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The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD‐seq) require large amounts of high‐quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low‐quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next‐generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

Spatial capture–recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark–resight, gSMR), or no individual identification (spatial count or spatial presence– absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a hybrid model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species, we genotyped fecal DNA collected with detection dogs during a 20-d period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 d contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by <10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple data sets are incorporated when possible.

Diet studies are frequently used to improve understanding of predator ecology, potential effects of carnivores on prey populations, and competition among predators. However, field identification of carnivore scat typically relies on scat morphology, size, and contents resulting in possible subjective predator identification and potentially biased results. Advancements in noninvasive genetic sampling allow for molecular identification of predator scat, eliminating many issues associated with field identification methods. We collected scat samples once per month from June 2011 to May 2012 in western Virginia, USA, using morphological characteristics for field identification of the predator. We then used mitochondrial DNA to identify the predator species of each scat and identified prey remains visually. Using confusion matrices, we found a range of accuracy in field identification for the 3 target species: coyotes (Canis latrans; 54.0%), bobcats (Lynx rufus; 57.1%), and black bears (Ursus americanus; 95.2%), even though we only considered samples with high-confidence field identification. We found a high coyote false-positive rate (52.7%), indicating we often incorrectly identified scats as coyote (98% of misidentified bobcat scats and 75% of misidentified black bear scats were recorded as coyote in the field). This asymmetrical bias in predator identification resulted in inaccurate estimates of dietary niche breadth and overlap between competitors. Our results suggest that caution should be exercised when interpreting results from studies in which carnivore species are identified by scat morphology. Future studies should employ noninvasive genetic sampling for carnivore scat identification, especially in areas with sympatric predator species that have similar scat morphology.

After centuries of population decline and range contraction, gray wolves (Canis lupus) are now expanding in Europe. Understanding wolf social structure and population dynamics and predicting their future range expansion is mandatory to design sound conservation strategies, but field monitoring methods are difficult or exceedingly expensive. Noninvasive genetic sampling offers unique opportunities for the reliable monitoring of wolf populations. We conducted a 9-year-long monitoring program in a large area (approximately 19,171 km²) in northern Italy, aiming to identify individuals, estimate kinship, reconstruct packs, and describe their dynamics. Of 5,065 biological samples (99% scats), we genotyped and sexed 44% reliably using 12 unlinked autosomal microsatellites, 4 Y-linked microsatellites, and a diagnostic mitochondrial DNA control-region sequence. We identified 414 wolves, 88 dogs, and 16 wolf × dog hybrids. Wolves in the study area belonged to at least 42 packs. We reconstructed the genealogy of 26 packs. The mean pack size was 5.6 ± 2.4 SD, including adoptees, with a mean minimum pack home range of 74 km² ± 52 SD. We detected turnovers of breeding pairs in 19% of the packs. Reproductive wolves were unrelated and unrelated dispersers founded new packs, except for 1 pack founded by a brother–sister pair. We did not detect multiple breeding females in any packs. Overall, the population was not inbred. We found significant isolation by distance and spatial autocorrelation, with nonrandom genetic structure up to a distance of approximately 17 km. We detected 37 dispersers, 14 of which became breeders in new or already existing packs. Our results can be used to model habitat use by wolves, to estimate survival rates, to predict future expansion of the wolf population, and to build risk maps of wolf–human conflicts.

Climate-caused changes in prey abundance may alter predator–prey dynamics in the Arctic food web. Lemmings (Dicrostonyx spp.) are important prey for Arctic foxes (Vulpes lagopus) and their annual population fluctuations drive fox reproduction, creating strongly linked predator–prey population cycles. Winter diet directly impacts Arctic fox reproductive success, but winter prey diversity on the tundra is low. Strategies such as using the marine environment to scavenge seals have allowed Arctic foxes to persist during years of low lemming abundance. However, warming winters have decreased snowpack quality, preventing lemmings from reaching their previous high abundances, which may reduce their impact on predator dynamics. We investigated Arctic fox dietary response to lemming abundance by reconstructing Arctic fox winter diet in the low Arctic. Next-generation sequencing of fecal DNA, from samples (n = 627) collected at dens in winters of 2011–2018, identified prey both from terrestrial and marine environments. Despite lemming cycle damping, Arctic foxes still increased lemming consumption during years of higher lemming abundance. Alternative prey such as marine resources were consumed more during years of low lemming abundance, with up to 45% of samples containing marine resources in low lemming years. In addition, Arctic foxes consumed high proportions of meadow voles (Microtus pennsylvanicus), which may represent a new alternative prey, suggesting climate change may be creating new foraging opportunities. Changes in prey abundance illustrate how climate-caused disturbances are altering Arctic food-web dynamics. Dietary flexibility and availability of alternative prey may become increasingly important for Arctic predators as the Arctic continues to change.

Background/Objectives: Loss and fragmentation of habitat from agricultural conversion led to the near extirpation of the pygmy rabbit (Brachylagus idahoensis Merriam, 1891) population in the Columbia Basin (CB) of Washington, USA. Recovery efforts began in 2002 and included captive breeding, translocations from other regions for genetic rescue, and reintroduction into native habitat in three sites: Sagebrush Flat (SBF), Beezley Hills (BH), and Chester Butte (CHB). Methods: We used noninvasive and invasive genetic sampling to evaluate demographic and population genetic parameters on three translocated populations of pygmy rabbits over eight years (2011–2020). For each population, our goal was to use fecal DNA sampling and 19 microsatellite loci to monitor spatial distribution, apparent survival rates, genetic diversity, reproduction, effective population size, and the persistence of CB ancestry. Over the course of this study, 1978 rabbits were reintroduced as part of a cooperative conservation effort between state and federal agencies. Results: Through winter and summer monitoring surveys, we detected 168 released rabbits and 420 wild-born rabbits in SBF, 13 released rabbits and 2 wild-born in BH, and 16 released rabbits in CHB. Observed heterozygosity (Ho) values ranged from 0.62–0.84 (SBF), 0.59–0.80 (BH), and 0.73–0.77 (CHB). Allelic richness (AR) ranged from 4.67–5.35 (SBF), 3.71–5.41 (BH), and 3.69–4.65 (CHB). Effective population (Ne) within SBF varied from 12.3 (2012) to 44.3 (2017). CB ancestry persisted in all three wild populations, ranging from 15 to 27%. CB ancestry persisted in 99% of wild-born juveniles identified in SBF. Apparent survival of juvenile rabbits differed across years (1–39%) and was positively associated with release date, release weight, and genetic diversity. Survival of adults (0–43%) was positively influenced by release day, with some evidence that genetic diversity also positively influenced adult apparent survival. Conclusions: Noninvasive genetic sampling has proven to be an effective and efficient tool in monitoring this reintroduced population, assessing both demographic and genetic factors. This data has helped managers address the goals of the Columbia Basin recovery program of establishing multiple sustainable wild populations within the sagebrush steppe habitat of Washington.

Careful monitoring of reintroduced threatened species is essential for informing conservation strategies and evaluating reintroduction efforts in an adaptive management context. We used noninvasive genetic sampling to monitor a reintroduction of a threatened shrubland specialist, the New England cottontail (Sylvilagus transitionalis), in southeastern New Hampshire, USA. We monitored the apparent survival and breeding success of founder individuals and tracked changes in population size and genetic diversity for 5 years following an initial reintroduction in 2013. We released 42 rabbits, documented 29 unique offspring in years following releases through noninvasive surveys, and identified 6 founder individuals and 9 recruited offspring that bred. Apparent survival of founders was variable and greatest in the first year of the reintroduction. Predation was the primary cause of mortality and greatest in the first month after release and after heavy snowfall. Population size remained small but relatively stable until a stochastic decline in the fourth year following reintroduction, followed by a slight rebound after population augmentation and offspring production by wild-born rabbits. Genetic diversity increased after the initial founders with diverse genetic backgrounds were released and then they and their subsequent offspring bred. We documented successful dispersal 700m from the release site to a high-quality patch of habitat, which remained occupied throughout the study. For New England cottontail reintroductions to be successful in the long term, releases will be needed at multiple patches within dispersal distance, and habitat corridors need to be restored among patches to create a functioning metapopulation. For small or isolated reintroduced populations, continued intensive monitoring is needed to detect stochastic declines in population size or changes in sex ratios and guide subsequent management reactions via additional reintroductions or population augmentations. Noninvasive genetic sampling is a valuable tool to monitor reintroductions of the New England cottontail and other threatened species to provide managers with detailed information to inform decision-making in an adaptive management framework.

The European wildcat, Felis silvestris silvestris , serves as a prominent target species for the reconnection of central European forest habitats. Monitoring of this species, however, appears difficult due to its elusive behaviour and the ease of confusion with domestic cats. Recently, evidence for multiple wildcat occurrences outside its known distribution has accumulated in several areas across Central Europe, questioning the validity of available distribution data for this species. Our aim was to assess the fine-scale distribution and genetic status of the wildcat in its central European distribution range. We compiled and analysed genetic samples from roadkills and hundreds of recent hair-trapping surveys and applied phylogenetic and genetic clustering methods to discriminate wild and domestic cats and identify population subdivision. 2220 individuals were confirmed as either wildcat (n = 1792) or domestic cat (n = 342), and the remaining 86 (3.9 %) were identified as hybrids between the two. Remarkably, genetic distinction of domestic cats, wildcats and their hybrids was only possible when taking into account the presence of two highly distinct genetic lineages of wildcats, with a suture zone in central Germany. 44 % of the individual wildcats where sampled outside the previously published distribution. Our analyses confirm a relatively continuous spatial presence of wildcats across large parts of the study area in contrast to previous analyses indicating a highly fragmented distribution. Our results suggest that wildcat conservation and management should take advantage of the higher than previously assumed dispersal potential of wildcats, which may use wildlife corridors very efficiently.

Wildlife managers often need to estimate population abundance to make well-informed decisions. However, obtaining such estimates can be difficult and costly, particularly for species with small populations, wide distributions, and spatial clustering of individuals. For this reason, DNA surveys and capture–recapture modeling has become increasingly common where direct observation is consistently difficult or counts are small or variable. We compared the precision, as indicated by the coefficient of variation (CV), and cost-effectiveness of 2 methods to estimate abundance of desert bighorn sheep (Ovis canadensis nelsoni) populations: traditional ground-based mark–resight and fecal DNA capture–recapture. In the Marble Mountains in the Mojave Desert of southeastern California, USA, we conducted annual ground-based mark–resight surveys and collected fecal samples at water sources concurrently during the dry seasons(Jun–Jul) of 2016 and 2017. Fecal DNA samples were genotyped to identify unique individuals. The Lincoln–Peterson bias-corrected estimator and Huggins closed-capture recapture models were used to estimate abundance for the ground-based mark resight and fecal DNA capture–recapture, respectively. We compared costs between the 2 methods for our study and used simulations to estimate costs for a variety of possible sampling scenarios for our study system based on field-based estimates. Population abundance estimates from fecal DNA capture–recapture achieved much greater precision (CV = 5–7%) than estimates derived from ground-based mark–resight (CV = 21–56%). Our simulations indicated that for a population of 100, 2 sampling occasions, and resight probability of 0.20, the lowest CV obtained by mark–resight was approximately 12%. We predict the cost of abundance estimates for this level of precision (CV = 12%) from fecal DNA capture–recapture would be 28% of the cost of ground-based mark–resight (i.e., a 72% cost reduction). We conclude that fecal DNA capture–recapture is a highly cost-effective alternative for estimating abundance of relatively small populations (≤300) of desert bighorn sheep. More broadly, integrating simulated study designs with cost analyses provides a tool to identify the most effective method for estimating abundance over a wide variety of sampling scenarios.

Fecal analysis is a useful tool for studying the species identity of rare mammals. The possibility of using non-invasive biological materials in molecular genetic studies of rare bovids is shown, using the example of the markhor and Siberian ibex of Uzbekistan. Field work including noninvasive genetic sampling collection was carried out in the study area in spring and autumn 2022-2023 in the Hissar, Surkhan State Reserves and Ugam-Chatkal State National Natural Park and Termez zoo in Uzbekistan. We used species-specific 16S rRNA mitochondrial gene fragments for polymerase chain reaction amplification for species identification. The results of the molecular analysis with the 16S rRNA mitochondrial gene allowed the identification of Capra sibirica, C. falconeri and C. hircus belonging to the subfamily Caprinae using a noninvasive genetic sampling method. This method is quite easy to use, while avoiding direct contact with the animal, which minimizes the degree of impact on the object being studied and does not require significant material and labor costs for researchers. We believe that noninvasive genetic sampling is emerging as one of the most effective and accurate methods for estimating the population size of animals, and we recommend considering this approach for endangered and rare species. The protocol developed could be a valuable tool in the management and conservation of the Capra species occurring on the Uzbekistan.