Combined use of mark-recapture and genetic analyses reveals response of a black bear population to changes in food productivity

McCall, Barbara S.; Mitchell, Michael S.; Schwartz, Michael K.; Hayden, Jim; Cushman, Samuel A.; Zager, Pete; Kasworm, Wayne F.

doi:10.1002/jwmg.617

Cited by 13 publications

(14 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some of the most rigorous examples of using genetic tags to link demographic parameters to the environment is through a series of studies conducted on black bears (McCall et al 2013), grizzly bears (Sawaya et al 2012, Whittington and Sawaya 2015, and wolverines (Brøseth et al 2010, Efford and. For example, Brøseth et al (2010) examined wolverine survival using genetically tagged individuals sourced from scat collection covering 65,000 km 2 across Norway.…”

Section: Why and How Does Population Density Change Across The Landscmentioning

confidence: 99%

See 1 more Smart Citation

Genetic tagging in the Anthropocene: scaling ecology from alleles to ecosystems

Lamb

Ford

Proctor³

et al. 2019

Ecological Applications

View full text Add to dashboard Cite

The Anthropocene is an era of marked human impact on the world. Quantifying these impacts has become central to understanding the dynamics of coupled human‐natural systems, resource‐dependent livelihoods, and biodiversity conservation. Ecologists are facing growing pressure to quantify the size, distribution, and trajectory of wild populations in a cost‐effective and socially acceptable manner. Genetic tagging, combined with modern computational and genetic analyses, is an under‐utilized tool to meet this demand, especially for wide‐ranging, elusive, sensitive, and low‐density species. Genetic tagging studies are now revealing unprecedented insight into the mechanisms that control the density, trajectory, connectivity, and patterns of human–wildlife interaction for populations over vast spatial extents. Here, we outline the application of, and ecological inferences from, new analytical techniques applied to genetically tagged individuals, contrast this approach with conventional methods, and describe how genetic tagging can be better applied to address outstanding questions in ecology. We provide example analyses using a long‐term genetic tagging dataset of grizzly bears in the Canadian Rockies. The genetic tagging toolbox is a powerful and overlooked ensemble that ecologists and conservation biologists can leverage to generate evidence and meet the challenges of the Anthropocene.

show abstract

Section: Why and How Does Population Density Change Across The Landscmentioning

confidence: 99%

“…Some of the most rigorous examples of using genetic tags to link demographic parameters to the environment is through a series of studies conducted on black bears (McCall et al. ), grizzly bears (Sawaya et al. , Whittington and Sawaya , Lamb et al.…”

Section: Introductionmentioning

confidence: 99%

Genetic tagging in the Anthropocene: scaling ecology from alleles to ecosystems

Lamb

Ford

Proctor³

et al. 2019

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…Species that live secretively in dense cover, mostly alone, or at a low density in a landscape challenge managers seeking to make informed decisions (Piggott and Taylor 2003;McCall et al 2013). Although remote photography has some advantages over video in terms of battery consumption, storage-space use and processing time, video offers a richer dataset for learning about individuals and behaviour.…”

Section: Discussionmentioning

confidence: 99%

Individual identification via remote video verified by DNA analysis: a case study of the American black bear

Ramsey¹,

Sawaya

Bullington³

et al. 2019

Wildl. Res.

View full text Add to dashboard Cite

Context Researchers and managers often use DNA analysis and remote photography to identify cryptic animals and estimate abundance. Remote video cameras are used less often but offer an increased ability to distinguish similar-looking individuals as well as to observe behavioural patterns that cannot be adequately captured with still photography. However, the use of this approach in species with minimally distinguishing marks has not been tested. Aims To determine the utility and accuracy of distinguishing characteristics of American black bears, Ursus americanus, observed on remote video for identifying individuals in an open population. Methods We compared individuals identified on video with individuals and their sex identified by DNA analysis of hairs collected from hair traps visited by the bears. Key results We found that remote video could be used to determine the number of male and female black bears sampled by the video cameras. Specifically, we matched 13 individual bear genotypes with 13 video identifications, one genotype for each individual. We correctly matched ~82% of video identifications with all 38 genotypes collected from hair traps. Conclusions We demonstrated that distinguishing characteristics of a cryptic animal in remote video can be used to accurately identify individuals. Remote video complements genetic analysis by providing information about habitat use and behaviour. Implications When remote video cameras can be used to identify individuals, a wealth of other information will subsequently be obtained. Multi-year video-based studies can show sex ratios, and relative physical condition; shed light on fine-scale habitat use, such as when and where animals feed and what they eat; and display social interactions and rare behaviours.

show abstract

“…Larger differences in encounter probability among classes will lead to more heterogeneity in encounter probability and therefore more bias in estimating N. The second approach is that one could analyze the data set by discarding the encounter histories of individuals with missing sex information. While this has been done in practice (e.g., Boulanger et al 2004, McCall et al 2013, it is not advisable because it will necessarily bias estimates of population size. The expected value ofN in this case is not the true population size but, rather, the size of the population that is expected to produce non-missing sex information if it were exhaustively sampled.…”

Section: Simulation Studymentioning

confidence: 99%

“…This is especially true in studies with non-invasively collected samples of tissue, hair, or scat in which genetic analyses can fail to determine individual sex even though individual identity of the sample can be determined (Waits and Paetkau 2005). In studies where sex of individuals cannot be determined with certainty, it has been common to either ignore sex and not estimate sex-specific parameters (e.g., Mowat and Strobeck 2000, Immell and Anthony 2008, Frary et al 2011 to discard the individuals with unknown sex and proceed with sex-specific models (Belant et al 2005, McCall et al 2013. Utilizing only the known-sex individuals can result in a biased sample when sex determination is not independent of encounter probability.…”

Section: Introductionmentioning

confidence: 99%

Likelihood analysis of spatial capture‐recapture models for stratified or class structured populations

Royle¹,

Sutherland

Fuller

et al. 2015

Ecosphere

View full text Add to dashboard Cite

2015. Likelihood analysis of spatial capture-recapture models for stratified or class structured populations. Ecosphere 6(2):22. http://dx.Abstract. We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

show abstract

Combined use of mark-recapture and genetic analyses reveals response of a black bear population to changes in food productivity

Cited by 13 publications

References 58 publications

Genetic tagging in the Anthropocene: scaling ecology from alleles to ecosystems

Genetic tagging in the Anthropocene: scaling ecology from alleles to ecosystems

Individual identification via remote video verified by DNA analysis: a case study of the American black bear

Likelihood analysis of spatial capture‐recapture models for stratified or class structured populations

Contact Info

Product

Resources

About