Age-at-harvest models as monitoring and harvest management tools for Wisconsin carnivores

Abstract

Quantifying and estimating wildlife population sizes is a foundation of wildlife management. However, many carnivore species are cryptic, leading to innate difficulties in estimating their populations. We evaluated the potential for using more rigorous statistical models to estimate the populations of black bears (Ursus americanus) in Wisconisin, and their applicability to other furbearers such as bobcats (Lynx rufus). To estimate black bear populations, we developed an AAH state-space model in a Bayesian framework based on Norton (2015) that can account for variation in harvest and population demographics over time. Our state-space model created an accurate estimate of the black bear population in Wisconsin based on age-at-harvest data and improves on previous models by using little demographic data, no auxiliary data, and not being sensitive to initial population size. The increased accuracy of the AAH state-space models should allow for better management by being able to set accurate quotas to ensure a sustainable harvest for the black bear population in each zone. We also evaluated the demography and annual harvest data of bobcats in Wisconsin to determine trends in harvest, method, and hunter participation in Wisconsin. Each trait of harvested bobcats that we tested (mass, male:female sex ratio, and age) changed over time, and because these were interrelated, and we inferred that harvest selection for larger size biased harvests in favor of a) larger, b) older, and c) male bobcats by hound hunters. We also found an increase in the proportion of bobcats that were harvested by hound hunting compared to trapping, and that hound hunters were more likely to create taxidermy mounts than trappers. We also found that decreasing available bobcat tags and increasing success have occurred over time, and correlate with substantially increasing both hunter populations and hunter interest.