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

Boulanger, John; Kendall, Katherine; Stetz, Jeffrey; Roon, David; Waites, Lisette; Paetkau, David

We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark–recapture data from grizzlybears (Ursus arctos). We improved population estimates by incorporating additional DNA‘‘captures’’ of grizzly bears obtained by collecting hair from unbaited bear rub treesconcurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersenestimator with hair snag captures as the initial session and rub tree captures as the recapturesession and develop an estimator in program MARK that treats hair snag and rub treesamples as successive sessions. Using empirical data from a large-scale project in the greaterGlacier National Park, Montana, USA, area and simulation modeling we evaluate thesemethods 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 butmore precise estimates if capture and recapture rates are reasonably high for both methods.Simulation results suggest that estimators are potentially affected by correlation of captureprobabilities between sample types in the presence of heterogeneity. Overall, closed populationHuggins-Pledger estimators showed the highest precision and were most robust to sparse data,heterogeneity, and capture probability correlation among sampling types. Results alsoindicate that these estimators can be used when a segment of the population has zero captureprobability for one of the methods. We propose that this general methodology may be usefulfor other species in which mark–recapture data are available from multiple sources.

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

Series

Collections