Discussion
We provide the first assessment of bobcat density for the recovering
population in Ohio using eDNA from scats and SECR analysis. Bobcat
density differed between the AEP and Vinton-Zaleski study areas (17.9 ±
4.3 SE and 11.3 ± 2.9 SE bobcats/100 km2respectively). Our results support prior telemetry data which indicated
that bobcats in eastern Ohio (AEP area) had smaller home-ranges than
bobcats in southern Ohio (Vinton-Zaleski area) and thus could support a
higher density of individuals (Prange and Rose 2020) and camera trap
studies that indicated lower habitat occupancy by bobcats in the
Vinton-Zaleski area (Bencin 2018; Rich et al. 2018). However, the
mechanism/s driving these differences are not fully understood. Prange
and Rose (2020) hypothesized that differences in home-range sizes
between the two areas were a result of differences in food availability,
habitat quality, and body size as other studies have shown (Litvaitis et
al. 1986; Anderson 1987; Knick 1990). While Rich et al. (2018) found
landscape variables had little effect on occupancy, but coyote presence
had a strong negative influence on bobcat occupancy. Bobcats and coyotes
are sympatric throughout most of North America and interference
competition between the two predators is rare (Dyck et al. 2022).
However, bobcats and coyotes have only recently begun to co-occur in the
US Midwest (Deems and Pursley 1978; Woolf and Hubert 1998). The
concomitant recolonization by bobcats (Reding et al. 2012) and range
expansion by coyotes (Hody and Kays 2018) represents a unique situation
as species are co-occurring that have shared evolutionary histories but
have not coexisted in recent time. While our study provides additional
support for regional differences in bobcat density and abundance, it
does not address the mechanisms driving these differences, and
additional research into this topic is needed and would provide useful
insights for bobcat management.
When comparing density estimates across the bobcat range from SECR
analyses, our estimates for AEP are at the higher end of those reported
elsewhere, while estimates from Vinton-Zaleski are within the average
(Clare et al. 2015; Thornton and Pekins 2015; Rounsville Jr 2018; Morin
et al. 2018; Jacques et al. 2019; Greenspan et al. 2020). However, when
comparing SECR density estimates for another recovering Midwest bobcat
population, the estimates from both study areas are much higher than
those reported for Illinois (1.4 individuals/100 km2;
Jacques et al. 2019). There are several factors that may explain
differences in bobcat density between our study and Illinois.
First, there are distinct differences in the type and distribution of
habitat between the two studies. Our study areas are characterized
primarily by forested habitat (60.1% - 92.7%) with minor areas of
developed land (2.8% - 3.8%; Figure 1), while the study site in
Illinois was dominated by agriculture (53.2%) and pasture-hay (12.6%)
with a lesser-degree constituting forest (27.3%; Jacques et al. 2019).
Prior investigation into habitat suitability for the bobcat population
in Ohio indicated that bobcats select for forest habitat, natural
herbaceous vegetation habitat, and areas of low road density (Popescu et
al. 2021). Bobcat habitat suitability is also highest in southern and
southeast Ohio (Popescu et al. 2021), given our estimates are from high
suitability habitat it is likely that they represent the higher end of
density for the state.
Second, field methods between the two studies differed. Jacques et al.
(2019) used infrared-triggered cameras which are a common non-invasive
tool that can be used with capture-mark-recapture methods to estimate
density and abundance of bobcats and other felid species due to their
unique recognizable pelage patterns (Karanth and Nichols 1998; Silver et
al. 2004; Greenspan et al. 2020; Iosif et al. 2022). However, this
method requires quality images of both flanks of an animal and
sufficient variation in pelage/individual markings for observers to
accurately identify individuals. Jacques et al. (2019) deployed cameras
for 77 days and had 139 unique bobcat events but had to discard 18.7%
due to low image quality and a small subset (6.2%) of the remaining
images were classified as tentative identifications. Bobcat pelage
varies across their range (Young 1978; Croteau et al. 2012) and some
areas are known to have individuals with less distinct markings (Morin
et al. 2018).
Third, harvest of bobcats (hunting or trapping) is currently not
permitted in Ohio, while Illinois has had regulated hunting or trapping
season for bobcats since 2016 (Illinois DNR). The protected status of
bobcats in Ohio has played a role in their recovery and may act as a
mechanism for ‘mesopredator release’ allowing population densities to
exceed those in states without protection. Legal harvest accounts for a
large portion of bobcat mortality in exploited populations (Rolley 1985;
Knick 1990; Fuller et al. 1995; Chamberlain et al. 1999; Blankenship et
al. 2006) and therefore if harvest mortality is additive with other
sources of mortality it is expected that population size would be higher
for unexploited populations such as Ohio.