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.