Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 July 2021 | 13(8): 19079–19092
ISSN 0974-7907 (Online) | ISSN 0974-7893
(Print)
https://doi.org/10.11609/jott.7102.13.8.19079-19092
#7102 | Received 21 January 2021 | Final
received 25 February 2021 | Finally accepted 30 June 2021
Limitations of current knowledge
about the ecology of Grey Foxes hamper conservation efforts
Maximilian L. Allen 1, Alexandra C. Avrin
2, Morgan J. Farmer 3, Laura S. Whipple 4, Emmarie P. Alexander 5 , Alyson M. Cervantes
6 & Javan M. Bauder 7
1,7 Illinois Natural History Survey,
University of Illinois, 1816 S. Oak Street, Champaign, IL 61820, USA.
1,2,4,6 Department of Natural Resources
and Environmental Sciences, University of Illinois, 1102 S. Goodwin, Urbana, IL
61801, USA.
3 Department of Forest and Wildlife
Ecology, University of Wisconsin, 1630 Linden Drive, Madison, WI 53706, USA.
5 Department of Animal Sciences,
University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
1 maxallen@illinois.edu
(corresponding author), 2 aavrin@illinois.edu, 3 morales1995@berkeley.edu,
4 laurasw2@illinois.edu,
5 emmarie2@illinois.edu, 6 alyson2@illinois.edu,
7 javanvonherp@gmail.com
Editor: Anonymity requested. Date
of publication: 26 July 2021 (online & print)
Citation: Allen, M.L., A.C. Avrin, M.J. Farmer, L.S. Whipple, E.P. Alexander, A.M.
Cervantes & J.M. Bauder (2021). Limitations of current knowledge
about the ecology of Grey Foxes hamper conservation efforts. Journal of Threatened Taxa 13(8): 19079–19092. https://doi.org/10.11609/jott.7102.13.8.19079-19092
Copyright: © Allen et al. 2021. Creative Commons Attribution
4.0 International License. JoTT allows unrestricted use, reproduction, and
distribution of this article in any medium by providing adequate credit to the
author(s) and the source of publication.
Funding: Funding was generously
provided by the Illinois Natural History
Survey and the University
of Illinois.
Competing interests: The authors
declare no competing interests.
Author details: MLA is a carnivore ecologist at
the Illinois Natural History Survey and University of Illinois. ACA is a M.S.
student at the university of Illinois at Urbana-Champaign, with research
focusing on effective monitoring techniques for mesocarnivores
as carnivore interactions and community structure. MJF is a is a PhD student in
the Department of Forest and Wildlife Ecology at the University of Wisconsin -
Madison, with research focusing on urban canids and their interactions with
each other, their environment, and with humans throughout North America. LSW
earned her B.S. from the University of Illinois and is currently a M.S. student
at Northern Michigan University, with research focusing on large carnivore
ecology and environmental education. EPA is an early-stage researcher and
undergraduate student at the University of Illinois at Urbana-Champaign, with
research and interests centered on mammalian behavior and ecology. AMC is a M.S. student at the University of
Illinois Urbana-Champaign, with research focusing on coyote and red fox
interactions across the Chicago metropolitan area. JMB was a postdoctoral
researcher with the Illinois Natural History Survey and is currently an
Assistant Unit Leader with the U.S. Geological Survey’s Arizona Cooperative
Fish and Wildlife Research Unit in Tucson studying the population and landscape
ecology of terrestrial vertebrates.
Author contributions: MLA led the review of the
literature and the writing of the manuscript. JMB led the statistical analyses.
All authors contributed to the review of literature, statistical analyses, and
writing of the manuscript.
Acknowledgements: We thank the Illinois Natural
History Survey and the University of Illinois for their support.
Abstract: Species-specific conservation is
important for maintaining the integrity of ecological communities but is
dependent on sufficiently understanding multiple aspects of a species’ ecology.
Species-specific data are commonly lacking for species in geographic areas with
little research and species perceived to have insufficient charisma or economic
importance. Despite their widespread distribution across central and North
America and status as a furbearing mammal, little is known about the ecology of
Grey Foxes Urocyon cinereoargenteus
compared to other species of furbearing mammals. To understand what is known
about this species, especially factors affecting population dynamics, we
performed a systematic review of the scientific literature. We found 234
studies about Grey Foxes, with studies increasing substantially over time but
with geographic gaps in the Great Plains and most of Mexico and central
America. Most studies we reviewed examined relative abundance or occupancy (n=
35), habitat associations (n= 30), primarily as part of larger mammalian
community studies, or spatiotemporal effects of other mammalian carnivores (n=
19), predominately Coyote Canis latrans. Grey Foxes were primarily forest-associated
although associations with specific forest communities or anthropogenically
disturbed habitats varied among studies. Multiple studies across ecoregions
reported this fox as among both the most- and least-abundant mammalian
carnivore. The inter-specific effects of Coyote were often, but not
exclusively, negative and were likely mediated by landscape composition and
human development. Importantly, very few studies examined population-effects of
coyotes on Grey Foxes. Studies of population trends, demographics, and space
use of Grey Foxes were comparatively rare and small inter- and intra-study
sample sizes limited our ability to infer broader patterns. We suggest multiple
avenues for future research to better understand the population status of this
species throughout their range.
Keywords: Abundance, co-occurrence,
demography, ecology, habitat, Urocyon cinereoargenteus.
Introduction
Conservation
biology has seen dramatic increases in effectiveness in the last century, from
increasing conservation of ecological communities through bioreserves to
species-specific conservation strategies. Implementation of species-specific
conservation strategies has been effective at increasing species of
conservation concern. For example, captive rearing and removal of lead
ammunition has brought California Condors Gymnogyps californianus back from the brink of
extinction (Walters et al. 2010), while cultural education and habitat
preservation has increased populations of Giant Pandas Ailuropoda
melanoleuca resulting in their down-listing from
the endangered species list (Swaisgood et al. 2018).
Species-specific conservation can be important for maintaining the integrity of
ecological communities but is dependent on sufficiently understanding multiple
aspects of a species’ ecology. For example, modeling population viability and
evaluating potential drivers of decline requires accurate estimates of demographic
parameters, such as age- and sex-specific estimates of survival and fecundity
(Boyce 1992; Mumme et al. 2000; Hostetler et al. 2009). Baseline estimates of
abundance or occupancy are required to evaluate population trends and identify
future changes in population status, while understanding habitat associations
can help better assess present and future threats to population persistence
(Haines et al. 2006; Aldridge et al. 2007). However, such ecological data are
commonly lacking for many species, particularly those in developing countries
with relatively few resources for science and conservation (Holmgren &
Schnitzer 2004; Allen et al. 2020) or those perceived to have insufficient
charisma or economic importance (Fuller & Cypher 2004).
Grey Foxes Urocyon cinereoargenteus
are one such understudied species (Image 1).
Despite their widespread distribution across Central and North America
and status as a furbearing mammal (Fritzell & Haroldson 1982; Fuller & Cypher 2004), little is known
about their ecology compared to other species of furbearing mammal (e.g., Sillero-Zubiri et al. 2004; Gehrt
et al. 2010). Grey Foxes are currently listed as ‘Least Concern’ by the
International Union for Conservation of Nature (Roemer et al. 2016) and do not
contribute to crop damage or other sources of human-wildlife conflict (Fuller
& Cypher 2004). Collectively, these factors likely work to deprioritize
research and monitoring efforts for this species, especially compared to their
only congener, Island Foxes Urocyon littoralis, which is federally endangered and a focus
of large research efforts (e.g., Bakker et al. 2009). A lack of such efforts
makes it difficult to detect large-scale population changes. For example, grey
foxes are thought to be declining in the Midwestern USA (Bauder
et al. 2020) despite minimal changes to land cover composition over the past
several decades (Walk et al. 2010). However, it is unclear if such putative
declines are regional in nature or more widespread. The goal of this paper,
therefore, was to provide a range-wide review and synthesis of the currently
available scientific literature on grey foxes to better understand their
population status and ecology and identify geographic and topical gaps in the
literature as avenues for future research.
Literature
Review
We
performed a systematic search of the scientific literature through Web of
Science on 28 May 2020 using the terms (“gray fox*” OR “grey fox*” OR “Urocyon”). We then examined each entry and removed
duplicate and mismatched publications (e.g., papers about island foxes), as
well as those not from peer-reviewed journals or studies of captive animals.
Our literature search yielded 430 peer-reviewed studies, 234 of which included
research on Grey Foxes (solely or as part of a broader mammalian community).
The number of studies about this species increased substantially since the
1940s (Figure 1a). Most studies were conducted within the states of California
and Texas and across the southeastern USA (Figure 2). Major gaps in the
geographic distribution of studies about Grey Foxes included the Great Plains
ecoregion in the midwestern United States and wet and dry tropical forests
ecoregions across Mexico and central America (Figure 2). We further describe
the geographic distribution of studies with reference to the Level I Ecological
Regions of North America (Omernik & Griffith
2014; Appendix 1).
We
classified the 234 studies of grey foxes into ten topical categories (Figure
1b). Most studies focused on disease (n= 92 articles) followed by habitat and
distribution (n= 42 articles). All other categories had < 25 studies (Figure
1b). We focused our review on five categories we deemed most relevant to the
management and conservation of these foxes defined as follows:
1) Abundance: spatiotemporal estimates of the absolute or relative number
of individuals, density, or occupancy; 2) Demography: estimates of
population vital rates (e.g., survival rates, mortality rates, sex ratio, mean
age, litter size); 3) Habitat: modeling aspects of ecology or behavior of
Grey Foxes (e.g., spatial locations, home range size, occupancy, or relative
abundance) as a function of one or more habitat features (e.g., vegetation
characteristics, land cover type, etc.); 4) Co-occurrence with dominant
carnivores: evaluated the spatiotemporal distribution or interactions of Grey
Foxes in relation to other carnivores; and 5) Space Use: spatial
distribution of individual Grey Fox. We separated distribution studies from
habitat studies for further consideration because the former dealt exclusively
with distributional or range expansion records. We also included studies
reporting occupancy estimates in abundance rather than distribution because
such studies occurred across relatively limited geographic extents. We only
included demography studies that reported model-based estimates of vital rates.
Similarly, we excluded habitat studies that were purely descriptive and lacking
an underlying statistical model. For co-occurrence with dominant carnivores, we
only considered studies that statistically examined how mammalian carnivores
directly affected these foxes through statistical analyses.
We found
seven distribution studies (Figure 2). Three studies provided records extending
the distribution of Grey Foxes in New Brunswick (Mcalpine
et al. 2008), Alberta (Moore 1952), and South Dakota (Schantz 1950). Two
studies also reported new within-range occurrence records in New Mexico
(Anderson & Stuart 1993) and Texas (Jones & Frey 2008), USA. Peterson
(1953) described the historical and contemporary distribution of this species
in Ontario, and Zielinski et al. (2011) found that the distribution of these
foxes in the Sierra Nevada was similar between the early 1900s and 1996–2002,
but Grey Foxes were detected less frequently during 1996–2002.
Abundance
We found 25
studies that reported abundance of Grey Foxes and 10 studies reporting
occupancy. All but three of the studies reported these foxes as part of the
larger mammalian or carnivore community. Most studies that reported relative
abundance (RAB) for this species used camera traps (n= 14), track and scat
transects (n= 6), or track plots (n= 3). Hair snares (Downey et al.
2007), observations by archery deer hunters (Cooper et al. 2012), and
environmental DNA (eDNA, Klymus et al. 2017) were each
reported detecting Grey Foxes by a single study.
Distributions
of RAB estimates from camera trap and transect studies were generally similar
across ecoregions (Figure 3). Studies with relatively high RAB occurred in
multiple ecoregions including the Temperate Sierras (Cunningham et al. 2006; Gallina et al. 2016), Eastern Temperate Forests
(Chamberlain et al. 1999), Tropical Wet Forests (Davis et al. 2011),
Mediterranean California (Allen et al. 2017), Great Plains (Karlin
& De La Paz 2015), and Marine West Coast Forests (Eriksson et al. 2019). To
further explore geographic variation in abundance of Grey Foxes, we calculated
the rank-order of RAB or occupancy across all mammalian carnivores detected in
the study, including grey fox. We then calculated the number of studies where
these foxes were in the top, middle, or bottom third ranks across seven
ecoregions. Grey Foxes were among the most abundant carnivores in Mediterranean
California, Northwestern Forested Mountains, and Tropical Dry Forests ecoregions
and among the least abundance carnivores in the Eastern Temperate Forests and
Tropical Wet Forests ecoregions (Figure 4). This species ranked among the top
third in at least one study within each ecoregion and in the bottom third in at
least one study in five ecoregions. Our results indicate that Grey Foxes may
show substantial intra- and inter-regional variation in abundance and highlight
the value of mammalian community studies for obtaining information on their
abundance and distribution.
Relatively
few studies reported trends in RAB of Grey Foxes and these studies were limited
in geographical scope. Long-term studies in Pennsylvania using bounty records
(Richmond 1952) and in Texas using nocturnal spotlight surveys (Schwertner et al. 2006) reported positive trends over 15
and 25 years, respectively. A 15-year study in Mississippi using trapper
harvest records reported stable trends (Lovell et al. 1998). Other studies
evaluating temporal variation in RAB or occupancy of this species were
conducted over relatively short (<3 year) periods (Chamberlain et al. 1999;
Cunningham et al. 2006; Gallina et al. 2016). In
contrast, Bauder et al. (2020) found evidence of
declines in Grey Foxes in Illinois over 43 years and two studies in the
midwestern USA found that they were the least prevalent species in the native
carnivore community (Lesmeister et al. 2015; Rich et
al. 2018). Lesmeister et al (2015) found that site
extinction rates for these foxes were higher than site colonization rates, and
other studies have suggested declines of Grey Foxes in the midwestern USA
(Cooper et al. 2012). Our literature review suggests that this species can
exhibit relatively high abundance in many parts of their range, but the paucity
of long-term studies about these foxes make it difficult to evaluate their
range-wide population status. Future Grey Fox monitoring efforts should
consider the diverse factors necessary for optimizing statistical power to
detect trends over a specified monitoring period, including initial abundance,
sampling method, number of sites, study length, and state variable (e.g.,
occupancy or RAB; Maxwell & Jennings 2005; Mahard
et al. 2016; Brown et al. 2017; Ward et al. 2017).
Demography
Six studies
reported demographic parameter estimates and all but one was from the Eastern
Temperate Forest with the sixth from Mediterranean California (Figure 2). Three
studies reported mean annual survival rates of 0.58–0.69 (Table 1). Studies did
not report statistically significant differences in survival between adults and
juveniles or males and females (Chamberlain & Leopold 2000; Farias et al.
2005; Temple et al. 2010) although one study found that adult annual survival
(0.77) was nearly twice that of juveniles (0.34; Farias et al. 2005). Reported
sources of mortality for Grey Foxes included legal harvest, predation, vehicle
mortality, canine distemper, canine hepatitis, and rabies (Chamberlain &
Leopold 2000; Weston & Brisbin 2003; Farias et
al. 2005; Glenn et al. 2009; Temple et al. 2010). Model-based estimates of
annual cause-specific mortality included 0.34 for human-caused (Temple et al.
2010) and 0.42 for predator-caused (Farias et al. 2005) mortality. Coyotes Canis latrans were
the primary cause of predation mortality (Weston & Brisbin
2003; Farias et al. 2005) although predation by Bobcats Lynx rufus was also reported (Farias et al. 2005). The
percentage of confirmed mortalities from Coyote predation varied from 28.6%
(Weston & Brisbin 2003) to 67% (Farias et al.
2005).
Estimates
of other demographic parameters were only available from a single population in
South Carolina, with a mean population age of 3.5 years and a slightly
female-biased sex ratio (31:44; Weston & Brisbin
2003). Estimated fecundity from corpora lutea counts was 1.94–3.6 pups/litter
(Weston & Brisbin 2003), and mean litter size was
3.1 (n= 8 litters, range= 2–5; Glenn et al. 2009).
The paucity
of demographic studies on Grey Foxes and their limited sample sizes and
geographic scope represent a substantial gap in our understanding of their
population ecology. Accurate demographic parameter estimates, particularly sex-
and age-specific survival and fecundity estimates, are important for evaluating
population viability and understanding causes of temporal changes in population
size. We therefore encourage future studies across the species range to provide
model-based demographic parameter estimates. The potential for high Coyote
mortality may have important implications for population dynamics of Grey Foxes
as Coyotes have expanded their distribution across North and central America (Gompper 2002; Hody & Kays
2018). However, our review illustrates that Coyote predation on Grey Foxes can
vary widely across populations and future studies could focus on linking
individual-level effects of predation from Coyotes to population-level
responses of Grey Foxes.
Habitat
We found 30
studies that modeled habitat associations of Grey Foxes (Table 2) excluding an
additional four studies that were purely descriptive and therefore were not
included in subsequent totals. Most habitat studies used camera traps (n= 14),
either in isolation or with other sampling methods, followed by transect
sampling (tracks or scat; n= 8), very high frequency (VHF) (n= 6) or global
positioning system telemetry (n= 1), and observations by archery deer hunters
(n= 1). Studies occurred in a diverse range of landscape types including urban,
natural areas surrounded or adjacent to urban areas, pinyon-juniper forest,
chaparral, eastern deciduous & coniferous forest, and tropical forest (Table
2). Studies were conducted in East Temperate Forest, Mediterranean California,
Temperate Sierras, and Tropical Dry Forest ecoregions (Figure 4).
Grey Foxes
were positively associated with forest environments throughout their range,
although associations with other vegetation communities or structural features
varied geographically (Table 2). For example, Grey Foxes in California and
Oregon were often positively associated with chaparral or shrub-scrub habitats
(Fedriani et al. 2000; Farias et al. 2012; Erikson et
al. 2019). Several studies found weak or no association with forest-related
covariates including forest cover (Rich et al. 2018), canopy cover (Davis et
al. 2011; Reed 2011), distance to nearest forest (LeFlore
et al. 2019), or basal area (Barrett et al. 2012) perhaps reflecting
insufficient covariate variability within the study area or regional variation
in habitat associations. Results from several studies suggest that these foxes
may use more open forest environments (Barrett et al. 2012; Borchert 2012),
edge habitats (Davis et al. 2011; Deuel et al. 2017; Harmsen
et al. 2019; Pearman-Gillman et al. 2020), and heterogenous landscapes (Cooper
et al. 2012; Lesmeister et al. 2015; but see Constible et al. 2006). Despite the methodological
variation across studies, our review highlights the importance of forest
environments for Grey Foxes across their range.
Early
research indicated that Grey Foxes were closely associated with hardwood forest
(Fritzell & Haroldson
1982). Studies in pine-dominated landscapes within the Eastern Temperate Forest
ecoregion reported selection for hardwood forest although the degree of
selection varied by spatial scale and season (Sawyer & Fendly
1994; Chamberlain et al. 2000; Temple et al. 2010; Deuel et al. 2017).
Selection for mature (≥ 30-year) and 9–15-year-old pine and mixed pine-hardwood
forests was also reported (Chamberlain et al. 2000). Hardwood species may offer
vertical escape cover from Coyotes given the climbing abilities of Grey Foxes (Fritzell & Haroldson 1982) and
small mammal prey may also be more abundant in hardwood forests (Chamberlain et
al. 2000; Temple et al. 2010; Lesmeister et al.
2015). However, few studies in landscapes not dominated by coniferous forests
directly compared selection of hardwood and coniferous forest (Table 2). Ordenana et al. (2010) reported positive associations with
oak woodland in California but Lesmeister et al.
(2015) reported an overall negative association between Grey Foxes and hardwood
forests in forest-agriculture landscapes in southern Illinois. However, Lesmeister et al. (2015) found that these foxes were more
likely to use hardwood forests when Coyotes were present. Our review suggests
that associations of this species with hardwood forest may not be universal but
rather conditional upon the broader landscape context and carnivore community.
We encourage future research evaluating the role of vegetation community,
structural characteristics (e.g., canopy cover), resource availability (e.g.,
small mammal abundance), and carnivore community on habitat suitability for
Grey Foxes.
Studies
evaluating associations of Grey Foxes with anthropogenic development (e.g.,
urbanization, roads) often reported conflicting information (Table 2). Several
studies reported negative associations between Grey Foxes and anthropogenic
development (e.g., Markovchick-Nicholls et al. 2008; Ordennana et al. 2010; Farias et al. 2012; Kowalski et al.
2012; Lombardi et al. 2017), yet other studies found that these foxes
utilize a range of human development intensities (Harrison 1993, 1997; Riley
2006; Kapfer & Kirk 2012; Lombardi et al. 2017).
Similarly, associations of Grey Foxes with agriculture varied among studies.
For example, studies from forest-agriculture landscapes in the Eastern
Temperate Forest ecoregion reported negative associations with agriculture
(Cooper et al. 2012; Lesmeister et al. 2015) as well
as positive or neutral associations (Temple et al. 2010; Deuel et al. 2017;
Pearman-Gillman et al. 2020). The particular response of Grey Foxes to
anthropogenic land covers may depend on factors including the intensity of
human or agricultural development, resource availability, diel period, or the
local carnivore community (Harrison 1997; Rota et al. 2016; Nickel et al.
2020). For example, positive association of these foxes with anthropogenic
development may reflect avoidance behavior of Coyotes (Lesmeister
et al. 2015; Wang et al. 2015) and agricultural edges may offer food from crops
and small mammal prey (Temple et al. 2010; Cortes-Marcial
et al. 2014). The impacts of anthropogenic landscape change on the habitat
associations of this species therefore represents an important avenue of future
research to better understand population dynamics of Grey Foxes.
Co-occurrence
with Dominant Carnivores
We reviewed
19 studies that evaluated interactions between Grey Foxes and other carnivores
by analyzing spatial (n= 13) or temporal overlap (n= 5) or by reporting
predation events (n= 4). These studies most frequently used camera traps
(n= 14), and to a lesser degree track plates (n= 3), scat collection
(n= 3), radio-telemetry (n= 2), and spotlight surveys (n= 1).
Studies were conducted in East Temperate Forest, Mediterranean California,
Maritime West Coast Forest, Northwestern Forested Mountains, North American
Deserts, Great Plains, Temperate Sierras, and Tropical Dry Forest (Figure 4).
Most
studies (n= 7 of 11) that examined spatiotemporal interactions between Grey
Foxes and Coyotes found evidence of negative effects of Coyotes on these foxes
(Table 3), consistent with the general expectation that Coyote negatively
affect smaller sympatric canids (Donadio &
Buskirk 2006). In a rare experimental study, Henke & Bryant (1999) found
that RAB of Grey Foxes in western Texas increased following removal of Coyotes.
However, negative effects of Coyotes were often weak or not statistically
significant (Borchert 2012; Lombardi et al. 2017; LeFlore
et al. 2019) and two studies reported positive effects (Rota et al. 2016; Rich
et al. 2018). Showing similar contrasts, LeFlore et
al. (2019) reported near complete temporal overlap between Coyotes and Grey
Foxes (Figure 5) while Lesmeister et al. (2015) found
that these foxes were detected less frequently during nights when Coyotes were
also detected. Such variability may be at least partially explained by
variation in sampling unit spatial scale and landscape conditions (Lesmeister et al. 2015). For example, Chamberlain &
Leopold (2005) found extensive home range overlap between Coyotes and Grey
Foxes but very little core area overlap. Similarly, Rota et al. (2016) found
that occupancy of this species in the presence of Coyotes increased with
increasing human development although Lombardi et al. (2017) found no spatial
relationships between these foxes and Coyotes within urban landscapes. We
therefore encourage studies evaluating interactions within carnivore
communities to consider the potential effects of scale and landscape context in
their analyses.
Relatively
few studies reported interactions of Grey Foxes with other carnivores (Table
3). Five of six studies including Bobcats reported negative effects on these
foxes but the strength of these relationships was often low (Table 3).
Interestingly, two of four studies reported strong positive relationships
between occupancy of Grey Foxes and Red Foxes (Lesmeister
et al. 2015; Rota et al. 2016). Davis et al. (2011) examined relationships
between the RAB of Grey Foxes and three larger sympatric felids but low
empirical support for inter-specific effects. However, other studies have shown
that larger carnivores (i.e., Puma Puma concolor) can have a positive effect on Grey Foxes by
directly limiting Coyotes (Allen et al. 2015, 2017). Other species may also
have positive effects on Grey Foxes and more research is needed to understand
the interactive relationships between Grey Foxes and the larger mammalian
carnivore community.
Space Use
We found 11
studies that reported space use estimates for Grey Foxes. Ten studies used VHF
telemetry and one used global positioning system (GPS) telemetry. Multiple home
range estimation methods were used within and across studies including minimum
convex polygons and fixed or adaptive kernel estimators (Table 4). All but
three studies were conducted in the Eastern Temperate Forest (Figure 2).
Estimated
home range sizes for Grey Foxes varied by almost an order of magnitude across
studies (range= 0.69–6.69 km2, Table 4). However, variation in home
range estimation method and tracking duration limited our ability to determine
the extent to which this variation was methodological or due to seasonal,
regional, or environmental variation. For example, Chamberlain et al. (2000)
and Temple et al. (2010) found that home range sizes of Grey Foxes varied
seasonally but Greenberg et al. (1994) and Deuel et al. (2017) found that home
range sizes were similar across seasons. Several studies reported that home
range sizes were similar between sexes and among age classes (Greenberg et al.
1994; Chamberlain & Leopold 2000; Riley 2006; Temple et al. 2010; Deuel et
al. 2017). Lack of inter-sexual differences in home range size may reflect the
widespread presence of pair-bonding in Grey Foxes (Greenberg et al. 1994;
Chamberlain et al. 2000; Riley 2006; Deuel et al. 2017). In contrast to studies
of other canids (e.g., Riley et al. 2003; O’Donnell & delBarco-Trillo
2020), studies of Grey Foxes in and near urban environments found that home
range size was not strongly affected by urban development (Harrison 1997; Riley
2006). The limited number and geographic distribution of studies of space use
by these foxes, combined with high methodological variability, inhibit our
ability to infer general patterns of space use by this species. We therefore
encourage additional studies of the spatial ecology of Grey Foxes and recommend
that researchers standardize tracking duration and home range estimation
methods across studies to facilitate inter-study comparisons.
The degree
of home range overlap varied within and between sexes. Several studies reported
that intra-sex home range overlap and overlap between unbonded males and
females was relatively low while home range overlap between bonded adult
male-female pairs relatively high (Greenberg et al. 1994; Chamberlain et al.
2000; Riley 2006; Deuel et al. 2017). However, Deuel et al. (2017) found
multiple instances of extra-home range forays in both males and females which
may reflect attempted extra-pair copulations (e.g., Glenn et al. 2008). Home
range overlap between adults and subadults was also relatively high (Greenberg
et al. 1994). It is likely that instances of low home range overlap are
explained by territoriality while high spatial overlap between bonded pairs
likely reflects shared duties of pup-rearing (Nicholson et al. 1985;
Chamberlain & Leopold 2000, 2002; Elbroch &
Allen 2013). However, the mechanisms for maintaining or defending territorial
boundaries appear to be largely unexplored in Grey Foxes. Because patterns of
spatial overlap are important in ultimately influencing population density and
carrying capacity, future research could focus on describing the degree of and
environmental factors influencing home range overlap for Grey Foxes.
Conclusions
Our review
provides a summary of the ecology of Grey Foxes for researchers and managers,
while also highlighting several existing gaps in our knowledge. We found large
gaps in geographic distribution of published studies about Grey Foxes, as most
studies were conducted in the southeastern or southwestern USA. In contrast,
Mexico, central America, and more northerly latitudes of their range were
underrepresented in our review. A paucity of demographic and space use studies
was particularly striking and limits our understanding of how individual-level
effects of landscape features and sympatric carnivores may affect
population-level processes of Grey Foxes. Additional demographic and space use
studies of Grey Foxes in anthropogenically developed landscapes within the
context of the larger carnivore community could help better understand the
extent to which populations of these foxes in those landscapes are
self-sustaining or acting as population sinks.
While Grey
Foxes can be locally abundant throughout their range, long-term data on the RAB
or occupancy of these foxes is scarce and often limited to harvest records
which are subject to a range of potentially confounding factors (e.g., trapper
effort and pelt prices; Bauder et al. 2020). We were
therefore unable to assess the population status of Grey Foxes throughout much
of their range although our results largely support the hypothesized decline of
these foxes in the midwestern USA. However, the mechanisms for such a decline
are unclear. While our review provides evidence that Coyote can negatively
affect the behavior and survival of grey foxes, the magnitude of such effects
can vary and may depend on study-specific conditions such as habitat
availability or resource abundance. However, the effects of competing canids
are complex because of range-wide shifts, including the recent expansion of
coyotes into eastern North America (Gompper 2002; Hody & Kays 2018). These changes in canid and carnivore
distributions shift dynamics in communities, but they also make the lack of
information on Grey Foxes more important because we do not have historical
baseline data to help us interpret current Grey Fox distribution, abundance,
and ecology.
We offer
several suggestions for avenues of future research on Grey Foxes. First, we
recommend additional demographic studies on Grey Foxes to allow for more
rigorous estimates of population viability and trends. Second, we encourage
researchers to examine existing data sets from mammalian carnivore community
studies and furbearer harvest records to provide additional information on
geographic variation of population trends in Grey Foxes. While researchers must
account for temporal variation in trapper or hunter harvest effort (e.g., Bauder et al. 2020), harvest data are regularly recorded by
wildlife management agencies and may represent the longest, most spatially
diverse data set available for evaluating the population trends of Grey Foxes.
Third, a systematic review of the effects of disease on population ecology of
Grey Foxes by experts in the field would be beneficial. Finally, we encourage
additional research on interactions between Grey Foxes and Coyotes to evaluate
the extents to which Coyotes influence the population dynamics of these foxes.
Finally, citizen science has been used to inform the ecology and management of
other canids (Mueller et al. 2019) and could be a beneficial approach for
future studies.
As with
many studies, we encourage researchers to use analytical approaches that allow
for the standardized reporting of estimates to facilitate future comparisons
across studies. Methodological variation among studies we reviewed made
inter-study comparisons difficult which compounded the problem of low numbers
of studies. For example, our ability to compare estimates of home range sizes
of Grey Foxes were greatly hindered by variation in sampling method, estimation
technique, and temporal period length. Similarly, studies of habitat
associations of Grey Foxes varied widely in their environmental covariates and
analytical approaches which also hindered inter-study comparisons. We also
encourage researchers to deposit data in open-access repositories (e.g., movebank or dryad) to facilitate future comparisons between
studies.
Table 1. Survival estimates for
Grey Foxes (estimates are pooled across sexes and seasons unless otherwise
noted).
|
Study |
Location |
Sample size |
Time period |
Estimation method |
Survival (95% CI) |
Legal harvest |
|
Farias et al. 2005 |
California |
17 7 15 7 n/a n/a |
Annual Adult Annual Adult Female Annual Adult Male 8-month Juvenile 8-month Juvenile Female 8-month Juvenile Male |
MICROMORT |
0.58 (0.39–0.85) 0.69 (0.41–1.00) 0.49 (0.27–0.88) 0.34 (0.11-0.99) 0.40 (0.11–1.00 0.30 (0.06–1.00) |
No |
|
Temple et al. 2010 |
Georgia |
33 |
Annual 4-month (Breeding) 4-month (Kit-rearing) 4-month (Winter) |
Kaplan-Meier |
0.61 (0.41–0.81) 0.81 (0.68–0.95) 0.75 (0.55–0.94) 0.82 (0.64–0.99) |
Yes |
|
Chamberlain & Leopold 2000 |
Mississippi |
37 |
Annual |
Not reported* |
0.56 |
Yes |
|
Weston & Brisbin 2003 |
South Carolina |
75 |
Annual |
Krebs (1999) |
0.69 (0.63–0.74) |
No |
* Estimated reported in Farias et
al. (2005) based on calculations from data in Chamberlain & Leopold (2000).
Table 2. Summary of habitat
associations of Grey Foxes, with the direction of effect presented as negative
(-), positive
(+), or no effect. Studies were classified as no effect when a given habitat
feature was used in proportion to availability, coefficient estimates were not
reported (e.g., covariate removed via step-wise model selection), or if the
habitat was not the most significantly used habitat within a compositional
analysis. Asterisks indicate strong empirical support and multiple symbols per
study or habitat indicate multiple sampling methods or spatial scales. Habitats
include forest (FRST), hardwood forest (HARD), coniferous forest (CONF),
chaparral or shrub (SHRB), habitat heterogeneity (e.g., heterogeneity in
landscape composition, habitat edge; HTRO), agriculture (AGRI), and
anthropogenic (e.g., urban, roads; ANTH).
|
Citation |
Location |
FRST |
HARD |
CONF |
SHRB |
HTRO |
AGRI |
ANTH |
|
Barrett et al. 2012 |
Arizona |
– |
|
|
|
|
|
|
|
Cunningham et al. 2006 |
Arizona |
+/– |
|
|
|
|
|
|
|
Reed 2011 |
Arizona |
. |
|
|
|
|
|
|
|
Davis et al. 2011 |
Belize |
– |
|
|
|
|
|
|
|
Harmsen et al. 2019 |
Belize |
./+/– |
|
|
|
|
. |
|
|
Borchert 2012 |
California |
–* |
|
|
|
|
|
|
|
Farias et al. 2012 |
California |
|
. |
|
+* |
|
|
–* |
|
Kowalski et al. 2015 |
California |
|
|
|
|
|
|
–* |
|
Markovchick-Nicholls et al.
2008 |
California |
|
|
|
|
|
|
–* |
|
Ordenana et al. 2010 |
California |
|
+* |
|
. |
|
|
–* |
|
Patten & Burger 2018 |
California |
|
|
|
|
|
|
–* |
|
Schuette et al. 2014 |
California |
+ |
|
|
|
|
|
. |
|
Pineda-Guerrero et al. 2015 |
Colombia |
+* |
|
|
|
|
–* |
|
|
Deuel et al. 2017 |
Georgia |
|
+* |
+ |
+/+* |
+ |
+/+* |
+* |
|
Temple et al. 2010 |
Georgia |
|
+/+* |
+/+* |
–*/+* |
|
–/+* |
+* |
|
Cooper et al. 2012 |
Illinois |
+ |
|
|
|
+ |
– |
|
|
Lesmeister et al. 2015 |
Illinois |
+* |
|
|
|
+* |
–* |
+*/–* |
|
LeFlore et al. 2019 |
Massachusetts |
. |
|
|
|
|
– |
. |
|
Gallina et al. 2016 |
Mexico |
–* |
|
|
|
|
+* |
+* |
|
Perez-Solano et al. 2018 |
Mexico |
+* |
|
|
|
|
– |
|
|
Rota et al. 2016 |
Mid-Atlantic States |
|
|
|
|
|
|
./+* |
|
Chamberlain et al. 2000 |
Mississippi |
|
./+* |
./+* |
|
|
|
|
|
Constible et al. 2006 |
Mississippi |
|
|
|
|
–/+ |
|
|
|
Pearman-Gillman et al. 2020 |
New England |
|
. |
. |
. |
+* |
+* |
. |
|
Harrison 1993 |
New Mexico |
+* |
|
|
|
|
|
|
|
Harrison 1997 |
New Mexico |
+*/–* |
|
|
|
|
|
+*/–* |
|
Rich et al. 2018 |
Ohio |
– |
|
|
– |
|
–/+ |
– |
|
Eriksson et al. 2019 |
Oregon |
|
|
|
+* |
|
|
|
|
Sawyer & Fendly 1994 |
South Carolina |
|
./– |
+*/–* |
|
|
|
|
|
Lombardi et al. 2017 |
Texas |
|
|
|
|
|
|
./–* |
Table 3. Summary of effects of
larger carnivores on spatial overlap with Grey Fox, with the direction of
effect presented as negative (-), positive (+), or no effect. Studies were
classified as no effect when the inter-specific effect was not reported or if
predicted occupancy values were ≤0.02 between sites with and without the other
carnivore (Lesmeister et al. 2015). Asterisks (*)
indicate strong empirical support (P value < α, 95% CI excluded zero,
model with inter-specific effect has greater AIC weight than an intercept- or
habitat-only model, species interaction factor > 1.5 or < 0.5). Studies
with multiple directions of effect refer to multiple sampling scales. Rota et
al. (2016) encompassed the states of Maryland, Virginia, West Virginia,
Tennessee, North Carolina, and South Carolina.
|
Study |
Location |
Bobcat (Lynx rufus) |
Coyote (Canis
latrans) |
Fisher (Pekania
pennant) |
Jaguar (Panthera
onca) |
Ocelot (Leopardus
pardalis) |
Puma (Puma concolor) |
Raccoon (Procyon lotor) |
Red Fox (Vulpes vulpes) |
|
Atwood et al. 2011 |
Texas |
–* |
–* |
|
|
|
|
|
|
|
Barrett et al. 2012 |
Arizona |
|
–* |
|
|
|
|
+* |
|
|
Borchert 2012 |
California |
|
. |
|
|
|
|
|
|
|
Chamberlain & Leopold 2005 |
Mississippi |
– |
– |
|
|
|
|
|
|
|
Davis et al. 2011 |
Belize |
|
|
|
– |
– |
+ |
|
|
|
Fedriani et al. 2000 |
California |
|
–* |
|
|
|
|
|
|
|
Green et al. 2018 |
California/Oregon |
|
|
–* |
|
|
|
|
|
|
LeFlore et al. 2019 |
Massachusetts |
|
– |
|
|
|
|
– |
. |
|
Lesmeister et al. 2015 |
Illinois |
. |
./–* |
|
|
|
|
|
+* |
|
Lombardi et al. 2017 |
Texas |
|
. |
|
|
|
|
|
|
|
Reed 2011 |
Arizona |
– |
–* |
|
|
|
|
|
|
|
Rich et al. 2018 |
Ohio |
– |
+ |
|
|
|
|
– |
– |
|
Rota et al. 2016 |
Mid-Atlantic States |
– |
+ |
|
|
|
|
|
+* |
Table 4. Home range (100 % and 95
%) and core area (50 %) sizes (km2 and standard errors in
parentheses) estimates for Grey Foxes and the number of individuals used for
each estimate (n). Estimation methods include minimum convex polygons (MCP),
adaptive kernel (AK), or fixed kernel (FK) estimators.
|
Reference |
HR calculation method |
Composite HR |
Breeding HR |
Pup-rearing HR |
Non-breeding HR |
|
Harrison 2002 |
95 % MCP |
4.81 (1.79) |
|
|
|
|
Greenberg et al. 1994 |
100 % MCP |
3.97 (1.51) |
2.72 (0.17)a |
2.32 (0.43)b |
2.83 (0.42)c |
|
Trapp 1978 |
100 % MCP |
1.07 |
|
|
|
|
Riley et al. 2006 |
95 % MCP |
0.69 (0.03)° |
|
|
|
|
Chamberlain & Leopold 2000 |
95 % AK |
|
3.53 (0.20)d |
2.02 (0.20)e |
1.66 (0.19)f |
|
Temple et al. 2010 |
95 % FK |
|
0.91 (0.13)d |
1.00 (0.18)e |
1.52 (0.32)f |
|
Harmsen et al. 2019 |
95 % Kernel area* |
3.31-6.69 |
|
|
|
|
|
HR calculation method |
Winter HR (Jan–March) |
Spring HR (April–June) |
Summer HR (July–Sept) |
Fall HR (Oct–Dec) |
|
Deuel et al. 2017 |
95 % FK |
2.17 (0.54) |
1.61 (0.32) |
2.15 (0.32) |
2.01 (0.43) |
|
|
HR calculation method |
Gender |
Pre-mate loss HR |
Post-mate loss HR |
Percent Change |
|
Chamberlain et al. 2002 |
95 % FK |
Female |
4.48 |
6.37 |
30% |
|
|
|
Male |
2.86 |
17.16 |
83% |
|
|
|
Male |
2.19 |
0.93 |
-58% |
|
|
|
Female |
0.96 |
0.64 |
-33% |
For
figures & image - - click here
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