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Accurate sex identification of prey remains can provide valuable insights into selective predation, but field studies are often constrained by degraded or digested material. We developed and validated a molecular sexing protocol for the Brown lemming ( Lemmus trimucronatus), a keystone prey species in the Canadian High Arctic. Using tissues from known-sex individuals, we tested candidate primers and established a multiplex PCR combining sex-chromosomal zinc-finger genes (ZFX and ZFY) and sex-determining region Y protein (SRY) markers. This method reliably distinguished males and females, with 98% concordance between genetic and morphological sexing. Validation included dentary bones subjected to artificial digestion, demonstrating consistent success regardless of tissue type or degradation treatment. We then applied the protocol to field-collected lemming remains from snowy owl pellets, ermine caches, and predated lemming winter nests. Despite variable preservation and exposure conditions, 87% of samples yielded viable results, with soft tissues achieving highest success rates and bones and teeth remaining suitable DNA sources even after digestion. Our results confirm that molecular sexing of lemmings from predator-derived remains is feasible, accurate, and robust to sample quality. This protocol can enable researchers in Arctic ecosystems to analyze sex-specific predation patterns even when direct observation or fresh tissue sampling is impractical.

The broad negative consequences of habitat degradation on biodiversity have been studied, but the complex effects of natural–agricultural landscape matrices remain poorly understood. Here we used stable carbon and nitrogen isotopes to detect changes in mammal resource and habitat use and trophic structure between preserved areas and human-modified landscapes (HMLs) in a biodiversity hot spot in South America. We classified mammals into trophic guilds and compared resource use (in terms of C₃- and C₄-derived carbon), isotopic niches, and trophic structure across the 2 systems. In HMLs, approximately one-third of individuals fed exclusively on items from the agricultural matrix (C₄), while in preserved areas, ∼68% depended on forest remnant resources (C₃). Herbivores, omnivores, and carnivores were the guilds that most incorporated C₄ carbon in HMLs. Frugivores maintained the same resource use between systems (C₃ resources), while insectivores showed no significant difference. All guilds in HMLs except insectivores presented larger isotopic niches than those in preserved areas. We observed a complex trophic structure in preserved areas, with increasing δ15N values from herbivores to insectivores and carnivores, differing from that in HMLs. This difference is partially explained by species loss and turnover and mainly by the behavioral plasticity of resilient species that use nitrogen-enriched food items. We concluded that the landscape cannot be seen as a habitat/nonhabitat dichotomy because the agricultural landscape matrix in HMLs provides mammal habitat and opportunities for food acquisition. Thus, favorable management of the agricultural matrix and slowing the conversion of forests to agriculture are important for conservation in this region.

Environmental DNA (eDNA) extracted from water samples has recently shown potential as a valuable source of population genetic information for aquatic macroorganisms. This approach offers several potential advantages compared with conventional tissue‐based methods, including the fact that eDNA sampling is noninvasive and generally more cost‐efficient. Currently, eDNA approaches have been limited to single‐marker studies of mitochondrial DNA (mtDNA), and the relationship between eDNA haplotype composition and true haplotype composition still needs to be thoroughly verified. This will require testing of bioinformatic and statistical software to correct for erroneous sequences, as well as biases and random variation in relative sequence abundances. However, eDNA‐based population genetic methods have far‐reaching potential for both basic and applied research. In this paper, we present a brief overview of the achievements of eDNA‐based population genetics to date, and outline the prospects for future developments in the field, including the estimation of nuclear DNA (nuDNA) variation and epigenetic information. We discuss the challenges associated with eDNA samples as opposed to those of individual tissue samples and assess whether eDNA might offer additional types of information unobtainable with tissue samples. Lastly, we provide recommendations for determining whether an eDNA approach would be a useful and suitable choice in different research settings. We limit our discussion largely to contemporary aquatic systems, but the advantages, challenges, and perspectives can to a large degree be generalized to eDNA studies with a different spatial and temporal focus.

Reliable abundance estimates provide essential information in ecology, conservation and management of many wild grouse populations. In this 3-year study, we comparatively evaluate the suitability of traditional line transect distance sampling of flushed birds versus a spatial capture–recapture survey with noninvasive DNA samples for individual identification to estimate spring densities of black grouse and capercaillie in a ~ 30 km2 boreal forest area in central Norway. The number of observed flushed birds during each field survey period and survey year were low, and did not allow for reliable estimation of abundance from distance sampling any of the three years with a total search effort of 745 km. Collection of noninvasive DNA samples and spatial capture-recapture models provided absolute spring density estimates of 1.6 and 2.3 black grouse km−2 in two out of three survey years, and 0.7 capercaillie km−2 in one out of three survey years. Spring population surveys based on collection of noninvasive DNA samples in a boreal forest habitat could be a better alternative to traditional line transect surveys based on distance sampling of flushed birds in estimating abundance for black grouse and capercaillie, but rely on sufficient number of unique individuals captured and recaptured at different spatial locations

Spatial capture–recapture (SCR) models have increasingly been used as a basis for combining capture–recapture data types with variable levels of individual identity information to estimate population density and other demographic parameters. Recent examples are the unmarked SCR (or spatial count model), where no individual identities are available and spatial mark–resight (SMR) where individual identities are available for only a marked subset of the population. Currently lacking, though, is a model that allows unidentified samples to be combined with identified samples when there are no separate classes of “marked” and “unmarked” individuals and when the two sample types cannot be considered as arising from two independent observation models. This is a common scenario when using noninvasive sampling methods, for example, when analyzing data on identified and unidentified photographs or scats from the same sites. Here we describe a “random thinning” SCR model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model. Our model was fitted in a Bayesian framework using NIMBLE. We investigate the improvement in parameter estimates by including the unknown identity samples, which was notable (up to 79% more precise) in low‐density populations with a low rate of identified encounters. We then applied the random thinning SCR model to a noninvasive genetic sampling study of brown bear (Ursus arctos) density in Oriental Cantabrian Mountains (North Spain). Our model can improve density estimation for noninvasive sampling studies for low‐density populations with low rates of individual identification, by making use of available data that might otherwise be discarded. Here we describe a “random thinning” spatial capture–recapture model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model and where individuals cannot be classed by mark status.

The use of unconventional DNA sources has increased because the acquisition of traditional samples can be invasive, destructive, or impossible. Mollusks are one group for which novel genetic sources are crucial, but methodology remains relatively undeveloped. Many species are important ecologically and in aquaculture production. However, mollusks have the highest number of extinctions of any taxonomic group. Traditionally, mollusk shell material was used for morphological research and only recently has been used in DNA studies. In the present article, we review the studies in which shell DNA was extracted and found that effective procedures consider taxon-specific biological characteristics, environmental conditions, laboratory methods, and the study objectives. Importantly, these factors cannot be considered in isolation because of their fundamental, sometimes reciprocal, relationships and influence in the long-term preservation and recovery of shell DNA. Successful recovery of shell DNA can facilitate research on pressing ecological and evolutionary questions and inform conservation strategies to protect molluscan diversity.

Information about how animal abundance varies across landscapes is needed to inform management action but is costly and time-consuming to obtain; surveys of a single population distributed over a large area can take years to complete. Surveys employing small, spatially replicated sampling units improve efficiency, but statistical estimators rely on assumptions that constrain survey design or become less reasonable as larger areas are sampled. Efficient methods that avoid assumptions about similarity of detectability or density among replicates are therefore appealing. Using simulations and data from >3500 black bears sampled on 73 independent study areas in Ontario, Canada, we (1) quantified bias induced by unmodeled spatial heterogeneity in detectability and density; (2) evaluated novel, design-based estimators of average density across replicate study areas; and (3) evaluated two estimators of the variance of average density across study areas: an analytic estimator that assumed an underlying homogeneous spatial Poisson point process for the distribution of animals' activity centers, and an empirical estimator of variance across study areas. In simulations where detectability varied in space, assuming spatially constant detectability yielded density estimates that were negatively biased by 20% to 30%; estimating local detectability and density from local data and treating study areas as independent, equal replicates when estimating average density across study areas using the design-based estimator yielded unbiased estimates at local and landscape scales. Similarly, detectability of black bears varied among study areas and estimates of bear density at landscape scales were higher when no information was shared across study areas when estimating detectability. This approach also maximized precision (relative SEs of estimates of average black bear density ranged from 7% to 18%) and computational efficiency. In simulations, the analytic variance estimator was robust to threefold variation in local densities but the empirical estimator performed poorly. Conducting multiple, similar SECR surveys and treating them as independent replicates during analyses allowed us to efficiently estimate density at multiple scales and extents while avoiding biases caused by pooling spatially heterogeneous data. This approach enables researchers to address a wide range of ecological or management-related questions and is applicable with most types of SECR data.

Information on the distribution of multiple species in a common landscape is fundamental to effective conservation and management. However, distribution data are expensive to obtain and often limited to high‐profile species in a system. A recently developed technique, environmental DNA (eDNA) sampling, has been shown to be more sensitive than traditional detection methods for many aquatic species. A second and perhaps underappreciated benefit of eDNA sampling is that a sample originally collected to determine the presence of one species can be re‐analyzed to detect additional taxa without additional field effort. We developed an eDNA assay for the western pearlshell mussel (Margaritifera falcata) and evaluated its effectiveness by analyzing previously collected eDNA samples that were annotated with information including sample location and deposited in a central repository. The eDNA samples were initially collected to determine habitat occupancy by nonbenthic fish species at sites that were in the vicinity of locations recently occupied by western pearlshell. These repurposed eDNA samples produced results congruent with historical western pearlshell surveys and permitted a more precise delineation of the extent of local populations. That a sampling protocol designed to detect fish was also successful for detecting a freshwater mussel suggests that rapidly accumulating collections of eDNA samples can be repurposed to enhance the efficiency and cost‐effectiveness of aquatic biodiversity monitoring. A perhaps underappreciated benefit of eDNA sampling is that a sample originally collected to determine the presence of one species can be re‐analyzed to detect additional taxa without additional field effort. We developed an eDNA assay for the freshwater mussel western pearlshell (Margaritifera falcata) and evaluated the efficacy of re‐analyzing eDNA samples originally collected for the large‐scale detection of nonbenthic stream fishes. Our results were largely consistent with historical western pearlshell surveys, and we further detected peripheral populations, demonstrating the validity of repurposing collections of eDNA samples to enhance the efficiency and cost‐effectiveness of aquatic biodiversity monitoring.

Population census size (N C) and effective population sizes (N e) are two crucial parameters that influence population viability, wildlife management decisions, and conservation planning. Genetic estimators of both N C and N e are increasingly widely used because molecular markers are increasingly available, statistical methods are improving rapidly, and genetic estimators complement or improve upon traditional demographic estimators. We review the kinds and applications of estimators of both N C and N e, and the often undervalued and misunderstood ratio of effective-to-census size (N e /N C). We focus on recently improved and well evaluated methods that are most likely to facilitate conservation. Finally, we outline areas of future research to improve N e and N C estimation in wild populations.

Sebum lipids, accessible via groomed latent fingerprints, may be a valuable, underappreciated sample source for future biomarker research. Sampling sebum lipids from the skin is painless for patients, efficient for researchers, and has already demonstrated the potential to contain disease biomarkers. However, before sebum sampling can be implemented in routine studies, more information is needed regarding sampling reproducibility and variability. This information will enable researchers to choose the best practices for sebum-based studies. Herein, we use our recently established workflow for the collection and analysis of groomed fingerprints to assess the reproducibility of lipid profiles obtained via mass spectrometry. Using 180 fingerprint samples collected from 30 participants, we also assess lipid changes according to biological sex and anatomical grooming region (cheek, neck, and forehead) via supervised and unsupervised classification. The results demonstrate that this sampling protocol achieves satisfactory reproducibility, and negligible differences exist between male and female groomed fingerprint lipids. Moreover, the anatomical grooming region can impact the fingerprint lipid profile: cheek- and forehead-groomed fingerprints are more similar to one another than either collection site is to neck-groomed fingerprints. This information will inform future sebum-based biomarker investigations, enabling researchers to collect meaningful lipidomic datasets from groomed fingerprint samples.