ABSTRACT
OCCUPANCY, HABITAT USE, AND SEASONAL FLUCTUATIONS
OF MEDIUM TO LARGE MAMMALIAN PREDATORS AND
OMNIVORES IN SIERRA NEVADA FOOTHILL
OAK WOODLAND
Mammalian predators are known to be sensitive to relatively low levels of
habitat perturbations, and disturbances to these species are underway due
anthropogenic development and climate change in the Sierra Nevada Foothills
(SNF) of California. This was the first study to use motion-activated cameras to
detect these target species in oak woodland habitat of the central SNF. From
February 2014 to February 2015 seven mammalian predators were detected on the
Sierra Foothill Conservancy’s McKenzie Preserve at three different elevations:
coyote (Canis latrans), gray fox (Urocyon cinereoargenteus), bobcat (Lynx rufus),
striped skunk (Mephitis mephitis), raccoon (Procyon lotor), American badger
(Taxidea taxus), and black bear (Ursus americanus). Occupancy models indicated
that the bobcat, coyote, gray fox, and raccoon were using the preserve with 100%
probability, and were widely distributed throughout the preserve. Habitat use was
patchy for the American badger, black bear, and striped skunk. Generalized linear
models showed interactions between the gray fox, raccoon, bobcat and coyote to
suggest coexistence on the preserve is being maintained through resource
partitioning and not temporal or spatial separation. This newly established
baseline of mammalian predators is informative for future monitoring,
management, and development plans in the SNF.
Ryan Michael Smith
December 2015
OCCUPANCY, HABITAT USE, AND SEASONAL FLUCTUATIONS
OF MEDIUM TO LARGE MAMMALIAN PREDATORS AND
OMNIVORES IN SIERRA NEVADA FOOTHILL
OAK WOODLAND
by
Ryan Michael Smith
A thesis
submitted in partial
fulfillment of the requirements for the degree of
Master of Science in Biology
in the College of Science and Mathematics
California State University, Fresno
December 2015
APPROVED
For the Department of Biology:
We, the undersigned, certify that the thesis of the following student
meets the required standards of scholarship, format, and style of the
university and the student's graduate degree program for the
awarding of the master's degree.
Ryan Michael Smith
Thesis Author
Paul R. Crosbie (Chair)
Biology
Steven Blumenshine
Biology
Madhusudan Katti
Biology
For the University Graduate Committee:
James Marshall, Division of Graduate Studies
AUTHORIZATION FOR REPRODUCTION
OF MASTER’S THESIS
X
I grant permission for the reproduction of this thesis in part or in
its entirety without further authorization from me, on the
condition that the person or agency requesting reproduction
absorbs the cost and provides proper acknowledgment of
authorship.
Permission to reproduce this thesis in part or in its entirety must
be obtained from me.
Signature of thesis author:
ACKNOWLEDGMENTS
The completion of this thesis has been made possible by the roles my
professors, the university’s College of Science and Mathematics, the Sierra
Foothill Conservancy, undergraduates and my wife have played in the duration of
the process. I would like to acknowledge and thank them all.
My committee chair and advisor, Dr. Paul Crosbie played the most integral
role in guiding me through the process and furthering my abilities to design,
conduct, analyze, and finish this thesis. My remaining committee members, Dr.
Madhusudan Katti and Dr. Steven Blumenshine, I thank for providing constructive
mentoring and guidance. Dr. John Constable was an inspirational professor and
source of encouragement when I was first starting to consider the graduate
program, and then again in the classroom and during numerous brief encounters
throughout the program. Thank you all.
To the College of Science and Mathematics, for offering the M.S. in
Biology and the financial support provided by the Faculty Sponsored Student
Research Award, I am grateful. To the Department of Biology, thank you for your
professionalism and guidance in and out of the classroom. Thank you to
undergraduate biology students Francisco Barajas and Jessica Wilson for their
assistance in the field. Thank you to the Sierra Foothill Conservancy; for
permission to collect data at the McKenzie Preserve.
Lastly, I want to thank my family. To my dad, Tim Smith, for his company
and assistance on hikes up and down the hills. To my mom, Judy Smith, for her
support in the flatlands. Finally, to my wife, Candice, for her love, patience and
ability to make my time away from our boys, Holden and Sawyer, as unnoticeable
as possible. Thank you.
TABLE OF CONTENTS
Page
LIST OF TABLES .................................................................................................. ix
LIST OF FIGURES .................................................................................................. x
INTRODUCTION .................................................................................................... 1
Overview ........................................................................................................... 1
Sierra Nevada Foothills ..................................................................................... 2
Target Species ................................................................................................... 4
Mesocarnivores ................................................................................................. 9
Sierra Foothill Conservancy............................................................................ 15
Camera Trapping and Occupancy ................................................................... 16
Goals and Objectives....................................................................................... 17
MATERIALS AND METHODS ........................................................................... 18
Study Area Description ................................................................................... 18
Camera Trap Sites ........................................................................................... 23
Measurement of Habitat and Weather Variables ............................................ 23
Image Count and Management ....................................................................... 24
Analysis ........................................................................................................... 25
RESULTS ............................................................................................................... 33
Capture Data.................................................................................................... 33
Target Species Distribution and Habitat Use .................................................. 39
Species Occupancy.......................................................................................... 43
DISCUSSION......................................................................................................... 47
Mammalian Mesocarnivore Distribution and Activity ................................... 48
Habitat and Environmental Characteristics..................................................... 50
viii
Page
Intraguild Interactions ..................................................................................... 52
Future Research ............................................................................................... 54
REFERENCES ....................................................................................................... 56
APPENDICES ........................................................................................................ 65
APPENDIX A: POSITIVE CAPTURE IMAGES OF EACH
TARGET SPECIES..................................................................................... 66
APPENDIX B: MEASUREMENT OF HABITAT VARIABLES
COLLECTED FROM SAMPLING SITES ................................................ 71
LIST OF TABLES
Page
Table 1 -- Sampling Site Locations and Elevations within the
McKenzie Preserve ................................................................................ 20
Table 2 -- Habitat Descriptions for Each of the Six Sampling Sites within the
McKenzie Preserve ................................................................................ 22
Table 3 -- Relative Use of Study Sites by the Six Target Species on the SFC’s
McKenzie Preserve in the SNF.............................................................. 33
Table 4 -- Resulting Categories of Habitat Variables Showing Significant
Differences in Relative Activity of Target Species and the Variables
VIF ......................................................................................................... 41
Table 5 -- Top Ranked Use Models Incorporating Survey-Period Specific
Covariates for Each Target Species (bobcats, coyotes, gray foxes, and
raccoons) ................................................................................................ 44
Table 6 -- Estimated Mean Seasonal Detectability of Target Species (bobcats,
coyotes, gray foxes, and raccoons) at the McKenzie Preserve .............. 45
Table 7 -- Use of McKenzie Preserve Models Incorporating Site-Specific
Covariates for Each Target Species (bobcats, coyotes, gray foxes, and
raccoons) ................................................................................................ 46
LIST OF FIGURES
Page
Figure 1 -- Concept map of interspecies interactions in the SNF. Solid arrows
indicate negative impact at point of arrow, dotted lines indicate
potential negative impact (adapted from Lesmeister et. al 2015). .......... 10
Figure 2 -- Map of the Sierra Foothill Conservancy’s (SFC) McKenzie
Preserve and the location of the 6 study sites. ........................................ 19
Figure 3 -- High elevation Sites 2 (top) and 3 (bottom) in the summer and
winter. ..................................................................................................... 20
Figure 4 -- Mid elevation Sites 1 (top) and 4 (bottom) in the summer and
winter. ..................................................................................................... 21
Figure 5 -- Low elevation Sites 5 (top) and 6 (bottom) in the summer and
winter. ..................................................................................................... 21
Figure 6 -- Camera mounts at sampling sites on a tree and t-post. ........................ 24
Figure 7 -- Residuals of relative activity of target species at each of the six
study sites on the Sierra Foothill Conservancy’s McKenzie Preserve
of the SNF ............................................................................................... 34
Figure 8 -- Total number of captures of each species during each season of the
study ........................................................................................................ 35
Figure 9 -- Mean monthly activity of the entire guild of mammalian carnivores
and each individual species, represented by the frequency of capture
each month .............................................................................................. 36
Figure 10 -- Diel activity of the six target species represented by the frequency
of capture at each hour of the day ........................................................... 36
Figure 11 -- Total number of captures of all target species combined for each
month compared to the mean temperature each month .......................... 37
Figure 12 -- Total number of captures of all target species combined for each
month compared to the total monthly precipitation ................................ 38
Figure 13 -- Total number of captures of all target species combined for each
month compared to monthly relative humidity....................................... 38
Figure 14 -- Generalized linear models of raccoon activity in response to
coyote activity in the winter (top left), spring (top right), winter
(middle left) and bobcat activity in the winter (middle right), spring
(bottom left), summer (bottom right) ...................................................... 42
xi
Page
Figure 15 -- Generalized linear models of gray fox activity in response to
coyote activity in spring (top left) and bobcat activity in winter (top
right), spring (bottom left), summer (bottom right) ................................ 43
INTRODUCTION
Overview
Mammalian predators are known to be sensitive to relatively low levels of
habitat perturbations, and disturbances to predator assemblages may have a
considerable impact on the health and functionality of the larger ecosystem (Noss
et al., 1996; Crooks et al., 2002; Faeth et al., 2005; Ordenana et al., 2010). Even
though predatory mammals have been well studied globally (Lucherini et al.,
2009; Schuette et al., 2013; DiMarco et al., 2014; Monterroso et al., 2014a),
nationally (McDonald et al., 2008; Beschta and Ripple, 2009; Lesmeister et al.,
2015), and within California (Hilty et al., 2006; Ordenana et al., 2010; Wang et al.,
2015), little is known of the contemporary mammalian carnivore community in the
Sierra Nevada foothills of California. Oak woodland habitats of the Sierra Nevada
foothills are currently considered to be undergoing threats to their continued
viability due to anthropogenic development and climate change (Jongsomjit et al,
2013). Projections indicate the intensity of these threats to increase in coming
years. Thus far, no studies have been conducted that assessed the diversity,
distribution, or habitat use of mammalian predators in oak woodland habitats of
the Central San Joaquin Valley foothills.
This study employed a noninvasive method of data collection, camera
trapping, within semi-protected oak woodland habitat of the Sierra Nevada
foothills to estimate mammalian carnivore diversity, distribution, habitat use, and
occupancy. In addition, temporal and spatial use of a habitat immersed within a
matrix of anthropogenic development by these species allowed inference of
behavioral adaptations. Finally, the study attempted to provide recommendations
2
for habitat management to preserve healthy mammalian populations in the study
area and immediate surroundings.
Sierra Nevada Foothills
The United States Department of Agriculture Forest Service (USDA-FS)
defines the Sierra Nevada Foothills (SNF) as an ecological subregion of the United
States (http://www.fs.fed.us/land/pubs/ecoregions/ch33.html#M261F). The SNF
stretch from Lake Almanor (Plumas.County), 264 km north of Sacramento, south
to Tehachapi (Kern County) along the western slope of the Sierra Nevada
mountains at an elevation of 152-1,520 m (Storer et al. 2004), a distance of 782
km. They are one of the most diverse and widely distributed habitats in California
(Schoenherr, 1992). The biological diversity of the region can be attributed in part
to geologic processes from 250-150 mya, climate, topography, soil composition,
and the presence of 12 large river systems that run from the Sierra Nevada
mountains and through the western foothills (Storer et al. 2004).
The central region of the SNF (within the counties of Mariposa, Madera,
Fresno, and Tulare) is composed of a patchwork of grasslands, chaparral, riparian
habitat, oak woodlands, and mixed oak and conifer forest. Predominant tree
species include the Gray Pine, Pinus sabiniana; Blue Oak, Quercus douglasii; and
Interior Live Oak, Quercus wislizeni (Schoenherr, 1992). Winter rainfall and
runoff in the SNF frequently form vernal pools when the water is unable to
percolate into the soils. These conditions form ecological islands, and an
estimated 50% of over 100 plant species associated with these vernal pools are
endemic to California (Schoenherr, 1992). Nearly 66% (1.131 million ha) of
vernal pool habitat has been lost to human disturbance and grazing, with the
greatest number of pools in the best condition remaining on the high terraces of
3
the SNF (Schoenherr, 1992, pg. 526). Despite the diversity and endemism of the
habitats of the SNF they are one of the least protected against climate change
(Wiens et al., 2011) and anthropogenic pressures (Underwood et al., 2009 and
Martinuzzi et al., 2013).
Development projections in California’s oak woodlands show the Central
Valley and SNF to be the region of the state under the greatest threat by 2040
(Gaman & Firman, 2006) with urban and suburban development doubling and
exurban developments tripling in the same region of the SNF by 2070 (Jongsomjit
et al., 2013). This study was conducted at a site in this central region of the SNF,
within Fresno County, northeast of the large metropolitan and suburban area of
Fresno and Clovis, CA, USA and in proximity to the foothill communities of
Friant, Prather and Auberry. Two large suburban developments are in various
stages of development near the study site: Ventana Hills, less than 6 km (3.7
miles) to the west of the study site, a 122 ha (302 acre) gated community
containing 90 one ha (two acre) plots (http://www.livevh.com/site-plan.htm) and
the Millerton New Town Project, over 3,000 houses being developed east of Friant
(http://abclocal.go.com//story?section=news/local&id=8574426).
When climate change projections and an estimated decrease in the
probability of species occurrence are considered, the effects of anthropogenic
perturbations of natural habitats in the Central Valley and SNF may be potentially
amplified (Jongsomjit et al., 2013). Further, 18 bird species associated with oak
woodlands are predicted to expand their ranges in response to climate change,
finding refuge in the central region of the SNF, which is projected to experience
an 80% habitat loss due to exurban development (Jongsomjit et al., 2013). This
predicted shift in response to climate change has been observed in Sierra Nevadan
bird, butterfly, mammal and tree species over the last 35-100 years, and some
4
species have shifted down (Moritz et al., 2008; Tingley et al., 2009; Forister et al.,
2010; Crimmins et al., 2011). This trend suggests that regular monitoring of the
biological communities of the SNF must occur on a routine basis and the first step
in the process is to establish accurate baselines.
Quantitative estimates of medium to large mammalian carnivore habitat use
in SNF habitats appear to be unknown; general statements of species presence in
the SNF are all that are available. However, surveys have been conducted using
camera trapping at higher elevations of the Sierra Nevada Mountain Range
(Zielinski et al., 2005). This study focused on the community of mammalian
omnivores and carnivores residing within a specific landscape of the central SNF.
Target Species
The historical range of several medium to large-sized carnivores and
omnivores includes the SNF ecoregion. Those animals are members of several
families : Canidae – Coyote (Canis latrans), Gray Fox (Urocyon
cinereoargenteus); Felidae – Mountain Lion (Puma concolor), Bobcat (Lynx
rufus); Mustelidae – Striped Skunk (Mephitis mephitis), Spotted Skunk (Spilogale
putorius), Badger (Taxidea taxus), various members of the Mustela genus
(Weasels and Minks); Procyonidae – Ringtail (Bassariscus astutus), Raccoon
(Procyon lotor); Ursidae – Black Bear (Ursus americanus) (Barrett et al., 1980;
Jameson & Peeters, 1988); and the only marsupial in the United States, Virginia
Opossum (Didelphis virginiana), a non-native species introduced to California in
1910 (Jameson & Peeters, 1988). Preliminary data (P.R. Crosbie et al. pers.
observ.) indicated that a sub set of the taxa above were the most likely occupants
of the preserve: coyotes, bobcats, raccoons, skunks, badgers and gray foxes, and
these were considered the target taxa described below.
5
Canidae
Canis latrans (Coyote) is a Nearctic canid that includes 19 subspecies varying
in size between geographic locations, but with males always larger (10.3-16 kg)
than females (8-14.2 kg). The coyote inhabits diverse habitats distributed
throughout the US and Canada and between Northern Alaska (70˚ N) and Costa
Rica (10˚ N) (Bekoff and Gese, 2003). The mean home range of coyotes in a
fragmented habitat of California’s Santa Monica Mountains and Simi Hills was
6.17 km2 for males and 2.84 km2 for females (Riley et al, 2003). Coexistence with
other carnivores is common and likely mediated by resource partitioning.
However, in some areas coyote tolerance for smaller canids and bobcats can be
low and they are particularly likely to kill swift, kit and gray foxes. Coyotes are
opportunistic predators with a diet dominated by lagomorphs, rodents and
ungulates. Their diet also includes birds, amphibians, lizards, berries and fruit.
The availability of food plays a major factor in regulating pack size, reproductive
rates, survival, dispersal and space use patterns (Bekoff and Gese, 2003).
Mating season is between January and March. Litters averaging six pups
are born after a ~63 day gestation, typically in April. Dispersal of young occurs
within the first or second year during the autumn or winter months. Population
density of the coyote is estimated to be 0.2-0.4/km2 (Bekoff and Gese, 2003).
Urocyon cinereoargenteus (Gray Fox) is distributed within wooded, brushy
and rocky habitats of North America, from southern Canada southward to northern
South America. Most recently this the range of the gray fox has expanded into the
Great Plains and regions in northeastern United States. California gray fox
populations are most abundant between 1150-1525 m and favor brushy vegetation
associated with rugged broken terrain. Home range of California individuals
averaged 129 ha (males) and 122 ha (females) that included dens in hallowed logs
6
or trees, rock outcroppings, and underground burrows in brush and wooded
habitats. Gray foxes breed between January and April, varying among geographic
location. Population density ranges from 0.4-1.5/km2 depending on location.
Gray fox mass can range from 3-7 kg; males are slightly larger than
females. The presence of gray foxes can negatively influence weasel populations
yet have no effect on skunks, raccoons or opossums. Main interspecific threats to
the gray fox are man, golden eagles, coyotes and bobcats. Gray fox diet is
composed mainly of mammals, rabbits and rodents in the winter. During summer
months invertebrates can dominate their diet while plant foods are consumed more
in autumn months (Cypher, 2003).
Felidae
Lynx rufus (Bobcat) is distributed throughout Canada, the United States and
Mexico except in Hawaii, Alaska, Vancouver Island, Prince Edward Island or
Newfoundland. Habitat selection is variable and is typically determined by prey
availability. It is common for males and females to prefer different habitats
seasonally. Males can prefer higher elevations in the summer months and lower
elevations in rocky terrain with a southwest facing slope in the winter. Bobcats
are polygamous and females are seasonally polyestrous mating between December
and July. Females most commonly begin mating during their second spring and
give birth to a litter of 1-6 kittens. California populations have been estimated to
be 0.7-0.9/km2.
The average size of the bobcat is between 4.1-18.3 kg. Their diet is strictly
carnivorous consisting predominantly of lagomorphs, sciurids and ground
dwelling microtines. The bobcat will also prey on mule deer, white tailed deer,
galliformes, reptiles, fish and insects. As food availability decreases the home
7
range of the bobcat increases. Home ranges are always smaller for females than
males. The home range of a male bobcats overlap with other males and females
and the size is influenced by adjacent and overlapping home ranges (Lariviere and
Walton, 1997). Research in California’s Golden Gate National Recreation Area in
Marin County found the bobcat’s mean home range 1453 ha (males) and 633.1 ha
(females) in rural areas and 638.5 ha (male) and 105.9 ha (female) in urban areas
(Riley, 2006). Daily movement of males in Montana averaged 4.9 km and 1.1 km
for males and females, respectively (Lariviere and Walton, 1997).
Procyonidae
Procyon lotor (Raccoon) is distributed from Southern Canada south to
Panama. They are not hibernators but have been known to remain in hollowed
trees during exceptionally cold winters. Raccoons more typically occupy a den
site for an average 1.5 days before shifting to other available dens in hallowed
trees, ground dens vacated by striped skunks, or rock crevices. Breeding season is
predominately in March, but can vary between December and June with
geographic location. The average litter size is between 1.9 and 5 young. Each can
grow to be an average 5.94 kg (females) and 6.76 kg (males).
The average home range of the raccoon is 49 ha and will decrease in size as
density increases. Diet includes a wide range of plant and animal matter: berries,
nuts, seeds, arthropods, rarely vertebrates, and accounts of sea turtle and bird eggs.
Predators include man, bobcat, coyote, and owls. The raccoon becomes active
before sunset to feed throughout the night to finish before sunrise (Lotze and
Anderson, 1979; Gehrt, 2003).
8
Mustelidae
Mephitis mephitis (Striped Skunk) is distributed throughout Southern
Canada, the United States, and Northern Mexico from sea level to 1800 m.
Density estimates range from 1.8-4.8/km2 and fluctuate greatly as a possible result
of disease outbreaks and high recruitment and turnover rates. Within an average
minimum adult home range of 378.0 ha (female) and 511.5 ha (male) mountain
lions, coyotes, bobcats, badgers, foxes, Great horned owls, and eagles are the
striped skunk’s main predators. Though primarily insectivorous the striped skunk
is opportunistic and its diet can shift between animal and plant matter: arthropods,
mice, voles, eggs and young of ground nesting birds, fruits and berries.
The striped skunk is active within one hour of sunset through the night until
dawn throughout the year except for up to 118 days of winter. During these winter
months communal denning of multiple females and one male can occur as early as
late fall through early spring. Breeding also takes place during February or
March. Females with young will remain in a den trough the spring and summer
with an average litter size of 5.8-7.8. Adult striped skunks will grow to be 1.2 –
5.3 kg (Wade-Smith and Verts, 1982).
Taxidea taxus (Badger) can weigh up to 12 kg and is distributed throughout
southern Canada, western and central United States, and northern Mexico at
elevations lower than sea level to 3660 m. The density of badgers is estimated to
be 1/2.6 km2 and have an average overall home range size of 850 ha that varied
with season: 725 ha (summer), 53 ha (autumn), and 2 ha (winter). Though not true
hibernators, badgers can experience torpid in winter at higher elevations and
latitudes. Diet of the badger consists of mostly rodents, fish, snakes, insects,
honey combs, bees, larvae, and bank-swallow eggs. Predators include the coyote
and golden eagle (Long, 1973).
9
These species can be defined as mesocarnivores or mesopredators due to
their size and taxonomic characters. Despite little being known about the presence
or abundance of mesocarnivores in the SNF, recent studies suggest their ecological
role to be diverse and important (Prugh et al., 2009 and Roemer et al., 2009).
Mesocarnivores’ population dynamics are influenced by habitat fragmentation and
urbanization, and temporal and spatial trophic and intraguild interactions (Prugh et
al., 2009 and Roemer et al., 2009).
Mesocarnivores
Only recently has research shown that mesocarnivores may have a much
more vital ecological role than once assumed. The near complete eradication and
considerable range reduction of North American carnivores (Laliberte and Ripple,
2004) has complicated the web of direct and indirect interactions within terrestrial
ecosystems (Prugh et al., 2009). Among the biomes of North America, temperate
grasslands, savannas and broadleaf/mixed forests have experienced the greatest
number of lost carnivore and ungulate species (Laliberte and Ripple, 2004).
Consequently, the structure and function of these communities and ecosystems can
be altered further due to the absence of predator driven direct effects and by feardriven indirect effects induced by a small number of large carnivorous animals
(Roemer et al., 2009). In the absence of apex large carnivores the importance of
their ecological function may be assumed by the smaller (<15 kg) species defined
as mesocarnivores (Roemer et al., 2009).
Regardless of the largest most dominant carnivores in an ecosystem being
present, mesocarnivores have a relatively high species richness and abundance and
exhibit a great range of character traits: solitary to highly social, frugivorous to
hypercarnivorous, habitat specialists to generalists (Roemer et al., 2009). These
10
ecological traits and their necessity for movement within a landscape contribute to
their heterogeneous sensitivities to habitat fragmentation variables, making them
effective focal organisms for evaluating habitat conditions and functional
connectivity in fragmented areas (Crooks, 2002). Furthermore, mesocarnivores
have the potential to strongly impact ecosystem function and health both directly
and indirectly. These impacts can then be influenced by anthropogenic habitat
fragmentation and urbanization, and trophic and intraguild interactions. Only
recently has the role of the mesocarnivore been more intensely studied. A recent
study (Lesmeister et al. 2015) of a mesocarnivore guild in Illinois suggested a
possible network of interactions between members of the guild. A similar
conceptual model (Figure 1) was developed for the target mammals in this study.
Coyote
Bobcat
Badger
Striped
Skunk
Gray Fox
Raccoon
Figure 1 -- Concept map of interspecies interactions in the SNF. Solid arrows
indicate negative impact at point of arrow, dotted lines indicate potential negative
impact (adapted from Lesmeister et. al 2015).
11
Effects of Fragmentation and
Urbanization
Mammalian carnivore populations generally have a low resilience to habitat
disturbance and ecosystem alteration due to characteristics such as low population
density, large range size and slow population growth rates (Noss et al. 1996;
Ordeñana et al., 2010). Therefore, land use change and habitat fragmentation are
explicit and sustained threats to mammalian carnivore populations (Crooks, 2002;
Riley, 2003; Hilty et al., 2006; Ordeñana et al., 2010; Goad et al., 2014) and are
projected to reduce habitat of Mediteranean like ecosystems in Califonia by 7%
before 2051 (Martinuzzi et al., 2013). These threats of habitat loss and the
projections of climate change in California make the SNF and similar
Mediterranean like habitats and ecosystems areas of biodiversity significance,
posing real challenges to their conservation (Martinuzzi et al., 2013). Establishing
a baseline of species richness in such habitats will be critical in measuring the
effectiveness of conservation actions and the biological response of species to
habitat perturbations and climate change.
In Colorado exurban development has been shown to have varying impacts
on habitat use by carnivore species: both bobcats and coyotes were negatively
impacted by development, while red foxes found potential refuge in exurban
developed areas (Goad et al., 2014). In the same study Black bears were found to
be mainly using the periphery of exurban development, only using urban areas as a
source of food. (Goad et al., 2014). Proximity to and intensity of urbanization in
Southern California negatively impacted species richness in a study detecting 12
carnivore species (9 native, 3 nonnative) (Ordeñana et al., 2010). Oak woodland
and vineyard landscapes of northern California, undergoing increased
fragmentation from agricultural development, indicate a decreased probability of
native mammalian predator occurrence in large vineyards relative to small isolated
12
vineyards and native oak woodland habitat (Hilty et al., 2006). In addition to the
reduction of species richness and abundance due to habitat alteration and
fragmentation, there may also be shifting activity patterns, increased home range
size, and human imposed mortality among mesocarnivores (Riley et al., 2003;
Salek, 2015; Wang et al., 2015).
Radio telemetry studies in Southern California showed home range sizes
and nocturnal activity patterns of bobcats and coyotes, two large mesocarnivores
and apex predators in some communities, to increase with their association to
altered and developed habitats (Riley et al., 2003). In a metaanalysis of 411
articles, Salek (2015) found home range size of 6 mesocarnivores to decrease and
population density to increase for 3 mesocarnivore species as the proximity to
urbanization increased. Additionally, human imposed mortality from vehicle
collisions and poisoning are indicated to affect mesocarnivores in fragmented
habitats (Riley et al., 2003). These studies strengthen findings that suggest
minimizing the impact on carnivores at edges of protected habitats, which may be
essential to conservation efforts (Woodroffe and Ginsberg, 1998).
It is acknowledged that the impact of land use change and habitat
fragmentation may be relative to the body mass, diet, social structure or resource
specialization of the species (Crooks, 2002). Despite these relative sensitivities
among mammalian carnivores, effects of anthropogenic disturbance on native
habitat includes: carnivore extirpations, potentially leading to additional loss of
species, the release of the more resilient mesocarnivores and potential trophic
cascades (Soule et al., 1988, Crooks and Soule, 1999; Hilty et al., 2006;
Casanovas et al., 2012). This suggests that in ecosystems controlled by top-down
forces, predators can function as strong indicators of ecosystem health due to their
place in the community’s food web (Faeth et al., 2005).
13
Mesocarnivores and Trophic Control
Soule et al. (1988) described an ecological phenomena they called
“mesopredator release” as an increase in the abundance of small and medium sized
predators and omnivores (mesocarnivores) when larger more dominant predators
are absent. Prugh et al. (2009) broadened the definition to the expansion in
density, distribution, or change in behavior of middle ranked predators following
the decline of apex predator density or distribution, making mesopredator release
the result of intraguild interactions among predators.
The exclusion of vertebrate predators from boreal grasslands of western
Finland showed indirect effects on the vegetation cover of specific species of
plants suggesting a species level trophic cascade (Norrdahl et al., 2002). The
presence of predators controlled vole populations from reaching high densities
which resulted in the decline of biomass in plant species available to herbivory
during winter months. Abiotic factors (e.g. ice and snow) during the winter
months provided protection to herbaceous plant species. In a similar study
conducted in Norway, seasonality also influenced the degree of indirect effects
predators had on plant communities from predation on vole populations. On
islands free of mammalian mesocarnivores, coverage by dwarf shrub species was
reduced by 50% compared to mainland sites were activity of mammalian predators
was high, suggesting a stronger community level trophic cascade (Hamback et al.,
2004). These field experiments suggest the potential for the mesocarnivores to
trigger top down species level cascades. Determining relative activity levels of
mesocarnivores between seasons may assist land managers in strategically
implementing management plans. In addition to the changing trophic dynamics of
a community, mesopredator release suggests investigating further the ecological
function of mesocarnivore species. Mesocarnivores can potentially ascend to the
14
role of apex predator as a result of mesopredator release (Laliberte and Ripple,
2004; Prugh et al., 2009). Therefore, understanding intraguild interactions and the
mechanisms that promote coexistence become important in conserving ecosystem
function.
Intraguild Interactions
Intraguild interactions include a range of behaviors that prevent competitors
from establishing habitat, and finding food and mates, and are classified into two
categories: exploitative and interference interactions. Exploitative interactions,
between both prey and predator species, directly result from a low density of
resources. Intraguild interference interactions among predators are unique for two
reasons: interactions can more frequently result in death of a competitor and can
arise in environments when resources are not a limiting factor (Linnell and Strand,
2000). Therefore, in the presence of intense intraguild interactions, avoidance
behavior can minimize negative effects on an individuals’ fitness and its
coexistence with the competitor (Schuette et al., 2013). Selection for avoidance
behaviors in mesoccarnivores is greater than it is in the prey species of apex
predators; two ways mesocarnivores reduce interaction with apex predators are
through selection of habitat with greater refuge, and changing foraging and
activity periods (Ritchie and Johnson, 2009). A number of studies have
documented avoidance both spatially and temporally.
In a diverse carnivore community in sub-Saharan Africa, subordinate
species have evolved a temporal niche that avoided peak activity periods of
dominant competitors (Schuette et al., 2013). In the high Andes of South America
two similar sized specialist cat species, the Andean cat (Leopardus jacobita) and
15
the Pampas cat (Leopardus culpaeus), appeared to be segregating their activity
temporally to avoid interference interactions (Lucherini et al., 2009).
Intraguild interactions between most target species in this study were
investigated in Illinois, showing gray foxes to display both temporal and spatial
shifts in behavior as a likely response to the presence of coyotes (Lesmeister et al.,
2015). Furthermore, two studies in Southern California found gray foxes to shift
activity patterns in response to coyotes and bobcats. Gray fox abundance was
reduced in grassland and open valley oak habitats, two habitats with increased
coyote and bobcat abundance (Fedriani et al., 2000), and temporal activity of gray
foxes was greater during the day and lesser during night than both the coyote and
bobcat (Farias et al., 2012). Finally, coyote and raccoon detection was negatively
impacted by puma occupancy in a camera trapping study conducted in the Santa
Cruz Mountains of California (Wang et al., 2015). Each of these studies suggest
the differences in habitat use and activity patterns are, in part, a response to
minimize risk and exposure to larger or stronger intraguild competitors.
Considering the high interspecific overlap of resource use among the target
species of this study and the anthropogenic effects underway in the SNF,
establishing a baseline of temporal and spatial activity patterns and understanding
how sympatric carnivore species are minimizing costly interactions can prove
valuable when designing conservation efforts and monitoring programs. This and
similar studies can play integral roles in conservation planning and guide
surveying protocols and efforts.
Sierra Foothill Conservancy
The Sierra Foothill Conservancy (SFC) operates in the central region of the
SNF ecological subregion and states Puma concolor, Lynx rufus, and Urocyon
16
cinereoagenteus to be target species protected within their preserves and
easements (http://www.sierrafoothill.org/index.php/about-us/facts/). Additionally,
the International Union for Conservation of Nature’s Redlist of Threatened
Species describes habitat loss and fragmentation to be major threats to Puma
concolor (Caso et al., 2008), Lynx rufus (Kelly et al., 2008), and Urocyon
cinereoagenteus (Cypher et al., 2008) populations. The goals of the SFC on its
preserves are to protect selected endangered, threatened or specially protected
species (e.g. mountain lion) and to preserve and manage foothill habitats and clean
water resources to ensure continuing public benefits
(http://awww.sierrafoothill.org/index.php/about-us/mission/). Therefore,
establishing an understanding of mammalian species composition and distribution
within local communities is essential in the conservation and management of
regional ecosystems. This study evaluated the presence, occupancy and seasonal
distribution of mammalian mesocarnivores within oak woodland habitat of the
SNF, and was the first of its kind in SNF habitats.
Camera Trapping and Occupancy
Capturing medium-sized mammals alive is expensive, impractical, and may
lead to mortality from capture myopathy or other physical trauma. Camera
trapping methods are inexpensive, noninvasive, and effective at studying elusive
and difficult to observe animal species that roam over areas too large to sample
completely (O'Brien, 2011). Monterroso et al. (2014b) found camera traps to be
more effective than snare traps when detecting mesocarnivores. Additionally,
analysis of camera trapping data, when addressing species detectability and spatial
variability, allows inferences to be made about animal populations (O'Connell et
al., 2011). For example, camera trapping data can be used with site occupancy
17
modeling to make robust analyses and biological inferences (Tobler et al., 2009;
Hines et al., 2010; O'Connell & Bailey, 2011; Cove et al., 2012). The occupancy
models can then be used to develop estimates of habitat use by diverse vertebrates
(Manley et al., 2004; Mattfeldt et al. 2009; Tobler et al., 2009; Krauze-Gryz et al.,
2012; Schuette et al., 2013).
Goals and Objectives
1) What is the presence, distribution, and habitat use of mammalian
carnivores and omnivores in Sierra Foothill habitats?
2) How does the presence and occupancy of mammalian carnivores and
omnivores and their use of habitat change seasonally?
3) What selected environmental, temporal and spatial variables correlate
with the presence and occupancy of each identified species between studied
habitats?
MATERIALS AND METHODS
Study Area Description
The SFC manages eight nature preserves and conservation easements that
total over 10,117 ha (25,000 acres) within the foothills of the central Sierra
Nevada mountain range between Yosemite (YNP) and Kings Canyon (KCNP)
National Parks. The McKenzie Preserve (Figure 2) encompasses 1,197 ha (2,960
acres) of grassland with oak woodlands on south facing slopes that approach basalt
lava tables; the north facing slopes of these lava tables are chaparral and pine
forest and drain into the San Joaquin River (http://www.sierrafoothill.org/
preserves.htm). The sampling sites for this study are within a landscape currently
under encroachment from urban development of varying degrees. The geographic
location (latitude and longitude) and elevation of all sites were recorded (Table 1).
The six sampling sites within the boundaries of the McKenzie Preserve
were chosen based on differing habitat variables (e.g. amount of ground cover,
substrate type, and dominant vegetation), accessibility, and likelihood of detection
of the target species. These sites collectively represented each of the main habitats
(i.e. oak woodland, mixed oak and conifer, grassland, seasonal riparian) and
elevation ranges (Table 2) found on the preserve to allow inferences about
differential habitat use by the target species. Three elevation ranges were defined
on the preserve (i.e. low, mid, and high) and two sampling sites were located
within each of these elevation ranges (Figures 3-5). The dominant plant species
and degree of vegetative and canopy cover were recorded for each sampling site
and weather variables were collected for the entire preserve throughout the study.
19
3
2
1
5
4
6
Figure 2 -- Map of the Sierra Foothill Conservancy’s (SFC) McKenzie Preserve
and the location of the 6 study sites.
20
Table 1 -- Sampling Site Locations and Elevations within the McKenzie Preserve
Site
GPS Location
Elevation (m)
1
TN 37˚01.238’, W 119˚35.097’
354
2
N 37˚01.497’, W 119˚35.442’
563
3
N 37˚01.563’, W 119˚35.237’
561
4
N 37˚00.644’, W 119˚35.750’
340
5
N 37˚00.654’, W 119˚35.518’
269
6
N 37˚0.094’, W 119˚35.511’
236
Figure 3 -- High elevation Sites 2 (top) and 3 (bottom) in the summer and winter.
21
Figure 4 -- Mid elevation Sites 1 (top) and 4 (bottom) in the summer and winter.
Figure 5 -- Low elevation Sites 5 (top) and 6 (bottom) in the summer and winter.
22
Table 2 -- Habitat Descriptions for Each of the Six Sampling Sites within the
McKenzie Preserve
Elevation Range
Low Elevation
General Habitat Description
Site 5
Site 6
(236 to 269
Riparian habitat along
Riparian habitat along
meters)
seasonal creek
seasonal creek
Open Bromus dominated
Sparse oak woodland
grassland
Bromus dominated
Oak woodland
grasses
surrounding open
grassland
Mid Elevation
Site 1
Site 4
(340 to 354
Mixed oak and conifer
Predominately oak
meters)
woodland
woodland
Bromus dominated grasses
Bromus dominated
Granite rock outcropping
grasses
Year around water tank
Seasonal creek and pond
On slope of hill side
High Elevation
Site 2
Site 3
(561 to 563
Basalt table top
Basalt table top
meters)
Sparse oak woodland
Denser mixed oak and
Close proximity to vernal
conifer woodland
pool habitat
Along hiking trail
Bromus grasses among
Bromus grasses among
larger community of
larger community of
annual plants
annual plants
23
Camera Trap Sites
At each of the six sites three motion activated digital cameras (Moultrie
Game Spy D55, Stealth Cam STC-1850, or Wildgame Innovations Model #W4B,
in a randomized combination) were mounted approximately 0.5 m from the
ground on available trees or, if suitable trees were unavailable, on steel t-posts
(Figure 6). The fields of view (50-52 degrees) of each of the three cameras at each
site did not overlap, to provide maximum habitat coverage and increased
detectability of target species at each site. Compass direction and coordinates of
each camera’s field of view were recorded. A can of wet cat food was used for
bait within the flash and detection range (10-18 m) and the field of view of each
camera, at each sampling site. The cans were punctured (but not opened), to allow
the scent of the food to escape, and fixed to the earth with 20 cm long galvanized
steel stakes. Each camera contained an 8 gigabyte memory card that stored
images. At 2 - 3 week intervals, each camera station was visited to collect
memory cards and replace them with an empty memory card. In addition, bait
cans were replaced at every visit and batteries changed on an as needed basis. The
cameras were set to collect images continuously for one calendar year beginning
in February 2014. The number of trap days was calculated for each site. One trap
day equaled one camera operating for one 24 h period.
Measurement of Habitat and Weather Variables
Habitat variables were quantified at each of the six sampling sites. Each of
the three cameras at each site was used as a center point to run 20 m transects in
the four cardinal directions (north, south, east, and west). Ground cover substrate
(grass, rock, wood, and bare soil) and canopy cover was recorded at each meter
along each transect. These data were used to calculate the percentage of the site
under tree canopy and covered by each defined ground substrate. Additionally,
24
Figure 6 -- Camera mounts at sampling sites on a tree and t-post.
the number of trees within 20 m of each camera was counted and their diameter at
breast height (DBH) measured. The number of rodent burrows within 20 m of
each camera was also counted to estimate potential rodent prey abundance. To
account for gross seasonal averages and variation in weather, variables (i.e. daily
low, high and mean °C and relative humidity, and total daily precipitation) were
gathered from the Western Regional Climate Center website
(http://www.wrcc.dri.edu/) that records data collected at the Hurley California
NOAA weather station located ~ 2 km from the preserve in oak woodland habitat.
Image Count and Management
All images were downloaded for storage and analysis. Information
including species, date, and time of day for images capturing target species were
recorded into a database. Images taken of the same species at any one of the
25
cameras at the same site within 30 minutes of each other were considered as a
single sighting (Wang et al., 2015).
Analysis
Previous Studies’ Statistical Methods
Identifying activity patterns of terrestrial mammals can prove valuable in
the construction of conservation and management plans. Activity patterns of
animals can be influenced by a number of abiotic and biotic factors within the
species’ ecosystem. Camera trap data lend efficiency to the process of defining
activity patterns and shifts due to the time stamp that images receive when the
camera sensor is tripped. However, generalization and comparison across studies
is hampered due to inconsistent analyses of camera trap data to infer species
activity.
Differences in the activity patterns and habitat use of three canids in central
Brazil were assessed using F-statistics of average photographic rates tested under
randomization procedures in ECOSIM 7.0 (Jacomo et al, 2004). By contrast,
Lucherini et al (2009) compared activity patterns of carnivores in the Andes by
calculating a similarity coefficient index using the percentage similarity of
Renkonen. Gray fox activity and distribution in southern California was analyzed
using a multiple-logistic-regression model and compositional analysis (Farias et al,
2012). Non-parametric kernel density estimation was used to compare temporal
activity of eight mammalian carnivores and a marsupial at differing human
activity levels in the Santa Cruz Mountains of California (Wang et al, 2015). As a
last example, Poisson regression was used to relate the number of photographs of
four small mesocarnivore species to the potential impact of larger carnivores and
to analyze differences in activity patterns between species in a mesocarnivore
26
guild of southern Illinois. In the same study a mixed-model logistic regression
was used to find evidence that mesocarnivores adjust their diel distribution of
activity in response to intraguild predation risk (Lesmeister et al, 2015).
Explanatory Variables
Weather variables were used in reports of descriptive analyses of number of
captures of target species and to define seasonal averages. Those variables were
daily temperature (mean, TEMPMEAN; maximum, TEMPMAX; minimum,
TEMPMIN), daily relative humidity (mean, HUMMMEAN; maximum,
HUMMAX; minimum, HUMMIN), and daily precipitation (PRECIP). As these
variables were only available for the McKenzie Preserve as a whole, it was not
possible to statistically evaluate their possible effects on individual sites or
elevations.
Sampling site (SITE), elevation range (ELEV), and SEASON (winter,
December-February; spring, March-May; summer, June-August; and fall,
September-November) were all categorical variables used with ANOVA, KruskalWallis (KW), and occupancy analyses.
A scatterplot matrix and a stepwise regression method (Zuur et al., 2007)
was used to identify collinearity in habitat variables: percent ground cover (four
types, BARE SOIL, ROCK, GRASS, WOOD), density of ground squirrel burrows
(BURROW), percent canopy cover (CANOPY), tree density (TREE), and mean
diameter at breast height of present trees (AVGDBH). Variables with a variance
inflation factor (VIF) less than three were considered to have greater explanatory
power (Zuur et al., 2010) and were used in KW and occupancy analyses.
Proximity to a water source was originally intended as a measurable variable to be
used in analyses, but it could not be ascertained.
27
Temporal, Seasonal, and Site
Analyses
Activity of target species at varying temporal periods: hour, week, month,
and SEASON were described using one of two metrics, either the total number of
captures of that species or capture frequency. Capture frequency was defined by
dividing the number of captures of a species in a time by the total number of
captures of the species in the duration of the study.
ANOVA (parametric) and KW (non-parametric) tests were performed to
evaluate the significance SEASON, SITE, and ELEV had on the target species rate
of capture and activity. The response variable in ANOVA and KW tests, were the
mean number of captures and relative activity of each target species, respectively.
Relative activity was calculated by dividing the number of captures of each
species at each site and season by the number of trap days at that site and season.
Post hoc Tukey tests followed up ANOVA analyses of variables with
significant differences to identify the specific levels of the variables that showed
differing rates of animal capture. Analyses finding significance with the KW test
used the Wilcoxon method as a post hoc test to find significance between SITE
comparisons. The Steel-Dwass method was the post hoc comparison test used for
ELEV and SEASON.
All analyses were conducted in SPSS (SPSS Inc., Chicago, IL), and/or
JMP® Pro (SAS Institute Inc., Cary, NC).
Habitat Analyses
Habitat use within the study area was described by changes in relative
activity of each target species at each of the six study sites and between differing
habitat variables. One way analyses using the KW test were used in consideration
of the small number of captures of raccoons, striped skunks and badgers during the
28
study, and to account for the data not showing a normal distribution. These
analyses also provide an alternative assessment of animal habitat use by using the
relative activity data in the analysis. Relative activity (number of images/number
of trap days) of each target species was used as a response variable with the
selected habitat variables as explanatory variables.
The habitat variables measured and with the most explanatory power were
sorted into three categories per variable. The difference between the maximum
and minimum measurements of each variable was divided by three to determine an
approximate range for each category. For every variable, category 1 represented
sampling sites with the minimum metric (e.g. least amount of BARE SOIL), while
category 2 were moderate sites and category 3 maximum sites. The three
categories were created to address the fact that all 6 sites had differing quantities
of each habitat variable and an analysis of the variables without being categorized
would have been identical to the analyses of SITE alone. The Steel-Dwass post
hoc comparison method was used for habitat variables showing a significant
difference in target species activity.
Intraguild Interactions
Generalized linear models identified fit of relative activity between pairs of
potential intraguild predators each season. Neither badgers nor striped skunks
were included in these analyses. In every model pair gray fox or raccoon activity
were response variables and bobcat or coyote activity were explanatory variables.
The count data violates the normality assumption of ordinary least squares linear
regression. Therefore, Poisson distribution with a Log link function was used to
link the linear predictor of the models with the expected value of the data (Zuur et
29
al., 2007). Finally, to correct for overdispersion in the data, overdispersion tests
and intervals were used.
All analyses were conducted in JMP® Pro (SAS Institute Inc., Cary, NC).
Occupancy Analysis
Many previous camera trapping studies have been conducted with the target
taxa being large predator species with identifiable individuals (e.g. big cats)
(Karanth, 1995; Karanth and Nichols, 1998; Carbone et al., 2001; Soisalo and
Cavalcanti, 2006). This study was unable to identify individuals of the target
species, as most lacked sufficiently distinctive morphological characteristics (e.g.
whisker patterns) needed for individual identification, and many images were of
other than head views. Additionally, a general characteristic of the target species
is low population density, which was expected throughout the duration of this
study. Therefore, the camera images obtained in the study could not be used to
employ traditional capture-recapture methods of estimating abundance. However,
site occupancy models have been designed to address these specific limitations
(i.e. non-detection, imperfect detection and unidentifiable individuals) while
permitting unbiased inferences of abundance for each of a study’s target species
(MacKenzie et al., 2002). To clarify, a separate analysis was possible for each
individual species detected.
Site occupancy models are contingent upon the following three
assumptions: 1) occupancy state is closed (i.e. no migration events), 2) sites are
independent, and 3) there is no unexplained heterogeneity in occupancy or
detectability (Bailey and Adams, 2005). It is unclear whether all these
assumptions are valid within the McKenzie Preserve. In the case that either the
closed occupancy state and/or the site independence assumptions are violated,
30
models have since been developed to relax each of these assumptions allowing
greater flexibility (Hines et al., 2010; Kendall et al., 2013). Therefore, using these
site occupancy models allowed the analysis of mammalian occupancy within the
McKenzie Preserve. In order to address this study’s objectives, occupancy
represented the probability that the species occupied the habitat and may also be
viewed as a surrogate of abundance measures. In addition, covariates like
elevation, vegetation coverage, and occupancy of co-occurring species were
incorporated into the models (MacKenzie, Bailey, and Nichols, 2004) to address
the biological questions of how the target species are using the habitat throughout
the year. Program PRESENCE has been used in multiple studies to model
occupancy (Bailey and Adams, 2005; Tobler et al., 2009, Lesmeister et al., 2015,
Wang et al., 2015) and was used to conduct all occupancy model analyses for this
study.
The duration of the study was divided into 28 survey periods (13 days per
survey). The count data collected throughout the study was converted to detection
(1) non-detection (0) data and used to construct detection histories (e.g.
010110001…) of each site for all 28 survey periods for bobcats, coyotes, gray
foxes, and raccoons. These detection histories were then used in Program
PRESENCE 9.7 (Hines, 2006) to run single season (not the same as season in this
study; season refers here to a single time period, in this case the year of the study)
occupancy models for each species.
The multiyear lifespan of the target species and their tendency to maintain
stable home ranges gave reason to assume occupancy was closed during the course
of the study (Riley, 2006; Wang et al., 2015). However, in the case that an
individual of any target species moved randomly in or out of the study area during
the course of the study, the closed assumption provided the flexibility to interpret
31
occupancy as use (MacKenzie et al., 2005; Cove et al., 2012). Therefore, resulting
occupancy estimates have been interpreted to estimate the probability that the
target species is using McKenzie Preserve (ψ).
Habitat site specific variables with significance from the Kruskall-Wallis
analyses for each target species were used in occupancy models as site-specific
covariates. The survey period-specific covariates used were SEASON,
TEMPMEAN, HUMMEAN, and PRECIP; these variables change with survey
periods, the first with every seven periods, and the latter three with each of the 28
periods. These site and survey covariates were incorporated into the occupancy
models with a logit link function to account for possible heterogeneity in use (ψ)
and detectability (p) during the course of the study (MacKenzie et al., 2005). This
avoided biased estimates of and identified changes in probability of species ψ and
p as a result of the modeled covariates. SEASON data was converted to a series of
four binary indicator variables, one for each of the four seasons (MacKenzie,
2012). All other variables were treated as continuous covariates and were ztransformed for use in the occupancy models (Lesmeister et al., 2015; Wang et al.,
2015).
Finally, it was assumed that the study design violated the assumption of site
independence. This violation is understood to overstate occupancy (use) estimates
due to a form of overdispersion resulting from fewer effective sampling sites than
the actual number of sampling sites (6 in this study) (MacKenzie et al., 2005).
Detection probability (p) was established first. For each of the target
species, a model holding both ψ and p constant and equal for all 28 surveys
(psi(.)p(.)) was used to compare models incorporating all possible combinations of
the four survey period-specific covariates (Lesmeister et al., 2015). These
variables accounted for heterogeneity in detection during each survey period.
32
Models were ranked by their Akaike’s Information Criterion (AIC) values and
model weight (ѡ), with the lowest AIC values as an indicator of model support
(MacKenzie et al., 2005).
Once a top model was established using the survey period-specific
covariates, it was used to model site-specific covariates and account for any
heterogeneity in ψ. The site-specific covariates used for each target species were
those thought to have a biological effect on ψ and found to be significant in the
Kruskall-Wallis analyses for the target species. Each of the determined covariates
was added to the top model (Lesmeister et al., 2015) individually and collectively.
Again, models were ranked by their AIC values and ѡ, the lowest AIC values
indicated greater model support (MacKenzie et al., 2005).
RESULTS
Capture Data
During the study, 18 cameras were continuously on for a calendar year (20
February 2014 to 19 February 2015), except for technical reasons (e.g. battery
failure). With three cameras at each sampling site a total of 5,619 trap days were
used for analysis. Sites averaged 936.5 trap days each. A total of 1,157 images
were taken of target species. Coyotes were captured most frequently (580)
followed by gray foxes (250), bobcats (181), raccoons (97), striped skunks (32),
and badgers (17). Two images of black bears were captured at two of the study
sites, insufficient number to be included in any analysis. A representative image
of each species is included in Appendix A.
Badgers, bobcats, gray foxes, and raccoons were captured more at mid
elevation Site 1 than any other site. High elevation sites (Site 2 and 3) had the
fewest number of captures of badgers, bobcats, coyotes, raccoons, and striped
skunks (Table 3).
Table 3 -- Relative Use of Study Sites by the Six Target Species on the SFC’s
McKenzie Preserve in the SNF
Species
N
Relative Use of Sites (ELEV Site#)*
Badger
17
Mid 1, Low 5, Low 6, Mid 4, High 3
Bobcat
183
Mid 1, Low 5, Low 6, Mid 4, High 2, High 3
Coyote
580
Low 6, Mid 1, Mid 4, High 3, Low 5, High 2
Gray Fox
250
Mid 1, Mid 4, High 3, High 2, Low 5, Low 6
Raccoon
97
Mid 1, Low 6, Mid 4, High 3, Low 5, High 2
Striped Skunk
32
Mid 4, Mid 1, Low 6, Low 5, High 3
*sites listed in descending order of activity
34
The varying number of captures translated into difference in relative
activity for each target species among sites, with coyotes most active at each of the
six study sites, showing positive residuals at each site (Figure 7). The badgers and
striped skunks were the only two species to have negative relative activity
residuals at every site.
0.12
Residuals of Relative Activity
0.1
0.08
0.06
0.04
0.02
0
-0.02
-0.04
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
Badger
Bobcat
Coyote
Gray fox
Raccoon
Striped skunk
-0.06
1
2
3
4
5
6
Study Site and Target Species
Figure 7 -- Residuals of relative activity of target species at each of the six study
sites on the Sierra Foothill Conservancy’s McKenzie Preserve of the SNF
Differences in relative activity were also seen between seasons, the total
number of captures of the six target species was greatest in the fall (396) and
summer (372) seasons. The winter season saw the fewest number of captures
(164). During the spring season, 225 images of target species were captured
(Figure 8). However, variation between species did exist. The badgers and the
35
striped skunks were not detected during multiple winter months of the study. All
six species were seen during at least one month of the spring, summer, and fall
seasons (Figure 9). Peak activity for striped skunks was in the summer while
bobcats, gray foxes and raccoons saw two peaks, one in the summer and a second
in the fall. Badger and coyote activity peaked in the spring and again during the
fall, although the total number of badger captures (17) was small. Coyotes were
consistently active throughout the year, with a comparable number of captures
throughout the year, but peaking in late summer and fall months. At the smaller
temporal scale, of hour, the diel activity of each target species was analyzed. All
six of the target species used for analysis were found to be active primarily during
the hours of dusk, night, and dawn (Figure 10). Bobcats, coyotes, and gray foxes
were the three target species most frequently captured during the day. However,
their frequency of capture remained low relative to dark hours.
600
Number of Captures
500
400
Fall
300
Summer
Spring
200
Winter
100
0
Badger
Bobcat
Coyote
Gray Fox
Raccoon
Striped
Skunk
Figure 8 -- Total number of captures of each species during each season of the
study
36
0.35
Capture Frequency
0.3
0.25
0.2
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Coyote
Striped Skunk
Gray Fox
Badger
Bobcat
Mean Freq
Raccoon
Figure 9 -- Mean monthly activity of the entire guild of mammalian carnivores and
each individual species, represented by the frequency of capture each month
0.3
Capture Frequency
0.25
0.2
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour of Day
Coyote
Gray Fox
Bobcat
Raccoon
Striped Skunk
Badger
Figure 10 -- Diel activity of the six target species represented by the frequency of
capture at each hour of the day
37
Changes in mean monthly temperature and relative humidity and total
precipitation were compared to changes in the total number of captures of the
entire mammalian mesocarnivore guild. The guild was more active during periods
of warmer mean temperatures (Figure 11). Months with higher total precipitation
and the following month saw a decrease in the number of captures (Figure 12).
Finally, captures were higher when relative humidity was lower (Figure 13).
These comparisons corresponded with the monthly and seasonal shifts seen in
guild capture frequencies.
160
60
140
50
40
100
80
30
60
20
40
10
20
0
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Animal Captures
MEANTEMP C
Figure 11 -- Total number of captures of all target species combined for each
month compared to the mean temperature each month
MEANTEMP (ͦC)
Number of Captrures
120
38
160
500
450
140
400
350
100
300
80
250
200
60
150
Precipitation (mm)
Number of Captures
120
40
100
20
50
0
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Animal Captures
Precipitation
Figure 12 -- Total number of captures of all target species combined for each
month compared to the total monthly precipitation
160
100
90
140
80
Number of Captures
70
100
60
80
50
40
60
30
40
20
20
10
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Month
Animal Captures
RHMEAN
Figure 13 -- Total number of captures of all target species combined for each
month compared to monthly relative humidity
Relative Humidity (%)
120
39
Target Species Distribution and Habitat Use
Capture and Relative Activity
Variations by Season and Site
The differences in mean number of captures or relative activity of each
target species were not significantly different between any of the four seasons.
Differences in mean number of captures between sites were found to be significant
(P < 0.05) for bobcats, coyotes, and raccoons. Post hoc Tukey tests showed
bobcat captures to be significantly higher at Site 1 than all five other sites: Site 2
(P = 0.006), Site 3 (P = 0.005), Site 4 (P = 0.032), Site 5 (P = 0.035) and Site 6
(P = 0.025). Site 1 produced significantly higher numbers of raccoon captures
when compared with Site 2 (P = 0.004), Site 3 (P = 0.005), Site 4 (P= 0.006) and
Site 5 (P = 0.004). Coyote numbers were higher at Site 1 than at Site 2 (P =
0.024) and Site 5 (P = 0.037), and Site 6 had significantly higher capture numbers
than Site 2 (P = 0.026) and Site 5 (P = 0.040).
Differences in relative activity between sites was also found to be
significant for bobcats (P = 0.0089), raccoons (P = 0.0093), and coyotes (P =
0.0122). Non parametric post hoc tests using the Wilcoxon method showed that
bobcat activity at Sites 1 and 5 was higher than activity at Site 2 (P = 0.0304) and
Site 3 (P = 0.0294). Coyote activity at Site 1 was higher than activity at Sites 2, 3,
4, and 5 (P = 0.0304). Also, Sites 4 and 6 showed greater coyote activity than Site
2 (P = 0.0304). Site 1 also showed greater raccoon activity when compared with
Sites 2 (P = 0.0265), 3 (P = 0.0304), 4 and 5 (P = 0.0294). Lastly, raccoon
activity at Site 6 was higher that Site 5 (P = 0.0294).
Spatial differences in capture were also seen between elevations for both
bobcats and gray foxes (P < 0.05). Bobcats were seen more at the mid elevation
sites than the higher elevation sites (P = 0.018), while gray foxes were captured
40
more at the mid elevation sites than the low elevation sites (P = 0.006). No other
target species was captured more or less times at the three different elevations.
The KW analysis of relative activity at the three elevation ranges, indicated
differing amounts of activity for the bobcat (P = 0.0019), coyote (P = 0.0133),
gray fox (P = 0.0075), and badger (P = 0.0206). Bobcats were less active at the
high elevation sites than at both the low (P = 0.0072) and mid (P = 0.0148)
elevation sites. Coyotes were active at the mid elevation sites more than at the
high elevation sites (P = 0.0108), while the gray foxes were more active at the mid
elevation sites than the low elevation sites (P = 0.0191). Finally, badgers showed
greater activity at the low elevation sites when compared with the high elevation
sites (P = 0.0248). Neither raccoons nor striped skunks were more or less active
at the three different elevations.
Habitat Species Activity Analysis
Measurements of habitat variables are reported in Appendix B. All ground
cover and canopy cover variables are reported as percent cover. BURROW and
TREE are counts and represent density. AVGDBH was measured in cm. All
habitat variable measurements were different at every site; not one site had a
similar measurement in any variable as any other site. The variables with the
strongest explanatory power were WOOD, ROCK, CANOPY, TREE, and
BURROW (P < 0.05; VIF < 3.0) and each was divided to make three categories
for inclusion in KW analyses (Table 4). All five habitat variables tested against
relative activity of target species was significant for at least one of the species.
ROCK was significant for the gray foxes (P = 0.0092). Sites with
moderate rock coverage had higher activity than the sites with the least amount of
rock cover (P = 0.0103). Bobcat activity was significantly different between
41
Table 4 -- Resulting Categories of Habitat Variables Showing Significant
Differences in Relative Activity of Target Species and the Variables VIF
Habitat Variable
1
2
3
VIF
WOOD%
0-3
4-7
8-11
*
ROCK%
0-6
7-14
15-21
1.85
CANOPY%
4-10
11-17
18-24
1.51
TREE
3-10
11-18
19-27
1.14
BURROW
0-25
26-50
51-78
2.05
%
Numbers represent the percent ground and canopy cover
* Wood was the response variable in the last step of the regression model and was not given a VIF
sites with differing percentages of WOOD (P = 0.0132). Sites with less wood
cover had greater bobcat activity (P = 0.0147).
Canopy cover showed differences in activity for badgers (P = 0.0248),
bobcats (P = 0.0019), coyotes (, P = 0.0026), and raccoons (P = 0.0007). Sites
with the most canopy cover showed more activity relative to sites with a moderate
canopy (badgers P = 0.0250, bobcats P = 0.0077, coyotes P = 0.0055, and
raccoons P = 0.0051). Only coyotes (P = 0.0476) and raccoons (P = 0.0036)
were more active at the sites with a large canopy relative to sites with the least
canopy cover. Bobcats were the single species showing more activity at sites with
the least canopy cover relative to the sites with a moderate canopy (P = 0.0148).
The number of trees at sites was significant for gray foxes only (P = 0.0179).
Sites with the most trees had more activity than the sites with the least number of
trees (P = 0.0257).
Finally, burrow count was significant for gray fox activity only (P =
0.0168). Sites with the least number of rodent burrows had greater activity of gray
foxes than sites with a moderate number of burrows (P = 0.0257).
42
Intraguild Interactions
Raccoon activity responded positively to bobcat and coyote activity (Figure
14). The seasonal responses to bobcat activity were seen in the winter (P <
0.0001), spring (P = 0.0002), and summer (P < 0.0001). The positive relationship
between the raccoon and coyote was seen in winter (P = 0.0062), spring (P =
0.0022), and fall (P < 0.0001).
Figure 14 -- Generalized linear models of raccoon activity in response to coyote
activity in the winter (top left), spring (top right), winter (middle left) and bobcat
activity in the winter (middle right), spring (bottom left), summer (bottom right)
43
Gray fox activity also showed a response to bobcat and coyote activity
(Figure 15). In the winter, gray fox activity declined as bobcat activity increased
(P = 0.0289). Spring (P = 0.0002) and summer (P = 0.0057) seasons showed an
increase in gray fox activity as bobcat activity increased. The coyote was
positively related to gray fox activity in the summer season only (P = 0.0121).
Figure 15 -- Generalized linear models of gray fox activity in response to coyote
activity in spring (top left) and bobcat activity in winter (top right), spring (bottom
left), summer (bottom right)
Species Occupancy
The models with ∆AIC values ≤ 2 from the top model, and psi(.),p(.) for
comparison, are shown in Table 5 (Lesmeister et al., 2015). Support for the
raccoon model was not strengthened by any of the four survey period-specific
covariates. In all other cases, top supported models included a single covariate or
44
an interaction between two covariates (bobcats: MEANTEMP; coyotes:
MEANTEMP+PRECIP; gray foxes: SEASON+MEANHUMID).
Table 5 -- Top Ranked Use Models Incorporating Survey-Period Specific
Covariates for Each Target Species (bobcats, coyotes, gray foxes, and raccoons)
Model
Bobcat
psi(.),p(MEANTEMP)
psi(.),p(MEANTEMP+MEANHUMID)
psi(.),p(MEANTEMP+PRECIP)
psi(.),p(.)
Coyote
psi(.),p(MEANTEMP+PRECIP)
psi(.),p(MEANTEMP)
psi(.),p(MEANTEMP+HUMID)
psi(.),p(.)
Gray Fox
psi(.),p(SEASON+MEANHUMID)
psi(.),p(SEASON+MEANTEMP+MEANHUMID)
psi(.),p(SEASON+MEANHUMID+PRECIP)
psi(.),p(.)
Raccoon
psi(.),p(.)
psi(.),p(MEANTEMP)
psi(.),p(SEASON)
psi(.),p(MEANHUMID)
psi(.),p(PRECIP)
AIC
ΔAIC
ѡ
K
223.84
225.46
225.48
233.46
0
1.62
1.64
9.62
0.5281
0.2349
0.2326
0.0043
3
4
4
2
141.53
142.75
143.3
148.78
0
1.22
1.77
7.25
0.5044
0.274
0.2082
0.0134
4
3
4
2
209.3
210.51
211.08
232.86
0
1.21
1.78
23.56
0.5111
0.2791
0.2099
0
7
8
8
2
205.02
206.14
206.63
206.63
207.01
0
1.12
1.61
1.61
1.99
0.3527
0.2015
0.1577
0.1577
0.1304
2
3
6
3
3
AIC - Akaike’s Information Criteria value
ΔAIC – Difference between the AIC value of the top ranked model (MacKenzie, 2012)
ѡ – AIC model weight; measure of support for the model being the best
K – Number of parameters in the model
MEANTEMP had positive coefficient estimates for both the bobcat (0.5478
± 0.1657) and coyote (0.7655 ± 0.2405). Additionally, PRECIP produced a
positive coefficient estimate (0.4276 ± 0.2573) in the coyote model. The top gray
fox model estimated a negative coefficient for MEANHUMID (-0.7748 ± 0.3667).
45
SEASON was a second covariate in the top gray fox model. The coefficient
estimates during the winter and fall were positive, while the spring and summer
were negative.
Estimates of p are reported from the output of each top model. Model
output indicated p estimates to be the same at all sites for each survey period.
However, p for the bobcats, coyotes, and gray foxes varied across all 28 survey
periods. The calculated mean 95% confidence interval for the seven survey
periods of each season are reported in Table 6. The summer season estimated the
highest p for both bobcats (p = 0.4715 - 0.7088) and coyotes (p = 0.8439 -0.9678).
The fall season estimated the highest p for gray foxes (p = 0.5513 - 0.8661).
Bobcat and coyote detection was lowest in winter (bobcats: p = 0.1930 - 0.3901;
coyotes p = 0.5896 - 0.8723). During the spring, gray foxes were least likely to be
detected (p = 0.1070 - 0.3820). The raccoon estimated p was constant across all
survey periods of the study (p = 0.2225 - 0.3586).
Table 6 -- Estimated Mean Seasonal Detectability of Target Species (bobcats,
coyotes, gray foxes, and raccoons) at the McKenzie Preserve
Winter p
Spring p
Summer p
Fall p
Bobcat
0.19 - 0.39
0.32 - 0.49
0.4715 - 0.71
0.34 - 0.52
Coyote
0.59 - 0.87
0.75 -0.90
0.84 -0.97
0.76 - 0.91
Gray Fox
0.17 -0.44
0.11 - 0.38
0.31 - 0.61
0.55 - 0.87
Raccoon
0.22 - 0.36
0.22 - 0.36
0.22 - 0.36
0.22 - 0.36
After each of the determined site-specific covariates modeled to account for
heterogeneity in ψ, support was not added to the top models produced by the
survey period-specific covariates for any of the target species (Table 7). Estimates
of ψ are reported from the output produced in each of the top models for each
46
target species. The probability of use (ψ) of the McKenzie Preserve by bobcats,
coyotes, gray foxes, and raccoons was 1.0 ± 0.0. When the ψ parameter estimates
are derived with consideration of the detection history for each species at each
sampling site, the parameter is called conditional psi (ψc) (MacKenzie, 2012). The
95% confidence interval of ψc was 1.0-1.0 for all species modeled.
Table 7 -- Use of McKenzie Preserve Models Incorporating Site-Specific
Covariates for Each Target Species (bobcats, coyotes, gray foxes, and raccoons)
Model
Bobcat
psi(.),p(MEANTEMP)
psi(CANOPY),p(MEANTEMP)
psi(WOOD),p(MEANTEMP)
psi(ELEVAT),p(MEANTEMP)
psi(WOOD+CANOPY+ELEVAT),
p(MEANTEMP)
Coyote
psi(.),p(MEANTEMP+PRECIP)
psi(ELEVAT),p(MEANTEMP+PRECIP)
psi(CANOPY),p(MEANTEMP+PRECIP)
psi(ELEVAT+CANOPY),p(MEANTEMP+
PRECIP)
Gray Fox
psi(.),p(SEASON+MEANHUMID)
psi(BURROW),p(SEASON+MEANHUMID)
psi(TREE),p(SEASON+MEANHUMID)
psi(ELEVAT),p(SEASON+MEANHUMID)
psi(ELEVAT+BURROW+TREE),p(SEASON+
MEANHUMID)
Raccoon
psi(.),p(.)
psi(CANOPY),p(.)
psi(ELEVAT),p(.)
psi(CANOPY+ELEVAT),p(.)
AIC
ΔAIC
ѡ
K
223.84
225.84
225.84
225.84
0
2
2
2
0.4644
0.1708
0.1708
0.1708
3
4
4
4
229.84
6 0.0231
6
141.53
143.53
143.53
0 0.5344
2 0.1966
2 0.1966
4
5
5
145.53
4 0.0723
6
209.3
211.3
211.3
211.3
0
2
2
2
7
8
8
8
215.3
6 0.0231 10
205.02
207.02
207.02
209.02
0
2
2
4
0.4644
0.1708
0.1708
0.1708
0.5344
0.1966
0.1966
0.0723
AIC - Akaike’s Information Criteria value
ΔAIC – Difference between the AIC value of the top ranked model
ѡ – AIC model weight; measure of support for the model being the best (MacKenzie, 2012)
K – Number of parameters in the model
2
3
3
4
DISCUSSION
This study captured 1,157 images used for analysis during the winter
(February and December), spring, summer and fall seasons of 2014 and the winter
(January and February) season of 2015. Historically, more than 12 species of
mammalian omnivores and carnivores were estimated to inhabit the region of the
SNF where this study was conducted (Barrett et al., 1980; Jameson & Peeters,
1988). This study detected seven of those species, establishing a contemporary
baseline of species richness in a localized area of the SNF. All of the detected
species are considered to be mesocarnivores with heterogenous sensitivities to
habitat fragmentation (Crooks, 2002; Ordenana et al., 2010). Detection of these
animals within the McKenzie Preserve suggests that there is sufficient
connectivity to adjacent and suitable foothill habitat where these mammals would
also be expected to occur. Species that might have been detected but were not are
either small, have patchy distributions and more restricted habitats (spotted skunk,
ringtail, and various weasels), or have very low population densities (mountain
lion) (Jameson & Peeters, 1988; Crooks, 2002).
The apparent reduction of species in this mammalian community agrees
with the assertion that the predators of North America are experiencing a reduction
of their ranges (Laliberte and Ripple, 2004). Despite this possible reduction, this
study provided insight into how the activity of the six analyzed species was
distributed spatially and temporally within the McKenzie Preserve of the SNF.
Additionally, habitat and environmental characteristics were identified that may be
important for both the coexistence and sustainability of mammalian predator
populations and for future research designs.
48
Mammalian Mesocarnivore Distribution and Activity
Five of the six study sites captured all six species (badger, bobcat, coyote,
gray fox, raccoon, and striped skunk) used in analyses. Site 2 was the only site
that lacked both badgers and striped skunks. Additionally, the occupancy models
estimated the probability of habitat use on the McKenzie Preserve to be 100% for
bobcats, coyotes, gray foxes, and raccoons. Badgers and striped skunks were not
incorporated in occupancy models; both were detected a small number of times,
17 and 32 respectively. This could be partly due to their home ranges being
smaller than the McKenzie Preserve and partly due to patchy distribution (Long,
1973; Wade-Smith and Verts, 1982). Also, the differing number of captures for
each species and the occupancy estimates may be interpreted as insight into
species abundance. Allowing for this interpretation, badger and striped skunk
abundances were depressed relative to the other target species, while an elevated
abundance was suggested for the coyote, with 580 captures. In this study the
number of captures was used to represent activity, because animals of any of the
species were not individually identifiable, as they lacked distinctive intraspecific
markings, unlike for example, big cats (Karanth and Nichols, 1998), and facial
images are often necessary for definitive identification; many captures in this
study were not head-on.
That badger and striped skunk activities were relatively lower than all the
other species, reaching zero during winter months, is supported by their natural
history. Badgers can retract their home range to 55 ha and experience a torpid
condition during winter months (Long, 1973) and striped skunks can remain
inactive for 118 days during the winter season (Wade-Smith and Verts, 1982).
Overall, Site 1 had the most activity throughout the duration of the study.
In both the ANOVA and Kruskall-Wallis analyses Site 1 had significantly higher
49
activity than at least one other site for bobcats, coyotes, and raccoons. This
elevated activity may be attributed, in large part, to the water trough at the site.
The locations of other permanent water sources within the preserve, either natural
or anthropogenic, were not available. Without this information, water availability
could not be considered as a potential reason bobcats showed elevated activity at
Site 5 relative to Sites 2 and 3. Coyotes were also more active at sites other than
Site 1; Sites 4 and 6 had greater coyote activity than Site 2. This could be partly
due to an increase in the number of captures of coyotes in the summer and fall and
the proximity of Site 6 to a natal den. Site 6 captured coyote pups in July (see
Appendix A), only two months after the birth month of coyotes (Bekoff and Gese,
2003). Raccoons were also more active at Site 6 than Site 5. This could be a
result of Site 6 being closest to the preserve entrance, picnic area, and where the
preserve’s only trash receptacles are located. Raccoons are generalists and are
successful at exploiting areas with greater anthropogenic use and alteration
(Bateman and Fleming, 2012). Alternatively, the raccoon does have an estimated
home range of 49 ha (Gehrt, 2003), small enough for McKenzie Preserve to
accommodate multiple raccoon home ranges. Therefore, Sites 1 and 6 may have
been in greater proximity to a number of raccoon home ranges than Sites 2, 3, 4,
and 5. According to the most supported occupancy models, for all species, there
was no difference in the probability of use between study sites, ψ = 1 for all sites.
Bobcats, coyotes, and badgers were all more active at the low and mid
elevation sites than the high elevation sites. Bobcats have been shown to be more
active at higher elevations in the summer (1852 m) and lower (1365 m) elevations
in the winter, but this study did not occur at similar elevations (Koehler and
Hornocker, 1989). However, the Koehler and Hornocker (1989) study suggests
that bobcat activity on McKenzie Preserve could be higher in the winter, possibly
50
providing refuge from higher elevation snow, but no significant difference in
activity was found between seasons for the bobcat or any other target species.
This could be due to the current state of drought in California, although without
any previous assessments of mammalian activity, this is speculation. The activity
of bobcats at lower elevations could be explained by the geology of the McKenzie
Preserve. The high elevation sites atop basalt lava tables are less likely to support
abundant prey populations (e.g., lagomorphs and rodents, many of which burrow)
for both bobcats and coyotes. Badgers are also dependent on the ability to burrow
and hunt (Long, 1973) and may find this more possible at the lower elevation sites.
High points on the McKenzie Preserve are nearly 1000 m below the
optimal elevation range for gray fox activity, 1150 – 1525 m (Cypher, 2003).
However, the mid and high elevation study sites (340 – 563 m) had more gray fox
activity than the low elevation sites (236 – 269 m). This indicates that gray foxes
are finding suitable habitat well below the range were they are expected to be most
abundant, but still at the highest elevations of the preserve.
Diel activity of all species was lowest during the day and highest during the
hours of twilight and night. This corresponds with the normal nocturnal nature of
the species in the study. Badgers, raccoons, and striped skunks are almost entirely
nocturnal (Long, 1973; Wade-Smith and Verts, 1982; Gehrt, 2003). Only the
striped skunk was captured during the daytime hours, once during the ninth hour
of the day. Badgers and raccoons were never captured during the day.
Habitat and Environmental Characteristics
The habitat variables found to have any association with the target species
were variable aspects of ground cover (WOOD and ROCK), CANOPY, TREE,
and BURROW. WOOD may have had a positive relationship with activity of
51
bobcats, coyotes, or gray foxes due to their prey base likely finding refuge in
fallen woody debris, as has been previously hypothesized (Bunnell and Houde,
2010; Lesmeister et al., 2015). Lower percentages of wood debris were associated
with higher bobcat activity. Site 1 had the very least amount of wood debris, but
did have the water trough and a higher number of bobcat captures than any of the
other sites. This was the same case with ROCK. The gray fox showed greater
activity as sites with moderate ROCK cover. This agrees with the natural history
of the gray fox, being associated with rugged terrain and rocky outcroppings for
denning (Cypher, 2003). However, Site 1 had a moderate amount of ROCK
ground cover and the water trough, confounding this inference.
TREE and CANOPY are variables indicating tree density and maturity.
Sites with higher numbers and percentages of these variables were thought to
exhibit higher activity from species more associated with mature forest patches:
gray foxes (Cypher, 2003; Farias et al., 2012) and bobcats (Lariviere and Walton,
1997) for denning, cover, protection, or escape from larger predators (e.g.
coyotes). This was supported by a positive relationship between the TREE
variable and gray fox activity. The two sites with the greatest number of trees had
the highest gray fox activity, possibly suggesting that gray foxes were more active
in these habitats on the preserve to potentially den or escape coyote interaction
(Farias et al., 2012). However, this inference is confounded by Site 1, with the
water trough, being one of the two sites with the greatest number of trees. Sites
with the highest percent of canopy cover saw more activity in badgers, bobcats,
coyotes, and raccoons. CANOPY and bobcat activity supports the association of
the bobcat with wooded habitats, especially in the summer season (Koehler and
Hornocker, 1989). Still, the high category of CANOPY included Site 1 (with the
water trough).
52
All the results for these variables, including the relationship of sites with
the least number of burrows seeing the greatest levels of gray fox activity, are
confounded by the water trough at Site 1. Site 1 was not discarded in the analyses
because the site sample size was already small at n = 6. Any future study would
have to account for this, to allow for any accurate inferences about the impact of
these variables on the activity of the target species. And it is clearly essential to
know the locations of permanent water sources within the preserve.
Intraguild Interactions
In all but one instance, activity of gray foxes and raccoons was positively
associated with increased activity of bobcats or coyotes. In all cases raccoon
activity was aslo positively associated with both bobcat and coyote activity. The
increase of activity by gray foxes in the spring as coyote activity increased
contradicts findings in previous studies, reporting evidence for interference
interaction between the two species (Fedriani et al., 2000; Farias et al., 2012;
Lesmeister et al., 2015). This allows for the presumption that there would have
been a decrease in gray fox activity. The generalized linear models did not find a
significant fit, positive or negative, between coyote and gray fox activity during
any other season. However, bobcat activity was negatively related to gray fox
activity during the winter season. This can be explained by a potential overlap in
diet during the winter, found in previous studies (Neale and Sacks, 2001). The
winter diet for the gray fox consists predominately of lagomorphs and rodents,
more than during any other season (Fedriani et al., 2000; Cypher, 2003), causing a
dietary overlap with the hypercarnivorous bobcat (Lariviere and Walton, 1997;
Fedriani et al., 2000). During the spring and summer seasons, when the gray fox
diet shifts to comprise invertebrates and plant material (Cypher, 2003), the
53
generalized linear models showed positive interaction in activity between the
bobcat and gray fox.
The co-occurrence of all six target species throughout the study and the
lack of evidence of avoidance at the temporal or spatial scales addressed in the
study, other than bobcats and gray foxes in the winter, suggests niche
differentiation and resource partitioning to be allowing coexistence of the target
species on McKenzie Preserve (Azevedo et al., 2006). Perhaps an analysis of the
data at smaller temporal scales or an experiment designed at a larger spatial scale
would have identified differences between these species, as found in previous
studies (Schuette et al., 2012; Monterosso et al., 2014; Lesmeister et al., 2014;
Wang et al., 2015).
This was the first quantitative survey of the mammalian carnivore
community in SNF oak woodland habitat. The study produced a baseline
assessment of mammalian mesocarnivore richness for a local region of oak
woodland habitat in the SNF, providing a preliminary indication of distribution
and habitat use. Additionally, the probability of habitat use on McKenzie Preserve
in combination with the intraguild interactions identified suggests the species of
the community are successfully addressing the pressures of exploitative and
interference interaction and are coexisting by their use of temporal, spatial and
resource partitions. Nevertheless, species activities at larger scales remain
unknown, and the results here suggest further studies of mammalian population
dynamics are warranted throughout the SNF, one of the most anthropogenically
threatened and degraded ecosystems in the state.
54
Future Research
Addressing the violation of independence between sampling sites,
increasing the number of sampling sites, and covering a larger and more diverse
area of SNF habitat would not only clarify the results of the single species
occupancy models, but also allow the use of species co-occurrence occupancy
models, and multi-season occupancy models. These changes and additions, and
more adequate control of confounding variables (e.g. sources of water), would
give potential to more clearly interpret potential intraguild interactions underway
within SNF oak woodland habitat. Additionally, a redesign would allow greater
attention on which habitat variables have associations with mesocarnivore use,
occupancy, abundance, colonization and extinction (MacKenzie et al., 2004;
Bailey et al., 2014; Wang et al., 2015). The probability of detection identified in
this study can inform future researchers what time of year and during what seasons
to concentrate data collection and surveying efforts. The probability of detecting
coyote and bobcat presence is greatest in the summer, suggesting future surveying
for coyotes or bobcats take place in that season, perhaps with greater sampling
breadth and intensity to allow for more accurate estimates of habitat use. The
study also suggests focusing gray fox surveys in the fall. Addressing these
suggestions can improve the efficiency of future studies. Additionally, these
future studies would be valuable for monitoring programs and conservation
management plans, considering the ongoing anthropogenic development and
climate change underway in the region. Additionally, they could be compared
with the results here to identify and monitor changes in richness and shifts in
activity and distribution of the species.
Furthermore, the non-detection of the mountain lion suggests the coyote
has ascended to become the apex predator in the community (Laliberte and Ripple,
55
2004; Prugh et al., 2009). Also, the detection of the black bear suggests a
potential change in distribution and exploitation of the exurban development in the
region (Goad et al., 2014), maybe as a response to drought conditions or climate
change. These changes also indicate potential for future community shifts and top
down trophic cascades with potential to impact bird populations (Crooks and
Soule, 1999) and vegetation (Norrdahl et al., 2002; Hamback et al., 2004). The
seasonal activity baseline on the McKenzie Preserve established in this study
could be used to address bird and plant community and phenology data along with
the grazing regime of cattle on private lands to better inform future management
and development plans in the oak woodlands of the SNF region.
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APPENDICES
APPENDIX A: POSITIVE CAPTURE IMAGES OF EACH
TARGET SPECIES
67
Positive capture image of a badger at Site 5.
Positive capture image of a bobcat at Site 3.
68
Positive capture image of a coyote at Site 4.
Positive capture image of coyote pups at Site 6.
69
Positive capture image of a gray fox at Site 3
Positive capture image of a raccoon at Site 1.
70
Positive capture image of a striped skunk at Site 1.
Positive capture image of a black bear at Site 5.
APPENDIX B: MEASUREMENT OF HABITAT VARIABLES
COLLECTED FROM SAMPLING SITES
72
Habitat Variables Collected from Each Sampling Site
SITE
ELEVAT
BARE
ROCK
GRASS
WOOD
BURROW
CANOPY
TREE
AVGDBH
WATER
1
354
14
10
75
1
25
20
19
24.08
Annual
2
563
19
21
60
0
0
17
5
51.5
No
3
561
2
14
73
11
0
18
27
21.69
No
4
340
3
7
90
0
78
9
16
34.7
Seasonal
5
269
0
0
100
0
40
4
3
27.9
Seasonal
6
236
21
5
74
0
30
24
8
36.55
Seasonal
ELEVAT – Elevation measured in meters
BARE – Mean percent of ground cover within the 20 m radii circles around each camera that is bare soil
ROCK – Mean percent of ground cover within the 20 m radii circles around each camera that is rock
GRASS – Mean percent of ground cover within the 20 m radii circles around each camera that is grass
WOOD – Mean percent of ground cover within the 20 m radii circles around each camera that is wood
debris
BURROW – Total count of burrows within the 20 m radii circles around each camera
CANOPY – Mean percent of 20 m radii circles around each camera that is under canopy cover
TREE - Total count of tress within the 20 m radii circles around each camera
AVGDBH – Mean diameter of trees at breast height
WATER – Type of water source at each site
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