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.

Resource pulses shape seasonal and individual variation in the diet of an omnivorous carnivore.

Resource pulses are ecologically important phenomenon that occur in most ecosystems globally. Following optimal foraging theory, many consumers switch to pulsatile foods when available, examples of which include fruit mast and vulnerable young prey. Yet how the availability of resource pulses shapes the ecology of predators is still an emerging area of research; and how much individual variation there is in response to pulses is not well understood. We hypothesized that resource pulses would lead to dietary convergence in our population, which we tested by tracking both population-level and individual coyote diets for 3 years in South Carolina, USA. We (1) described seasonal dietary shifts in relation to resource pulses; (2) compared male and female diets across seasons; and (3) tested this dietary convergence hypothesis by quantifying individual dietary variation both across and within periods when resource pulses were available. We found that pulses of white-tailed deer fawns and blackberries composed over half of coyote diet in summer, and persimmon fruits were an important component in fall. Male and female coyotes generally had similar diets, but males consumed more deer in fall, perhaps driven by scavenging more. We found support for our dietary convergence hypothesis, where individuals had more similar diets during resource pulses compared to a non-pulse period. We also found that this convergence happened before peak availability, suggesting a non-symmetric response to pulse availability. We show that nearly all coyotes eat fawns, suggesting that targeted efforts to remove "fawn killers" would be in vain. Instead, given how quickly coyotes collectively converge on resource pulses, our findings show that resource pulses could potentially be used by managers to alter the behavior of apex predators. More broadly, we open a new line of inquiry into how variation in individual foraging decisions scales up to shape the effects of resource pulses on ecological communities.

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.