Management and conservation implications
Our results corroborate previous work suggesting uneven recovery of bobcats in Ohio (Prange and Rose 2020), but that bobcat density is relatively high in areas of suitable habitat. These findings highlight the successful self-repatriation of a large carnivore after decades of absence due to habitat recovery and improved land management practices. Bobcats were extirpated from Ohio by 1850 coinciding with massive forest clearing which reduced forest cover in the state from ~95% to 10% by the early 1900s. The development of the first state forestry agency (now Division of Forestry) in 1885 and continued efforts from this agency to purchase and protect Ohio forests resulted in a 2.5-fold increase in forested land (~33%) by 2011 (Widmann et al. 2014). These efforts in combination with the protection of bobcats under Ohio’s state list of threatened and endangered species were major factors contributing to the recovery of this species.
Estimates of bobcat density are needed to validate and supplement ongoing research into population viability for this recovering carnivore. Outcomes of bobcat population simulation models were heavily influenced by density (Dyck et al. In review) and our results can be incorporated into these models to project future population dynamics more accurately. These data can also be used by wildlife managers in combination with prior habitat suitability analysis (Popescu et al. 2021) to inform delineations of harvest zones and regional-specific quota limits to ensure sustainable management practices.
However, our results represent a snapshot in space and time during the continual recovery process of bobcats in the Midwest and effective bobcat management in Ohio requires continuous population monitoring, including periodic estimates of density as the population continues to expand (Popescu et al. 2021). Our study outlines a feasible, efficient, and fully transparent method for estimating bobcat density that can be repeated and applied to other areas and habitats. Results from this study are also relevant at a regional level for other recovering populations in the US Midwest and can be compared to indirect measures of density such as maximum clique analysis (Jones et al. 2022) in neighboring Indiana. Overall, the results from this study provides critical information on density for recovering bobcats, outline a feasible monitoring scheme to evaluate population density as recovery continues, and can be used in combination with a variety of other quantitative tools (e.g., population simulation models, habitat suitability models) to improve management and conservation decisions for recovering bobcats.