Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore.

Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral.

Using bear rub data and spatial capture-recapture models to estimate trend in a brown bear population.

Trends in population abundance can be challenging to quantify during range expansion and contraction, when there is spatial variation in trend, or the conservation area is large. We used genetic detection data from natural bear rubbing sites and spatial capture-recapture (SCR) modeling to estimate local density and population growth rates in a grizzly bear population in northwestern Montana, USA. We visited bear rubs to collect hair in 2004, 2009-2012 (3,579-4,802 rubs) and detected 249-355 individual bears each year. We estimated the finite annual population rate of change 2004-2012 was 1.043 (95% CI = 1.017-1.069). Population density shifted from being concentrated in the north in 2004 to a more even distribution across the ecosystem by 2012. Our genetic detection sampling approach coupled with SCR modeling allowed us to estimate spatially variable growth rates of an expanding grizzly bear population and provided insight into how those patterns developed. The ability of SCR to utilize unstructured data and produce spatially explicit maps that indicate where population change is occurring promises to facilitate the monitoring of difficult-to-study species across large spatial areas.

Multiple data sources improve DNA-based mark-recapture population estimates of grizzly bears.

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

Relationship between effective and demographic population size in continuously distributed populations.

Genetic monitoring of wild populations can offer insights into demographic and genetic information simultaneously. However, widespread application of genetic monitoring is hindered by large uncertainty in the estimation and interpretation of target metrics such as contemporary effective population size, Ne . We used four long-term genetic and demographic studies (≥9 years) to evaluate the temporal stability of the relationship between Ne and demographic population size (Nc ). These case studies focused on mammals that are continuously distributed, yet dispersal-limited within the spatial scale of the study. We estimated local, contemporary Ne with single-sample methods (LDNE, Heterozygosity Excess, and Molecular Ancestry) and demographic abundance with either mark-recapture estimates or catch-per-unit effort indices. Estimates of Ne varied widely within each case study suggesting interpretation of estimates is challenging. We found inconsistent correlations and trends both among estimates of Ne and between Ne and Nc suggesting the value of Ne as an indicator of Nc is limited in some cases. In the two case studies with consistent trends between Ne and Nc , FIS was more stable over time and lower, suggesting FIS may be a good indicator that the population was sampled at a spatial scale at which genetic structure is not biasing estimates of Ne . These results suggest that more empirical work on the estimation of Ne in continuous populations is needed to understand the appropriate context to use LDNe as a useful metric in a monitoring programme to detect temporal trends in either Ne or Nc .

Power of Sign Surveys to Monitor Population Trends.

The urgent need for an effective monitoring scheme for grizzly bear (Ursus arctos) populations led us to investigate the effort required to detect changes in populations of low-density dispersed animals, using sign (mainly scats and tracks) they leave on trails. We surveyed trails in Glacier National Park for bear tracks and scats during five consecutive years. Using these data, we modeled the occurrence of bear sign on trails, then estimated the power of various sampling schemes. Specifically, we explored the power of bear sign surveys to detect a 20% decline in sign occurrence. Realistic sampling schemes appear feasible if the density of sign is high enough, and we provide guidelines for designs with adequate replication to monitor long-term trends of dispersed populations using sign occurrences on trails.

Effects of exposure, diet, and thermoregulation on fecal glucocorticoid measures in wild bears.

We examined fecal glucocorticoid (fGC) measures of nutrition and thermoregulatory demands on wild bears in Glacier National Park, Montana, and assessed how these measures changed in samples left in the field. Both ambient temperature and exposure can impact thermoregulation and sample degradation. Bear diets vary markedly with season, affecting body condition and thus fGC. We collected fecal samples during September and October, 2001, when ambient temperatures ranged from 30°C to -5°C. We collected half of each sample immediately and left the other half in its original location for 1-28 days. We used generalized linear models (GLM) to first predict fGC concentrations in fresh samples based on proxies of nutrition, ambient temperature, thermal exposure, and precipitation. These same covariates were then used to predict degradation-based differences in fGC concentrations between the paired sample halves. Variation in fGC was predicted by diet, Julian date, aspect, and the interaction between Julian date and aspect in both fresh and exposed samples. Cumulative precipitation was also a significant predictor of fGC concentrations in the exposed samples, independent of time, indicating that precipitation contributes to sample degradation but not enough to mask effects of other environmental factors on fGC concentrations. Differences between sample halves were only predicted by cumulative precipitation and exposure time; cumulative precipitation decreased, whereas exposure time increased, fGC concentrations in the exposed sample halves. Results indicate that fGC can provide reliable indices of nutrition and thermoregulatory demands in bears and that sample degradation impacts on these relations are minimal and can be virtually eliminated by controlling for cumulative precipitation over the estimated exposure times.

Balancing precision and risk: should multiple detection methods be analyzed separately in N-mixture models?

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.

Evaluating mixed samples as a source of error in non-invasive genetic studies using microsatellites.

The use of noninvasive genetic sampling (NGS) for surveying wild populations is increasing rapidly. Currently, only a limited number of studies have evaluated potential biases associated with NGS. This paper evaluates the potential errors associated with analysing mixed samples drawn from multiple animals. Most NGS studies assume that mixed samples will be identified and removed during the genotyping process. We evaluated this assumption by creating 128 mixed samples of extracted DNA from brown bear (Ursus arctos) hair samples. These mixed samples were genotyped and screened for errors at six microsatellite loci according to protocols consistent with those used in other NGS studies. Five mixed samples produced acceptable genotypes after the first screening. However, all mixed samples produced multiple alleles at one or more loci, amplified as only one of the source samples, or yielded inconsistent electropherograms by the final stage of the error-checking process. These processes could potentially reduce the number of individuals observed in NGS studies, but errors should be conservative within demographic estimates. Researchers should be aware of the potential for mixed samples and carefully design gel analysis criteria and error checking protocols to detect mixed samples.

The influence of diet on faecal DNA amplification and sex identification in brown bears (Ursus arctos).

To evaluate the influence of diet on faecal DNA amplification, 11 captive brown bears (Ursus arctos) were placed on six restricted diets: grass (Trifolium spp., Haplopappus hirtus and Poa pratensis), alfalfa (Lupinus spp.), carrots (Daucus spp.), white-tailed deer (Odocoileus virginianus), blueberries (Vaccinium spp.) and salmon (Salmo spp.). DNA was extracted from 50 faecal samples of each restricted diet, and amplification of brown bear DNA was attempted for a mitochondrial DNA (mtDNA) locus and nuclear DNA (nDNA) locus. For mtDNA, no significant differences were observed in amplification success rates across diets. For nDNA, amplification success rates for salmon diet extracts were significantly lower than all other diet extracts (P < 0.001). To evaluate the accuracy of faecal DNA sex identification when female carnivores consume male mammalian prey, female bears were fed male white-tailed deer. Four of 10 extracts amplified, and all extracts were incorrectly scored as male due to amplification of X and Y-chromosome fragments. The potential biases highlighted in this study have broad implications for researchers using faecal DNA for individual and sex identification, and should be evaluated in other species.