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Domestic cats (Felis catus) have caused the extinction of many island species and are thought to kill many billions of birds and mammals in the continental United States each year. However, the spatial distribution and abundance of cats and their risk to our protected areas remains unknown. We worked with citizen scientists to survey the mammals at 2,117 sites in 32 protected areas and one urban area across 6 states in the eastern United States using camera traps. We found that most protected areas had high levels of coyote (Canis latrans) activity, but few or no domestic cats. The relative abundance of domestic cats in residential yards, where coyotes were rare, was 300 times higher than in the protected areas. Our spatial models of cat distribution show the amount of coyote activity and housing density are the best predictors of cat activity, and that coyotes and cats overlap the most in small urban forests. Coyotes were nocturnal at all sites, while cats were nocturnal in protected areas, but significantly more diurnal in urban sites. We suggest that the ecological impact of free-ranging cats in the region is concentrated in urban areas or other sites, such as islands, with few coyotes. Our study also shows the value of citizen science for conducting broadscale mammal surveys using photo-vouchered locations that ensure high data quality.
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Cats are rare where coyotes roam
Roland Kays,* Robert Costello, Tavis Forrester, Megan C. Baker, Arielle W. Parsons, Elizabeth
L. Kalies, George Hess, Joshua J. Millspaugh, and William McShea
North Carolina Museum of Natural Sciences, 11 W. Jones St., Raleigh, NC 27601, USA (RK, AWP)
Department of Forestry & Environmental Resources, North Carolina State University, Campus Box 7646, Raleigh, NC 27695,
Smithsonian National Museum of Natural History, 10th and Constitution Ave. NW, Washington, DC 20560, USA (RK, RC)
Smithsonian Conservation Biology Institute, 1500 Remount Rd., Front Royal, VA 22630, USA (TF, MCB, WM)
Department of Fisheries and Wildlife Sciences, 302 Anheuser-Busch Natural Resources Building, University of Missouri,
Columbia, MO 65211, USA (ELK, JJM)
* Correspondent:
Domestic cats (Felis catus) have caused the extinction of many island species and are thought to kill many
billions of birds and mammals in the continental United States each year. However, the spatial distribution and
abundance of cats and their risk to our protected areas remains unknown. We worked with citizen scientists to
survey the mammals at 2,117 sites in 32 protected areas and one urban area across 6 states in the eastern United
States using camera traps. We found that most protected areas had high levels of coyote (Canis latrans) activity,
but few or no domestic cats. The relative abundance of domestic cats in residential yards, where coyotes were
rare, was 300 times higher than in the protected areas. Our spatial models of cat distribution show the amount of
coyote activity and housing density are the best predictors of cat activity, and that coyotes and cats overlap the
most in small urban forests. Coyotes were nocturnal at all sites, while cats were nocturnal in protected areas, but
significantly more diurnal in urban sites. We suggest that the ecological impact of free-ranging cats in the region
is concentrated in urban areas or other sites, such as islands, with few coyotes. Our study also shows the value
of citizen science for conducting broadscale mammal surveys using photo-vouchered locations that ensure high
data quality.
Key words: camera trap, Canis latrans, citizen science, Felis catus, invasive species, protected areas
© 2015 American Society of Mammalogists,
Free ranging domestic cats (Felis catus) are a major conserva-
tion concern because of their predation on native wildlife (Loss
et al. 2013). This situation is worse on oceanic islands, where
prey species typically evolve without mammalian predators
and have little innate ability to avoid cats. Cats have caused the
extinction of 18 small terrestrial island vertebrates and are the
primary extinction risk for another 36 island vertebrates that are
now critically endangered (Medina et al. 2011). In island sys-
tems with simple food web structure, the addition of a predator
species can severely shift community dynamics.
A recent review of cat predation in the United States also
highlighted the conservation problems they pose to continen-
tal ecosystems. By combining typical kill rates and country-
wide cat population estimates, Loss et al. (2013) estimated that
domestic cats kill 1.4–3.7 billion birds and 6.9–20.7 billion
mammals annually. Free-ranging, un-owned cats, as opposed
to pet cats, are thought to cause the majority (69% for birds and
89% for mammals) of this mortality.
However, the spatial extent and ecological significance of
this predation on native species remains unknown. Exactly
where the more than 74 million pet cats (Shepherd 2012),
and additional un-owned cats, hunt in the United States is a
critical question. We might expect cats using residential areas
to hunt primarily common prey species that are of lower con-
servation concern. However, if they penetrate public lands
designed to protect native biodiversity, management action
may be needed to reduce their impact. Two tracking studies
of urban cats found them to avoid nature preserves, presum-
ably because of abundant predators populations (Kays and
DeWan 2004; Gehrt et al. 2013). Less is known about cats
outside of developed areas, where most important protected
natural areas are, although one tracking study found that
Journal of Mammalogy, 96(5):981–987, 2015
un-owned rural cats frequently used natural habitats (Horn
et al. 2011).
We worked with citizen scientists to use camera traps to sur-
vey cats and native wildlife in 32 protected areas across 6 states
in the eastern United States and in residential yards and small
urban forests (some along greenway trails) in Raleigh, North
Carolina. If coyotes in protected areas are negatively influenc-
ing cats, as seen in urban areas (Kays and DeWan 2004; Gehrt
et al. 2013), then we expect to find a negative relationship
between coyote and cat detections. The intensity of this compe-
tition between predators is not only interesting ecologically, but
also important for conservation managers concerned about the
potential negative impacts of cats on native prey.
Materials and Methods
Citizen science camera trap surveys.—From 2012 to 2014, we
recruited and trained 486 volunteer citizen scientists, under-
graduate students, and middle school students to deploy camera
traps across the study area. Most protected area cameras were
run from April to November, while the Raleigh area cameras
were run year-round. Camera traps set in protected areas were
deployed in groups of 3, with one camera placed on a hiking
trail, one 50 m from the trail, and one 100–200 m from the
trail. Camera traps along Raleigh’s greenways were set in pairs
with one camera on the trail and one approximately 25 m off-
trail in nearby wooded areas. Backyard camera traps were set
to minimize pictures of resident humans, typically along the
edge or towards the back of the yard, as described in our ear-
lier work (Kays and Parsons 2014). Volunteers used Reconyx
(RC55, PC800, and PC900; Reconyx, Inc. Holmen, Wisconsin)
and Bushnell (Trophy Cam HD, Bushnell Outdoor Products,
Overland Park, Kansas) camera traps that were equipped with
an infrared flash. These cameras all function similarly in hav-
ing highly sensitive triggers and quick trigger times, allowing
them to record animals passing rapidly in front of the camera
without the addition of bait. Volunteers attached the cameras to
trees at 40 cm above the ground and returned after 3 weeks to
retrieve the images and move the cameras. Cameras were set
on maximum trigger sensitivity and recorded multiple photo-
graphs per trigger, re-triggering immediately if the animal was
still in view.
Volunteers used custom eMammal software to provide ini-
tial identification of all wildlife species in camera trap images,
enter camera metadata (e.g., location), and uploaded pictures
to our database. We then reviewed the quality of all data using
the eMammal Expert Review Tool, confirming or correcting all
volunteer species identifications, and evaluating camera setup
from the view of the camera. After expert review, all data were
downloaded to a Smithsonian data repository for storage.
We grouped consecutive photos into sequences if they were
< 60 s apart and used these sequences as independent records
for subsequent analysis of detection rate and daily activity pat-
terns. Cats photographed from protected areas were identified
to individuals based on coat color pattern independently by 2
reviewers, who agreed on 100% of identifications. The Raleigh
area cats were not identified to individual because most cam-
eras were too widely scattered to obtain recaptures of the same
animals in different cameras.
Environmental variables.—We used ArcMap (ESRI 2012)
to obtain 2 environmental variables for each of our camera
sampling points: housing density and coyote (Canis latrans)
relative abundance. We used the Silvis housing density dataset
(Hammer et al. 2004) to calculate the average housing density
(houses/km2) at 2 spatial scales for each camera using a 250-m
and 5-km radius. We also used a 5-km buffer around each cam-
era and calculated the average coyote detection rate (count/day)
from our cameras within each buffer. On average, these 5-km
buffers included 73 cameras (SE = 1).
Statistical models.—We used spatial statistics (R pack-
age GeoR— Ribeiro and Diggle 2015) to evaluate if detec-
tion rates spatially autocorrelated using a semivariogram to
calculate a minimum distance at which spatial autocorrela-
tion becomes negligible (semivariogram range). We fitted a
semivariogram model to each empirical semivariogram using
weighted least squares and assessed goodness-of-fit by the
minimized sum of squares. We examined detections for cats
and coyotes across sites to consider removing outliers that
could represent a den or feeding station with very high detec-
tion rates. To evaluate the spatial determinants of cat distribu-
tion, we fitted a Poisson count model with a log-link to predict
the count of cat detections, offset by camera deployment
duration (n = 2,117). We used 6 covariates as fixed effects:
habitat type (dummy variable for yard or not yard, small
urban forests, protected areas), latitude and longitude of site,
average housing density (houses/km2) in a 250-m and 5-km
radius of the site, rate of coyote detection at the site (total
count/number of camera days), and average rate of coyote
detection from all cameras within a 5-km radius of the site.
We tested all covariates for multicollinearity using a correla-
tion matrix in Program JMP and considered any correlation
below 30% to be acceptable. We ran our model in a Bayesian
framework using OpenBUGS (Thomas et al. 2006) and R (R
Development Core Team 2011). Our model included a term
for extra-Poisson variation (Breslow 1984) to account for
overdispersion and excess zeros in our dataset. We compared
a suite of 18 covariate combinations which we felt best tested
potential relationships affecting cat distribution. We assessed
relative model deviance using deviance information criterion
(DIC) and fit of the top model using Pearson’s goodness-of-fit
statistic drawn from the posterior distribution (Johnson 2004).
We calculated posterior means and 95% Bayesian credibility
intervals using the most parameterized model within the top
4 DIC points. We separately assessed the significance of dif-
ferences in the intensity of use of different habitat types by
cats and coyotes using a Kruskal–Wallis rank-sum test and
Mann–Whitney U-test for pairwise comparisons in Program
JMP (SAS Institute 2012).
To estimate probabilities of occupancy, we used a single sea-
son occupancy model (MacKenzie et al. 2006) and estimated
detection probability (P), defined as the probability of detect-
ing an occurring species at a site and occupancy (ψ), defined
as the expected probability that a given site is occupied. For
each species (cat and coyote), we used RMark (Laake 2011)
in R (R Development Core Team 2011) to build and fit models
for each of our covariates, including no covariates (i.e., assum-
ing probabilities were constant across the sites), each combined
with a null model of detection. For each model, we computed
Akaike’s Information Criterion adjusted for small sample size
(AICc), ΔAICc, and Akaike weights (wij, weight of covariate i
for species j) (Burnham and Anderson 2002) and used these
values to assess model fit. We used the most parsimonious
model of occupancy probability for cats (containing the “habi-
tat” variable) to estimate the probability of occupancy in each
habitat type.
We created daily animal activity patterns by fitting density
functions based on circular statistics to independent animal
detections (MacKenzie et al. 2006) using package overlap
(Meredith and Ridout 2014) in R (R Development Core Team
2011). We tested for significant differences in activity patterns
using Watson’s 2-sample test for homogeneity in package
CircStats (Lund and Agostinelli 2014) in R (R Development
Core Team 2011).
Mammal surveys.—With 42,874 camera nights of survey effort
across 1,953 locations in 32 protected areas, we obtained 52,863
detections of native wildlife. This same effort returned only 55
detections of cats (0.0012 detections/day). Our semivariogram
showed that autocorrelation for cat rate became negligible after
only 3 m, indicating spatial independence. One camera had very
high detection rates for coyotes, probably representing a den
site or feeding station and so was removed from the analyses.
Cats were detected at 31 camera sites scattered through half of
the protected areas surveyed (Fig. 1; Supporting Information
S1), resulting in an occupancy rate (ψ) of 0.027 (SE = 0.0060)
across the region. Based on coat coloration, we were able to
identify all cats from protected areas to individual; in 14 of
the 32 protected areas, we detected only a single cat (some
Fig. 1.—Distribution of cats detected across 32 protected areas: 50% had no cats (Felis catus) detected, while 44% had just 1 cat, and 2 (6%) had
multiple cats. The 2 map insets are at the same scale and show typical camera arrangement and detection patterns for cats in rural (left, Stone
Mountain State Park) and urban protected areas (right, Rock Creek Park).
photographed multiple times). In the 2 protected areas with
the highest levels of cat activity, we detected 5 or 6 individual
cats photographed multiple times (Supporting Information S1).
Coyotes (Supporting Information S2) were detected 33 times
more often than cats in protected areas (0.044/day), occurred at
a higher level of occupancy (ψ = 0.49 ± 0.020), and were found
in all but one of the 32 protected areas.
We also used camera traps to survey mammals at 171 loca-
tions in Raleigh, North Carolina for a total of 2,760 camera
nights: including 60 sites in residential yards, and 111 in
small urban forests, 45 of which were along greenway trails.
Domestic cats (Supporting Information S3) were detected
more often on trail than off-trail, but were found at the high-
est rates in yards, followed by small urban forests, which were
both much higher than in larger protected areas (Fig. 2; Tables
1 and 2). Indeed, residential yards (0.44 detections/day) had
300 times more cat activity than protected areas (0.11 detec-
tions/day). Coyotes were detected in all habitats but were rare
in residential areas. Similarly, probability of occupancy for cats
was highest in yards (0.53 ± 0.067), followed by small urban
forests (0.27 ± 0.044), with the lowest rates in protected areas
(0.016 ± 0.0029). Coyotes had the lowest probability of occu-
pancy in yards (0.085 ± 0.041), with higher rates in small urban
forests (0.57 ± 0.061) and protected areas (0.35 ± 0.013).
Spatial and temporal model results.—None of our covari-
ates were highly correlated, all pairwise correlations fell
below 30%. Our top models predicting cat distribution across
all sites fit well (χ2 > 0.4). Parameter estimates from the most
parameterized model within the top 4 DIC points showed that
coyote activity levels and housing densities had the stron-
gest effects on cat detections (Tables 1 and 2). Housing den-
sity was included in only one of the top models (Table 1),
showing it was less important than coyote activity. Although
habitat was not an important covariate in the top multivariate
models of cat distribution, we note that cat detection rate dif-
fered significantly across these categories (Kruskal–Wallis test,
χ2 = 502.35, P < 0.0001). Cat rate was significantly higher
in yards than small urban forests (mean difference = 24.82,
SE = 6.76, Z = 3.67, P = 0.0002) and protected areas (mean dif-
ference = 508.17, SE = 22.76, Z = 22.33, P < 0.0001). Cat rate
was also significantly higher in small urban forests than pro-
tected areas (mean difference = 254.91, SE = 16.89, Z = 15.09,
P < 0.0001; Fig. 2). The intensity of use by coyotes across these
3 habitats was also significantly different (Kruskal–Wallis test,
χ2 = 31.1927, P < 0.0001, protected areas versus small urban
forests P < 0.0001, yards versus small urban forests P < 0.0001,
yards versus protected areas P = 0.001).
Our distribution model found a strong negative relationship
between the detection rate of coyotes at the 5-km scale and
cats across all sites (Tables 1 and 2; Supporting Information
S1). Additional support for the hypothesis that coyotes exclude
cats from protected areas comes from the only protected area
in which we found no coyotes, Gambrill State Park, which also
had the highest level of cat detections; the detection rate there
(0.023/day) was 3 times higher than the next most cat-rich
protected area.
Fig. 2.—Average detection rates of cats and coyotes (Canis latrans)
recorded by camera traps set in different habitats including 32 pro-
tected areas in the eastern United States and 177 urban sites around
Raleigh, North Carolina. Error bars show SE of the mean. Rates
were statistically different across habitats for both coyotes and cats
(Kruskal–Wallis test, P < 0.0001).
Table 1.—Model selection for describing variation in cat (Felis
catus) distribution as ranked by the deviance information criterion
(DIC). The yard variable is a categorical classification (yard, not
yard), the house variables are measures of housing density, and the
coyote (Canis latrans) variables are detection rates from camera traps.
LatXLong is a spatial term to account for broadscale geographic trends.
Model DIC Delta DIC
Coyotes 5 km 638 0
Coyotes 5 km + House 5 km 639 1
Coyotes at site 644 6
Null 645 7
Houses 5 km 645 7
LatXLong 650 12
LatXLong + Houses 5 km 651 13
Houses 250 m 651 13
LatXLong + Coyotes 5 km 652 14
Yard + Coyotes 5 km 653 15
LatXLong + Yard + Houses 250 m + Houses
5 km + Coyotes at site + Coyotes 5 km
654 16
Yard 655 17
Yard + Houses 5 km 655 17
Yard + Coyotes 5 km + Houses 5 km 656 18
LatXLong + Yard + Coyotes 5 km + Houses 5 km 656 18
LatXLong + Yard + Coyotes at site + Houses 250m 657 19
LatXLong + Yard + Coyotes 5 km 659 21
LatXLong + Yard 660 22
Table 2.—Parameter estimates results for Coyote (Canis latrans) 5
km + Housing Density 5 km model predicting cat (Felis catus) use of
protected and urban areas. Both variables were considered significant
because the 95% credible intervals did not include 0.
Variable Posterior mean 95% Credible interval
House 5 km 0.79 0.35, 1.20
Coyote 5 km −1.46 −2.08, −0.86
Coyotes and cats in protected areas showed nocturnal activ-
ity patterns that were not different from each other (Watson’s
U2 = 0.077, P = 0.50) but were both different than the more
diurnal activity of urban cats (coyotes-urban cats: Watson’s
1 = 2.242, P < 0.0001; park cats–urban cats: Watson’s
1 = 0.300, P = 0.005; Fig. 3).
Our large-scale survey shows that free-ranging cats are not
widespread in large protected areas in the eastern United States.
We detected no domestic cats in half of the 32 protected areas
we surveyed, and more than 1 individual cat in only 2 of them.
This is the first study to address cats in North American pro-
tected areas and suggests that they are not a widespread con-
servation concern for the larger protected areas in this region.
We found evidence that predators may be preventing cats
from colonizing protected areas, as most cat-free areas had
high activity rates of coyotes. Additionally, our measures of
coyote activity were negatively associated with cat activity in
our spatial model. Finally, the only protected area in which we
detected no coyotes had, by far, the highest levels of cat activ-
ity. Coyotes have been shown to prey on cats (Quinn 1997) and
prevent cats from using some urban natural areas (Crooks and
Soule 1999; Gehrt et al. 2013), but this is the first study to docu-
ment the partitioning of space between coyotes and cats across
large scales. The virtual absence (one or fewer) of cats in 94%
of the protected areas we surveyed suggests that there is a low
threshold level of coyote activity that effectively prevents cats
from using an area, and that most of the relatively large, pro-
tected areas we surveyed were above that level.
Compared to these protected areas, we detected many more
cats in our surveys of residential yards and small urban forests,
showing the extent to which cat activity is focused in urban
areas. Not surprisingly, cats were most common in yards,
which had 300 times more cat activity than protected areas.
This shows the limited degree to which most urban cats venture
past their neighborhoods, which is similar to what was found
for radio-tracked pet cats (Kays and DeWan 2004). Habitat type
was not featured in our top multivariate distribution models,
presumably because coyote distribution was a better predictor,
and was also correlated with habitat types (Fig. 2).
Why populations of cats and coyotes have virtually no over-
lap in protected areas but substantial spatial overlap in small
urban forests remains an important question. A tracking study
in Chicago also found spatial overlap between coyotes and cats
in small urban forests, although their core areas were separate
(Gehrt et al. 2013). We suspect that the fragmented arrange-
ments of natural and developed areas typical of American cities
may provide cats with sufficient nearby refuges they can access
if they encounter a predator. Our data confirm that residential
yards in Raleigh are safe havens for cats, with coyotes detected
in only 5 of the 64 yards we surveyed. This may be different
from some cities where coyotes are more urbanized (Gehrt
et al. 2009). The increased diurnal activity we found in urban
cats could also be a strategy, by cats or their owners, to avoid
nocturnal coyotes.
We used our camera trap photos as measures of local cat
relative abundance in 3 different ways, all showing the same
results, with cats rare in larger protected areas, present in small
urban forests at varying levels, and common in residential yards.
Because our camera traps were unbaited and simply recorded
the frequency that cats and coyotes walked by, we could use
this as a measure of relative abundance, as well as a measure
of the ecological impact of these 2 predators (Rowcliffe et al.
2008). Our occupancy models mirrored our results based on
raw detection rate. Finally, for the protected areas, we were
able to identify individual cats based on coat coloration, con-
firming that few individuals (typically one) were present.
We were not able to evaluate the origin of the cats we photo-
graphed, i.e., whether they were pets, wide-ranging feral cats,
or from a cat colony. Free-ranging cats are thought to prey on
substantially more native prey than pet cats (Loss et al. 2013),
and the establishment of localized cat colonies is of special
conservation concern due to the incredibly high predator den-
sities that can result, in addition to disease concerns (Clarke
and Pacin 2002). We did not specifically target sampling of cat
colonies and, given the relatively low cat detection rates, appar-
ently did not detect any within the protected areas or small
urban forests we surveyed. We were surprised to detect single
cats in the middle of large protected areas, far from houses or
neighborhoods. We think this detection rate is too low to rep-
resent truly feral populations, and suspect that some of these
could be cats that were abandoned at the parks by their own-
ers. Another alternative is that these were unusual pet cats that
moved much further from their house than is typical, which has
also been observed in one radio-tracked cat (Kays and DeWan
2004). Such wandering cats in protected areas might not have
knowledge of the local coyote populations, which could also
explain why they are temporally overlapping with them in
being primarily nocturnal.
The large scale of our survey, with more than 2,000 sample
points across 6 states, shows that our main result of few to no
cats in protected areas is a consistent pattern across the region.
This also shows the benefit of working with volunteer citizen
Fig. 3.—Daily activity patterns showing high overlap for coyotes
(Canis latrans) and cats (Felis catus) in protected areas and less in
urban areas, where cats are more diurnal. The activity patterns of coy-
otes from protected and urban areas were not different, and thus are
combined into one line.
scientists to scale-up this mammal survey (Cooper et al. 2007),
allowing us to not only sample more parks, but also efficiently
survey urban areas. By reviewing all photographic data col-
lected by citizens, we were able to ensure the high quality of the
data, unlike other citizen science work, which may not collect
vouchers (Cooper et al. 2007).
Because our urban results were from only one city, addi-
tional research will be needed to evaluate how predators and
cats interact in the varied urban landscapes around the coun-
try, including those with more urbanized coyotes (Gehrt et al.
2013), or even larger predators. Additional surveys of cats in
protected areas around the world with varied predator commu-
nities could also shed more light on which situations require
active management to reduce cats (Loyd and Devore 2010) and
which can allow their native predators to keep the cats out.
We thank all of our 486 volunteers for their hard work collect-
ing data for this study, including Master Naturalists, 3 North
Carolina State University undergraduate classes, Prairie
Ridge Ecostation, and students from Exploris Middle School.
For their field assistance and volunteer coordination, we thank
A. Rogers, J. Pearson, K. Hollifield, M. Davies, S. Hartley,
B. Davis, G. Schneider, D. Walker, D. Engebretson, J. Hall,
D. Todd, R. Gubler, S. Henry, R. Hughes, B. Yeaman,
M. Milton, A. Landsman, C. DiAntonio, D. Stapleton,
E. Kelley, L. Donaldson, M. Spurrier, D. Nisbet, B. Thompson,
C. Croy, M. Smith, L. Potts, V. Lebsock, J. Palumbo, and
the staff of the National Parks Service, United States Fish
and Wildlife Service, United States Forest Service, North
Carolina State Parks, The Nature Conservancy, North Carolina
Wildlife Resources Commission, Tennessee State Parks,
Tennessee Division of Forestry, South Carolina State Parks,
Virginia State Parks, Virginia Division of Game and Inland
Fisheries, Western Virginia Water Authority, the Wintergreen
Nature Foundation, Maryland State Parks, and Raleigh, Parks,
Recreation and Cultural Resources. For help reviewing photo-
graphs, we thank N. Fuentes, S. Higdon, C. Bland, T. Perkins,
L. Gatens, R. Owens, R. Gayle, C. Backman, K. Clark,
J. Grimes, and J. Simkins. We thank R. Montgomery for
input on study design. This work was conducted with fund-
ing from the National Science Foundation grant #1232442
and #1319293, the VWR Foundation, the US Forest Service,
the North Carolina Museum of Natural Sciences, and the
Smithsonian Institution.
Supporting Information
The Supporting Information documents are linked to this
manuscript and are available at Journal of Mammalogy online
( The materials consist of data
provided by the author that are published to benefit the reader.
The posted materials are not copyedited. The contents of all
supporting data are the sole responsibility of the authors.
Questions or messages regarding errors should be addressed
to the author.
Supporting Information S1.—Summary of the cats and coy-
otes detected by citizen science camera trap surveys of 32 pro-
tected areas across six states and Washington, DC. Rates are
Supporting Information S2.Camera trap picture of a pack
of coyotes hunting Sand Hills State Forest, South Carolina.
Supporting Information S3.Camera trap picture of a
domestic cat walking on the Raleigh greenway through a small
urban forest in North Carolina.
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Associate Editor was Bradley J. Swanson.
... Moreover, coyotes fulfill the role of apex predator in many cities (Gehrt & McGraw, 2007), thereby affecting the distribution and abundance of other urban mesocarnivores (Fascione et al., 2004;Greenspan, Nielsen & Cassel, 2018). For example, there is strong evidence that coyotes play a role in reducing free-ranging domestic cat populations (Crooks & Soulé, 1999;Grubbs & Krausman, 2009;Brashares et al., 2010;Cove et al., 2012;Kays et al., 2015). Coyotes are therefore an excellent model organism through which to study the effects of urbanization on predator-prey interactions and relative habitat use. ...
... One factor that may contribute to coyote-cat conflicts in southern California is the relative site use and site overlap between each species. Coyote presence and/or abundance may have a significantly negative effect on free-ranging cat distributions (Crooks & Soulé, 1999;Sims et al., 2008;Cove et al., 2012;Kays et al., 2015), with coyotes preferentially occupying less developed areas across urban to rural gradients, while domestic cats select for more urbanized and residential spaces (Gehrt et al., 2013;Vanek et al., 2021). However, small-scale natural areas within cities, such as urban green spaces, may also influence coyote and free-ranging cat occupancy. ...
... In addition to similarities in spatial use, temporal overlap between domestic cats and coyotes could further exacerbate domestic cat mortality in Culver City. Typically, coyotes display nocturnal activity patterns in urban environments, while domestic cats in urban areas are more diurnal (Kays et al., 2015). Given the abnormally high rates of cat depredation by coyotes in southern California (Larson et al., 2015;Larson et al., 2020), we predict that cats in Culver City may exhibit more nocturnal activity, thus demonstrating temporal overlap with coyotes across urban green spaces and residential sites. ...
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As habitat generalists, urban coyote ( Canis latrans ) populations often utilize an abundance of diverse food sources in cities. Within southern California, domestic cats ( Felis catus ) comprise a higher proportion of coyote diets than in other studied urban areas throughout the United States. However, it is unclear which ecological factors contribute to higher rates of cat depredation by coyotes in this region. While previous research suggests that coyote presence may have a negative effect on free-ranging domestic cat distributions, few studies have determined whether urban green spaces affect coyote or free-ranging domestic cat occurrence and activity within a predominantly urbanized landscape. We placed 20 remote wildlife cameras across a range of green spaces and residential sites in Culver City, California, an area of Los Angeles County experiencing pronounced coyote-domestic cat conflict. Using data collected across 6 months from 2019–2020, we assessed the influence of green space and prey species ( i.e ., cottontail rabbits ( Sylvilagus spp.) and domestic cats) on coyote habitat use and activity. Coyotes exhibited a preference for sites with higher amounts of green space, while domestic cat habitat use was high throughout our study region. Although cottontail rabbit habitat use was also highly associated with urban green space, neither cottontails nor domestic cats appeared to temporally overlap significantly with coyotes. Unlike other cities where coyotes and domestic cats exhibit strong habitat partitioning across the landscape, domestic cats and coyotes spatially overlapped in green space fragments throughout Culver City. We suggest that this pattern of overlap may be responsible for the frequent cases of domestic cat depredation by coyotes in Culver City.
... As such, humans Introduction Free-roaming domestic cats (Felis catus; hereafter, "cats") impact native wildlife through predation and the transmission of disease, posing serious threats to native wildlife (Fredebaugh et al., 2011;Loss et al., 2013;Loyd et al., 2013;Cove et al., 2018a;Dubey et al., 2020). Likewise, native wildlife can also pose risks to cats such as predation by native species like coyotes (Kays et al., 2015;Larson et al., 2020;Tan et al., 2020) and the transmission of rabies (Roseveare et al., 2009;Gehrt et al., 2013). These bidirectional risks are absent when cats are kept indoors, but manifest themselves when cats are allowed to roam freely outdoors. ...
... For instance, predation by cats is greatest near habitat edges (Kays and DeWan, 2004;Herrera et al., 2022;Pirie et al., 2022), and predation rates fluctuate based on the season and time of day (Thomas et al., 2012;Loyd et al., 2013;Seymour et al., 2020). Likewise, cats face less predation risk where native predators are scarce (Gehrt et al., 2013;Kays et al., 2015), and predation risk is presumably greater for cats whose diel patterns match those of native predators. Similarly, the risk of cat-wildlife disease transmission increases with heightened interactions between species (Beran and Frith, 1988;Theimer et al., 2015). ...
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Free-roaming domestic cats (Felis catus) are known to pose threats to ecosystem health via transmission of zoonotic diseases and predation of native wildlife. Likewise, free-roaming cats are also susceptible to predation or disease transmission from native wildlife. Physical interactions are required for many of these risks to be manifested, necessitating spatial and temporal overlap between cats and wildlife species. Therefore, knowledge of the location and extent of shared habitat and activity periods would benefit management programs. We used data from a 3-year camera trap survey to model species-specific occupancy and identify landscape variables that contribute to the distribution of free-roaming domestic cats and eight native mammal species in Washington, DC. (USA). Our analysis includes five species that are common prey items of domestic cats, and three species that are potential disease vectors or are otherwise known to be a risk to cats. We then predicted the probability of occupancy and estimated the probability of spatial overlap between cats and each native wildlife species at multiple scales. We also used kernel density estimations to calculate temporal overlap between cats and each native wildlife species. Across spatial scales, occupancy for potential disease vector species was generally positively correlated with canopy cover and open water. Prey species were also generally positively correlated with canopy cover, but displayed negative associations with human population density and inconsistent associations with average per capita income. Domestic cat occupancy was negatively correlated with natural habitat characteristics and positively correlated with human population density. Predicted spatial overlap between domestic cats and native wildlife was greatest for potential disease vector species. Temporal overlap was high (>0.50) between cats and all but two native wildlife species, indicating that temporal overlap is probable wherever species overlap spatially. Our findings indicate that the risk to and from domestic cats varies across urban landscapes, but primarily arises from human activities. As such, humans are implicated in the negative outcomes that result from cats interacting with wildlife. Data-driven management to reduce such interactions can aid in cat population management, biodiversity conservation, and public health campaigns.
... The adjacent land use is rural residential, which may explain the presence of domestic cat and human-adapted native species (Wang et al. 2015). As with the US 101 Aromas Hills undercrossings, the presence of domestic cats here may also indicate a lack of predators and/or degraded habitat for native predators such as bobcat, coyote, gray fox, and mountain lion because of development (Grubbs and Krausman 2010, Kays et al. 2015, Wang et al. 2015. ...
Technical Report
This study assessed ecological connectivity between the Southern Santa Crus, Gabian and Diablo mountain ranges, with a specific focus on the Aromas Hills and Upper Pajaro Valley. We assessed the need for improved permeability of the region’s highways and identified specific recommendations for improving connectivity.
... Free-roaming domestic cats (Felis catus; hereafter 'cats') are both common and found at high densities in urban areas worldwide (Hansen et al., 2018;Legge et al., 2016;Gehrt et al., 2013). Cats with outdoor access are subjected to numerous risks, including possible vehicle collisions (Rochlitz, 2003), heightened exposure to zoonotic disease (Gehrt et al., 2013;Roseveare et al., 2009), exposure to toxins (Tan et al., 2020;Berny et al., 2010), increased potential for abuse (Bonela Gomes et al., 2021), and possible predation by native predator species (Larson et al., 2020;Tan et al., 2020;Kays et al., 2015). Similarly, cats pose a risk to wildlife through the transfer of zoonotic disease (Lehrer et al., 2010) and direct predation (Cove et al., 2018;Loss et al., 2013;Loyd et al., 2013). ...
The ecological impact of free-roaming domestic cats (Felis catus) is well-studied. However, despite receiving considerable attention in both the scientific and popular literature, predation behavior is rarely an explicit consideration when developing cat population management plans. We used motion-activated wildlife cameras to document predation events by cats in Washington, D.C. (U.S.A), and assessed the relationships between predation and local environmental characteristics. Our analyses reveal that predation by cats is greatest where supplemental food is most abundant, and that the probability of a cat preying upon a native species increases closer to forest edges. Conversely, we found that the probability of a cat depredating a non-native brown rat increases with increasing distance from forest edges. Therefore, we recommend the implementation of cat exclusionary buffer zones around urban forests and that free-roaming domestic cat management policies explicitly consider the spatial location of cat-feeding sites. Our findings provide a data-driven approach to free-roaming cat management.
... We also found a positive correlation between cat and red fox presence. Perhaps the mere presence of cats could attract predators, such as foxes (Kays et al., 2015;Ordeñana et al., 2010;Shochat et al., 2004). By design, our camera trap survey targeted medium to large-sized mammals (e.g., skunks and larger; Gallo et al., 2017;O'Connell et al., 2010), which cats rarely prey upon (Baker et al., 2005;Loss et al., 2013). ...
Increased urbanization drives habitat loss, yet residential land-use represents significant habitat potential for mammals and could provide connectivity between patches of green spaces. Diverse mammal communities exist across urban gradients, but it is unclear how mammal community composition varies within residential lands. We conducted a camera trapping study in 36 residential yards across an urban gradient to assess the relative contributions of the degree of urbanization in the land-use context versus parcel habitat features, such as vegetation structure, on mammal community diversity and composition. We hypothesized that land-use context would more strongly influence mammal community metrics than parcel features, and that there would be species-specific differences in response. We detected 14 non-domesticated mammal species and found that species richness peaked in the suburbs and tapered off at the rural and urban ends of the gradient in accordance with patterns seen in other taxonomic groups, yet rarely quantified in mammals. Large-bodied interior forest species were associated with rural sites, urban-dwelling species were associated with urban sites, and suburban sites had an overlap of species types. Although composition of mammal species in residential yards appears to be strongly related to land-use context, which is often outside of residents’ control, management of parcel habitat features such as retention of large mature trees may facilitate connectivity between patches of habitat across urbanizing landscapes. Informed residential yard management remains an important tool for urban wildlife management in an era of global change.
... A histogram of time intervals between consecutive photos revealed that 99.6% of photos were captured either <5 min apart or >60 min apart (Supplementary Materials, Figure S1). To minimise temporal autocorrelation, we grouped consecutive photos that were <5 min apart to create independent records for subsequent analysis [50]. ...
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Abstract: Feral cats are difficult to manage and harder to monitor. We analysed the cost and the efficacy of monitoring the pre-and post-bait abundance of feral cats via camera-traps or track counts using four years of data from the Matuwa Indigenous Protected Area. Additionally, we report on the recovery of the feral cat population and the efficacy of subsequent Eradicat ® aerial baiting programs following 12 months of intensive feral cat control in 2019. Significantly fewer cats were captured in 2020 (n = 8) compared to 2019 (n = 126). Pre-baiting surveys for 2020 and 2021 suggested that the population of feral cats on Matuwa was very low, at 5.5 and 4.4 cats/100 km, respectively, which is well below our target threshold of 10 cats/100 km. Post-baiting surveys then recorded 3.6 and 3.0 cats/100 km, respectively, which still equates to a 35% and 32% reduction in cat activity. Track counts recorded significantly more feral cats than camera traps and were cheaper to implement. We recommend that at least two methods of monitoring cats be implemented to prevent erroneous conclusions.
... Human-wildlife conflict is a serious threat to many species and ecosystems, but it is especially deleterious for predator populations (Nyhus et al. 2003;Madden 2004;Inskip and Zimmermann 2009). Although coyotes are not an endangered species, they provide valuable ecosystem services (Sovada, Sargeant, and Grier 1995;Rogers and Caro 1998;Crooks and Soulé 1999;Henke and Bryant 1999;Silverstein 2005;Kays et al. 2015). In urban and suburban communities, they can also play the important role of apex predator. ...
Full-text available
Wildlife managers and others charged with resolving human-coyote conflict in urban and suburban areas cannot focus solely on ecology and coyote behavior. The perceptions of the people living in the affected communities play a significant role in the resolution of human-coyote conflict. In this study, we explore how residents of two communities in suburban Denver, CO, USA, mentally processed, made sense of, and acted upon human–coyote interactions in the face of conflict. By conducting interviews and using qualitative content analysis to explore existing documents, we examined how the use of language reflected and exacerbated the conflict over coyote management. Themes of violence, crime and war ran throughout our data. Anger and accusations of extremism were prevalent. Closely tied to the violent language and imagery used was a discussion of tolerance and intolerance, taking what is generally human-centric language and using it with wildlife. In addition, labeling coyotes as not belonging in an area (although they are a native species) further increased the urge to protect family and pets from the perception of the threat against ‘the other’, sometimes expressed in inflammatory language. Political and other messaging can either enhance or reduce a sense of threat, and we found that the language used in this debate enhanced the perceived threat of both coyotes and policy opponents. Finding ways to defuse this language could be a step toward a greater understanding of how to live with local wildlife in a way that minimizes harm to people and to the animals.
A new key concept for managing community cats is nuance. This is due to both the criticism and controversy as well as the need for creative partnerships to successfully manage community cats. It is critical to clearly determine and articulate what the management goal is and why. Decision‐making should be based on local data and newly published information. The plan will directly connect to the goals and data and can be adapted for the inevitable challenges and changes required to reach our goal. And nuanced and impactful communication with stakeholders will drive human behavior change because that is what will best help community cats.
Context Domestic cats (Felis catus) hold an important place in human society but can negatively impact ecosystems when roaming freely outdoors. Aims Specific research goals included identifying factors associated with cat abundance over the year. Methods We deployed trail cameras in Wellington County, Ontario, Canada to estimate what habitat characteristics were associated with cats in the spring/summer and the fall/winter. Within a subset of our study area, we also compared these findings to a previous study that used walking surveys. Key results In the spring/summer, cat abundance was positively related to proximity to buildings and negatively related to distance to agriculture. In the fall/winter, cat abundance was negatively related to the presence of coyotes (Canis latrans) and positively related to proximity to major roads. Overall, cat abundance was higher in urban than rural locations, and higher in spring/summer compared to fall/winter. Both our results from trail cameras and walking surveys from a previous study identified that median income, woodlots, and major roads were important habitat characteristics associated with cats during the summer, and we discuss the costs and benefits associated with both approaches. Conclusions Free-roaming cats are associated with different habitat characteristics in spring/summer versus fall/winter and vary in abundance across landscape type and season. Implications The development of management strategies aimed at reducing free-roaming cats in temperate areas should incorporate seasonal and landscape patterns.
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Nature reserves are an effective tool in protecting species that are threatened by anthropogenic factors. However, various subtle but significant human disturbances still negatively affect wildlife, such as the incursion of domestic dogs (Canis lupus familiaris) into wildlife communities. We conducted camera trap surveys and tracked GPS-collared dogs in and around a network of 17 nature reserves, and examined the spatio-temporal responses of eight abundant large and medium-sized wild animals to domestic dogs, including seven mammals (leopard cat, Prionailurus bengalensis; wild boar, Sus scrofa; Reeve's muntjac, Muntiacus reevesi; tufted deer, Elaphodus cepha-lophus; hog badger, Arctonyx albogularis; Siberian weasel, Mustela sibirica, and yellow-throated marten, Martes flavigula), and one pheasant (golden pheasant, Chrysolophus pictus). Our occupancy models indicated that the presence of domestic dogs negatively affected the occurrence probability of all focal species except for the yellow-throated marten. For wild boar, Reeve's muntjac, leopard cat and golden pheasant that we had sufficient data to further examine their temporal response to domestic dogs, we found that three species but leopard cat demonstrated temporal avoidance of domestic dogs, and dogs temporally followed the detections of these species. By overlapping the predicted distribution of dogs with nature reserve boundaries, we estimated that wildlife in approximately 19.8% of the 17-nature reserve network were potentially under the negative impact by domestic dog activity. Our study revealed the urgent need for nature reserves within the giant panda range, and possibly elsewhere, to consider domestic dogs as a significant human disturbance.
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The feral domestic cat (Felis catus) is a predatory invasive species with documented negative effects on native wildlife. The issue of appropriate and acceptable feral cat management is a matter of contentious debate in cities and states across the United States due to concerns for wildlife conservation, cat welfare, and public health. Common management strategies include: Trap-Neuter-Release, Trap- Neuter-Release with removal of kittens for adoption and Trap-Euthanize. Very little empirical evidence exists relevant to the efficacy of alternative options and a model-based approach is needed to predict population response and extend calculations to impact on wildlife. We have created a structured decision support model representing multiple stakeholder groups to facilitate the coordinated management of feral cats. We used a probabilistic graphical model (a Bayesian Belief Network) to evaluate and rank alternative management decisions according to efficacy, societal preferences, and cost. Our model predicts that Trap- Neuter-Release strategies would be optimal management decisions for small local populations of less than fifty cats while Trap-Euthanize would be the optimal management decision for populations greater than 50 cats. Removal is predicted to reduce feral cat populations quickly and prevent cats from taking a large number of wildlife prey.
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This article describes an extension of classical \chi^2 goodness-of-fit tests to Bayesian model assessment. The extension, which essentially involves evaluating Pearson's goodness-of-fit statistic at a parameter value drawn from its posterior distribution, has the important property that it is asymptotically distributed as a \chi^2 random variable on K-1 degrees of freedom, independently of the dimension of the underlying parameter vector. By examining the posterior distribution of this statistic, global goodness-of-fit diagnostics are obtained. Advantages of these diagnostics include ease of interpretation, computational convenience and favorable power properties. The proposed diagnostics can be used to assess the adequacy of a broad class of Bayesian models, essentially requiring only a finite-dimensional parameter vector and conditionally independent observations.
Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition, provides a synthesis of model-based approaches for analyzing presence-absence data, allowing for imperfect detection. Beginning from the relatively simple case of estimating the proportion of area or sampling units occupied at the time of surveying, the authors describe a wide variety of extensions that have been developed since the early 2000s. This provides an improved insight about species and community ecology, including, detection heterogeneity; correlated detections; spatial autocorrelation; multiple states or classes of occupancy; changes in occupancy over time; species co-occurrence; community-level modeling, and more. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition has been greatly expanded and detail is provided regarding the estimation methods and examples of their application are given. Important study design recommendations are also covered to give a well rounded view of modeling.
This chapter gives results from some illustrative exploration of the performance of information-theoretic criteria for model selection and methods to quantify precision when there is model selection uncertainty. The methods given in Chapter 4 are illustrated and additional insights are provided based on simulation and real data. Section 5.2 utilizes a chain binomial survival model for some Monte Carlo evaluation of unconditional sampling variance estimation, confidence intervals, and model averaging. For this simulation the generating process is known and can be of relatively high dimension. The generating model and the models used for data analysis in this chain binomial simulation are easy to understand and have no nuisance parameters. We give some comparisons of AIC versus BIC selection and use achieved confidence interval coverage as an integrating metric to judge the success of various approaches to inference.
The coyote (Canis latrans) is a common resident in urban areas throughout the United States, yet little is known about coyote diets in these environments. I characterized the annual diet of coyotes in an urban environment of western Washington by analyzing their scat from three areas representing typical patterns of human occupation and density: residential (1413 humans/km2), mixed agricultural residential (348 humans/km2), and mixed forest-residential (126 humans/km2). Coyote scats were collected twice a month for 1 year (Nov. 1989-Oct. 1990) in each habitat type. Fruits and mammals were the largest classes of food items in all habitat types and their seasonal use was similar among habitats. Apple (Malus spp.) and cherry (Prunus spp.) were the most abundant fruits in the scats, and ranged from 22-41% and 9-13% of the annual diet, respectively. Vole (Microtus spp.) was the most abundant mammalian food item (41.7%) of coyotes in mixed agricultural-residential habitat while house cat (Felis catus) and squirrel (Sciurus spp. and Tamiasciurus spp.) were the two most abundant mammalian food items (13.1 and 7.8%, respectively) of coyotes in residential habitat. No single mammalian species made up >6.0% of the coyote diet in mixed forest-residential habitat. Coyotes in my western Washington study area rely on foods that result from human activity but those foods, particularly mammals, may change as land use patterns change.
The domestic cat (Felis catus L.) population in the United States has more than doubled since 1970 and is estimated to exceed 100 million animals. Domestic cats are considered a direct predation threat to native wildlife, and, in a growing number of U.S. cities, conflicts are arising between land managers responsible for conserving native wildlife and members of the public concerned with the welfare of feral and abandoned cats. The removal of cats from natural areas has a strong sociopolitical component, including the support of a well-organized, well-funded special interest citizen group prepared to resist removal of cats. In addition, land managers must address removal within the larger political framework in which their agency is embedded. We describe the increasingly common trap-and-release approach to feral and abandoned cat management employed by cat welfare organizations. We use as examples two colony management organizations operating in south Florida. Land managers should take a proactive approach to the issue of feral and abandoned cats and undertake review of existing ordinances prior to the establishment of a significant cat population. Conservationists must expand their efforts to include support for the long-term effort to educate the public on the importance of responsible pet ownership and the establishment and enforcement of appropriate pet ordinances.
Urban areas are an important and growing land use class. Nearly 5 % of the world is covered with urban development and residential yards make up a large proportion of that area. Yards have unique but homogenous biological characteristics and are known to be rich with bird fauna, but little is known about backyard mammals. We used camera traps to sample mammal communities in backyards and urban woodlots in Raleigh-Durham, North Carolina, USA and related species activity to yard characteristics and levels of neighborhood development. We found a vibrant community of smaller herbivores and carnivores using residential yards in urban areas, but larger ungulates and carnivores were only detected on the urban fringe, or in woodlots. Backyard chicken coops were positively correlated with raccoon activity but were not positively correlated with other predators, suggesting that chicken coops are attracting raccoons, but not other predators, to yards. Fenced-in dogs were negatively correlated with most mammals suggesting that confined dogs keep mammals out of yards. Unfenced dogs and fences without dogs, showed a more varied relationship with mammal activity. These results show an encouraging sign of how humans can coexist with wildlife, even in urban areas, and suggest some strategies to minimize conflict regarding backyard chicken coops and dogs.