Multiple Data Sources Improve Dna-Based Mark–recapture Population Estimates of Grizzly Bears

Abstract

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.

Demography and Genetic Structure of a Recovering Grizzly Bear Population

“…Estimating Abundance, Mortality, Distribution, and Genetic Population Structure We developed an approach to abundance estimation that combined data from our 3 sampling methods (hair trap, bear rub, and physical capture) to construct individual bear encounter histories for use in Huggins-Pledger closed mark-recapture models (Huggins 1991, Pledger 2000, Boulanger et al 2008a, Kendall et al 2008). We performed all mark-recapture analyses in Program MARK Pledger model updated May 2007).…”

“…20%; Boulanger et al 2002) and thus of limited use for detecting trends or guiding management policy, such as setting harvest rates. Factors that contributed to the precision of our estimate (CV ¼ 3.8%) included the use of multiple sampling methods, the development of advanced mark-recapture modeling techniques (Boulanger et al 2008a), and the large scale of our study. Combining detections from multiple data sources into single encounter histories yielded robust estimates with higher precision than a single-source approach (Boulanger et al 2008a, Kendall et al 2008.…”

“…This represents the most conclusive evidence to date that bear population estimates derived from hair snaring include all sex-age classes. Our estimate of the DNA detection rate was likely conservative because 1) bears that have been previously live-captured may be less likely to be sampled in hair traps (Boulanger et al 2008a); 2) some known bears may have ranged beyond the study area boundary during our sampling season, making them unavailable for DNA detection; and 3) unrecorded deaths could have occurred before DNA sampling.…”

Sampling designs matching species biology produce accurate and affordable abundance indices

“…CMR studies often use 4 to 5 sampling sessions (Karanth & Nichols, 1998;Boulanger et al, 2008a;Boulanger et al, 2008b;Sawaya et al, 2012). We followed this practice, and simulated 5 sessions, each lasting 10 days (50 total days).…”

Sampling designs matching species biology produce accurate and affordable abundance indices

“…Since many studies sampling with grid configurations do not biologically justify the grid resolution chosen, they lack information to evaluate this heterogeneity violation (e.g. Woods et al, 1999; Boulanger et al, 2004;Mowat et al, 2005;Boulanger et al, 2008a; Kendall et al, 2008). In any event, for grid sampling, the solution relies on using small cell sizes to ensure that all individuals have a chance of being captured.…”