Efficient single-survey estimation of carnivore density using fecal DNA and spatial capture-recapture: a bobcat case study

Top-down and bottom-up effects modulate species co-existence in a context of top predator restoration

Mesopredators abundance is often limited by top-order predators and also by key food resources. However, the contribution of these bidirectional forces to structure carnivore community is still unclear. Here, we studied how the presence and absence of an apex predator which is currently recovering its former distribution range, the Iberian lynx (Lynx pardinus), determined the absolute abundance and fine-scale spatiotemporal avoidance mechanisms of two sympatric mesocarnivores (stone marten Martes foina and common genet Genetta genetta) with different dietary plasticity. We hypothesized that the lynx causes a mesopredator suppression and subordinate predators develop segregation strategies in respect to their trophic niche breadth. We placed 120 camera-traps in Southern Spain for 8 months in two consecutive years to estimate mesocarnivore abundances by using SCR Bayesian models, prey availability and assess spatio-temporal patterns. We found that the lynx reduced mesocarnivore abundance up to 10 times. Stone marten, a mesopredator with a broad food resources spectrum, showed a total spatial exclusion with the apex predator. Meanwhile, fine-scale avoidance mechanisms allowed the genet to persist in low density inside lynx territories, probably taking advantage of high availability of its preferred prey. Thus, the strength of these top-down and bottom-up effects was rather species-specific. Given the recent recovery of large carnivore populations worldwide, variation in suppression levels on different mesopredator species could modify ecosystem functions provided by the carnivore community in contrasting ways.

Splitting hairs: differentiating juvenile from adult deer (Odocoileus virginianus) by hair width

Ungulates are a main component in carnivore diets but determining consumption of juveniles is difficult. Past studies have used size of prey remains such as small hooves or bones to classify scat samples as containing content attributable to juveniles. Hair thickness and color may also be used, but seasonality could influence the coat of an adult by developing thinner hairs in summer that more closely resemble those from juveniles. Given this uncertainty, we aimed to quantitatively determine a hair diameter threshold to categorize the age-class of ungulate hair in scats. We obtained hair samples from captive (n = 133) and vehicle-killed (n = 5) white-tailed deer (Odocoileus virginianus) from Georgia and Virginia. We used microphotography image analysis to measure the width of hairs and their cuticular casts. We used a linear model to assess differences among body locations, age-classes, and locations along the hair strand. We also analyzed the change in hair width of juveniles as they aged. Hair diameter of adults, but not juveniles, differed significantly depending on body location, yet adult hairs were always significantly wider than those from juveniles. Juvenile hairs significantly increased in width after mid-September, when they molt into adult coats in our study area. We identified 104.2 µm measured at either 1/8 or 1/4 distance from the follicle as a threshold width to distinguish adult from juvenile hairs, with 95.3% accuracy. Our findings indicate that juvenile white-tailed deer can be distinguished from adults based on the width of hairs found in carnivore scats up until juveniles are 5 months old. More broadly, our results demonstrate that hair width may be used to classify juvenile versus adult prey remains in carnivore diet studies in other predator–prey systems.

Precision and bias of spatial capture-recapture estimates: A multi-site, multi-year Utah black bear case study

Spatial capture-recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence the precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical data sets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear (Ursus americanus) capture-recapture data set, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 to 74.33 bears/100 km² . Increasing total detections decreased the uncertainty of density estimates, whereas an increasing number of total recaptures and individuals with recaptures decreased the uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 coefficient of variation [CV]). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when <30% of recaptured individuals were spatially recaptured, density estimates were unreliable and ranged widely, in some cases to >3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture-recapture data sets that can provide an early signal of the need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.

Explaining detection heterogeneity with finite mixture and non-Euclidean movement in spatially explicit capture-recapture models

Landscape structure affects animal movement. Differences between landscapes may induce heterogeneity in home range size and movement rates among individuals within a population. These types of heterogeneity can cause bias when estimating population size or density and are seldom considered during analyses. Individual heterogeneity, attributable to unknown or unobserved covariates, is often modelled using latent mixture distributions, but these are demanding of data, and abundance estimates are sensitive to the parameters of the mixture distribution. A recent extension of spatially explicit capture-recapture models allows landscape structure to be modelled explicitly by incorporating landscape connectivity using non-Euclidean least-cost paths, improving inference, especially in highly structured (riparian & mountainous) landscapes. Our objective was to investigate whether these novel models could improve inference about black bear (Ursus americanus) density. We fit spatially explicit capture-recapture models with standard and complex structures to black bear data from 51 separate study areas. We found that non-Euclidean models were supported in over half of our study areas. Associated density estimates were higher and less precise than those from simple models and only slightly more precise than those from finite mixture models. Estimates were sensitive to the scale (pixel resolution) at which least-cost paths were calculated, but there was no consistent pattern across covariates or resolutions. Our results indicate that negative bias associated with ignoring heterogeneity is potentially severe. However, the most popular method for dealing with this heterogeneity (finite mixtures) yielded potentially unreliable point estimates of abundance that may not be comparable across surveys, even in data sets with 136-350 total detections, 3-5 detections per individual, 97-283 recaptures, and 80-254 spatial recaptures. In these same study areas with high sample sizes, we expected that landscape features would not severely constrain animal movements and modelling non-Euclidian distance would not consistently improve inference. Our results suggest caution in applying non-Euclidean SCR models when there is no clear landscape covariate that is known to strongly influence the movement of the focal species, and in applying finite mixture models except when abundant data are available.

Novel hair snare and genetic methods for non-invasive bobcat detection

Over the past 20 years, the use of non-invasive hair snare surveys in wildlife research and management has become more prevalent. While these tools have been used to answer important research questions, these techniques often fail to gather information on elusive carnivores, such as bobcats (Lynx rufus). Due to the limited success of previous bobcat studies using hair snares which required active rubbing, this technique has largely fallen out of use, in favor of camera trapping. The goal of our study was to construct a novel, passive bobcat hair snare that could be deployed regardless of terrain or vegetation features, which would be effective for use in capture-recapture population estimation at a large spatial scale. This new hair snare was deployed in 1500 10-km2 cells across West Virginia (USA) between two sampling seasons (2015-2016). Collected hair samples were analyzed with newly developed mitochondrial DNA primers specifically for felids and qPCR to determine species of origin, with enough sensitivity to identify samples as small as two bobcat hairs. Over the two years of the study, a total of 378 bobcat detections were recorded from 42,000 trap nights of sampling, for an overall rate of 0.9 detections/100 trap nights-nearly 2-6 times greater than any previous bobcat hair snare study. While the overall number of recaptured animals was low (n = 9), continued development of this platform should increase its usefulness in capture-recapture studies.

Evaluating and integrating spatial capture-recapture models with data of variable individual identifiability

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.

An empirical demonstration of the effect of study design on density estimations

The simultaneous development of technology (e.g. camera traps) and statistical methods, particularly spatially capture-recapture (SCR), has improved monitoring of large mammals in recent years. SCR estimates are known to be sensitive to sampling design, yet existing recommendations about trap spacing and coverage are often not achieved, particularly for sampling wide-ranging and rare species in landscapes that allow for limited accessibility. Consequently, most camera trap studies on large wide-ranging carnivores relies on convenience or judgmental sampling, and often yields compromised results. This study attempts to highlight the importance of carefully considered sampling design for large carnivores that, because of low densities and elusive behavior, are challenging to monitor. As a motivating example, we use two years of snow leopard camera trapping data from the same areas in the high mountains of Pakistan but with vastly different camera configurations, to demonstrate that estimates of density and space use are indeed sensitive to the trapping array. A compact design, one in which cameras were placed much closer together than generally recommended and therefore have lower spatial coverage, resulted in fewer individuals observed, but more recaptures, and estimates of density and space use were inconsistent with expectations for the region. In contrast, a diffuse design, one with larger spacing and spatial coverage and more consistent with general recommendations, detected more individuals, had fewer recaptures, but generated estimates of density and space use that were in line with expectations. Researchers often opt for compact camera configurations while monitoring wide-ranging and rare species, in an attempt to maximize the encounter probabilities. We empirically demonstrate the potential for biases when sampling a small area approximately the size of a single home range-this arises from exposing fewer individuals than deemed sufficient for estimation. The smaller trapping array may also underestimate density by significantly inflating [Formula: see text]. On the other hand, larger trapping array with fewer detectors and poor design induces uncertainties in the estimates. We conclude that existing design recommendations have limited utility on practical grounds for devising feasible sampling designs for large ranging species, and more research on SCR designs is required that allows for integrating biological and habitat traits of large carnivores in sampling framework. We also suggest that caution should be exercised when there is a reliance on convenience sampling.

Sex-specific effects of reproductive season on bobcat space use, movement, and resource selection in the Appalachian Mountains of Virginia

Across taxa, sex-specific demands vary temporally in accordance with reproductive investments. In solitary carnivores, females must provision and protect young independently while meeting increased energetic demands. Males seek to monopolize access to females by maintaining large territories and defending them from other males. For many species, it is poorly understood how these demands relate to broad-scale animal movements. To investigate predictions surrounding the reproductive strategies of solitary carnivores and effects of local conditions on bobcat (Lynx rufus) spatial ecology, we examined the effects of sex and reproductive season on home range size, movement rate, and resource selection of bobcats in the central Appalachian Mountains. Male seasonal home ranges were approximately 3 times larger than those of females (33.9 ± 2.6 vs. 12.1 ± 2.4 km2, x±SE), and male movement rates were 1.4 times greater than females (212.6 ± 3.6 vs. 155 ± 8.2 m/hr), likely reflecting male efforts to maximize access to females. Both sexes appear to maintain relatively stable seasonal home ranges despite temporally varying reproductive investments, instead adjusting movements within home ranges. Males increased movements during the dispersal period, potentially reflecting increased territoriality prior to breeding. Females increased movements during the kitten-rearing period, when foraging more intensively, and frequently returning to den sites. Both sexes selected home ranges at higher elevations. However, females selected deciduous forest and avoided fields, whereas males selected fields and avoided deciduous forest, perhaps explained by male pressure to access multiple females across several mountain ridges and higher risk tolerance. Seasonal changes in home range selection likely reflect changes in home range shape. Increased female avoidance of fields during kitten rearing may indicate female avoidance of presumably resource rich, yet risky, fields at the time when kittens are most vulnerable. Our results indicate that while reproductive chronology influences the spatial ecology of solitary carnivores, effects may be constrained by territoriality.

Fragmentation and low density as major conservation challenges for the southernmost populations of the European wildcat

Knowledge of population dynamics of threatened species in the wild is key to effective conservation actions. However, at present, there are many examples of endangered animals for which their current situation is unknown, and not just in remote areas and less developed countries. We have explored this topic by studying the paradigmatic case of the European wildcat (Felis silvestris silvestris), an endangered small carnivore whose status has been subjectively established on the basis of non-systematic approaches and opportunistic records. Little is known about its demographic situation, prompting the need for information to improve conservation measures. However, the secretive behaviour of felines along with its low density in natural conditions have prevented the gathering of sufficient data. We developed a field sampling strategy for one of the largest populations (Andalusia, South Spain, 87,268 km2), based on a logistically viable systematic non-intrusive survey by camera-trapping. This study offers the first large-scale estimation for any European wildcat population, based on analytical approaches applied on Species Distribution Models. A hierarchical approach based on a Maxent model for distribution estimation was used, along with Generalised Linear Models for density estimation from explicit spatial capture-recapture data. Our results show that the distribution range is smaller and more highly fragmented than previously assumed. The overall estimated density was very low (0.069 ±0.0019 wildcats/km2) and the protected areas network seems to be insufficient to cover a significant part of the population or a viable nucleus in demographic terms. Indeed, the most important areas remain unprotected. Our main recommendations are to improve the protected area network and/or vigilance programs in hunting estates, in addition to studying and improving connectivity between the main population patches.

Evaluation of fecal samples as a valid source of DNA by comparing paired blood and fecal samples from American bison (Bison bison)

Background

The collection and analysis of fecal DNA is a common practice, especially when dealing with wildlife species that are difficult to track or capture. While fecal DNA is known to be lower quality than traditional sources of DNA, such as blood or other tissues, few investigations have verified fecal samples as a valid source of DNA by directly comparing the results to high quality DNA samples from the same individuals. Our goal was to compare DNA from fecal and blood samples from the same 50 American plains bison (Bison bison) from Yellowstone National Park, analyze 35 short tandem repeat (STR) loci for genotyping efficiency, and compare heterozygosity estimates.

Results

We discovered that some of the fecal-derived genotypes obtained were significantly different from the blood-derived genotypes from the same bison. We also found that fecal-derived DNA samples often underestimated heterozygosity values, in some cases by over 20%.

Conclusions

These findings highlight a potential shortcoming inherent in previous wildlife studies that relied solely on a multi-tube approach, using exclusively low quality fecal DNA samples with no quality control to account for false alleles and allelic dropout. Herein, we present a rigorous marker selection protocol that is applicable for a wide range of species and report a set of 15 STR markers for use in future bison studies that yielded consistent results from both fecal and blood-derived DNA.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0722-3) contains supplementary material, which is available to authorized users.