We created genecap to facilitate analysis of multilocus genotype data for use in non‐invasive DNA sampling and genetic capture‐recapture studies. genecap is a Microsoft excel macro that uses multilocus genetic data to match samples with identical genotypes, calculate frequency of alleles, identify sample genotypes that differ by one and two alleles, calculate probabilities of identity, and match probabilities for matching samples. genecap allows the user to include background data and samples with missing genotypes for multiple loci. Capture histories for each user‐defined sampling period are output in formats consistent with commonly employed population estimation programs.

Estimating black bear (Ursus americanus) population size is a difficult but important requirement when justifying harvest quotas and managing populations. Advancements in genetic techniques provide a means to identify individual bears using DNA contained in tissue and hair samples, thereby permitting estimates of population abundance based on established mark‐capture‐recapture methodology. We expand on previous noninvasive population‐estimation work by geographically extending sampling areas (36,848 km2) to include the entire Northern Lower Peninsula (NLP) of Michigan, USA. We selected sampling locations randomly within biologically relevant bear habitat and used barbed wire hair snares to collect hair samples. Unlike previous noninvasive studies, we used tissue samples from harvested bears as an additional sampling occasion to increase recapture probabilities. We developed subsampling protocols to account for both spatial and temporal variance in sample distribution and variation in sample quality using recently published quality control protocols using 5 microsatellite loci. We quantified genotyping errors using samples from harvested bears and estimated abundance using statistical models that accounted for genotyping error. We estimated the population of yearling and adult black bears in the NLP to be 1,882 bears (95% CI = 1,389‐2,551 bears). The derived population estimate with a 15% coefficient of variation was used by wildlife managers to examine the sustainability of harvest over a large geographic area.

Variance in population estimates is affected by the number of samples that are chosen to genotype when multiple samples are available during a sampling period. Using genetic data obtained from noninvasive hair‐snags used to sample black bears (Ursus americanus) in the Northern Lower Peninsula of Michigan, USA, we developed a bootstrapping simulation to determine how precision of population estimates varied based on the number of samples genotyped. Improvements in precision of population estimates were not monotonic over all samples sizes available for genotyping. Estimates of cost, both financially and in terms of bias associated with increasing genotyping error and benefits in terms of greater estimate precision, will vary by species and field conditions and should be determined empirically.

As noninvasive sampling techniques for animal populations have become more popular, there has been increasing interest in the development of capture-recapture models that can accommodate both imperfect detection and misidentification of individuals (e.g., due to genotyping error). However, current methods do not allow for individual variation in parameters, such as detection or survival probability. Here we develop misidentification models for capture-recapture data that can simultaneously account for temporal variation, behavioral effects and individual heterogeneity in parameters. To facilitate Bayesian inference using our approach, we extend standard probit regression techniques to latent multinomial models where the dimension and zeros of the response cannot be observed. We also present a novel Metropolis-Hastings within Gibbs algorithm for fitting these models using Markov chain Monte Carlo. Using closed population abundance models for illustration, we re-visit a DNA capture-recapture population study of black bears in Michigan, USA and find evidence of misidentification due to genotyping error, as well as temporal, behavioral and individual variation in detection probability. We also estimate a salamander population of known size from laboratory experiments evaluating the effectiveness of a marking technique commonly used for amphibians and fish. Our model was able to reliably estimate the size of this population and provided evidence of individual heterogeneity in misidentification probability that is attributable to variable mark quality. Our approach is more computationally demanding than previously proposed methods, but it provides the flexibility necessary for a much broader suite of models to be explored while properly accounting for uncertainty introduced by misidentification and imperfect detection. In the absence of misidentification, our probit formulation also provides a convenient and efficient Gibbs sampler for Bayesian analysis of traditional closed population capture-recapture data.1. Introduction. Capture-recapture methods are commonly used to estimate demographic parameters for wildlife [e.g., Williams, Nichols and Conroy (2002)] and human [e.g., Yip et al. (1995aYip et al. ( , 1995b] populations. Passive (or "noninvasive") sampling techniques are becoming more common in capture-recapture studies, largely because these techniques can be less expensive and less invasive than the physical capture of animals [e.g., Karanth and Nichols (1998) Unfortunately, use of passive sampling techniques in capture-recapture studies is not entirely without problems. For example, matching photographs to individuals can be prone to identification error due to variable image quality [e.g

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Colorado Parks and Wildlife implemented a new statewide management policy in 1985 for nuisance black bears (Ursus americanus), known today as the 2‐strike directive. It allowed wildlife managers to assess the repeatability of nuisance bear behavior after translocating them to quality bear habitat away from human food sources. We evaluated this directive using 30 years (1987–2016) of nuisance black bear capture records. Statewide, 53% of 1,093 bears caught, marked, and moved (1st strike) were never reported again, while 25% were killed for a 2nd strike, and hunters harvested 17%. Subadult males committed 2nd strikes more quickly than adult males and females. Although time between strikes was greatest for adult females (496 days), they had the largest probability of committing a 2nd strike among all cohorts. We found that the number of 1st strike captures, from late summer through fall was greatest during years of poor mast production. We suggest that the 2‐strike policy has been an effective management tool for nuisance black bears in Colorado, USA, because of low rates of nuisance behavior following 1st‐strike translocation. If a state or local management objective is to increase black bear populations, wildlife managers may increase tolerance of adult bears that have received their 1st strike in years when fall mast crops largely fail because they are less likely to commit a 2nd strike. Lower tolerance of subadult males may be warranted in bad food years, especially in areas where reductions in bear populations are desired, because they tend to repeat nuisance behaviors more quickly than other bears. © 2019 The Wildlife Society.