Noninvasive Hair Sampling and Genetic Tagging of Co-Distributed Fishers and American Martens

ABSTRACT Estimation of abundance is important for assessing population responses to management actions. Accurate abundance estimates are particularly critical for monitoring temporal variation following reintroductions when the management goal is to attain population sizes capable of sustaining harvest. Numerous reintroductions have taken place in the Great Lakes region of North America, including efforts to restore extirpated fishers (Martes pennanti) and American martens (M. americana). We used a DNA-based noninvasive hair-snaring method based on one trap design and trapping -grid configuration, and evaluated capture—mark—recapture (CMR) analytical approaches to simultaneously estimate population size for co-distributed fishers and American martens in a 671-km² area of the Ottawa National Forest in the western Upper Peninsula of Michigan, USA. We included harvest as a final recapture period to increase probability of recapture and to evaluate potential violations of geographic closure assumptions. We used microsatellite markers to identify target species, eliminate congener species, and provide individual identity for estimation of abundance. Population estimates for fishers and martens on the study area ranged from 35 to 60 and 8 to 28, respectively. Estimators incorporating harvest data resulted in up to a 40% increase in abundance estimates relative to estimators without harvest. We considered population estimates not including harvest data the most appropriate for the study due to timing of sampling and environmental factors, but inclusion of harvested individuals was shown to be useful as a means to detect violations of the assumption of geographic closure. We suggest improvements on future CMR sampling designs for larger landscape scales of relevance to management through incorporation of habitat or historical harvest data. Noninvasive genetic methods that simultaneously estimate the numerical abundance of co-distributed species can greatly decrease assessment costs relative to traditional methods, and increase resulting demographic and ecological information.     

Hair-Trap Efficacy for Detecting Mammalian Carnivores in the Tropics

Abstract: Direct studies of mammalian carnivores are challenging due to the animals' secretive nature and the high costs associated with their capture and handling. Use of noninvasive hair sampling to survey these reclusive species has great potential as an alternative, with wide applicability in ecology and conservation. Hair-trapping has been extensively used for focal studies of temperate mammals, but its use and applicability as a means to survey mammals in tropical environs has never been addressed. We evaluated the effectiveness of 2 hair-trap types and 2 scents along an elevational gradient within El Cielo Biosphere Reserve (ECBR, Mexico) to detect presence of carnivores. Hair-traps that used roofing nails as a hair-collecting surface collected more hairs and detected a greater number of species than did hair-traps that used velcro strips. Different scent treatments (commercial fragrance and catnip oil) did not differ for these same variables. Of successful nail hair-traps, 60% collected ≥20 hairs (max. = 439), providing enough material for DNA analyses. Hair-trap surveys detected 74% of the potential target mammal species at ECBR with only 19 days of field effort. Developing countries have limited budgets for biodiversity monitoring and hair-traps compare favorably with other methods with a high cost-benefit ratio. Hair-traps are inexpensive, portable, can be made with over-the-counter materials, and can be successfully used to collect data applicable to population and genetic studies of tropical carnivores.     

Estimating Black Bear Density Using DNA Data From Hair Snares

ABSTRACT DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capture-recapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km². A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level.