Discerning Biases in a Large Scale Mark–Recapture Population Estimate for Black Bears

Abstract

We derived 3 rangewide mark–recapture estimates for American black bears (Ursus americanus) in Minnesota, USA, over a 12-year period (1991–2002) to aid in management of this hunted population. We used tetracycline-laden baits to biomark 700–1,200 bears over an area of 85,000 km2 during each of 3 summer marking sessions. Ingested tetracycline produced long-lasting marks in bones and permanent marks in teeth. We collected bone and tooth samples from bears harvested in both the year of marking and the following year and examined them for tetracycline marks. For each marking event, the cumulative recapture sample totaled 3,400–4,800, or 14–30%, of the estimated population. Estimates of population size, derived from a Lincoln–Petersen (L-P) estimator, pertained to the time of marking; loss of animals from the population after marking was thus inconsequential, so long as losses were unbiased with respect to marking. We detected tetracycline marks in a greater proportion of samples collected in the year of marking than the following year. We surmised that the harvest included a disproportionate number of marked bears compared to unmarked bears in the year of marking, probably because both marking and harvest involved the bears' attraction to bait. After removal of these most vulnerable marked bears, the proportion of marked bears declined the next year. We used population reconstruction and a data-driven model to help gauge the potential magnitude and direction of biases resulting from sex–age heterogeneity in mark–recapture estimates based on data from the first year's harvest (biased low), second year's harvest (biased high), or some combination of the two. Uncertainty regarding yearly estimates hampered assessment of population trend. We recommend biomarking with >1 year of recapture data for large-scale population estimation; however, we suggest modifications to our methodology to obtain larger and more representative samples of the population, thereby increasing accuracy and precision.