirmations of subspecies in the ecotones support the subspecies overlap predicted by the contemporary climate niche models. However, future mid-century projections of subspecies niches predict a substantial loss in range and subspecies overlap. Thus, reductions in hybridization potential could affect new recruitment of genetically variable tetraploids that are vital to this species' ecological role. Our results underscore the importance of ecotone conservation and restoration.

Whole genome resequencing identifies local adaptation associated with environmental variation for redband trout.

Aquatic ectotherms are predicted to harbour genomic signals of local adaptation resulting from selective pressures driven by the strong influence of climate conditions on body temperature. We investigated local adaptation in redband trout (Oncorhynchus mykiss gairdneri) using genome scans for 547 samples from 11 populations across a wide range of habitats and thermal gradients in the interior Columbia River. We estimated allele frequencies for millions of single nucleotide polymorphism loci (SNPs) across populations using low-coverage whole genome resequencing, and used population structure outlier analyses to identify genomic regions under divergent selection between populations. Twelve genomic regions showed signatures of local adaptation, including two regions associated with genes known to influence migration and developmental timing in salmonids (GREB1L, ROCK1, SIX6). Genotype-environment association analyses indicated that diurnal temperature variation was a strong driver of local adaptation, with signatures of selection driven primarily by divergence of two populations in the northern extreme of the subspecies range. We also found evidence for adaptive differences between high-elevation desert vs. montane habitats at a smaller geographical scale. Finally, we estimated vulnerability of redband trout to future climate change using ecological niche modelling and genetic offset analyses under two climate change scenarios. These analyses predicted substantial habitat loss and strong genetic shifts necessary for adaptation to future habitats, with the greatest vulnerability predicted for high-elevation desert populations. Our results provide new insight into the complexity of local adaptation in salmonids, and important predictions regarding future responses of redband trout to climate change.

Genetic diversity and family groups detected in a coyote population with red wolf ancestry on Galveston Island, Texas.

BACKGROUND: Hybridization can be a conservation concern if genomic introgression leads to the loss of an endangered species' unique genome, or when hybrid offspring are sterile or less fit than their parental species. Yet hybridization can also be an adaptive management tool if rare populations are inbred and have reduced genetic variation, and there is the opportunity to enhance genetic variation through hybridization. The red wolf (Canis rufus) is a critically endangered wolf endemic to the eastern United States, where all extant red wolves are descended from 14 founders which has led to elevated levels of inbreeding over time. Red wolves were considered extirpated from the wild by 1980, but before they disappeared, they interbred with encroaching coyotes creating a genetically admixed population of canids along coastal Texas and Louisiana. In 2018, a genetic study identified individuals on Galveston Island, Texas with significant amounts of red wolf ancestry. We collected 203 fecal samples from Galveston for a more in-depth analysis of this population to identify the amount of red wolf ancestry present and potential mechanisms that support retention of red wolf ancestry on the landscape. RESULTS: We identified 24 individual coyotes from Galveston Island and 8 from mainland Texas with greater than 10% red wolf ancestry. Two of those individuals from mainland Texas had greater than 50% red wolf ancestry estimates. Additionally, this population had 5 private alleles that were absent in the North American reference canid populations used in this study, which included 107 southeastern coyotes, 19 captive red wolves, and 38 gray wolves, possibly representing lost red wolf genetic variation. We also identified several individuals on Galveston Island and the mainland of Texas that retained a unique red wolf mitochondrial haplotype present in the red wolf founding population. On Galveston Island, we identified a minimum of four family groups and found coyotes on the island to be highly related, but not genetically depauperate. We did not find clear associations between red wolf ancestry estimates and landscape features, such as open green space or developed areas. CONCLUSION: Our results confirm the presence of substantial red wolf ancestry persisting on Galveston Island and adjacent mainland Texas. This population has the potential to benefit future red wolf conservation efforts through novel reproductive techniques and possibly through de-introgression strategies, with the goals of recovering extinct red wolf genetic variation and reducing inbreeding within the species.

Chromosomal-level reference genome assembly of the North American wolverine (Gulo gulo luscus): a resource for conservation genomics.

We report a chromosomal-level genome assembly of a male North American wolverine (Gulo gulo luscus) from the Kugluktuk region of Nunavut, Canada. The genome was assembled directly from long-reads, comprising: 758 contigs with a contig N50 of 36.6 Mb; contig L50 of 20; base count of 2.39 Gb; and a near complete representation (99.98%) of the BUSCO 5.2.2 set of 9,226 genes. A presumptive chromosomal-level assembly was generated by scaffolding against two chromosomal-level Mustelidae reference genomes, the ermine and the Eurasian river otter, to derive a final scaffold N50 of 144.0 Mb and a scaffold L50 of 7. We annotated a comprehensive set of genes that have been associated with models of aggressive behavior, a trait which the wolverine is purported to have in the popular literature. To support an integrated, genomics-based wildlife management strategy at a time of environmental disruption from climate change, we annotated the principal genes of the innate immune system to provide a resource to study the wolverine's susceptibility to new infectious and parasitic diseases. As a resource, we annotated genes involved in the modality of infection by the coronaviruses, an important class of viral pathogens of growing concern as shown by the recent spillover infections by severe acute respiratory syndrome coronavirus-2 to naïve wildlife. Tabulation of heterozygous single nucleotide variants in our specimen revealed a heterozygosity level of 0.065%, indicating a relatively diverse genetic pool that would serve as a baseline for the genomics-based conservation of the wolverine, a rare cold-adapted carnivore now under threat.

Reviving ghost alleles: Genetically admixed coyotes along the American Gulf Coast are critical for saving the endangered red wolf.

The last known red wolves were captured in southwestern Louisiana and eastern Texas in 1980 to establish a captive breeding population. Before their extirpation, gene flow with coyotes resulted in the persistence of endangered red wolf genetic variation in local coyote populations. We assessed genomic ancestry and morphology of coyotes in southwestern Louisiana. We detected that 38 to 62% of the coyote genomes contained red wolf ancestry acquired in the past 30 years and have an admixture profile similar to that of the canids captured before the extirpation of red wolves. We further documented a positive correlation between ancestry and weight. Our findings highlight the importance of hybrids and admixed genomes as a reservoir of endangered species ancestry for innovative conservation efforts. Together, this work presents an unprecedented system that conservation can leverage to enrich the recovery program of an endangered species.

Applying genomics in assisted migration under climate change: Framework, empirical applications, and case studies.

The rate of global climate change is projected to outpace the ability of many natural populations and species to adapt. Assisted migration (AM), which is defined as the managed movement of climate-adapted individuals within or outside the species ranges, is a conservation option to improve species' adaptive capacity and facilitate persistence. Although conservation biologists have long been using genetic tools to increase or maintain diversity of natural populations, genomic techniques could add extra benefit in AM that include selectively neutral and adaptive regions of the genome. In this review, we first propose a framework along with detailed procedures to aid collaboration among scientists, agencies, and local and regional managers during the decision-making process of genomics-guided AM. We then summarize the genomic approaches for applying AM, followed by a literature search of existing incorporation of genomics in AM across taxa. Our literature search initially identified 729 publications, but after filtering returned only 50 empirical studies that were either directly applied or considered genomics in AM related to climate change across taxa of plants, terrestrial animals, and aquatic animals; 42 studies were in plants. This demonstrated limited application of genomic methods in AM in organisms other than plants, so we provide further case studies as two examples to demonstrate the negative impact of climate change on non-model species and how genomics could be applied in AM. With the rapidly developing sequencing technology and accumulating genomic data, we expect to see more successful applications of genomics in AM, and more broadly, in the conservation of biodiversity.

Influence of environmental conditions at spawning sites and migration routes on adaptive variation and population connectivity in Chinook salmon.

Many species that undergo long breeding migrations, such as anadromous fishes, face highly heterogeneous environments along their migration corridors and at their spawning sites. These environmental challenges encountered at different life stages may act as strong selective pressures and drive local adaptation. However, the relative influence of environmental conditions along the migration corridor compared with the conditions at spawning sites on driving selection is still unknown. In this study, we performed genome-environment associations (GEA) to understand the relationship between landscape and environmental conditions driving selection in seven populations of the anadromous Chinook salmon (Oncorhynchus tshawytscha)-a species of important economic, social, cultural, and ecological value-in the Columbia River basin. We extracted environmental variables for the shared migration corridors and at distinct spawning sites for each population, and used a Pool-seq approach to perform whole genome resequencing. Bayesian and univariate GEA tests with migration-specific and spawning site-specific environmental variables indicated many more candidate SNPs associated with environmental conditions at the migration corridor compared with spawning sites. Specifically, temperature, precipitation, terrain roughness, and elevation variables of the migration corridor were the most significant drivers of environmental selection. Additional analyses of neutral loci revealed two distinct clusters representing populations from different geographic regions of the drainage that also exhibit differences in adult migration timing (summer vs. fall). Tests for genomic regions under selection revealed a strong peak on chromosome 28, corresponding to the GREB1L/ROCK1 region that has been identified previously in salmonids as a region associated with adult migration timing. Our results show that environmental variation experienced throughout migration corridors imposed a greater selective pressure on Chinook salmon than environmental conditions at spawning sites.

Evaluating otter reintroduction outcomes using genetic spatial capture-recapture modified for dendritic networks.

Monitoring the demographics and genetics of reintroduced populations is critical to evaluating reintroduction success, but species ecology and the landscapes that they inhabit often present challenges for accurate assessments. If suitable habitats are restricted to hierarchical dendritic networks, such as river systems, animal movements are typically constrained and may violate assumptions of methods commonly used to estimate demographic parameters. Using genetic detection data collected via fecal sampling at latrines, we demonstrate applicability of the spatial capture-recapture (SCR) network distance function for estimating the size and density of a recently reintroduced North American river otter (Lontra canadensis) population in the Upper Rio Grande River dendritic network in the southwestern United States, and we also evaluated the genetic outcomes of using a small founder group (n = 33 otters) for reintroduction. Estimated population density was 0.23-0.28 otter/km, or 1 otter/3.57-4.35 km, with weak evidence of density increasing with northerly latitude (ß = 0.33). Estimated population size was 83-104 total otters in 359 km of riverine dendritic network, which corresponded to average annual exponential population growth of 1.12-1.15/year since reintroduction. Growth was ≥40% lower than most reintroduced river otter populations and strong evidence of a founder effect existed 8-10 years post-reintroduction, including 13-21% genetic diversity loss, 84%-87% genetic effective population size decline, and rapid divergence from the source population (F ST accumulation = 0.06/generation). Consequently, genetic restoration via translocation of additional otters from other populations may be necessary to mitigate deleterious genetic effects in this small, isolated population. Combined with non-invasive genetic sampling, the SCR network distance approach is likely widely applicable to demogenetic assessments of both reintroduced and established populations of multiple mustelid species that inhabit aquatic dendritic networks, many of which are regionally or globally imperiled and may warrant reintroduction or augmentation efforts.

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 the inter- 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 geographical 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.

Detection criteria and post-field sample processing influence results and cost efficiency of occupancy-based monitoring.

Optimization of occupancy-based monitoring has focused on balancing the number of sites and surveys to minimize field efforts and costs. When survey techniques require post-field processing of samples to confirm species detections, there may be opportunities to further improve efficiency. We used scat-based noninvasive genetic sampling for kit foxes (Vulpes macrotis) in Utah, USA, as a model system to assess post-field data processing strategies, evaluate the impacts of these strategies on estimates of occupancy and associations between parameters and predictors, and identify the most cost-effective approach. We identified scats with three criteria that varied in costs and reliability: (1) field-based identification (expert opinion), (2) statistical-based morphological identification, and (3) genetic-based identification (mitochondrial DNA). We also considered four novel post-field sample processing strategies that integrated statistical and genetic identifications to reduce costly genetic procedures, including (4) a combined statistical-genetic identification, (5) a genetic removal design, (6) a within-survey conditional-replicate design, and (7) a single-genetic-replicate with false-positive modeling design. We considered results based on genetic identification as the best approximation of truth and used this to evaluate the performance of alternatives. Field-based and statistical-based criteria prone to misidentification produced estimates of occupancy that were biased high (˜1.8 and 2.1 times higher than estimates without misidentifications, respectively). These criteria failed to recover associations between parameters and predictors consistent with genetic identification. The genetic removal design performed poorly, with limited detections leading to estimates that were biased high with poor precision and patterns inconsistent with genetic identification. Both statistical-genetic identification and the conditional-replicate design produced occupancy estimates comparable to genetic identification, while recovering the same model structure and associations at cost reductions of 67% and 74%, respectively. The false-positive design had the lowest cost (88% reduction) and recovered patterns consistent with genetic identification but had occupancy estimates that were ˜32% lower than estimated occupancy based on genetic identification. Our results demonstrate that careful consideration of detection criteria and post-field data processing can reduce costs without significantly altering resulting inferences. Combined with earlier guidance on sampling designs for occupancy modeling, these findings can aid managers in optimizing occupancy-based monitoring.

Genomic association with pathogen carriage in bighorn sheep (Ovis canadensis).

Genetic composition can influence host susceptibility to, and transmission of, pathogens, with potential population-level consequences. In bighorn sheep (Ovis canadensis), pneumonia epidemics caused by Mycoplasma ovipneumoniae have been associated with severe population declines and limited recovery across North America. Adult survivors either clear the infection or act as carriers that continually shed M. ovipneumoniae and expose their susceptible offspring, resulting in high rates of lamb mortality for years following the outbreak event. Here, we investigated the influence of genomic composition on persistent carriage of M. ovipneumoniae in a well-studied bighorn sheep herd in the Wallowa Mountains of Oregon, USA. Using 10,605 SNPs generated using RADseq technology for 25 female bighorn sheep, we assessed genomic diversity metrics and employed family-based genome-wide association methodologies to understand variant association and genetic architecture underlying chronic carriage. We observed no differences among genome-wide diversity metrics (heterozygosity and allelic richness) between groups. However, we identified two variant loci of interest and seven associated candidate genes, which may influence carriage status. Further, we found that the SNP panel explained ~55% of the phenotypic variance (SNP-based heritability) for M. ovipneumoniae carriage, though there was considerable uncertainty in these estimates. While small sample sizes limit conclusions drawn here, our study represents one of the first to assess the genomic factors influencing chronic carriage of a pathogen in a wild population and lays a foundation for understanding genomic influence on pathogen persistence in bighorn sheep and other wildlife populations. Future research should incorporate additional individuals as well as distinct herds to further explore the genomic basis of chronic carriage.

Primers to highly conserved elements optimized for qPCR-based telomere length measurement in vertebrates.

Telomere length dynamics are an established biomarker of health and ageing in animals. The study of telomeres in numerous species has been facilitated by methods to measure telomere length by real-time quantitative PCR (qPCR). In this method, telomere length is determined by quantifying the amount of telomeric DNA repeats in a sample and normalizing this to the total amount of genomic DNA. This normalization requires the development of genomic reference primers suitable for qPCR, which remains challenging in nonmodel organism with genomes that have not been sequenced. Here we report reference primers that can be used in qPCR to measure telomere lengths in any vertebrate species. We designed primer pairs to amplify genetic elements that are highly conserved between evolutionarily distant taxa and tested them in species that span the vertebrate tree of life. We report five primer pairs that meet the specificity and reproducibility standards of qPCR. In addition, we demonstrate an approach to choose the best primers for a given species by testing the primers on multiple individuals within a species and then applying an established computational tool. These reference primers can facilitate qPCR-based telomere length measurements in any vertebrate species of ecological or economic interest.

Diet of a rare herbivore based on DNA metabarcoding of feces: Selection, seasonality, and survival.

In herbivores, survival and reproduction are influenced by quality and quantity of forage, and hence, diet and foraging behavior are the foundation of an herbivore's life history strategy. Given the importance of diet to most herbivores, it is imperative that we know the species of plants they prefer, especially for herbivorous species that are at risk for extinction. However, it is often difficult to identify the diet of small herbivores because: (a) They are difficult to observe, (b) collecting stomach contents requires sacrificing animals, and (c) microhistology requires accurately identifying taxa from partially digested plant fragments and likely overemphasizes less-digestible taxa. The northern Idaho ground squirrel (Urocitellus brunneus) is federally threatened in the United States under the Endangered Species Act. We used DNA metabarcoding techniques to identify the diet of 188 squirrels at 11 study sites from fecal samples. We identified 42 families, 126 genera, and 120 species of plants in the squirrel's diet. Our use of three gene regions was beneficial because reliance on only one gene region (e.g., only trnL) would have caused us to miss >30% of the taxa in their diet. Northern Idaho ground squirrel diet differed between spring and summer, frequency of many plants in the diet differed from their frequency within their foraging areas (evidence of selective foraging), and several plant genera in their diet were associated with survival. Our results suggest that while these squirrels are generalists (they consume a wide variety of plant species), they are also selective and do not eat plants relative to availability. Consumption of particular genera such as Perideridia may be associated with higher overwinter survival.

Landscape genetics of wolverines (Gulo gulo): scale-dependent effects of bioclimatic, topographic, and anthropogenic variables.

Climate change can have particularly severe consequences for high-elevation species that are well-adapted to long-lasting snow conditions within their habitats. One such species is the wolverine, Gulo gulo, with several studies showing a strong, year-round association of the species with the area defined by persistent spring snow cover. This bioclimatic niche also predicts successful dispersal paths for wolverines in the contiguous United States, where the species shows low levels of genetic exchange and low effective population size. Here, we assess the influence of additional climatic, vegetative, topographic, and anthropogenic, variables on wolverine genetic structure in this region using a multivariate, multiscale, landscape genetic approach. This approach allows us to detect landscape-genetic relationships both due to typical, small-scale genetic exchange within habitat, as well as exceptional, long-distance dispersal among habitats. Results suggest that a combination of snow depth, terrain ruggedness, and housing density, best predict gene flow in wolverines, and that the relative importance of variables is scale-dependent. Environmental variables (i.e., isolation-by-resistance, IBR) were responsible for 79% of the explained variation at small scales (i.e., up to ~230 km), and 65% at broad scales (i.e., beyond ~420 km). In contrast, a null model based on only space (i.e., isolation-by-distance, IBD) accounted only for 17% and 11% of the variation at small and broad scales, respectively. Snow depth was the most important variable for predicting genetic structures overall, and at small scales, where it contributed 43% to the variance explained. At broad spatial scales, housing density and terrain ruggedness were most important with contributions to explained variation of 55% and 25%, respectively. While the small-scale analysis most likely captures gene flow within typical wolverine habitat complexes, the broad-scale analysis reflects long-distance dispersal across areas not typically inhabited by wolverines. These findings help to refine our understanding of the processes shaping wolverine genetic structure, which is important for maintaining and improving functional connectivity among remaining wolverine populations.

Does harvest affect genetic diversity in grey wolves?

Harvest can affect vital rates such as reproduction and survival, but also genetic measures of individual and population health. Grey wolves (Canis lupus) live and breed in groups, and effective population size is a small fraction of total abundance. As a result, genetic diversity of wolves may be particularly sensitive to harvest. We evaluated how harvest affected genetic diversity and relatedness in wolves. We hypothesized that harvest would (a) reduce relatedness of individuals within groups in a subpopulation but increase relatedness of individuals between groups due to increased local immigration, (b) increase individual heterozygosity and average allelic richness across groups in subpopulations and (c) add new alleles to a subpopulation and decrease the number of private alleles in subpopulations due to an increase in breeding opportunities for unrelated individuals. We found harvest had no effect on observed heterozygosity of individuals or allelic richness at loci within subpopulations but was associated with a small, biologically insignificant effect on within-group relatedness values in grey wolves. Harvest was, however, positively associated with increased relatedness of individuals between groups and a net gain (+16) of alleles into groups in subpopulations monitored since harvest began, although the number of private alleles in subpopulations overall declined. Harvest likely created opportunities for wolves to immigrate into nearby groups and breed, thereby making groups in subpopulations more related over time. Harvest appears to affect genetic diversity in wolves at the group and population levels, but its effects are less apparent at the individual level given the population sizes we studied.