QUANTIFYING THE EFFECTS OF HABITAT DISTURBANCE ON THE TIMBER
RATTLESNAKE, Crotalus horridus, IN NORTHEASTERN PENNSYLVANIA

By

Jonathan M. Adamski, B.S.
East Stroudsburg University of Pennsylvania

A Thesis Submitted in Partial Fulfillment of
The Requirements for the Degree of
Master of Science in Biology
To the Office of Graduate and Extended Studies of
East Stroudsburg University of Pennsylvania

May 10, 2019

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ABSTRACT

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Biology to the Office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania

Student’s Name: Jonathan Adamski
Title: Quantifying the Effects of Habitat Disturbance on the Timber Rattlesnake, Crotalus
horridus, in Northeastern Pennsylvania
Date of Graduation: May 10, 2019
Thesis Chairperson: Thomas C. LaDuke, Ph.D.
Thesis Member: Shixiong Hu, Ph.D.
Thesis Member: Terry Master, Ph.D.
Thesis Member: Emily Rollinson, Ph.D.

Abstract:
This project examined the relationship between anthropogenic habitat disturbance and
population levels in Crotalus horridus (Timber Rattlesnake). This study relied on population
and habitat information collected by the Pennsylvania Fish and Boat Commission (PFBC)
during a previous study known as the Timber Rattlesnake Assessment Project (TRAP).
Geographic Information Science (GIS) was utilized to measure landscape features such as
canopy coverage, trails, and road density through habitat utilized by Timber Rattlesnakes.
Using the information from TRAP, in conjunction with GIS technology, quantitative results
were produced and analyzed to construct a clear picture of how human habitat alterations
affect Timber Rattlesnake populations. The results were primarily derived from two main
models, (1) a linear regression with a normalize distribution and (2) a generalized linear
model with a binomial distribution. An inverse relationship was found between rattlesnake
populations and proximity and density of buildings at the large spatial scale. These findings
suggest that anthropogenic disturbance impacts Timber Rattlesnakes negatively in the
commonwealth. The weak relationships between the variables assessed may be, in part,
attributable to the use of TRAP reports which were mostly based on one or two site visits and
not intended to provide population estimates. Further work will be necessary to refine our
models, including improved population estimates and expansion of our work to the entire
commonwealth.

Acknowledgments
My time in graduate school has been an incredibly rewarding endeavor that has
left me with memories and experiences that I won’t soon forget.
I would like to thank my friends, both new and old, for always being there to
bounce ideas off, to pick me up when I’m down, and for all the good times had.
Specifically, I’d like to thank the many other graduate students in the department who
have gone through the same cycle of many ups and many more downs with meAlexandra Machrone, Justin Clarke, Kristine Bentkowski, Joseph Schell, Brandon
Swayser, and Sebastian Harris. Thank you for teaching me about new biological areas,
helping with field work, and letting me join you in the field for your projects. Lastly, I’d
like to thank Nikolai Kolba for helping with various GIS questions over the years, doing
field work with me, and overall being a great friend.
I’d like to extend thanks to the Fish and Boat Commission and to Chris Urban,
specifically. This project would not have happened if not for the hard work put forth
through TRAP, nor without the research grant awarded to East Stroudsburg University
regarding the TRMP.
Thank you to the many professors that have helped shaped me into the person I
am today- Dr. Hu, Dr. Wilson, Dr. Smith, Dr. Brunkard, Dr. Whitford, and Dr. Hotz.
Thank you to Heather Dominguez for her help with logistics in the bio department
and ensuring the day to day mission was accomplished, as well as helping with travel
grants.
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Thank you to Dr. Whidden for the experiences in conservation, mammalian
surveying techniques, vegetation studies, and for enjoying a bonfire on many camping
trips, whether Stony Acres or various Bioblitz’s.
Thank you to Dr. Wallace, who introduced me to a whole new area of biology and
taxonomy and for allowing me to do independent research under him.
Thank you to Dr. Master for the many experiences over the years- Christmas bird
counts, field trips, adventures in Cape May, as well as the regular roasting. Thank you for
your contributions to this project and lending your experience.
Thank you to Dr. Rollinson: This project would not have been anywhere near
what is has become without your help. I’m incredibly grateful that you chose to come
work at ESU’s Biology Department and are available to answer questions on a regular
basis (Sorry that I constantly chase you down the hallway to ask statistic questions).
Additionally, thank you for all the hard work you’ve put into my project over the last
year. I’m sincerely grateful for everything you’ve done for me and the other graduate
students.
Thank you to Dr. Thomas LaDuke for being my mentor, advisor, supervisor, and
friend over the last 7 years. I’ve learned an incredible amount of knowledge from you
over the last few years, not all of it related to academia. I’m grateful that I came to ESU
when I did, and that I was able to work alongside someone as experienced as you in the
field. Thank you for all of your help with classes, undergraduate research, problems with
the animal labs, guiding me through my stressful thesis work, always lending an ear over

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a glass of whiskey, and for always giving a guiding hand when life became too
overwhelming.
Thank you to the many Pennsylvania GIS county coordinators for providing me
with building data for their respective counties.
Thank you to the Pennsylvania Spatial Data Access for providing public GIS
layers for use in my research.
Thank you to Jim and Lael Rutherford for their generous scholarship that helped
make this project possible.
Thank you to the many PARS, TRAP, and TRMP volunteers that assisted with
field work for the many projects involving our study species, Crotalus horridus. Without
your hard work this project would not have been possible.
Thank you to my family, who has always been supportive of my interests and
goals over the years and who have allowed me to pursue a career that I will always enjoy.
Thank you to my mother, Patricia, for always putting her children before her and for
always pushing us to pursue what we love.

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Table of Contents
Acknowledgments................................................................................................................ i
List of Figures .................................................................................................................... vi
List of Tables .................................................................................................................... vii
List of Appendices ............................................................................................................. ix
CHAPTER 1: INTRODUCTION ....................................................................................... 1
Life History of the Timber Rattlesnake........................................................................... 2
Decline of Timber Rattlesnake ........................................................................................ 9
Timber Rattlesnake Assessment Project ....................................................................... 12
Geographic Information Science ................................................................................... 12
Objectives ...................................................................................................................... 13
CHAPTER 2: METHODS AND MATERIALS .............................................................. 14
Study Area ..................................................................................................................... 14
Data Collection .............................................................................................................. 16
Correlation Factors ........................................................................................................ 19
Analysis ......................................................................................................................... 22
Presence/pseudo-absence comparisons ......................................................................... 24
CHAPTER 3: RESULTS .................................................................................................. 26
Model 1: Abundance Model .......................................................................................... 26
Model 1: Fifty-Meters ............................................................................................... 27
Model 1: Four-Hundred-Meters ................................................................................ 29
Model 1: Five-Thousand-Meters ............................................................................... 31
Model 2: Non-Zero Abundance Model ......................................................................... 34
Model 2: Fifty-Meters ............................................................................................... 34
Model 2: Four-Hundred-Meters ................................................................................ 35
Model 2: Five-Thousand-Meters ............................................................................... 37
Model 3: Presence-Absence Model............................................................................... 39
Model 3: Fifty-Meters ............................................................................................... 39
Model 3: Four-Hundred-Meters ................................................................................ 41
Model 3: Five-Thousand-Meters ............................................................................... 43
Model 4: Abundance Model Without Pike County....................................................... 45
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Model 4: Fifty-Meters ............................................................................................... 45
Model 4: Four-Hundred-Meters ................................................................................ 47
Model 4: Five-Thousand-Meters ............................................................................... 49
Model 5: Non-Zero Abundance Model Without Pike County ...................................... 50
Model 5: Fifty-Meters ............................................................................................... 50
Model 5: Four-Hundred-Meters ................................................................................ 52
Model 5: Five-Thousand-Meters ............................................................................... 54
Model 6: Presence-Absence Model Without Pike County............................................ 56
Model 6: Fifty-Meters ............................................................................................... 56
Model 6: Four-Hundred-Meters ................................................................................ 58
Model 6: Five-Thousand-Meters ............................................................................... 60
Presence/Pseudo-Absence Analyses ............................................................................. 62
CHAPTER 4: DISCUSSION ............................................................................................ 65
Model 1: Abundance Model .......................................................................................... 66
Model 2: Non-Zero Abundance Model ......................................................................... 67
Model 3: Presence-Absence Model............................................................................... 67
Model 4: Abundance Model Without Pike County....................................................... 68
Model 5: Non-Zero Abundance Model Without Pike County ...................................... 69
Model 6: Presence-Absence Model Without Pike County............................................ 70
Presence/Pseudo-Absence Comparisons ....................................................................... 71
Conclusion..................................................................................................................... 71
Future Goals .................................................................................................................. 75
WORKS CITED ............................................................................................................... 78
APPENDICES .................................................................................................................. 85
Appendix A: Raw Data of Models ................................................................................ 86
Appendix B: Descriptive Statistics ............................................................................. 159
Appendix C: Raw Data for Random Points ................................................................ 168
Appendix D: Descriptive Statistics for Random Points .............................................. 178
Appendix E: R-Squared and AIC Values .................................................................... 179
Appendix F: Significant Factors ................................................................................. 181
Appendix G: TRAP Sites ............................................................................................ 183
v

List of Figures
Figure 1. Several yellow phase C. horridus basking between boulders on a powerline
right of way. ......................................................................................................... 4
Figure 2. A large, female black phase C. horridus where the keeled scales, forked tongue,
and pit organs can be easily viewed. .................................................................... 4
Figure 3. A black phase C. horridus in defensive posturing with the rattle raised at one of
the northeastern field sites. .................................................................................. 6
Figure 4. Map of the regional variations in C. horridus venom as described by Glenn et
al., 1994. Notice that there is overlap between A and C in Georgia and Florida
as well as overlap between all four types in South Carolina. .............................. 7
Figure 5. A large fungal lesion found on a juvenile black phase. ..................................... 11
Figure 6. Regional map of the northeastern counties including the sites found within this
area. .................................................................................................................... 16

vi

List of Tables
Table 1. Correlation coefficients between each factor at 50m for Model 1. Moderate
correlations are bolded. ...................................................................................... 20
Table 2. Correlation coefficients between each factor at 400m for Model 1. Moderate
correlations are bolded. ...................................................................................... 21
Table 3. Correlation coefficients of all factors within the 5000m buffer zone. Moderate
correlations are bolded while strong correlations are italicized......................... 22
Table 4. Results of Model 1 at the 50m buffer zone. A significant relationship was
observed between population size and nearest building. ................................... 27
Table 5. Results of Model 1 at the 50m buffer zone after factors were centered. A
significant relationship was observed between population size and nearest
building. ............................................................................................................. 27
Table 6. Results of Model 1 at the 400m buffer zone. There were no significant
relationships observed. ....................................................................................... 29
Table 7. Results of Model 1 at the 400m buffer zone with factors centered. There were no
significant relationships observed. ..................................................................... 30
Table 8. Results of Model 1 at the 5000m buffer zone. A significant relationship was
observed between nearest building and population size as well as between
quantity of buildings and population size. ......................................................... 32
Table 9. Results of Model 1 at the 5000m buffer zone with factors centered. A
significant relationship was observed between nearest building and population
size as well as between quantity of buildings and population size. ................... 32
Table 10. Results of Model 2 at the 50m buffer zone with all factors included. There were
no building measures at 50m. A significant relationship was observed between
population size and nearest building. ................................................................. 34
Table 11. Results of Model 2 at the 400m buffer zone with all factors included. A
significant relationship was observed between population size and nearest
building. ............................................................................................................. 36
Table 12. Results of Model 2 at the 5000m buffer zone with all factors included. A
significant relationship was observed between population size and nearest
building. ............................................................................................................. 37
Table 13. Results of the GLM for Model 3 within the 50m buffer zone. There were no
buildings measured within this buffer zone. There was no significant
relationship observed at this spatial scale. ......................................................... 39
Table 14. Results of the GLM for Model 3 at the 400m buffer zone. A significant
relationship was observed between quantity of buildings and occupancy. ....... 42
Table 15. Results of the GLM for the 5000m buffer zone in Model 3. There was no
significant result observed between the factors and the response variable. ....... 43
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Table 16. Results of Model 4 at 50m showing a significant relationship between trail
density and population size. There were no buildings measured at this spatial
scale.................................................................................................................... 45
Table 17. Results of Model 4 at the 400m buffer zone. There was no significant
relationship observed between the factors and population size. ........................ 47
Table 18. Results of Model 4 at the 5000m buffer zone. A significant relationship was
observed between quantity of buildings and population size as well as canopy
cover and population size................................................................................... 49
Table 19. Results of Model 5 at the 50m buffer zone. A significant relationship was
observed between population size and nearest building. There were no buildings
measured at this spatial scale. ............................................................................ 51
Table 20. The results of Model 5 at the 400m buffer zone A significant relationship was
found between nearest building and population size. ........................................ 52
Table 21. Results of Model 5 at the 5000m buffer zone. A significant relationship was
observed between population size and road density, population size and quantity
of buildings, and population size and canopy cover. ......................................... 55
Table 22. Results of the GLM at the 50m buffer zone for Model 6. There was no
significant relationship observed between the factors and the response variable.
There were no buildings measured at this spatial scale. .................................... 57
Table 23. Results of the GLM at the 400m buffer zone for Model 6. There was no
significant relationship observed between the factors and the response variable.
............................................................................................................................ 58
Table 24. Results from the GLM at the 5000m buffer zone for Model 6. There were no
significant relationships observed between the factors and population. ............ 60

viii

List of Appendices
Appendix I. Raw data for Model 1 at the 50m buffer zone. ............................................. 86
Appendix II. Raw data for Model 1 at the 400m buffer zone. .......................................... 91
Appendix III. Raw data for Model 1 at the 5000m buffer zone. ...................................... 96
Appendix IV. Raw data for Model 2 at the 50m buffer zone. ........................................ 100
Appendix V. Raw data for Model 2 at the 400m buffer zone......................................... 104
Appendix VI. Raw data for Model 2 at the 5000m buffer zone. .................................... 108
Appendix VII. Raw data for Model 3 at the 50m buffer zone where Number of Snakes
(Population) has been changed to presence (1) - absence(0) data. .................. 111
Appendix VIII. Raw data for Model 3 at the 400m buffer zone where Number of Snakes
(Population) has been changed to presence (1) - absence(0) data. .................. 116
Appendix IX. Raw data for Model 3 at the 5000m buffer zone where Number of Snakes
(Population) has been changed to presence (1) - absence(0) data. .................. 121
Appendix X. Raw data for Model 4 at the 50m buffer zone........................................... 126
Appendix XI. Raw data for Model 4 at the 400m buffer zone. ...................................... 130
Appendix XII. Raw data for Model 4 at the 5000m buffer zone. ................................... 134
Appendix XIII. Raw data for Model 5 at the 50m buffer zone. ...................................... 138
Appendix XIV. Raw data for Model 5 at the 400m buffer zone. ................................... 141
Appendix XV. Raw data for Model 5 at the 5000m buffer zone. ................................... 144
Appendix XVI. Raw data for Model 6 at the 50m buffer zone where Number of Snakes
(Population) has been changed to presence (1) - absence(0) data. .................. 147
Appendix XVII. Raw data for Model 6 at the 400m buffer zone where Number of Snakes
(Population) has been changed to presence (1) – absence (0) data. ................. 151
Appendix XVIII. Raw data for Model 6 at the 5000m buffer zone where Number of
Snakes (Population) has been changed to presence (1) - absence ................... 155
Appendix XIX. Descriptive statistics of factors at the 50m buffer zone for Model 1. ... 159
Appendix XX. Descriptive statistics of factors at the 400m buffer zone for Model 1. .. 159
Appendix XXI. Descriptive statistics of factors at the 5000m buffer zone for Model 1. 160
Appendix XXII. Descriptive statistics of factors at the 50m buffer zone for Model 2... 160
Appendix XXIII. Descriptive statistics of factors at the 400m buffer zone for Model 2.
.......................................................................................................................... 161
Appendix XXIV. Descriptive statistics of factors at the 5000m buffer zone for Model 2.
.......................................................................................................................... 161
Appendix XXV. Descriptive statistics of factors at the 50m buffer zone for Model 3. . 162
Appendix XXVI. Descriptive statistics of factors at the 400m buffer zone for Model 3.
.......................................................................................................................... 162
Appendix XXVII. Descriptive statistics of factors at the 5000m buffer zone for Model 3.
.......................................................................................................................... 163
Appendix XXVIII. Descriptive statistics of factors at the 50m buffer zone for Model 4.
.......................................................................................................................... 163
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Appendix XXIX. Descriptive statistics of factors at the 400m buffer zone for Model 4.
.......................................................................................................................... 164
Appendix XXX. Descriptive statistics of factors at the 5000m buffer zone for Model 4.
.......................................................................................................................... 164
Appendix XXXI. Descriptive statistics of factors at the 50m buffer zone for Model 5. 165
Appendix XXXII. Descriptive statistics of factors at the 400m buffer zone for Model 5.
.......................................................................................................................... 165
Appendix XXXIII. Descriptive statistics of factors at the 5000m buffer zone for Model 5.
.......................................................................................................................... 166
Appendix XXXIV. Descriptive statistics of factors at the 50m buffer zone for Model 6.
.......................................................................................................................... 166
Appendix XXXV. Descriptive statistics of factors at the 400m buffer zone for Model 6.
.......................................................................................................................... 167
Appendix XXXVI. Descriptive statistics of factors at the 5000m buffer zone for Model 6.
.......................................................................................................................... 167
Appendix XXXVII. Raw data at the 50m buffer zone for the one-hundred random points.
.......................................................................................................................... 168
Appendix XXXVIII. Raw data at the 400m buffer zone for the one-hundred random
points. ............................................................................................................... 171
Appendix XXXIX. Raw data at the 5000m buffer zone for the one-hundred random
points. ............................................................................................................... 175
Appendix XL. Descriptive statistics of factors at the 50m buffer zone for the random
points. ............................................................................................................... 178
Appendix XLI. Descriptive statistics of factors at the 400m buffer zone for the random
points. ............................................................................................................... 178
Appendix XLII. Descriptive statistics of factors at the 5000m buffer zone for the random
points. ............................................................................................................... 178
Appendix XLIII. R-Squared and AIC values for all models, sorted by model number,
then by spatial scale. Note that GLMs do not give an R-squared value. ......... 179
Appendix XLIV. R-Squared and AIC Values for all models sorted by spatial scale
followed by model number. Note that GLMs do not give an R-squared value.
.......................................................................................................................... 179
Appendix XLV. All models shown ordered by spatial scale with an 'X' indicating factors
that showed a significant relationship with population size. ........................... 181
Appendix XLVI. All models shown ordered by model number with an 'X' indicating
factors that showed a significant relationship with population size. ............... 182
Appendix XLVII. Rattlesnake sites in the Northeast produced by TRAP through the
PFBC. Sites are randomly offset from actual locations by up to 5000m to
minimize the potential of poaching activity from this work. ........................... 183

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CHAPTER 1: INTRODUCTION
The timber rattlesnake, Crotalus horridus, has long been a species of interest and
concern to herpetologists and conservationists in the northeastern United States. Over the
years, C. horridus has seen severe declines in its northeastern range due to
overharvesting, persecution, and habitat loss (Galligan and Dunson, 1979; Stechert, 1982;
Reinert, 1990; Clark et al., 2010; Levin, 2016). As the conservation movement has gained
momentum, many studies have been conducted on the long-term effects of these factors
and changes in C. horridus populations (Martin, 1993; Andrews and Gibbons, 2005;
Clark et al., 2010, 2011; Urban, 2012). Since C. horridus has been delisted as a candidate
species in Pennsylvania, due to the relatively high numbers of snakes discovered by the
Pennsylvania Fish and Boat Commission (PFBC) during the Timber Rattlesnake
Assessment Project (TRAP), a monitoring program is needed to maintain confirmation of
population integrity. East Stroudsburg University, under Dr. Thomas C. LaDuke, is
creating the Timber Rattlesnake Monitoring Project (TRMP) through a series of
integrated studies including: (1) mark and recapture study using passive integrated
transponders (PIT) tags to assess population sizes; (2) assessing how anthropogenic
habitat features affect population sizes; (3) measuring microhabitat use by gravid
1

females; and (4) measuring population recruitment by tracking neonate
individuals returning to sites year after year. This specific project, number two under
TRMP, will measure habitat features and relate changes in these features to snake
populations as a means of assessing the relationship between specific habitat factors and
timber rattlesnake population size. This will be critical to the monitoring process as the
end goal is the ability to quantitatively assess population changes through disturbances in
C. horridus habitat.
Life History of the Timber Rattlesnake
Crotalus horridus is a medium to large, venomous, heavy bodied snake in the
family Crotalidae that can grow to four feet in length (Hulse et al., 2001). Males are
longer in length with a larger girth than females, they can reach lengths of 180cm. This
size difference can be attributed to the males’ combative nature (Sutherland, 1958;
Gibbons, 1972). Males also have greater than 21 subcaudal scales, representing clear
sexual dimorphism from females who generally have less than 21 sub caudal scales. This
species has dark, chevron shaped markings on the dorsum with a yellow to black
background, representing two distinct color morphs based on the color of the head
(Figure 1, Figure 2, Figure 3). It was formerly believed that color was loosely linked to
the sex of an individual, with more males being black and more females being yellow
(Klauber, 1956). Subsequent studies in Pennsylvania disproved this hypothesis, color is
independent of age or sex (Schaefer, 1969). Dark color morphs are commonly found in
mountainous regions of the East coast, and it was thought that black coloration was not a
result of genetics, but instead a result of ontogenetic changes in individuals (Gloyd,
1940). This, however, was also disproved by Schaefer (1969), as they found that light and
2

dark color phases could be distinguished at birth and the color only deepened into
adulthood. Juveniles commonly present with an orange, median stripe on the dorsum
while neonates are commonly light grey to beige in color with distinct crossbands (pers.
obs.). The ventrum of C. horridus is typically cream colored with dense black speckling
(Rubio, 2014). The scales of C. horridus are large and triangular with a distinct medial
keel.
The signature trait of the rattlesnake is the rattle found on the end of their tail.
This structure is typically used to warn would be predators or large fauna of the
rattlesnake’s presence by rapidly shaking the tail and allowing each bead to clack against
the others (Rubio, 2014).The rattle is composed of keratinized beads that form at the tip
of the tail after each molt (Hulse et al., 2001)(Figure 3). Neonates are born with only a
single keratinous button at the tip of the tail, but should add 2 to 5 more segments by the
end of their first year (Rubio, 2014). Some claim C. horridus can be somewhat accurately
aged by dividing the number of rattle segments by the average number of sheds per year,
but this only works on snakes with intact rattles still including the button (Furman, 2007).
Compared to other vipers, C. horridus appears to have a relatively mild temperament,
preferring to flee when humans are present (Gibbons, 2017).
Until recently, this species, Crotalus horridus, was separated into two distinct
subspecies, Crotalus horridus (Timber Rattlesnake) and Crotalus horridus atricaudatus
(Canebrake Rattlesnake). The subspecies C. h. atricaudatus was recognized due to
differences in dorsal scale row counts, a larger average adult size (30-60 inches in C. h.
horridus and 42-65 inches in C. h. atricaudatus), and an orange dorsal stripe that bisected
3

the chevron pattern medially (Gloyd, 1935; Rubio, 2014). Additionally, the southern
subspecies, C. h. atricaudatus has a stripe along the face extending from the eye to the
rear of the mouth (Gloyd, 1935). However, variation in scale counts is now thought to be
attributed to sexual dimorphism and not subspeciation, as the variation in morphological
traits is equal between C. h. horridus and C. h. atricaudatus (Pisani et al., 1973).
Additional genetic research has shown that there are distinct east-west populations of C.
horridus but not along north-south gradients (Clark et al., 2003).

Figure 1. Several yellow phase C. horridus basking between boulders on a powerline
right of way.

Figure 2. A large, female black phase C. horridus where the keeled scales, forked tongue,
and pit organs can be easily viewed.
4

C. horridus ranges from New Hampshire to Florida on the east coast of the United
States and extends westward to Texas and southeastern Minnesota (Conant and Collins,
1998). In the northern parts of its range, this species hibernates in the winter months at
communal den sites in crevices on south facing slopes (Galligan and Dunson, 1979;
Ernst, 1992; Gibbons, 2017). Of northern den sites examined, 70% faced south while the
other 30% faced southwest and southeast (Galligan and Dunson, 1979). Likewise,
members of the “canebrake” population in the south may hibernate in tree stumps or tree
root systems for short periods of extreme cold (Gibbons, 2017). This species has differing
habitat preferences across its range. In the northeast it prefers wooded areas for foraging
with nearby rocky edges for basking, gestation, and denning. In the southeastern portion
of the range it prefers lowland thickets, canebrakes, and swampy edges. Lastly, in the
western portion of the range the species prefers dry, brushy flatlands and beech-maplebirch woodlands (Campbell and Lamar, 2004).
In addition to having a rattle, C. horridus contains a trait common to all other pit
vipers, the facial pit. This pit is found on the head between the eyes and nostrils and
allows the snake to sense heat emanating from potential prey. The posterior portion of the
pit contains a membrane stretched across it which is in contact with thermal receptors
attached to the trigeminal nerve. Stimulation of these heat receptors travels along the
trigeminal nerve to the optic tectum where it can be represented as visual stimuli (Goris,
2011).

5

Figure 3. A black phase C. horridus in defensive posturing with the rattle raised at one of
the northeastern field sites.
This species has a solenoglyphous dentition and therefore has two large venom
glands at the posterior portion of the skull that lead to retractable fangs on the maxilla
bone (Reinert et al., 1984). The maxillary teeth found in other tetrapods have been
reduced to just these fangs. The venom of C. horridus varies geographically in its
composition as well as its potency and can be divided into four variations including: A,
B, A + B, and C. Type A venom is found in the southern portion of the range and
contains the neurotoxin canebrake toxin. The type B venom is the most common
throughout the range and consists of hemotoxins and polypeptides that cause
hemorrhagic damage to potential prey and predators. The third venom type, A+B, is
found in intergrade zones between A and B and has been noted in eastern South Carolina,
southeastern Georgia, southwestern Arkansas, and northern Louisiana. The last venom,
6

Type C, had one of the lowest LD50’s the paper’s author had ever observed among snake
taxa and lacks both the canebrake toxin of Type A as well as the peptides of Type B.
Type C venom is found in Georgia, Florida, and South Carolina and seems to be, at least
partially, sympatric with Type A (Glenn et al., 1994) (Figure 4).

Figure 4. Map of the regional variations in C. horridus venom as described by Glenn et
al., 1994. Notice that there is overlap between A and C in Georgia and Florida as well as
overlap between all four types in South Carolina.
C. horridus is an ambush predator that often relies on fallen trees to find prey
items (Reinert et al., 1984). It has been shown that individuals will curl up next to fallen
trees with a portion of the body and the lower jaw coming in contact with the fallen trees
to feel for vibrations of incoming mammals, usually rodents, that compose a majority of
their prey (Reinert et al., 1984; Hulse et al., 2001). However, other prey items make up at
7

least a portion of the diet including members of “Lacertilia”, Serpentes, Anura,
Piciformes, Galliformes, Passeriformes, Chiroptera, and Eulipotyphla (Clark, 2002).
Using the Jacobson’s organ the snake can sense if incoming individuals are prey (Rubio,
2014). Rattlesnakes are generalists, thus, the proportion of prey consumed appears to
match the prey’s proportion in the environment with a majority of prey caught at night
(Reinert et al., 1984).
While C. horridus is often thought of as being near the top of the food chain, there
are several predators that prey on them when the chance arises. In the northern parts of
the range, Coluber constrictor is commonly found near den sites and is known to take
young C. horridus (Klemens, 1993). Anecdotally, when C. constrictor is present C.
horridus populations appear to be in flux. Additionally, hawks may prey even on adult
individuals (Klauber, 1956; Ernst and Ernst, 2003). In the southern portion of the range,
Drymarchon sp. and Lampropeltis sp. will commonly prey on large and small individuals
of C. horridus, being immune to their venom (Gibbons, 2017).
During the warmer months males, post-partum females, and non-breeding females
disperse from den sites into surrounding forest for feeding opportunities. In addition to
hunting, males will seek out receptive females to breed with throughout the late summer.
There is at least some evidence that males will guard basking females or a highly suitable
basking site for possible mating opportunities (Howey, 2017). Females start ovulation in
late spring and reproduction occurs in mid to late summer (Martin, 1993). Females of C.
horridus seem to aggregate in family groups of related females. This provides several
benefits including group defense against predators as well as increasing the ability to
8

thermoregulate. It is theorized that not only does group basking deter predators, but
females may be more likely to defend a site if they know that related members will
indirectly benefit. Likewise, if adults are grouped together it increases the likelihood that
neonates may scent trail an adult to den sites, increasing survivability of offspring (Clark
et al., 2012). C. horridus is strongly K-selected; females do not mature until roughly six
or seven years of age, they only breed once every 2-6 years depending on abiotic
conditions, and they have relatively small litters of 3-16 young (Gibbons, 1972; Galligan
and Dunson, 1979; Martin, 1993; Gibbons, 2017). This species is viviparous giving birth
to live young with at least some transfer of nutrients from mother to offspring
(Blackburn, 2000; Hulse et al., 2001). Mothers will stay with the young for up to two
weeks, roughly timing their parting with the first molt of the neonates (Gibbons, 2017).
During this time, mothers will typically become bolder and actively defend the young
against would-be predators. Surprisingly, neonate individuals tend to act in an opposite
way, being incredibly curious to the happenings around them and not readily avoiding
danger as they should (pers. obs.).
Decline of Timber Rattlesnake
There are many biotic and abiotic factors that contribute to a population’s decline
including habitat destruction, overharvesting, pollution, and disease (Wilcove et al.,
1998). The factors described by Wilcove et al. (1998) all contribute to population
changes in C. horridus. Habitat destruction is a pervasive problem that many species in
the modern age are facing, imperiled or otherwise. Roads have become commonplace
through many habitat types and have been shown to restrict gene flow and genetic
diversity among populations (Forman 2000; Shine et al., 2004; Andrews and Gibbons,
9

2005; Coffin, 2007; Row et al., 2007; Eigenbrod et al., 2008; Fahrig and Rytwinski,
2009; Clark et al., 2010; Beebee, 2013). C. horridus, specifically, has been shown to be
exceptionally susceptible to the impacts of roadways bisecting habitat because of their
unwillingness to traverse open habitat (Andrews and Gibbons, 2005). Studies have also
shown that C. horridus is already experiencing a decrease in genetic diversity in the south
due to population fragmentation by roadways (Clark et al., 2010). Overharvesting
occurred, until recently, in the form of rattlesnake roundups. In the modern era, these
events are strictly educational and all snakes that are not being tagged with a hunting
license are returned to the site that they were collected from. These events awarded prizes
to participants in various categories such as largest snake and longest rattle (Reinert,
1990). Many individual snakes observed at hunts appeared to be injured, with several
showing signs of damaged cervical vertebrae (Reinert, 1990). Of the snakes collected at
hunts, a large number appeared to be gravid females, thought to have been collected in
such numbers due to their preference for open areas with high amounts of sunlight
(Reinert, 1990). While hunters were supposed to return captured snakes to the same area
they were captured, several hunters explained they had no intention of doing so. It has
been shown that C. horridus who have been relocated experience high mortality in the
range of 50% (Reinert and Rupert, 1999). The relocation of snakes coupled with severe
injury and handling of gravid individuals could potentially carry many unintended
consequences.
There are anecdotal accounts that repeated handling or excess stress may cause
infections of Snake Fungal Disease (SFD) to become more severe. There are reports of O.
ophiodiicola in Pennsylvania in Luzerne (LaDuke pers. comm., pers. obs.) and Lycoming
10

(Dunning pers. comm.) counties (Figure 5). With enough warmth and several molts it
would seem that many individuals can overcome infections (Lorch et al., 2016). Fungal
diseases have impacted many other reptile and amphibian taxa as well including
Batrachochytrium dendrobatidis in Anura (Retallick et al., 2001), B. salamandrivorans in
Caudata (Martel et al., 2013), Pseudogymnoascus destructans in Chiroptera (Blehert et
al., 2009), and Ophidiomyces ophiodiicola in Serpentes (Allender et al., 2015; McBride
et al., 2015; Guthrie et al., 2016).The full impacts of Snake Fungal Disease are unknown
but are one more reason that a species with a cryptic lifestyle and low fecundity should be
monitored. In addition to these factors, hiking trails have become more abundant
throughout the commonwealth. One study revealed a negative correlation between
species abundance and trail area in wood turtles (Garber and Burger, 1995). The average
person is largely biased against rattlesnakes, owed to the sensationalized view that
rattlesnakes are an aggressive species, and hiking trails through habitat increase the
likelihood of human interaction with the species, leading to eventual mortality.

Figure 5. A large fungal lesion found on a juvenile black phase.

11

Timber Rattlesnake Assessment Project
Our understanding of the status of the timber rattlesnake in Pennsylvania has been
improving gradually over the years. Until 2016 it was listed as a Candidate Species in
Pennsylvania (Stauffer, 2016). The Pennsylvania Fish and Boat Commission conducted a
study from 2003-2014 known as the Timber Rattlesnake Assessment Project (TRAP)
whose purpose was confirming historical site occupancy and generally checking potential
habitat for the presence of C. horridus (Urban, 2012). This study found C. horridus at
more than 1000 sites in Pennsylvania, showing they are more numerous than previously
thought. With the conclusion of this study, the species’ conservation status was reduced
(Stauffer, 2016). However, the species’ hunting limits will remain in place and
environmental impact studies will still be conducted on and near C. horridus habitat.
Geographic Information Science
Geographic Information Systems (GIS) reference geospatial data in the real world
by overlaying various landscapes/ habitat features on a base map, thus providing a view
of the spatial orientation of mapped features and the ability manipulate and analyze such
data (Maguire, 1991). There are seemingly innumerable GIS applications but we are
using it to track wildlife populations (Peterson, 2001) as well as monitor habitat loss and
fragmentation (Vogelmann, 1995; Heilman et al., 2002).
Studies involving herpetofauna and GIS have typically been limited to habitat
suitability modeling for a given species or group (Raxworthy et al., 2003; Santos et al.,
2006, 2009). Other projects, such as the Pennsylvania Amphibian and Reptile Survey,
have used citizen science jointly with GIS technology to map out population ranges.
There are also projects that have attempted to work out passages between territories over
12

roadways (Clevenger et al., 2002). This project will attempt a novel use, regarding
timber rattlesnakes in Pennsylvania, of GIS technology in assessing population integrity
of given sites in relationship to habitat features at different spatial scales.
Objectives
Due to the low fecundity of individual females, the risk of spreading pathogens,
and the ever-increasing habitat destruction from human development, this project aims to
accomplish two goals using GIS technology:
1. Use GIS technology to evaluate the relationship between anthropogenic habitat
alterations and population status where data are available.
2. Use the relationships revealed in 1, above, to produce formulae that can estimate
the impact of future changes of similar type on populations.

13

CHAPTER 2: METHODS AND MATERIALS
This project used geographic information science (GIS) technology to quantify
habitat features surrounding Timber Rattlesnake habitat within Pennsylvania. Data was
collected from several major sources including the Pennsylvania Fish and Boat
Commission (PFBC), Pennsylvania Spatial Data Access (PASDA), and local county GIS
coordinators. This data was processed in ESRI’s GIS program ArcMap®. Data for certain
counties was removed from consideration due to anomalies in structure. The data that
was processed in ArcMap® was then transferred to R where the analyses were conducted.
A set of six generalized linear models were produced to assess the relationships between
environmental factors and snake populations.
Study Area
The study area consisted of the northeastern Pennsylvania counties including
Monroe, Pike, Carbon, Luzerne, Lackawanna, Wayne, Wyoming, and Susquehanna
(Figure 6). This portion of the state was chosen due to ease of access for regular visits
during which additional population data could be collected. This area of the state has a
high rate of development and diverse habitat types, many of which are unsuitable to the

14

life history of Crotalus horridus. As such, while several of the sites hold substantial
colonies, many of the populations in this area have low population numbers. This wide
range of population sizes likely leads to a more realistic model, as there is no bias
towards large or small populations. However, there is bias in the overall methodology of
how data was collected from sites. The goal of the Timber Rattlesnake Assessment
Project (TRAP) was to confirm rattlesnake sites, not rattlesnake numbers. Due to these
methods low site numbers are a result of low effort while absences may represent pseudoabsences. All sites used for the project were verified by the TRAP and historically held
timber rattlesnake populations, or were new sites discovered by TRAP that contained a
population of rattlesnakes. All the sites reported by TRAP within the northeast counties
were used. The data from TRAP was imported into Microsoft Excel in the commaseparated values (CSV) format, as this is the only format that ArcMap® supports. Using
the latitude and longitude from the TRAP surveys, the sites were imported into ArcMap®,
creating the points for each rattlesnake site. Rattlesnake sites were clipped to the extent of
the focal counties, using the Clip tool in ArcMap®, to remove any additional rattlesnake
sites that were not included in the scope of this study. Each site was then isolated using
the Select function and then made into its own layer to individually create buffers around
each point for analysis. Buffers of interest (radii 50m, 400m, and 5,000m), were then
added to each site using the buffer tool in ArcMap®. These buffer zones align with
various life history components of C. horridus. The innermost buffer zone, 50m,
represents immediate habitat at a site that has been identified as critical to individuals in a
population, primarily basking and gestation habitat. The intermediate buffer zone (400m)
would likely contain the den site as well as alternate gestating and basking habitat that is
15

vital to biological maintenance of the population, especially gravid females. The last
buffer zone, 5000m, likely includes all other important habitat such as foraging habitat
based on farthest traveling distances of males seeking mating opportunities.

Figure 6. Regional map of the northeastern counties including the sites found within this
area.
Data Collection
Rattlesnake population information was collected by TRAP teams that visited
sites around the state. Population numbers at these sites varied widely, as many of the
sites were only visited once, and the number of snakes seen was recorded as the
population. There are a few exceptions to this, including PIT-tagging sites such as the
16

Hell Creek site that has a large population and has been visited numerous times over
several years. Snakes at several such sites across the state have been marked with passive
integrated transponder (PIT) tags. These tags are subdermal and can be checked with a
handheld receiver. Additionally, Dr. LaDuke and his students have visited many sites
around the northeast to mark snakes. This has helped to improve population estimates at
several different sites, mostly in Luzerne and Monroe counties. If snakes have been
marked at a site, the total number of marked snakes has been used as the population
estimate as opposed to the number provided by the TRAP. If snakes are not being marked
with PIT tags at a site, then the highest number observed at the site during a given visit is
used as the population estimate. This was modified if obvious characteristics give away
individuals as unique members, such as a yellow phase juvenile who hadn’t previously
been recorded. Neonate snakes were not added to population estimates due to the wide
mortality fluctuation in these individuals as well as the uncertainty that they would
remain within the same natal subpopulation.
Roadway data was collected from the Pennsylvania Spatial Data Access
(PASDA). Three roadway layers were collected: state, local, and unpaved. These three
layers were combined using the merge tool in ArcMap® to form one layer that could be
easily manipulated. This joint layer was then projected into the North America
Equidistant Conic projection, as were all the layers that were used. From here, a new
column was created in the road attribute table and given the name Shape_Length. Using
the calculate geometry tool within the attribute table the total length, in meters, of each
line segment was found. The roads were clipped, using the Clip tool in ArcMap®, to each
buffer zone and summed using the statistics tool within the attribute table. A density of
17

roads was then calculated for each site by taking the total distance of roads within the
buffer zone and dividing by the total area of the buffer zone, 7,853.98m2 for the 50m,
502,654.82m2 for the 400m, and 78,539,816.34m2 for the 5,000m. This density (m/m2)
relativized the measurements from each buffer zone. Additionally, the Near tool was used
to calculate the distance from each site to the nearest road. Trail data was collected from
PASDA and were processed using the same procedure described above. Recreational
waterways were excluded from the trail data.
Building data was collected for each county from its respective GIS county
coordinator. Since there was no standard method regarding the form geographic data was
in, each county represented buildings in different ways. Pike count only has data for land
parcels, instead of buildings, and represents this with polygon data. Monroe and Wayne
counties maintain building data as polygons. The remaining counties all use point data for
buildings. Due to Pike County only having land parcel data, the description field of the
attribute table was manually reviewed to identify all records that mentioned a building on
the property. Of the 61,000 attributes in the Pike County land parcel data, 36,000 were
identified as containing buildings. However, many of the land parcels with buildings
contained more than one building. Additionally, the polygons were converted to points to
represent the geographic location of the buildings in a more useful representation. This
works well for small land parcels but not for parcels as they become larger. Thus, the
buildings in Pike County may not be represented accurately for this model. The Near tool
was used to calculate distance from each site to the nearest building. Using the Clip tool
in ArcMap®, buildings were clipped to each buffer zone and a total count of buildings
within the buffer zone was conducted for each site. A handful of the counties included
18

highway markers with the building data. These points were subsequently removed from
the layer.
Canopy data was collected from PASDA in the raster format. This file spans the
entirety of Pennsylvania and has a resolution of 1x1m2. Due to its high resolution, this
data layer was ideal for the project and was chosen over other more highly recommended
data types such as a normalized difference vegetation index (NDVI), as the smallest
usable resolution that could be located was 250x250m2. However, this raster file only
contained values that held canopy cover (as a value of 1) and did not assign values to
open canopy. Using the Raster Calculator tool, within the Map Algebra toolbox, null
values were assigned a value of 0 within the raster layer. With the Raster Clip tool, within
Raster Processing tools, the canopy raster layer was clipped to each buffer zone. These
clipped raster files returned values of open and closed canopy within each buffer zone.
The amount of closed canopy grids was divided by the total amount of canopy grids to
find the percent canopy coverage for each buffer zone.
Correlation Factors
Correlation coefficients were examined to determine collinearity between
predictor variables in Model 1 at each spatial scale to establish if autocorrelation was
playing a role in each of the models. Moderate and high degrees of correlation were noted
between variables. Ideally, if factors are shown to be strongly autocorrelated the overall
factors used in the model can be reduced by eliminating one of the correlated factors.

19

At the fifty-meter buffer zone a moderate positive correlation was observed
between Nearest Trail and Nearest Road (r= 0.474, Table 1) and between Nearest
Building and Nearest Road (r= 0.547, Table 1).
Table 1. Correlation coefficients between each factor at 50m for Model 1. Moderate
correlations are bolded.
Nearest
Road
Road
Density
Nearest
Trail
Trail
Density
Nearest
Building
Total
Buildings
Canopy
Cover

Road
Density

Nearest
Trail

Trail.
Density

Nearest
Building

Total
Buildings

-0.169
0.474

-0.059

-0.090

-0.019

-0.157

0.547

-0.005

0.339

-0.166

-

-

-

-

-

0.086

-0.070

0.152

-0.278

0.049

-

At the four-hundred-meter buffer zone for Model 1 there was a moderate positive
correlation between Nearest Trail and Nearest Road (r= 0.474, Table 2), Nearest Building
and Nearest Road (r= 0.547, Table 2), and Road Density and Total Buildings (r= 0.461,
Table 2). A moderate negative correlation was observed between Nearest Road and Road
Density (r= -0.572, Table 2), Nearest Trail and Trail Density (-0.453, Table 2) and
Nearest Building and Total Buildings (-0.450, Table 2).

20

Table 2. Correlation coefficients between each factor at 400m for Model 1. Moderate
correlations are bolded.
Nearest
Road
Road
Density
Nearest
Trail
Trail
Density
Nearest
Building
Total
Buildings
Canopy
Cover

Road
Density

Nearest
Trail

Trail
Density

Nearest
Building

Total
Buildings

-0.572
0.474

-0.149

-0.200

-0.033

-0.453

0.547

-0.198

0.339

-0.339

-0.332

0.461

-0.192

0.173

-0.450

0.369

-0.372

0.291

-0.153

0.347

-0.394

At the five-thousand-meter buffer zone there were moderate positive correlations
between Nearest Road and Nearest Trail (r= 0.506, Table 3) and Nearest Road and
Nearest Building (r=0.535, Table 3). There was a strong positive correlation between
Road Density and Total Buildings (r= 0.873, Table 3). At this spatial scale there was a
moderate negative correlation between Road Density and Nearest Building (r= -0.415,
Table 3), Nearest Trail and Trail Density (r= -0.655, Table 3), and Road Density and
Nearest Trail (-0.520, Table 3). There was a strong negative correlation between Total
Buildings and Canopy Cover (r= -0.734, Table 3) as well as between canopy cover and
road density.

21

Table 3. Correlation coefficients of all factors within the 5000m buffer zone. Moderate
correlations are bolded while strong correlations are italicized.
Nearest
Road
Road
Density
Nearest
Trail
Trail
Density
Nearest
Building
Total
Buildings
Canopy
Cover

Road
Density

Nearest
Trail

Trail
Density

Nearest
Building

Total
Buildings

-0.377
0.506

-0.520

-0.260

0.116

-0.655

0.535

-0.415

0.345

-0.349

-0.272

0.873

-0.343

0.037

-0.344

0.324

-0.758

0.329

0.038

0.379

-0.734

The correlations that were observed between factors at different spatial scales
were ultimately deemed to be insignificant relative to our purposes. There were few
correlations observed, most of which were relatively low in magnitude. The few factors
that did show a higher degree of correlation were only found at the large spatial scale,
0.873 (total buildings and road density), -0.758 (Canopy Cover and Road Density) and 0.734 (total buildings and canopy cover) and were deemed to not have a strong influence
on the results of our models. Due to these low correlation values and the fact that
correlations were not replicated across spatial scales it was decided that all factors should
be retained in the models.
Analysis
All analyses were conducted using the statistical programming language R. A
table was made for each of the three buffer zones in a CSV format to be imported into R.
Snake population size was modeled as a function of the following fixed factors: Nearest
22

Road, Road Density, Nearest Trail, Trail Density, Nearest Building, Total Buildings, and
Canopy Cover (Model 1). These factors were chosen as they increase the likelihood of
detrimental effects on rattlesnake populations, usually in the form of mortality. This
model was treated as the base model against which others are compared, similarly to Vos
and Chardon (1998).
Two other models were used to separately address variation in snake population
size within occupied sites (Model 2) and to focus on drivers of presence-absence rather
than abundance of snakes (Model 3). Model 2 avoids possible issues of zero-inflation in
Model 1, while Model 3 removes noise from variation in abundance to focus just on
factors affecting presence. Model 2 used a normal linear regression model, while a
generalized linear model (GLM) assuming a binomial error distribution was used for
Model 3.
These three core models were also run with a subset of the data that excluded Pike
County, due to differences in GIS data resolution from Pike as compared to the other
Pennsylvania counties and certain effects of its positioning on the state border. The
spread of Pike County’s building data was irregular when compared to the other counties
and did not align with actual building location. Additionally, many of Pike County’s
rattlesnake sites occurred along the Delaware River near the New York border. Because
of this, buffer zones around these sites included land in New York State, for which no
GIS information was collected. Therefore, the models were re-evaluated after excluding
the sites from this county. These models (Model 4, 5, and 6) were otherwise identical to

23

Models 1, 2, and 3, respectively. These models (Model 1-6) were then repeated for each
spatial scale.
Additionally, a linear model was run on each factor individually for each buffer
zone to validate statistical significance in the aggregate models. The Bonferroni
correction was used to adjust critical values for multiple comparisons. A Bonferroniadjusted critical value of 0.00833 was used for comparisons when 6 factors were used
(Fifty-meter buffer zones) and a value of 0.0071 was used for the other two spatial scales.
Most models were conducted using unscaled predictor variables. Model 1 was
additionally tested with centered data (i.e., representing each predictor variable value as a
deviation from that variable’s mean) to assess the effect of centering on the model
outcome.
Presence/pseudo-absence comparisons
Finally, we wanted to account for the inherent sampling bias of the TRAP project.
As mentioned previously, teams were sent out to verify historic sites for rattlesnake
populations, but also looked for rattlesnake populations in suitable habitat. It is likely that
TRAP participants used their knowledge of what constitutes good rattlesnake habitat in
choosing where to search, thus biasing the location of sites. In addition to this factor,
TRAP surveyors searching for new sites probably avoided many tracts of private property
where permission to search could not be easily obtained. Therefore, we also compared
the rattlesnake sites to “pseudo-absences” generated by sampling random background
points in the northeast region of Pennsylvania using the Create Random Points Tool in
ArcMap®. One-hundred random points were generated within the study area with the
three spatial scale buffer zones added to each point. Canopy cover for pseudo-absences
24

was taken directly at the point, as opposed to the entire buffer zone. These values of 1’s
(Closed canopy) and 0’s (Open canopy) were used for comparisons. In addition to this,
nearest roads and nearest trails as well as road and trail densities were measured at each
spatial scale around the pseudo-absences. Using this data, an analysis of variance
(ANOVA) was conducted on each factor between the rattlesnake sites and random point
data. If the random data is significantly different from that of the rattlesnake points, this
demonstrates that the rattlesnake sites are not distributed randomly with respect to the
locations and densities of the factors (roads, trails, buildings, etc.), indicating that they are
either attracted to or repulsed by the presence of those factors. Comparing rattlesnake
sites to pseudo-absences (e.g., background environmental conditions) provides an
alternate method of testing whether these populations have specific habitat associations
within the available environmental options in the region. Additionally, this can help
account for possible bias introduced in the selection of the sites that generated the true
absences (e.g., if those sites were chosen to sample because they appeared to be plausible
rattlesnake habitat, rather than more broadly sampling habitat types within the region).

25

CHAPTER 3: RESULTS
The results are presented in model order from one to six. Within each model the
results are presented starting with the small spatial scale and then are presented in size
order following this. Each spatial scale is presented first with all factors included and
then with population size or occupancy as a function of each individual factor. Results
from the statistical tests are represented in tables when all factors are included and are
included in the text when just one factor was used. The predictor variables (Nearest Road,
Road Density, Nearest Trail, Trail Density, Nearest Building, Total Buildings, and
Canopy Cover) are the same across all models. Models one, two, four, and five are linear
regressions assuming a normal distribution of residuals, with population size (abundance)
as the response. Models 3 and Model 6 are generalized linear models (GLM) assuming
binomially-distributed residuals, using presence-absence data as the response.
Model 1: Abundance Model
The first linear model (Model 1) included population size as a function of all
factors and included all sites. This model examined how the factors affect snake
abundance, including absences, at the different spatial scales. Model 1: Fifty-Meters

26

Model 1: Fifty-Meters
At the fifty-meter buffer zone this model showed a significant relationship
between population size and distance to nearest building (p = 0.04, Table 4). Another
model was analyzed on this data set, for fifty meters, with the distribution of data
centered. Centering the data did not change the outcome with nearest building still being
the only significant factor (p= 0.04, Table 5).
Table 4. Results of Model 1 at the 50m buffer zone. A significant relationship was
observed between population size and nearest building.
R2= 0.0234
AIC= 806.53
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest
Building
Canopy Percent
Residuals

Coefficient
-0.0023
-460.58
-0.00014
378.78

Df
1
1
1
1

Sum Sq
41.98
11.01
50.60
164.49

Mean Sq
41.98
11.01
50.60
164.49

F value
0.655
0.171
0.789
2.56

Pr(>F)
0.420
0.679
0.376
0.112

0.0032
-2.84
5.81

1
1
107

277.12
12.64
6855.46

277.12
12.64
64.06

4.32
0.197

0.0399*
0.657

Table 5. Results of Model 1 at the 50m buffer zone after factors were centered. A
significant relationship was observed between population size and nearest building.
R2= 0.0234
AIC= 806.53
Coefficient
Nearest Road
-1.230
Road Density
-0.437
Nearest Trail
-0.707
Trail Density
1.307
Nearest Building
2.025
Canopy Percent
-0.348
Residuals
3.730

Df
1
1
1
1
1
1
107

Sum Sq
41.98
11.01
50.60
164.49
277.12
12.64
6855.46

27

Mean Sq
41.98
11.01
50.60
164.49
277.12
12.64
64.06

F value
0.655
0.171
0.789
2.567
4.325
0.197

Pr(>F)
0.420
0.679
0.376
0.112
0.0399*
0.657

Roadways varied in their distance to sites at the fifty-meter buffer from 29.9m to
2,445.7m with a mean distance of 720.8m (n=116). A linear model that was used with
population size as a function of only nearest road did not yield significant results
(ANOVA; df= (1, 115), F= 0.588, p= 0.444).
The density of roads within the fifty-meter buffer zone (found by dividing the
total length of roads by the area of the buffer zone) ranged from 0 to 0.009001m/m2 with
a mean density of 0.0001196m/m2 (n=118). The linear model relating road density to
population size did not produce a significant result (ANOVA; df= (1, 116), F= 0.0821, p=
0.775).
The distance of trails varied from 3.4m to 14,548.48 at the fifty-meter buffer in
model 1 with a mean distance of 5,043.22 meters (n=117). The linear model relating
population size as a function of this factor did not show a significant relationship
(ANOVA; df = (1, 115), F= 1.5519, p= 0.2154). The density of trails for this model at
fifty meters ranged from 0m/m2 to 0.02849m/m2 with a mean density of 0.000517m/m2
(n=118). The linear model for this factor did not yield a significant result (ANOVA; df =
(1,116), F= 3.0528, p= 0.08324).
The distance of nearby buildings to sites ranged from 51.5 meters to 3,311.77
meters with a mean distance of 882.32 meters (n=115). Another linear model using
population size as a function of distance to nearest building did not show a significant
result (ANOVA; df= (1, 113), F= 0.7657, p= 0.3834). There were no buildings within the
fifty-meter buffer zone for Model 1 (n=118).

28

The canopy cover of sites at fifty meters ranged from 28.64% to 100% with a
mean cover of 94.72% (n=117). The linear model relating canopy cover to snake
population size did not show a significant result (ANOVA; df= (1, 115), F= 0.9611, p=
0.329).
Model 1: Four-Hundred-Meters
The linear model at four-hundred-meters did not yield any significant results
though Nearest Building was just outside of this threshold (Table 6). In a separate run,
the four-hundred-meter buffer for model 1 was also scaled to center the factors used. A
linear model was run using these scaled factors. This model did not yield results different
from the original model (Table 7).
Table 6. Results of Model 1 at the 400m buffer zone. There were no significant
relationships observed.
R2= -0.005034
AIC= 810.73
Coefficients Df
Nearest Road
-0.0036
1
Road Density
-1507.50
1
Nearest Trail
-0.00012
1
Trail Density
156.18
1
Nearest Building
0.0032
1
Buildings Within
-0.035
1
Canopy Percent
-4.16
1
Residuals
8.72
106

Sum Sq
41.98
84.61
32.76
3.59
253.48
0.19
7.59
6989.11

29

Mean Sq
41.98
84.61
32.76
3.59
253.48
0.19
7.59
65.93

F value
0.636
1.283
0.496
0.054
3.844
0.002
0.115

Pr(>F)
0.426
0.259
0.482
0.815
0.052
0.956
0.735

Table 7. Results of Model 1 at the 400m buffer zone with factors centered. There were no
significant relationships observed.
R2= -0.005034
AIC= 810.73
Coefficients
Nearest Road
-1.936
Road Density
-1.230
Nearest Trail
-0.624
Trail Density
0.228
Nearest Building
2.037
Buildings Within
-0.106
Canopy Percent
-0.299
Residuals
3.749

Df
1
1
1
1
1
1
1
106

Sum Sq Mean Sq
41.98
41.98
84.61
84.61
32.76
32.76
3.59
3.59
253.48
253.48
0.19
0.19
7.59
7.59
6989.11
65.93

F value
0.636
1.283
0.496
0.054
3.844
0.002
0.115

Pr(>F)
0.426
0.259
0.482
0.815
0.052
0.956
0.735

The four-hundred-meter buffer zone did not vary from the fifty-meter buffer zone
regarding measurements of nearest road, nearest trail, or nearest building (Appendix XIX,
Appendix XX).
A linear model with nearest road alone at four-hundred-meters did not yield a
significant result (ANOVA; df= (1, 114), F= 0.5884, p= 0.4446). The density of roads
within the four-hundred-meter buffer zone for Model 1 ranged from 0 m/m2 to 0.003602
m/m2 with a mean density of 0.0004563 m/m2 (n=118). The linear model relating road
density to population size did not show a significant result (ANOVA; df= (1, 116), F=
0.3702, p= 0.5441).
The linear model with population size as a function of nearest trail did not show a
significant result (ANOVA; df= (1, 115), F= 1.5519, p=0.2154). The density of trails in
Model 1 at four-hundred-meters ranged from 0 m/m2 to 0.005346 m/m2 with a mean
density of 0.0006586 m/m2 (n=118). The linear model did not show a significant
30

relationship between trail density and population size at four-hundred-meters (ANOVA;
df= (1, 116), F= 0.1353, p= 0.7137).
No significant relationship was observed between population size and nearest
building (ANOVA; df= (1,113), F= 0.7657, p= 0.3834). The quantity of buildings within
the four-hundred-meter buffer zone in Model 1 ranged from zero to sixteen with a mean
quantity of 1.14 (n= 115). No significant relationship was discovered between quantity of
buildings and population size (ANOVA; df= (1, 115), F= 0.7274, p= 0.3955).
Canopy cover at four-hundred-meters in Model 1 ranged from 63.8% to 100%
with a mean cover of 94.736% (n= 117). The linear model with population size as a
function of canopy cover did not show a significant result (ANOVA; df= (1, 115), F=
0.001, p= 0.9744).
Model 1: Five-Thousand-Meters
The last buffer zone within Model 1, five-thousand-meters, showed a significant
relationship between population size and nearest building (p= 0.02, Table 8), as well as a
significant relationship between population size and quantity of buildings (p= 0.04, Table
8).
Another model was run with the factors scaled to adjust for the distribution of the
data, however, results did not change with this model. There was a significant
relationship between nearest building (p= 0.02, Table 9) and population size as well as
quantity of buildings and population size (p= 0.04, Table 9).

31

Table 8. Results of Model 1 at the 5000m buffer zone. A significant relationship was
observed between nearest building and population size as well as between quantity of
buildings and population size.
R2= 0.0879
AIC= 677.67
Coefficient
Nearest Road
-0.0028
Road Density
8623.13
Nearest Trail
0.00025
Trail Density
2897.49
Nearest Building
0.0043
Buildings Within
-0.0012
Canopy Percent
28.46
Residuals
-34.71

Df
1
1
1
1
1
1
1
86

Sum Sq
69.73
167.42
6.75
0.33
425.08
308.23
163.52
6144.23

Mean Sq
69.73
167.42
6.75
0.33
425.08
308.23
163.52
71.44

F value
0.976
2.343
0.094
0.004
5.94
4.314
2.288

Pr (>F)
0.325
0.129
0.759
0.945
0.016*
0.040*
0.133

Table 9. Results of Model 1 at the 5000m buffer zone with factors centered. A
significant relationship was observed between nearest building and population size as
well as between quantity of buildings and population size.
R2= 0.0879
AIC= 677.67
Coefficient
Nearest Road
-1.53
Road Density
7.04
Nearest Trail
1.32
Trail Density
1.02
Nearest Building
2.77
Buildings Within
-3.23
Canopy Percent
2.14
Residuals
3.99

Df
1
1
1
1
1
1
1
86

Sum Sq
69.73
167.42
6.75
0.33
425.08
308.23
163.52
6144.23

Mean Sq
69.73
167.42
6.75
0.33
425.08
308.23
163.52
71.44

F value
0.976
2.343
0.094
0.004
5.949
4.314
2.288

Pr(>F)
0.325
0.129
0.759
0.945
0.016*
0.040*
0.133

The minimum and maximum distance from sites to nearest road did not change
for the five-thousand-meter buffer zone, ranging from 29.9m to 2445.7m, however the
mean, 764.4 (n=101), is slightly altered due to the lower sample size of this buffer zone.
The linear model with population size as a function of nearest road alone did not yield a
significant result (ANOVA; df= (1, 99), F= 0.775, p= 0.3808). The density of roads
within the five-thousand-meter buffer for Model 1 ranged from 0.0003487m/m2 to
32

0.004001m/m2 with a mean density of 0.001383m/m2 (n=102). This linear model did not
show a significant result between road density and population size (ANOVA; df= (1,
100), F= 3.0216, p= 0.08524).
The distance of trails to sites in this buffer zone ranged from 3.4m to 14,548.48m
with a mean of 5,177.062 (n=102). The linear model for this factor did not show a
significant relationship (ANOVA; df= (1, 100), F= 1.4362, p=0.2336). The density of
trails within this buffer zone ranged from 0m/m2 to 0.001597m/m2 with a mean density of
0.0002557m/m2 (n=102). The linear model for trail density at five-thousand-meters for
Model 1 did not show a significant relationship between trail density and population size
(ANOVA; df= (1, 100), F= 0.3271, p= 0.5687).
Buildings had a mean distance of 936.45m (n= 96) with a minimum distance of
78.1m and a maximum distance of 15,706m. There was no significant relationship
between nearest building and population size at 5 five-thousand-meters in Model 1
(ANOVA; df= (1, 94), F= 0.6195, p= 0.4332). The quantity of buildings within the fivethousand-meter buffer zone ranged from forty-two to fifteen-thousand-seven-hundredand-six with a mean quantity of buildings of 1,871.03 (n=95). The linear model did not
show a significant relationship between number of buildings within the five-thousandmeter buffer zone and population size (ANOVA; df= (1, 93), F= 0.2731, p= 0.6025).
Lastly, the amount of canopy cover in Model 1 for five-thousand-meters ranged
from 58.44% to 97.76% with a mean cover of 88.56% (n= 101). There was no significant
relationship between canopy cover and population size at five-thousand-meters for Model
1 (ANOVA; df= (1, 99), F= 0.0266, p= 0.8708).
33

Model 2: Non-Zero Abundance Model
The second linear model (Model 2) included population size as a function of all
factors but removed all sites that did not have snake populations. This was done to
remove the bias associated with zero inflation. Model 2 assesses the relationship between
the predictor variables and snake abundance at sites where at least some snakes are
present.
Model 2: Fifty-Meters
The model that was run for the fifty-meter buffer zone showed a significant
relationship between population size and nearest building (p= 0.04, Table 10).
Table 10. Results of Model 2 at the 50m buffer zone with all factors included. There were
no building measures at 50m. A significant relationship was observed between population
size and nearest building.
R2= 0.0302
AIC= 562.81
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Canopy Percent
Residuals

Coefficients
-0.0045
-901.69
-0.00025
331.24
0.0050
1.37
4.37

Df
1
1
1
1
1
1
69

Sum Sq
93.21
50.20
120.20
65.38
385.89
1.90
5930.19

Mean Sq
93.21
50.20
120.20
65.38
385.89
1.90
85.94

F value
1.084
0.584
1.398
0.760
4.489
0.022

Pr (>F)
0.301
0.447
0.241
0.386
0.037*
0.882

At the fifty-meter buffer distances of roadways to sites ranged from 29.9m to
2,061.8m with a mean distance of 737.5m (n=77). The linear model between nearest road
and population size did not yield a significant result at fifty-meters (ANOVA; df= (1, 75),
F= 1.0863, p= 0.3006). The density of roads within the fifty-meter buffer zone ranged
from 0m/m2 to 0.009m/m2 with a mean density of 0.00017m/m2 (n=79). A linear model

34

was used to assess the relationship between road density and snake populations but did
not reveal a significant result (ANOVA; df= (1, 77), F= 0.2722, p= 0.6033).
The distance of trails at the fifty-meter buffer zone for Model 2 ranged from 3.4m
to 14,517.335m with a mean distance of 5,182.67 (n=78). There was no significant
relationship found between nearest trail and population size at this spatial scale
(ANOVA; df= (1, 76), F= 2.2363, p= 0.1389). The density of trails at the fifty-meter
buffer zone ranged from 0m/m2 to 0.0284m/m2 with a mean density of 0.0007724m/m2
(n=79). The linear model did not show a significant relationship between population size
and road density (ANOVA; df= (1, 77), F= 1.3973, p= 0.2408).
Distances of buildings ranged from 51.5m to 3,311.77m at the fifty-meter buffer
zone with a mean distance of 913.12m (n= 77). The linear model did not show a
significant relationship between nearest building and population size (ANOVA; df= (1,
75), F= 0.4582, p= 0.5006). There were zero buildings measured within the fifty-meter
buffer zone for all sites (n= 79).
Canopy cover within the fifty-meter buffer zone ranged from 41.67% to 100%
with a mean cover of 93.4% (n=78). The linear model that was used to compare the
relationship between canopy cover and population size did not show a significant result
(ANOVA; df= (1, 76), F= 0.2181, p= 0.6419).
Model 2: Four-Hundred-Meters
The linear model for the four-hundred-meter buffer zone yielded a significant
result between population size and nearest building (p= 0.02, Table 11).

35

Table 11. Results of Model 2 at the 400m buffer zone with all factors included. A
significant relationship was observed between population size and nearest building.
R2= 0.0348
AIC= 563.34
Coefficients
Nearest Road
-0.0077
Road Density
-3178.28
Nearest Trail
-0.00014
Trail Density
557.45
Nearest Building
0.0063
Buildings Within
0.29
Canopy Percent
-9.11
Residuals
15.99

Df
1
1
1
1
1
1
1
68

Sum Sq
93.21
142.95
90.83
0.63
465.36
15.85
21.66
5816.47

Mean Sq
93.21
142.95
90.83
0.63
465.36
15.85
21.66
85.53

F value
1.089
1.671
1.061
0.007
5.440
0.185
0.253

Pr(>F)
0.300
0.200
0.306
0.931
0.022*
0.668
0.616

The distances between the fifty-meter and four-hundred-meter buffer zones did
not change regarding nearest road, nearest trail, and nearest building (Appendix XXII,
Appendix XXIII).
The linear model for nearest road at four-hundred-meters did not show a
significant result (ANOVA; df= (1, 75), F= 1.0863, p= 0.3006). The density of roads
ranged from 0m/m2 to 0.003107m/m2 with a mean density of 0.000427m/m2. The linear
model that evaluated population size and road density did not yield a significant result
(ANOVA; df= (1, 77), F= 0.207, p= 0.6504).
There was no significant relationship between nearest trail and population size
within the four-hundred-meter buffer zone (ANOVA; df= (1, 76), F= 2.2363, p= 0.1389).
The density of trails within the four-hundred-meter buffer zone ranged from 0m/m2 to
0.00534m/m2 with a mean density of 0.000558m/m2 (n= 79). The linear model did not
show a significant relationship between population size and trail density (ANOVA; df=
(1, 77), F= 0.6022, p= 0.4401).
36

The linear model did not produce a significant result between nearest building and
population size (ANOVA; df= (1, 75), F= 0.4582, p= 0.5006). The quantity of buildings
within the four-hundred-meter buffer zone ranged from zero to twelve with a mean
quantity of .66 (n= 78). There was no significant relationship between population size
and total buildings shown by the linear model (ANOVA; df= (1, 76), F= 0.0069, p=
0.9339).
Canopy cover at the four-hundred-meter buffer zone for Model 2 ranged from
67.7% to 100% with a mean cover value of 95.4% (n=78). The linear model did not show
a significant result between canopy cover and population size at the four-hundred-meter
buffer (ANOVA; df= (1, 76), F= 0.2982, p= 0.5866).
Model 2: Five-Thousand-Meters
A linear model was used at five-thousand-meters to assess the relationship
between the measured factors and population size, however, only nearest building was
significant (p= 0.03, Table 12).
Table 12. Results of Model 2 at the 5000m buffer zone with all factors included. A
significant relationship was observed between population size and nearest building.
R2= 0.1097
AIC= 468.03
Coefficients
Nearest Road
-0.0053
Road Density
11848.70
Nearest Trail
0.00035
Trail Density
7101.51
Nearest Building
0.0061
Buildings Within
-0.0025
Canopy Percent
44.66
Residuals
-51.09

Df
1
1
1
1
1
1
1
54

Sum Sq
165.08
269.61
7.151
46.22
495.25
189.02
213.75
5155.62

37

Mean Sq
165.08
269.61
7.15
46.22
495.25
189.02
213.75
95.47

F value
1.729
2.823
0.074
0.484
5.187
1.979
2.238

Pr(>F)
0.194
0.098
0.785
0.489
0.026*
0.165
0.140

The distance of sites from roadways within the five-thousand-meter buffer zone
ranged from 29.9m to 2,061.8m with a mean distance of 796.123m (n=64). A linear
model did not show a significant result between population size and nearest road
(ANOVA; df= (1, 62), F= 1.7025, p= 0.1968). The density of roads within this buffer
zone ranged from 0.000419m/m2 to 0.00359m/m2 with a mean density of 0.00137m/m2
(n=65). The relationship between road density and population size was not significant
(ANOVA; df= (1, 63), F= 3.6841, p= 0.05947).
For the five-thousand-meter buffer zone the distance from sites to trails ranged
from 3.4m to 14,517.33m with a mean distance of 5,390.93. The linear model used to
assess the relationship between nearest trail and population size did not show a
significant result (ANOVA; df= (1, 63), F= 2.1766, p= 0.1451). Trail density within this
buffer zone ranged from 0m/m2 to 0.00133m/m2 with a mean density of 0.000223m/m2
(n=65). No relationship was found between trail density and population size seen for this
buffer zone (ANOVA; df= (1, 63), F= 1.3572, p= 0.2484)
The building distances recorded at the five-thousand-meter buffer zone for Model
2 ranged from 78.16m to 3,311.77m with a mean distance of 985.9m (n=64). There was
no significant relationship between distance to buildings and population size within this
buffer zone (ANOVA; df= (1, 62), F= 0.2266, p= 0.6357). The quantity of buildings
within this buffer zone ranged from forty-two to seven-thousand-five-hundred-ninety-one
with a mean quantity of 1,675.58 (n=63). The linear model did not yield a significant
result when run with quantity of buildings and population size (ANOVA; df= (1, 61), F=
1.4683, p= 0.2303).
38

Canopy cover within this buffer zone ranged from 70.1% to 97.69% with a mean
cover of 89.1% (n=64). There was no significant relationship discovered between canopy
cover and population size (ANOVA; df=( 1, 62), F= 0.0578, p= 0.8108).
Model 3: Presence-Absence Model
The third model that was explored used a generalized linear model with a
binomial distribution to relate occupancy data as a function of the factors previously
mentioned. All factors were included in this model. If the site had a population size of
zero, it was assigned a value of zero, for absent, while any sites with a population size
greater than or equal to one had a value of one assigned to them, for present, indicating
that the site was occupied at the time it was visited. The goal of Model 3 was to assess
which factors determine whether snakes will be present or absent.
Model 3: Fifty-Meters
This model did not show a significant relationship between factors and site
occupancy at fifty-meters (Table 13).
Table 13. Results of the GLM for Model 3 within the 50m buffer zone. There were no
buildings measured within this buffer zone. There was no significant relationship
observed at this spatial scale.
AIC= 128.75
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Canopy Percent
Residuals

Coefficient
-0.0000091
2949.74
0.000045
1504.12
0.00014
-2.97
3.12

Df
1
1
1
1
1
1
107

39

Z- Value
-0.018
0.007
0.965
0.012
0.339
-1.257
1.360

Pr (>|z|)
0.986
0.994
0.334
0.991
0.734
0.209
0.174

The distance of sites to nearest roadways varied from 29.9m to 2,061.8m with a
mean distance of 737.5m (n=77) for occupied sites while distances at unoccupied sites
varied from 88.5m to 2,445.7m with a mean distance of 687.69 (n=39). There was no
significant relationship seen between nearest road and site occupancy for this spatial scale
in Model 3 (GLM; df= (1, 114), Z= 0.484 p= 0.628). The density of roadways in
occupied sites ranged from 0m.m2 to 0.009m/m2 with a mean density of 0.000178m/m2
(n=79) while no roadways were recorded within the fifty-meter buffer zone for
unoccupied sites. The model did not show a significant relationship between road density
and occupancy at fifty-meters for Model 3 (GLM; df=(1, 106), Z= 0.011, p= 0.990).
Within this buffer zone (50m) the distances of trails to sites varied from 3.4m to
14,517.34 with a mean distance of 5,182.67 (n=78) for occupied sites while unoccupied
sites ranged from 87.3 to 14,548.48m with a mean distance of 4,764.34m (n=39). The
GLM did not show a significant relationship between population and trail density for this
spatial scale (GLM; df= (1, 115), Z= 0. .435, p= 0. 663). The density of trails at this
spatial scale ranged from 0m/m2 to 0.2849m/m2 for occupied sites while unoccupied sites
did not have any trails within the buffer zone for Model 3. There was no significant
relationship observed between trail density and occupancy at this spatial scale for Model
3 (GLM; df= (1, 116), Z= 0.012, p= 0.990).
The distances from sites to buildings ranged from 51.5m to 3,311.77m with a
mean distance of 913.12m (n=77) for occupied sites while nearest building ranged from
98.7m to 2,253.4m for unoccupied sites with a mean distance of 822.94m (n=33). The
GLM did not show a significant relationship between site occupancy and nearest building
40

(GLM; df= (1, 113), Z= 0.733, p=0.263). There were no buildings present within the
fifty-meter buffer zone for Model 3.
Canopy cover ranged from 41.67% to 100% for occupied sites with a mean cover
of 93.43% (n=78) while the canopy cover at unoccupied sites ranged from 28.6 to 100%
with a mean cover of 97.29% (n= 39). There was no significant relationship between
occupancy and canopy cover for Model 3 at fifty-meters (GLM; df= (1, 115), Z= -1.512,
p= 0.1306).
Model 3: Four-Hundred-Meters
The GLM at the four-hundred-meter buffer zone showed a significant relationship
between quantity of buildings and population (p=0.03, Table 14). There was no
difference between measurements regarding nearest road, nearest trail, and nearest
building between the fifty-meter and four-hundred-meter buffer zones (Appendix XXV,
Appendix XXVI).
The density of roadways within the four-hundred-meter buffer zone for occupied
sites ranged from 0m/m2 to 0.0031m/m2 with a mean density of 0.000428m/m2 (n=79)
while the density of roadways at the unoccupied sites ranged from 0m/m2 to 0.0036m/m2
with a mean density of 0.000514m/m2 (n=39). The GLM did not show a significant
relationship between road density and site occupancy at this spatial scale in Model 3
(GLM; df= (1, 116), Z= -0.539, p= 0.589).

41

Table 14. Results of the GLM for Model 3 at the 400m buffer zone. A significant
relationship was observed between quantity of buildings and occupancy.
AIC= 152.33
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Buildings Within
Canopy Percent
Residuals

Coefficient
0.00013
388.76
0.0000034
-99.55
-0.00053
-0.21
3.07
-1.69

Df
1
1
1
1
1
1
1
106

Z- Value
0.210
0.959
0.062
-0.633
-1.083
-2.137
0.937
-0.552

Pr (>|z|)
0.833
0.337
0.950
0.526
0.278
0.032
0.580
.5306

At the four-hundred-meter buffer zone in Model 3 trail densities ranged from
0m/m2 to 0.00534m/m2 with a mean density of 0.000558m/m2 (n=79) for occupied sites
while trail density in unoccupied sites ranged from 0m/m2 to 0.00528m/m2 with a mean
density of 0.000862m/m2 (n=39). No significant relationship was observed between trail
density and occupancy for this spatial scale in Model 3 (GLM; df= (1, 116), Z= -1.052,
p= 0.2928).
The quantity of buildings for occupied sites at four-hundred-meters ranged from
zero to twelve with a mean quantity of 0.667 (n=78). For unoccupied sites the quantity of
buildings ranged from zero to sixteen with a mean quantity of 2.102 (n=39). The GLM
did not show a significant relationship between quantity of buildings and occupancy at
the four-hundred-meter buffer zone for Model 3 after the Bonferroni correction
accounting for multiple comparisons (GLM; df= (1, 115), Z= -2.203, p= 0.0276).
Canopy cover at the four-hundred-meter buffer zone ranged from 67.7% to 100%
with a mean cover of 95.43% at occupied sites while cover ranged from 63.8% to 100%
with a mean cover of 93.33% (n= 39) at unoccupied sites. There was no significant
42

relationship observed between canopy cover and population for this spatial scale (GLM;
df= (1, 115), Z= 1.461, p= 0.144).
Model 3: Five-Thousand-Meters
The GLM at the five-thousand-meter buffer zone in Model 3 did not show a
significant relationship between the factors and site occupancy (Table 15).
Table 15. Results of the GLM for the 5000m buffer zone in Model 3. There was no
significant result observed between the factors and the response variable.
AIC= 128.75
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Buildings Within
Canopy Percent
Residuals

Coefficient
0.000098
1438.44
-0.000024
-1240.32
0.000071
-0.00038
5.58
-5.20

Df
1
1
1
1
1
1
1
86

Z- Value
0.175
1.706
-0.296
-1.281
0.138
-1.682
1.108
-1.053

Pr (>|z|)
0.861
0.087
0.767
0.200
0.889
0.092
0.267
0.292

The distance of nearest roadways to occupied sites ranged from 29.9m to
2,061.8m with a mean distance of 796.12m (n=64) while the distance from unoccupied
sites to nearest road ranged from 88.5m to 2,445.7m with a mean distance of 709.54m
(n=37). The GLM did not show a significant relationship between site occupancy and
nearest roadway (GLM; df= (1, 99), Z= 0.785, p= 0.433). The density of roadways at this
spatial scale for occupied sites in Model 3 ranged from 0.000419m/m2 to 0.003599m/m2
with a mean density of 0.00137m/m2 (n=65) while unoccupied sites had a density range
of 0.0003m/m2 to 0.004m/m2 with a mean density of 0.00139m/m2 (n= 37). The GLM
did not show a significant relationship between site occupancy and road density within
the five-thousand-meter buffer zone for Model 3 (GLM; df= (1, 100), Z= -0.0109, p=
43

0.913) The distance from trails to sites at five-thousand-meters ranged from 3.4m to
14,517.34m with a mean distance of 5,309.93 (n=65) for occupied sites while unoccupied
sites ranged from 87.3m to 14, 548.48m with a mean distance of 4,801.33m (n=37).
There was no significant relationship observed between distance to nearest trail and site
occupancy for this spatial scale in Model 3 (GLM; df= (1, 100), Z= 0.556, p= 0.578). The
density of trails within the five-thousand-meter buffer zone ranged from 0m/m2 to
0.00133m/m2 for occupied sites with a mean density of 0.00022m/m2 (n=65) while
unoccupied sites ranged from 0m/m2 to 0.00159m/m2 with a mean density of
0.000312m/m2 (n=37). The GLM did not show a significant relationship between trail
density and population size at this spatial scale for Model 3 (GLM; df= (1, 100), Z= 1.217, p= 0.2234).
For this spatial scale, in Model 3, the distance to nearest building for occupied
sites ranged from 78.16m to 3,311.77m with a mean distance of 985. 93m (n= 64) while
the distance of nearest buildings to unoccupied sites ranged from 146.76m to 2,253.4m
with a mean distance of 837.5m (n= 32). There was no significant relationship observed
between nearest building and population at this spatial scale for Model 3 (GLM; df= (1,
94), Z= 1.074, p= 0.283). The quantity of buildings within the five-thousand-meter buffer
zone for occupied sites ranged from forty-two to seven-thousand-five-hundred-ninety-one
with a mean quantity of 1,675.58 (n= 63). For the unoccupied sites the quantity of
buildings ranged from eighty-four to fifteen-thousand-seven-hundred-six with a mean
quantity of 2,255.81 (n= 32). The GLM did not show a significant relationship between
quantity of buildings and site occupancy at this spatial scale for model 3 (GLM; df= (1,
93), Z= -1.033, p= 0.3014).
44

The amount of canopy cover for occupied sites at the five-thousand-meter buffer
zone in Model 3 ranged from 70.1% to 97.69% with a mean cover of 89.15% (n= 64)
while unoccupied sites had 58.44% to 97.76% cover with a mean of 87.54% (n=37). The
linear model did not show a significant relationship between canopy cover and site
occupancy at the five-thousand-meter buffer zone for Model 3 (GLM; df= (1, 99), Z=
1.027, p= 0.304).
Model 4: Abundance Model Without Pike County
The fourth model (Model 4) was identical to Model 1, however, the data from
Pike county is removed. This model included population size as a function of all
measured factors.
Model 4: Fifty-Meters
At the fifty-meter buffer zone there was a significant relationship between trail
density and population size (p= 0.01, Table 16).
Table 16. Results of Model 4 at 50m showing a significant relationship between trail
density and population size. There were no buildings measured at this spatial scale.
R2= 0.0557
AIC= 648.38
Coefficients
Nearest Road
-0.0030
Road Density
-630.29
Nearest Trail
-0.00010
Trail Density
1031.66
Nearest Building
0.0037
Canopy Percent
0.91
Residuals
1.98

Df
1
1
1
1
1
1
80

Sum Sq
56.58
13.75
24.46
520.43
252.31
0.92
6274.92

Mean Sq
56.58
13.75
24.46
520.43
252.31
0.92
78.43

F value
0.721
0.175
0.311
6.635
3.216
0.011

Pr(>F)
0.398
0.676
0.578
0.011*
0.076
0.913

As with previous models, each factor was put into a linear model individually to
assess the relationship between each factor and population size at each site. Distances
45

from roadways to sites varied from 29.9m to 2,445.7m with a mean distance of 767.91
(n=89). The model relating population size to nearest roadway at fifty-meters did not
yield a significant result (ANOVA; df= (1, 87), F= 0.6256, p=0.4311). The density of
roads within this buffer zone ranged from 0m/m2 to 0.009m/m2 with a mean density of
0.0001m/m2 (n= 90). The linear model for road density at fifty-meters did not reveal a
significant result (ANOVA; df= (1, 87), F= 0.0799, p= 0.7782).
The distance of trails to sites at fifty-meters varied from 21.6m to 14,548.48m
with a mean distance of 5,676.42m (n= 90). There was no significant relationship
observed between population size and distance to nearest trail for this spatial scale
(ANOVA; df= (1, 88), F= 0.963, p= 0.3291). The density of trails at fifty-meters for
Model 4 ranged from 0m/m2 to 0.0227m/m2 with a mean density of 0.000361m/m2 (n=
90). However, the linear model for this spatial scale showed a significant relationship
between trail density and population size after correcting for multiple comparisons
(Bonferroni, critical value= 0.0083) (ANOVA; df= (1, 88), F= 7.5827, p= 0.00716).
The distance from buildings to sites at the fifty-meter buffer zone ranged from
78.16m to 3,311.77m with a mean distance of 913.342m (n=88). The linear model used at
this spatial scale for nearest building and snake numbers did not show a significant
relationship (ANOVA; df= (1, 86), F= 0.2152, p= 0.6439). There were no buildings
measured within the fifty-meter buffer zone for Model 4.
The canopy cover for Model 4 at fifty-meters ranged from 28.64% to 100% with a
mean cover of 96.28% (n=89). The linear model did not show a significant relationship
between canopy cover and population size (ANOVA; df= (1, 87), F= 0.5957, p= 0.4423).
46

Model 4: Four-Hundred-Meters
Within the four-hundred-meter buffer zone for Model 4 there was no significant
relationship discovered between the factors and population size (Table 17).
The values of nearest factor did not differ between the fifty-meter and fourhundred-meter buffer zones for Model 4 (Appendix XXVIII, Appendix XXIX). The
linear model for four-hundred-meters in Model 4 between nearest road and population
size did not show a significant result (ANOVA; df= (1, 87), F= 0.625, p= 0.4311). The
density of roads for this spatial scale in Model 4 ranged from 0m/m2 to 0.0031m/m2 with
a mean density of 0.0004177m/m2 (n=90). There was no significant relationship found
between road density and population size (ANOVA; df= (1, 88), F= 0.096, p= 0.7574).
Table 17. Results of Model 4 at the 400m buffer zone. There was no significant
relationship observed between the factors and population size.
R2= -0.0337
AIC= 643.89
Coefficients
Nearest Road
-0.0040
Road Density
-1587.84
Nearest Trail
-0.00010
Trail Density
253.59
Nearest Building
0.0033
Buildings Within
-0.14
Canopy Percent
-4.56
Residuals
9.17

Df
1
1
1
1
1
1
1
79

Sum Sq
56.58
66.41
16.35
2.017
203.70
8.06
6.85
6783.40

Mean Sq
56.58
66.41
16.35
2.01
203.70
8.06
6.85
85.86

F value
0.659
0.773
0.190
0.023
2.37
0.093
0.079

Pr(>F)
0.419
0.381
0.663
0.878
0.127
0.760
0.778

The linear model relating nearest trail and population size did not show a
significant result (ANOVA; df= (1, 88), F= 0.963, p= 0.3291). The densities of trails
within the four-hundred-meter buffer zone ranged from 0m/m2 to 0.00534m/m2 with a
mean density of 0.000789m/m2 (n=90). The linear model did not show a significant
47

relationship at this spatial scale between trail density and population size (ANOVA; df=
(1, 88), F= 0.2414, p= 0.6244).
Within this buffer zone for Model 4 there was no relationship found between
nearest building and population size (ANOVA; df= (1,86), F= 0.2152, p= 0.6439). The
quantity of buildings within this buffer zone ranged from zero to sixteen with a mean
quantity of 0.9438 (n=89). There was no significant relationship seen between total
buildings within the buffer zone and population size for Model 4 at four-hundred-meters
(ANOVA; df= (1, 87), F= 0.3617, p=0.5492).
Canopy cover within the four-hundred-meter buffer zone ranged from 67.7% to
100% with a mean cover of 94.44% (n=89). There was no significant relationship seen
between canopy cover and population size at this buffer zone for Model 4 (ANOVA; df=
(1, 87), F= 0.116, p= 0.7342).
The last buffer zone for Model 4, five-thousand-meters, showed a significant
relationship between quantity of buildings and population size (p=0.02, Table 18) as well
as canopy cover and population size (p=0.048, Table 18).

48

Table 18. Results of Model 4 at the 5000m buffer zone. A significant relationship was
observed between quantity of buildings and population size as well as canopy cover and
population size.
R2= 0.122
AIC= 592.01
Coefficients
Nearest Road
-0.0017
Road Density
11645.94
Nearest Trail
0.00016
Trail Density
-491.08
Nearest Building
0.0028
Buildings Within
-0.0018
Canopy Percent
43.21
Residuals
-48.70

Df
1
1
1
1
1
1
1
73

Sum Sq
65.18
269.36
0.26
0.69
307.84
459.84
311.71
5671.62

Mean Sq
65.18
269.36
0.26
0.69
307.84
459.84
311.71
77.69

F value
0.839
3.467
0.003
0.008
3.96
5.918
4.012

Pr(>F)
0.362
0.066
0.953
0.924
0.050
0.017*
0.048*

The distance between roadways and sites within this buffer zone for Model 4
varied from 29.9m to 2,445.7m with a mean distance of 770.84m (n=88). The linear
model that tested population size as a function of distance to nearest roadways did not
show a significant result (ANOVA; df= (1, 86), F= 0.6335, p= 0.4283). The density of
roadways within this buffer zone in Model 4 ranged from 0.000348m/m2 to
0.004001m/m2 with a mean density of 0.0011354m/m2 (n=89). The linear model relating
population size as a function of road density for this spatial scale did not show a
significant result (ANOVA; df= (1 87), F= 3.9419, p= 0.05025).
Model 4: Five-Thousand-Meters
Within the five-thousand-meter buffer zone for Model 4 the distances from sites
to nearest trail ranged from 21.6m to 12,548.48m with a mean distance of 530.453m
(n=89). The linear model for nearest trail distance and population size did not show a
significant result (ANOVA; df= (1, 87), F= 0.9948, p= 0.3213). Densities of trails within
the five-thousand-meter buffer zone ranged from 0m/m2 to 0.00160m/m2 with a mean
49

density of 0.000249m/m2 (n= 89). There was no significant relationship seen between
trail density and population size at five-thousand-meters for Model 4 (ANOVA; df= (1,
87), F= 0.0964, p= 0.7569).
The distance of nearest building ranged from 78.16m to 3,311.77m with a mean
distance of 914.548m (n=83). The linear model that tested population size as a function
of distance to nearest building did not show a significant result (ANOVA; df = (1, 81),
F= 0.2176, p= 0.6421). At this spatial scale, for Model 4, the quantity of buildings within
the buffer zone ranged from forty-two to fifteen-thousand-seven-hundred-six with a mean
quantity of 1,904.304 (n= 82). The linear model did not show a significant relationship
between population size and quantity of buildings for this spatial scale (ANOVA; df= (1,
80), F= 0.4506, p= 0.504).
Canopy cover within this buffer zone for Model 4 ranged from 58.44% to 97.7%
with a mean cover of 88.44% (n=88). The linear model did not show a significant
relationship between canopy cover and population size at this spatial scale (ANOVA; df=
(1, 86), F= 0.0034, p= 0.9536).
Model 5: Non-Zero Abundance Model Without Pike County
The fifth model, Model 5, was identical to Model 2- that is, all sites that had a
value of zero recorded for their population size were removed. Additionally, for this
model Pike county was removed.
Model 5: Fifty-Meters
The linear model for the fifty-meter buffer zone showed a significant relationship
between population size and nearest building (p=0.03, Table 19).
50

Table 19. Results of Model 5 at the 50m buffer zone. A significant relationship was
observed between population size and nearest building. There were no buildings
measured at this spatial scale.
R2= 0.100
Coefficients Df
AIC= 394.96
Nearest Road
-0.0081
1
Road Density
-1594.83
1
Nearest Trail
-0.00032
1
Trail Density
1002.14
1
Nearest Building
0.0087
1
Canopy Percent
8.44
1
Residuals
-1.55
44

Sum Sq

Mean Sq

F value

Pr(>F)

180.47
66.73
150.96
281.53
604.67
42.43
5036.86

180.47
66.73
150.96
281.53
604.67
42.43
114.47

1.576
0.583
1.318
2.459
5.282
0.370

0.215
0.449
0.257
0.123
0.026*
0.545

Nearest distance of roadways to sites varied within the fifty-meter buffer zone for
Model 5 from 29.9m to 2,061.8m with a mean distance of 809.45m (n=52). The linear
model did not find a significant result relating nearest distance of roadways to site
(ANOVA; df= (1, 50), F= 1.4744, p= 0.2304). The density of roadways at this spatial
scale for fifty-meters ranged from 0m/m2 to 0.009m/m2 with a mean density of
0.0001m/m2 (n=53). A linear model was run relating population size as a function of road
density and did not find a significant result (ANOVA; df= (1, 51), F= 0.2047, p= 0.6529).
The distance of trails ranged from 21.6m to 14,517.33m with a mean distance of
6,287.33m (n=53). There was no significant result discovered between nearest trail and
population size for this spatial scale in Model 5 (ANOVA; df= (1, 51), F= 2.3026, p=
0.1353). The density of trails for Model 5 ranged from 0m/m2 to 0.227m/m2 with a mean
density of 0.000613m/m2 (n=53). The linear model relating population size as a function
of trail density did not show a significant relationship for this spatial scale in Model 5
(ANOVA; df= ( 1, 51), F= 3.6766, p= 0.06079).

51

The distance of nearest building to sites ranged from 78.16m to 3,311.77m with a
mean distance of 953.65m (n=52). The linear model relating nearest building to
population size did not show a significant relationship (ANOVA; df= (1, 50), F= 0.0574,
p= 0.8117). There were no buildings measured within the fifty-meter buffer zone in
Model 5.
The total amount of canopy cover in Model 5 at this spatial scale ranged from
41.67% to 100% with a mean cover of 95.39% (n=52). There was no significant
relationship reported between canopy cover and population size at fifty-meters (ANOVA;
df= (1, 50), F= 0.2676, p= 0.6072).
Model 5: Four-Hundred-Meters
Within the four-hundred-meter buffer zone for Model 5 there was a significant
relationship seen between nearest building and population size (p=0.04, Table 20).

Table 20. The results of Model 5 at the 400m buffer zone A significant relationship was
found between nearest building and population size.
R2= 0.03858
AIC= 399.18
Coefficient
Nearest Road
-0.011
Road Density
-4191.94
Nearest Trail
-0.00034
Trail Density
-52.31
Nearest Building
0.0092
Buildings Within
1.51
Canopy Percent
0.77
Residuals
9.54

Df
1
1
1
1
1
1
1
43

Sum Sq
180.47
169.81
119.84
14.24
564.17
53.40
0.11
5261.61

Mean Sq
180.47
169.81
119.84
14.24
564.17
53.40
0.11
122.36

F value
1.474
1.387
0.979
0.116
4.610
0.436
0.000929

Pr(>F)
0.231
0.245
0.327
0.734
0.037*
0.512
0.975

The values of nearest roadway, trail, and building did not differ between the fiftymeter and four-hundred-meter buffer zones(Appendix XXXI, Appendix XXXII). The
52

linear model relating population size as a function of nearest road for the four-hundredmeter buffer did not show a significant result (ANOVA; df= (1, 50), F= 1.4744),
p=0.2304). The density of roads at this spatial scale ranged from 0m/m2 to 0.003107m/m2
with a mean density of 0.000399m/m2 (n=53). There was not a significant relationship
measured between road density and population size for Model 5 at this spatial scale
(ANOVA; df= (1, 51), F= 0.0446, p= 0.8336).
There was no significant relationship seen between nearest trail and population
size at four-hundred-meters in Model 5 (ANOVA; df= (1, 51), F= 2.3026, p= 0.1353).
The density of trails within this buffer zone for Model 5 ranged from 0m/m2 to
0.00534m/m2 with a mean density of 0.000706m/m2 (n= 53). The linear model did not
show a significant relationship between trail density and population size (ANOVA; df=
(1, 51), F= 0.508, p= 0.4792).
The linear model relating population size as a function of nearest building at fourhundred-meters for Model 5 did not show a significant relationship (ANOVA; df= (1,
50), F= 0.0574, p=0.08117). The quantity of buildings within this buffer zone ranged
from zero to six with a mean quantity of 0.3269 (n=52). The linear model did not show a
significant relationship between quantity of buildings and population size (ANOVA; df=
(1, 50), F= 0.4601, p= 0.5007).
The amount of canopy cover within the four-hundred-meter buffer zone ranged
from 67.7% to 100% with a mean cover of 94.78% (n= 52). The linear model did not
show a significant relationship between canopy cover and population size for this buffer
zone in Model 5 (ANOVA; df= (1, 50), F= 0.2912, p= 0.5918).
53

Model 5: Five-Thousand-Meters
For the last buffer zone, five-thousand-meters, within Model 5 there was a
significant relationship observed between road density and population size (p= 0.03,
Table 21), quantity of buildings and population size (p= 0.03, Table 21), and canopy
percent and population size (p= 0.03, Table 21). Additionally, the relationship between
distance to nearest building and population size was nearly significant (p= 0.05, Table
21).
Distances of nearest road to each site varied from 29.9m to 2,061.8m with a mean
distance of 815.31m (n= 51). The linear model that related population size as a function
of distance to nearest road did not show a significant result (ANOVA; df= (1, 49), F=
1.533, p= 0.2215). The density of roadways within the five-thousand-meter buffer zone
for Model 5 ranged from 0.000419m/m2 to 0.003599m/m2 with a mean density of
0.00132m/m2 (n=52). The linear model relating population size as a function of road
density did not show a significant result after Bonferroni corrections (ANOVA; df= (1,
50), F= 5.1955, p= 0.02695).

54

Table 21. Results of Model 5 at the 5000m buffer zone. A significant relationship was
observed between population size and road density, population size and quantity of
buildings, and population size and canopy cover.
R2= 0.221
AIC= 375.3433 Coefficient
Nearest Road
-0.0030
Road Density
21705.37
Nearest Trail
-0.00024
Trail Density
-227.35
Nearest Building
0.0050
Buildings Within
-0.0061
Canopy Percent
78.25
Residuals
-82.51

Df
1
1
1
1
1
1
1
41

Sum Sq
180.96
501.09
1.76
1.80
411.80
510.68
512.32
4216.09

Mean Sq
180.96
501.09
1.76
1.809
411.80
510.68
512.32
102.83

F value
1.759
4.872
0.017
0.017
4.004
4.966
4.982

Pr(>F)
0.191
0.032*
0.896
0.895
0.052
0.031*
0.031*

The distance of trails to sites for Model 5 within the five-thousand-meter buffer
zone ranged from 21.6m to 14,517.33m with a mean distance of 6,391.553m (n= 52). The
linear model relating nearest trail to population size did not show a significant
relationship (ANOVA; df= (1, 50), F= 2.4856, p= 0.1212). The density of roadways
within this buffer zone ranged from 0m/m2 to 0.00133m/m2 with a mean density of
0.000204m/m2 (n=52). There was no significant relationship observed between trail
density and population size within this buffer zone for Model 5 (ANOVA; df= (1, 50), F=
0.8757, p= 0.3539).
The distance of buildings to sites within the five-thousand-meter buffer zone
ranged from 78.16m to 3,311.77m with a mean distance of 962.886m (n= 51). There was
no significant relation seen between nearest building and population size for this spatial
scale in Model 5 (ANOVA; df= (1, 49), F= 0.0405, p= 0.8414). The total amount of
buildings within this buffer zone for Model 5 varied from forty-two to seven-thousand55

five-hundred-ninety-one with a mean quantity of 1,679.34 (n= 50). The linear model that
related population size as a function of total buildings did not show a significant
relationship (ANOVA; df= (1, 48), F= 1.8941, p= 0.1751).
The amount canopy cover within this buffer zone for Model 5 ranged from
70.13% to 97.69% with a mean cover of 89.09% (n= 51). There was no significant
relationship observed between canopy cover and population size within this buffer zone
(ANOVA; df= (1, 49), F= 0.0972, p= 0.7566).
Model 6: Presence-Absence Model Without Pike County
The last model, Model 6, was derived from Model 3 and followed a similar
structure to the previous two models with Pike County removed.
Model 6: Fifty-Meters
The first buffer zone, fifty-meters, did not show a significant relationship between
the predictor and response variables (Table 22).
The distance from nearest road to sites ranged from 29.9m to 2,061.8m with a
mean distance of 809.45m (n=52) for occupied sites while the distances ranged from
88.5m to 2,445.7m for unoccupied sites with a mean distance of 709.54m (n=37). The
GLM did not show a significant relationship between nearest roadway and population for
this spatial scale in Model 6 (GLM; df= 1, 87), Z= 0.844, p= 0.399). The density of
roadways for occupied sites ranged from 0m/m2 to 0.009m/m2 with a mean density of
0.000169m/m2 (n= 53). There were no roadways measured within the fifty-meter buffer
zone for Model 6. The GLM did not show a significant relationship between population
and road density (GLM; df= (1, 88), Z= 0.010, p= 0.992).
56

Table 22. Results of the GLM at the 50m buffer zone for Model 6. There was no
significant relationship observed between the factors and the response variable. There
were no buildings measured at this spatial scale.
AIC= 124.15
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Canopy Percent
Residuals

Coefficient
-0.000019
1958.22
0.000096
1643.22
-0.00015
-1.44
1.28

Df
1
1
1
1
1
1
80

Z- Value
-0.036
0.004
1.806
0.009
-0.316
-0.689
0.620

Pr (>|z|)
0.972
0.996
0.071
0.993
0.752
0.491
0.535

The distance of nearest trail to occupied sites ranged from 21.6m to 14,517.34m
with a mean distance of 6,287.33m (n=53) while distance of unoccupied sites to nearest
trails ranged from 87.3m to 14,538.48m with a mean distance of 4,801.33m. There was
no significant relationship observed between trail density and site occupation at this
spatial scale for Model 6 (GLM; df= (1, 88), Z= 1.312, p=, 0.190). The density of trails
within this buffer zone ranged from 0m/m2 to 0.0227m/m2 for occupied sites with a mean
density of 0.000613m/m2 (n=53). There were no trails measured within the fifty-meter
buffer zone for Model 6. The GLM did not show a significant relationship between trail
density and population at this spatial scale (GLM; df= (1, 88), Z= 0.014, p= 0.989).
At this spatial scale, fifty-meters, distance from occupied sites to nearest building
ranged from 78.16m to 3,311.77m with a mean distance of 953.65m (n=53) while the
distance of unoccupied sites to nearest sites ranged from 146.76m to 2,253.4m with a
mean distance of 855.11m (n=37). There was no significant relationship observed
between nearest building and site occupancy at this spatial scale for Model 6 (GLM; df=
57

(1, 86), Z= 0.720, p= 0.472). There were no buildings measured within the fifty-meter
buffer zone.
Canopy cover for the fifty-meter buffer zone ranged from 41.6% to 100% for
occupied sites with a mean cover of 95.39% (n= 52) while canopy cover ranged from
28.6% to 100% for unoccupied sites with a mean cover of 97.52% (n=37). The GLM did
not show a significant relationship between canopy cover and site occupancy at this
spatial scale for Model 6 (GLM; df= (1, 87), Z= -0.820, p= 0.412).
Model 6: Four-Hundred-Meters
At the four-hundred-meter buffer zone there was no significant relationship
observed between the predictors and population, though total buildings were nearly
significant (p=0.06, Table 23). There was no difference between the fifty-meter buffer
zone and four-hundred-meter buffer zone regarding nearest road, nearest trail, and nearest
building (Appendix XXXIV, Appendix XXXV).
Table 23. Results of the GLM at the 400m buffer zone for Model 6. There was no
significant relationship observed between the factors and the response variable.
AIC= 121.16
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Buildings Within
Canopy Percent
Residuals

Coefficient
0.00027
556.60
0.00010
194.76
-0.00061
-0.49
-2.47
2.44

Df
1
1
1
1
1
1
1
79

58

Z- Value
0.408
1.209
1.575
0.898
-1.085
-1.919
-0.620
0.680

Pr (>|z|)
0.683
0.227
0.115
0.369
0.278
0.055
0.535
0.496

The density of roads within the four-hundred-meter buffer zone for occupied sites
ranged from 0m/m2 to 0.0031m/m2 with a mean density of 0.000399m/m2 (n= 53) while
the density of unoccupied sites ranged from 0m/m2 to 0.00224m/m2 with a mean density
of 0.000444m/m2 (n=37). The GLM did not show a significant relationship between
population and road density at this spatial scale (GLM; df= (1, 88), Z= -0.278, p= 0.781).
The density of trails for occupied sites within the four-hundred-meter buffer zone
ranged from 0m/m2 to 0.00534m/m2 with a mean density of 0.000706m/m2 (n= 53) while
the density of trails at unoccupied sites ranged from 0m/m2 to 0.00528m/m2 with a mean
density of 0.000908m/m2 (n= 37). There was no significant relationship observed
between trail density and occupancy at this spatial scale for Model 6 (GLM; df= (1, 88),
Z= -0.593, p= 0.5530).
The quantity of buildings within the four-hundred-meter buffer zone ranged from
zero to six for occupied sites with a mean quantity of 0.3269 (n= 52) while the quantity at
unoccupied sites ranged from zero to sixteen with a mean quantity of 1.81 (n=37). There
was no significant relationship observed between number of buildings within the buffer
zone and population for Model 6 at this spatial scale after using the Bonferroni correction
to account for multiple comparisons (GLM; df= (1, 87), Z= -1.981, p= 0.0476).
The amount of canopy cover for occupied sites ranged from 67.7% to 100% with
a mean cover of 94.78% (n= 52) while canopy cover at unoccupied sites ranged from
74.8% to 100% with a mean cover of 93.96% (n= 37). There was no significant
relationship observed between canopy cover and population at this spatial scale (GLM;
df= (1, 87), Z= 0.531, p= 0.595).
59

Model 6: Five-Thousand-Meters
There were no significant relationships observed between the predictor variables
and occupancy at the five-thousand-meter buffer zone (Table 24).
The distance of nearest roadway to occupied sites varied from 29.9m to 2,061.8m
with a mean distance of 815.31m (n=51) while the distance from nearest road to
unoccupied sites ranged from 88.5m to 2,445.7m with a mean distance of 709.54m (n=
37). There was no significant relationship observed between nearest road and occupancy
at this spatial scale for Model 6 (GLM; df= ( 1, 86), Z= 0.886, p= 0.376). The density of
roadways at occupied sites ranged from 0.000419m/m2 to 0.00359m/m2 with a mean
density of 0.00132m/m2 (n= 52) while the density of roadways at unoccupied sites ranged
from 0.000348m/m2 to 0.004m/m2 with a mean density of 0.00139m/m2 (n=37). There
was no significant relationship observed between road density and occupancy at this
spatial scale for Model (GLM; df= (1, 87), Z= -0.381, p= 0.704).
Table 24. Results from the GLM at the 5000m buffer zone for Model 6. There were no
significant relationships observed between the factors and population.
AIC= 118.15
Nearest Road
Road Density
Nearest Trail
Trail Density
Nearest Building
Buildings Within
Canopy Percent
Residuals

Coefficient
0.00015
1408.76
0.000028
-1249.63
-0.00036
-0.00034
5.68
-5.47

Df
1
1
1
1
1
1
1
73

60

Z- Value
0.270
1.620
0.323
-1.084
-0.612
-1.507
1.059
-1.073

Pr (>|z|)
0.787
0.105
0.747
0.278
0.541
0.132
0.290
0.283

The distance of occupied sites to nearest trail ranged from 21.6m to 14,517.34m
with a mean distance of 6,391.55m (n=52) while the distance from nearest trail to
unoccupied sites ranged from 87.3m to 14,548.48m with a mean distance of 4,801.339m
(n= 37). There was no significant relationship observed between nearest trail and
occupancy at this spatial scale for Model 6 (GLM; df= (1, 87), Z= 1.396, p= 0.163). The
density of trails within the five-thousand-meter buffer zone for occupied sites ranged
from 0m/m2 to 0.00133m/m2 with a mean density of 0.000204m/m2 (n=52) while the
density at unoccupied sites ranged from 0m/m2 to 0.00159m/m2 with a mean density of
0.000312m/m2 (n=37). There was no significant relationship observed between trail
density and population at the five-thousand-meter buffer zone for Model 6 (GLM; df= (1,
87), Z= -1.374, p= 0.1695).
The distance of nearest building to occupied sites ranged from 78.16m to
3,311.77m with a mean distance of 962.88m (n=51) while the distance from nearest
building to unoccupied sites ranged from 146.76m to 2,253.4m with a mean distance of
837.5m (n= 32). There was no significant relationship observed between nearest building
and population size at this spatial scale for Model 6. (GLM; df= (1, 81), Z= 0.864, p=
0.387). The quantity of buildings within the five-thousand-meter buffer zone for occupied
sites ranged from forty-two to seven-thousand-five-hundred-ninety-one with a mean
quantity of 1,679.34m (n=50). The amount of buildings within the five-thousand-meter
buffer zone for unoccupied sites ranged from eighty-four to fifteen-thousand-sevenhundred-six with a mean quantity of 2,255.81 (n=32). There was no significant
relationship observed between quantity of buildings and population at this spatial scale
for Model 6 (GLM; df= (1, 80), Z= -0.935, p= 0.350).
61

Canopy cover within the five-thousand-meter buffer zone for Model 6 ranged
from 70.13% to 97.69% for occupied sites with a mean cover of 89.09% (n=51) while the
canopy cover of unoccupied sites ranged from 58.44% to 97.76% with a mean cover of
87.54% (n=37). There was no significant relationship observed between occupancy and
canopy cover for this spatial scale in Model 6 (GLM; df= (1, 86), Z= 0.892, p= 0.373).
Presence/Pseudo-Absence Analyses
There were one-hundred total points added to the Northeast region in ArcMap®.
Two points were removed from Nearest Trail as the distance from the site to the nearest
trail was greater than the distance from the site to the state border. Due to the nature of
how canopy was measured for the random points, the values of canopy did not change
between buffer zones for random points. (Appendix XL).
The distance of random points to nearest road varied from 0.8484m to 1,266.63m
with a mean distance of 269.03m (n=100). A significant difference was found between
nearest roads to rattlesnake sites and nearest roads to random points (ANOVA; df= (1,
214), F= 59.33, p< 0.0001). The distance of nearest trail to the random points ranged
from 6.779m to 13,125.97m with a mean distance of 3,917.05m (n=98). There was not a
significant difference observed between nearest trail to rattlesnake sites and nearest trail
to random points (ANOVA; df= (1, 213), F= 3.874, p= 0.0503).
Within the fifty-meter buffer zone the density of roadways ranged from 0m/m2 to
0.026m/m2 with a mean density of 0.0029m/m2 (n=100). There was a significant
difference between the density of roadways within fifty-meters of a rattlesnake site and
the density of roads within fifty-meters of the random points (ANOVA; df= (1, 216), F=
62

22.23, p< 0.0001). The density of trails at this spatial scale for random points ranged
from 0m/m2 to 0.0125m/m2 with a mean density of 0.000341m/m2 (n=100). There was
not a significant difference observed between the trail density within fifty-meters of a
rattlesnake site and the trail density within fifty-meters of a random point (ANOVA; df=
(1, 216), F= 0.204, p= 0.652). The amount of canopy cover for the fifty-meter buffer zone
ranged from 0% to 100% with a mean cover of 64% (n= 100). There was a significant
difference between the canopy cover of rattlesnake sites at fifty-meters and the canopy
cover of random points (ANOVA; df= (1, 215), F= 44.15, p< 0.0001).
The density of roadways within the four-hundred-meter buffer zone for random
points ranged from 0m/m2 to 0.0213m/m2 with a mean density of 0.00285m/m2 (n=100).
There was a significant difference observed between road density around rattlesnake sites
at four-hundred meters and road density around the random points at four-hundredmeters (ANOVA; df= (1, 216), F= 58.33, p< 0.0001). The density of trails at this spatial
scale ranged from 0m/m2 to 0.00347m/m2 with a mean density of 0.00009468m/m2
(n=100). There was a significant difference observed between trail density around
rattlesnake sites and trail density around the random points (ANOVA; df= (1, 216), F=
13.74, p< 0.001). There was a significant difference observed between the canopy cover
around rattlesnake sites at four-hundred-meters and canopy cover at the random points
(ANOVA; df= (1, 215), F= 46.32, p< 0.0001).
The density of roadways within the five-thousand-meter buffer zone for random
points ranged from 0.000398m/m2 to 0.0142m/m2 with a mean density of 0.00441m/m2
(n=100). There was a significant difference observed between the road density around
63

rattlesnake sites at five-thousand-meters and the road density around random points at
five-thousand meters (ANOVA; df= (1, 200), F= 129.2, p<0.0001). The density of trails
at this spatial scale ranged from 0m/m2 to 0.00173m/m2 with a mean density of
0.000253m/m2 (n=100). The was no significant difference observed between trail density
around rattlesnake sites at five-thousand-meters and trail density around random points at
five-thousand-meters (ANOVA; df= (1, 200), F= 0.003, p= 0.954). There was a
significant difference observed between canopy cover around rattlesnake sites at fivethousand-meters and canopy cover of random points (ANOVA; df= (1, 199), F= 25.56,
p< 0.0001).

64

CHAPTER 4: DISCUSSION
Another recently published work relating habitat to C. horridus populations was
limited to using habitat suitability models to predict where populations of this species
should be (Kolba, 2016). Our work on this project represents a novel method of
measuring the effects of disturbance on this species at various spatial scales. Likewise,
whereas the previous work explored presence data as well as habitat features, both natural
and abiotic, to predict where timber rattlesnakes should be, our approach explores where
members of this species have been observed and relates anthropogenic impacts to these
real-world observations to assess how population estimates are impacted. This project can
have real-world implications in the management of this species at large spatial scales.
The following section will describe in detail the significance of the results produced by
the project. The layout of the discussion will follow the same order as the results,
covering each model in detail before moving on to overall conclusions and future
directions.

65

Model 1: Abundance Model
This model, which examined snake populations as a function of all factors in a
linear model with all counties, showed a significant positive relationship between
population size and distance to nearest building at the small and large spatial scales
(50mand 5000m, respectively), with an additional significant negative relationship to
total buildings at the large spatial scale. This relationship suggests snake populations do
better at greater distances from buildings. As with all the models, R-Squared values are
much higher at the large spatial scale while Akaike Information Criterion (AIC) values
are lowest, suggesting that our data explains more of the variation in population size at
this spatial scale. There are low quantities of trails and roads found within fifty-meters of
a handful of sites with all sites in close proximity to these features containing a non-zero
population of snakes (Appendix XIX). While canopy cover was not shown to be
significant at any spatial scale, the pattern of the data fits the biology of the rattlesnake
with canopy cover at small spatial scales having lower values than at the intermediate and
large spatial scale, though the average amount of cover between the small and
intermediate spatial scale did not differ very much. This suggests that snakes utilize small
amounts of open habitat within this buffer zone that they would use primarily for
maintenance behaviors including gestation, digestion, and ecdysis. The higher values of
canopy cover at the large spatial scale suggest that forested habitat is required, likely for
foraging and mate seeking behavior. There were no buildings measured at the small
spatial scale, making their effect impossible to interpret. However, a negative relationship
was observed between quantity of buildings and snake populations at the large spatial

66

scale, suggesting that developing land with associated structures may have a detrimental
effect on populations.
Model 2: Non-Zero Abundance Model
Model 2 included snake abundance only within presence-sites. Within this model,
all spatial scales showed a significant positive relationship between population size and
distance to nearest building, again suggesting that as buildings encroach on snake
habitats, snake populations become smaller. This model showed a similar pattern of
higher R-squared values and lower AIC values at the large spatial scale, similarly
suggesting that the observations better explain variation in snake populations at the large
spatial scale. Removing the variance applied to sites with population numbers of zero
does not seem to greatly change model results, with significant relationships and
coefficients not differing by much. This model shows that small spatial scales have a
wider range of canopy cover values with some sites having very low values at this spatial
scale. Additionally, the large spatial scale seems to have much higher overall canopy
cover with a smaller range of values. This reinforces the idea that forest cover seems to
be more important at large spatial scales while the small spatial scale is reliant on patches
of open canopy for maintenance habitat. Additionally, this model again shows that roads
and trails are present close to rattlesnake populations. There was a negative relationship
observed between buildings and populations at the large spatial scale, further suggesting
that buildings are detrimental to snake populations at the landscape level.
Model 3: Presence-Absence Model
The third model used a generalized linear model with a binomial distribution and
converted population size to occupancy data as a function of all factors. This model
67

showed a significant negative relationship between quantity of buildings and occupancy
at the intermediate spatial scale. This model represented an interesting result in that it is
the only model showing a significant relationship between these factors at this spatial
scale, though it does reinforce the idea that buildings have a negative impact at larger
spatial scales relative to the snake site. However, the small and large spatial scales within
this model did not reveal a significant relationship and both had lower AIC values than
the intermediate spatial scale, suggesting that this model better fits the data at these
scales. This model also reveals that the factors are in line with what would be expected
relative to presence-absence data; that is, sites where snakes are absent show higher
densities of roads and trails, and have roads, trails, and buildings closer to them than sites
where rattlesnakes are present (Appendix XXV, Appendix XXVI, Appendix XXVII,
Appendix XXXIV, Appendix XXXV, Appendix XXXVI). This is further evidence that
as human development encroaches on rattlesnake habitat, sites may become extirpated.
Model 4: Abundance Model Without Pike County
As mentioned previously, the next three models are mirrors of Model 1, Model 2,
and Model 3 with Pike County removed. Model 4 showed a significant positive
relationship between trail density and population size at the small spatial scale, which
was corroborated when trail density was run individually in relation to population size.
This was the only model to show a relationship with trail density and was the only model
to show a significant relationship between an individual factor and population size after
the critical value was corrected using the Bonferonni correction. This represents an
unusual outcome in the otherwise consistent results. It may represent a Type I error in the
results, incorrectly rejecting the null hypothesis. However, given the small p-value that
68

was observed here, it seems unlikely that this is true. Additionally, a significant negative
relationship was observed between quantity of buildings and population size as well as a
significant positive relationship between canopy cover and population size. This species,
C. horridus, utilizes larger spatial scales for mate-seeking and foraging behaviors, and
thus it would make sense that increased canopy and reduced quantity of buildings are
favored by timber rattlesnakes. The R-squared values again suggest that the factors at the
large spatial scale better explain the variation in population size.
Model 5: Non-Zero Abundance Model Without Pike County
This model, a repeat of Model 2 except that Pike County data was removed,
showed a significant positive relationship between distance to nearest building and
population size at the small and intermediate spatial scales. Additionally, the large spatial
scale showed a significant positive relationship between canopy cover and population
size as well as road density and population size as well as a significant negative
relationship between total buildings and population size. The findings from this model
corroborate observations from other models in that snake populations have an inverse
relationship with distance to nearest building as well as building density around sites.
Likewise, the canopy data reinforces the idea that this species needs forest habitat to
disperse into. The road data here represents an interesting result in that it suggests that
snake populations are higher when road density is higher. This is likely another type I
error, as no other model showed a significant relationship between this factor and
population size, nor is high road density congruent with the life history of timber
rattlesnakes (Andrews and Gibbons, 2005). Once again, the R-squared values were much

69

higher at the large spatial scale while AIC values were lowest suggesting that more of the
variation in population size can be explained by the predictors at this spatial scale.
Model 6: Presence-Absence Model Without Pike County
The last model was a mirror of Model 3 with Pike County removed. This model
did not show any significant relationships between predictors and population size at any
spatial scale, whether in one model or separate models for individual factors. Despite this
absence of statistically significant relationships, some trends were present in the data. The
roadway and trail data agreed with what would be expected for this species, with trails
and roads being in lower densities around occupied sites and distances to these factors
being higher around occupied sites. Building data for this model was in line with the
other models in that occupied sites had less buildings within the buffer zones and distance
to nearest building was farther for occupied sites, suggesting that building presence
influences C. horridus populations. Lastly, canopy cover was higher around occupied
sites at larger spatial scales while being lower at small spatial scales. This is in line with
the known life history of C. horridus where habitats needed for maintenance and
gestating represent small openings within largely forested regions and would be mostly
visible at smaller spatial scales while at large spatial scales the habitat needed for
dispersing, either for mating or feeding behavior, would dominate. Additionally, this
model repeats what was shown in Model 3: roadways and trails are denser at unoccupied
sites with more buildings within buffer zones, and lower overall canopy cover at
unoccupied sites.

70

Presence/Pseudo-Absence Comparisons
The random points were added to the map to explore whether the sites represented
truly random points where snakes were observed or if there was a bias associated with
locating the rattlesnake sites. Whereas the six models examined previously compare
designated rattlesnake sites to one another, the present comparison asks whether they
have a preference for a specific habitat type compared to random samples of habitat
within the region. The random background points differed significantly from the known
rattlesnake locations in terms of their factors at nearly every spatial scale except for trail
density at small and large spatial scales as well as distance to nearest trail. These results
suggest sampling bias associated with the rattlesnake sites which is in line with the
habitat requirements of this species, specifically at the small spatial scale where open
canopy is necessary for maintenance behaviors associated with basking. Individuals of
this species can be easily located in springtime after exiting a den site or in the fall just
before ingress for hibernation. Additionally, these results show us that C. horridus has
specific habitat requirements and these sites that were explored likely represent the
realized niche of the species. Due to this preference for habitat during various parts of the
year this species can be more readily located if the habitat requirements are understood.
Our results show that this is likely the case with our sites, at least for sites that were
newly discovered during the TRAP. The bias in our data likely contributes to the low Rsquared values in our models as well as the low degree of significance that was observed.
Conclusion
These results present an interesting look into the forces that affect rattlesnake
populations through various degrees of disturbance. The main conclusions are that,
71

among the factors examined, building density and canopy cover seem to be the main
forces affecting population size at the large spatial scale. This information is reflective of
the biology of the timber rattlesnake (Reinert, 1984a, 1984b) as well as the idea that
buildings create disturbance zones that affect wildlife populations (Theobald et al., 1997).
In nearly all models examined, buildings had a significant effect, although with a low
effect size, whether it was distance to the nearest building or total quantity of buildings
within the buffer zone. This information suggests that encroaching development may be
detrimental to timber rattlesnake populations at the large scale level and may affect
foraging habitat quality in some way, possibly by reducing the number of prey items,
either through habitat loss or through the increase of meso-predators that are commensal
with human settlements (Theobald et al., 1997). Additionally, anthropogenic impacts may
isolate populations and reduce genetic diversity (Clark et al., 2010) while also increasing
human-snake interactions, causing mortality (sensu Garber and Burger, 1995). The
reduced canopy cover caused by development at the large spatial scale also likely reduces
the quantity of prey items for individuals.
It’s strange that few significant effects were observed between roads and
population size in any model. Studies have shown that roadways have a major effect on
individual snakes with high rates of mortality (Shine et al., 2004; Andrews and Gibbons,
2005; Frazer, 2005; Row et al., 2007; Clark et al., 2010). However, this could be related
to one of the flaws represented in this work in that road area and road use were not
accounted for. There is at least some difference in the effect of a large highway relative to
that of a country dirt road. Additionally, some work has shown that hiking trails should
have a measurable effect on herpetofauna populations by increasing the interactions of
72

humans and wildlife. This can result in direct mortality or collection for the pet trade, a
problem which seems pervasive throughout all herpetofauna taxa (Garber and Burger,
1995; pers. obs.). As mentioned previously, timber rattlesnakes in particular are
susceptible to the hazards of roadways due to their habit of relying on cryptic coloration
(Andrews and Gibbons, 2005). However, the lack of significant results arising from these
two predictor categories likely stems from the initial selection of survey sites, as
illustrated by the comparison with pseudo-absence or background points. Specifically,
rattlesnakes seem to have a preference for specific habitat types and surveyors have likely
become attuned to this habitat specificity. Roadways and trails are commonly used to
scout for rattlesnake habitat and this could be affecting the results of the model, since
most sites will theoretically have trails or roads associated with them. Even though roads
and trails did not show up as significant factors, it’s assuring to see that measurements of
these features fall in line with what would be expected: roadways and trails are less dense
at occupied sites, there is higher canopy cover at occupied sites, there are fewer buildings
at occupied sites, and lastly buildings, trails, and roads were farther away from occupied.
One explanation of the results seen here is that roadways and trails may represent
a transient threat to individuals while buildings represent a more persistent threat. While
interactions with vehicles undoubtedly cause mortality to wildlife crossing them, there
are a number of factors that must combine to cause this mortality: snakes must encounter
a road and make a conscious decision to cross, a vehicle must be traveling down the same
roadway, the driver may or may not see the snake crossing the road, and finally there is a
chance that drivers may decide to safely stop and allow a snake to cross a roadway if they
observe one in the road. This logic follows for trailways where a snake must make the
73

decision to cross, a person must be coming down the trail at the same time, and the
person must be aware of the snake’s presence on the trail which may or may not occur
depending on how cryptic a snake is and the degree to which a person is searching.
Alternatively, buildings, and all things they include, represent a permanent human
presence in a given area. The building presence comes with a more regular human
presence, along with pets that may or may not interact with wildlife, increased vehicle
presence, increased impermeable surfaces, increased habitat loss, destruction, and
alteration. Based on my results, these factors seem to combine to be a larger threat to
snake populations, overall.
Finally, due to the higher R-squared values and low AIC values seen at the large
spatial scale versus the small and intermediate scales, it can be suggested that
anthropogenic habitat features better explain the variation in population size at the large
spatial scale. One of the drawbacks of this project was that it did not include natural
abiotic factors. Due to the low R-squared values shown at the small spatial scale it seems
likely that other factors are having the greatest influence on population size such as slope
and slope aspect, cover objects, elevation, or temperature. Additionally, the fourhundred-meter buffer relationships do not usually agree with many of the results of the
other two spatial scales. This buffer zone consistently had lower R-squared values that
were reinforced by higher AIC values than either of the other spatial scales. There were
several cases where the R-squared values for this spatial scale were adjusted below zero.
It is likely that this spatial scale is too close in size to the small spatial scale and not large
enough to capture intermediate differences where the effects of natural habitat factors
drop off and the effects of anthropogenic factors pick up.
74

Running the models without Pike County seems to have improved them. In
addition to high R-squared values in the last three models, AIC values also seem to be
lower suggesting that the predictor variables better explain the range of response
variables seen. Overall, these two indicators of how well a model fits followed a
consistent pattern among models. In both model series (1-3 and 4-6) the fifty-meter
buffer zone had higher AIC values and lower R-squared values while the five-thousandmeter buffer zone had lower AIC values and higher R-squared values, showing that the
variance in population size and occupancy is better explained by our variables at the large
spatial scales. Overall, all three models tell us different things. However, the R-squared
values are highest for Model 5 while the AIC values were lowest for Model 6. This
suggests that these two models explain more of the variation in population size and
occupancy. However, Model 4 may be more informative when a model that accounts for
zero-inflation is used.
Future Goals
There are several factors that should be considered in terms of future work with
this project. First, anyone undertaking a follow-up study should consider adding in
natural factors, such as slope, slope aspect, rock cover, elevation, etc., to see how their
interactions are impacted by anthropogenic factors. Likewise, these features may
contribute more to the models and may be more strongly predictive of the rattlesnake
abundance. Additionally, the project should be expanded to more of the state to bolster
the sample size and amplify any factors that are significant.
One of the major flaws in this study is that population estimates were low at
nearly every site that did not have long term monitoring, primarily due to the nature of
75

TRAP where the goal was to locate populations and not to assess their size. With better
populations estimates the models shown here would have better predictive ability and
would give better insight into the effect our factors are having on the population. The
other TRAMP efforts, most notably mark and recapture, can likely improve population
estimates and help refine our models.
Additionally, it may be worth adding other buffer zones to assess just where the
overlap between anthropogenic and natural factors lies. Both categories clearly influence
rattlesnake populations, though our model lacks the ability to assess just where one ends
and one picks up. It may be worth adding several buffers of differing size such as 750m,
1500m, and 2250m. These smaller changes in spatial scale could likely give a better
picture of what is happening at the intermediate spatial scale and what may be the driving
force behind population size at this level.
Lastly, it may be worth modifying how the road data is used in the model. One
possible change would be to use road area within a buffer zone to assess how roads relate
to population size at given spatial scales. This would require road layers to include width
of the roadway in addition to length. Additionally, road substrate and road use could be
included as random factors in a generalized linear model. Road substrate, whether
asphalt, dirt, or gravel, may affect the role that the roadways play. The amount of time
that a road is used on a given day would also affect the overall impact of a roadway. A
road that is traversed once or twice a day will have a strongly different impact than a road
that sees constant traffic throughout the day.

76

In conclusion, our project is a stepping stone into the study of how habitat affects
populations of the timber rattlesnake at the landscape level. Anthropogenic factors have a
larger impact at the large spatial scale with buildings being the main driving force.
Likewise, natural factors are likely the driving force behind population size at the small
spatial scale. There are many ways that our work can be improved upon to narrow down
how habitat features specifically affect population levels, but this project gives a glimpse
into the nature of how anthropogenic features are changing rattlesnake populations.

77

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84

APPENDICES

85

Appendix A: Raw Data of Models

Appendix I. Raw data for Model 1 at the 50m buffer zone.

86

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.000

2124.90

0.000

451.1

0

0.584

Christman 1

Carbon

0

279.10

0.000

197.70

0.000

222.6

0

0.990

Christman 10

Carbon

0

151.90

0.000

1062.20

0.000

146.8

0

1.000

Christman 11

Carbon

29

397.10

0.000

21.60

0.023

78.2

0

0.662

Christman 12

Carbon

10

408.70

0.000

58.00

0.000

195.0

0

1.000

Christman 1N

Carbon

2

165.70

0.000

569.10

0.000

614.9

0

1.000

Christman 2

Carbon

4

186.80

0.000

227.90

0.000

414.2

0

1.000

Christman 3

Carbon

0

854.40

0.000

88.20

0.000

158.5

0

0.931

Christman 4

Carbon

0

316.90

0.000

252.60

0.000

315.3

0

1.000

Christman 5

Carbon

0

1224.10

0.000

595.70

0.000

624.2

0

1.000

Christman 6

Carbon

1

1126.70

0.000

411.50

0.000

423.0

0

1.000

Christman 7

Carbon

0

436.60

0.000

302.80

0.000

458.6

0

1.000

Christman 8

Carbon

0

401.50

0.000

192.05

0.000

350.9

0

1.000

Christman 9

Carbon

0

588.30

0.000

393.40

0.000

489.8

0

1.000

Hell Creek

Carbon

73

145.00

0.000

3037.30

0.000

1582.9

0

1.000

Hickory Run 4

Carbon

11

1544.20

0.000

552.50

0.000

2021.8

0

1.000

Hickory Run 5

Carbon

16

1101.90

0.000

86.40

0.000

89.2

0

1.000

Lehighton 1N

Carbon

2

475.30

0.000

240.90

0.000

244.5

0

0.932

Nesquehoning 1

Carbon

0

297.40

0.000

2154.20

0.000

319.8

0

0.956

Tamaqua 1

Carbon

0

247.57

0.000

3289.00

0.000

978.9

0

1.000

Tamaqua 1N

Carbon

0

415.50

0.000

2830.20

0.000

600.6

0

1.000

87

Weatherly 1

Carbon

0

1437.60

0.000

854.90

0.000

884.3

0

1.000

Weatherly 1N-Ribello

Carbon

2

348.80

0.000

2379.90

0.000

1126.1

0

0.973

Weatherly 1N-Stan

Carbon

1

219.30

0.000

162.60

0.000

322.7

0

1.000

Weatherly 2

Carbon

0

398.30

0.000

229.10

0.000

387.5

0

1.000

Weatherly 3

Carbon

1

544.20

0.000

316.30

0.000

440.4

0

1.000

Weatherly 4

Carbon

1

29.90

0.009

2393.90

0.000

1101.3

0

0.980

Weatherly 5

Carbon

0

217.40

0.000

162.80

0.000

320.7

0

1.000

Weatherly 6

Carbon

1

732.90

0.000

3411.40

0.000

660.9

0

0.998

Weatherly 7

Carbon

2

1466.50

0.000

4823.60

0.000

2034.3

0

1.000

Avoca 7

Luzerne

6

265.90

0.000

4099.60

0.000

463.7

0

1.000

Dutch Mountain 6

Luzerne

0

320.70

0.000

6494.40

0.000

2013.9

0

1.000

Hickory Run 1-Koval

Luzerne

0

238.80

0.000

1199.50

0.000

606.1

0

1.000

Hickory Run 2- Koval

Luzerne

31

966.60

0.000

1260.40

0.000

1114.2

0

1.000

Hickory Run 3- Koval

Luzerne

2

583.00

0.000

944.50

0.000

525.8

0

0.912

Nanticoke 1N

Luzerne

4

1110.80

0.000

2009.10

0.000

1253.6

0

1.000

Pittston 1

Luzerne

0

363.80

0.000

4098.00

0.000

151.6

0

1.000

Pittston 2

Luzerne

0

258.00

0.000

3557.40

0.000

158.4

0

1.000

Pittston 3

Luzerne

0

632.70

0.000

5916.00

0.000

858.0

0

0.960

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.000

3289.90

0.000

1312.7

0

0.286

Red Rock 2

Luzerne

0

1116.90

0.000

194.80

0.000

1637.0

0

1.000

Red Rock 3

Luzerne

0

766.10

0.000

89.30

0.000

767.4

0

0.985

Sweet Valley 1

Luzerne

0

430.60

0.000

6257.30

0.000

2253.4

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.000

87.30

0.000

1945.0

0

1.000

Wilkes Barre East 1

Luzerne

0

811.20

0.000

5878.10

0.000

733.1

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.000

64.80

0.000

694.1

0

1.000

Mount Pocono 2N

Monroe

4

827.40

0.000

25.00

0.010

700.7

0

0.880

Pocono Pines 1N

Monroe

3

Stroudsburg 2N

Monroe

5

Lake Maskenozha 1N

Pike

3

Milford 1N

Pike

3

Narrowsburg 1N

Pike

21

907.56

0.000

3311.77

0.000

0.000

51.20

0.000

504.80

0.000

2424.60

0.000

377.60

0.000

377.60

0.000

0.000

3311.8

0
0

1.000

472.5

0

0.912

491.5

0

1.000

0

1.000

0.000

88

Narrowsburg 2

Pike

3

390.80

0.000

6085.00

0.000

269.9

0

0.925

Narrowsburg 2N

Pike

5

367.30

0.000

8573.00

0.000

1115.1

0

1.000

Narrowsburg 3

Pike

1

59.10

0.000

6611.90

0.000

1522.1

0

0.864

Pecks Pond 1N

Pike

2

286.10

0.000

3.40

0.028

195.0

0

0.715

Pond Eddy 1N

Pike

8

764.00

0.000

5170.00

0.000

703.8

0

0.961

Pond Eddy 2N

Pike

2

174.50

0.000

5259.00

0.000

179.7

0

0.898

Pond Eddy 3N

Pike

3

554.20

0.000

5595.00

0.000

369.5

0

0.898

Port Jervis North 1

Pike

2

507.00

0.000

6698.00

0.000

421.1

0

1.000

Promised Land 1

Pike

9

108.20

0.000

109.10

0.000

2184.0

0

1.000

Promised Land 2N

Pike

16

546.60

0.000

547.90

0.000

1350.9

0

0.513

Promised Land 3N

Pike

5

1275.80

0.000

691.70

0.000

1973.0

0

1.000

Rowland 1

Pike

4

122.60

0.000

257.40

0.000

95.2

0

1.000

Rowland 1N

Pike

5

959.07

0.000

959.07

0.000

876.2

0

0.815

Rowland 2N

Pike

3

1181.50

0.000

1600.20

0.000

745.2

0

0.838

Rowland 3N

Pike

6

928.30

0.000

1657.50

0.000

1367.7

0

0.916

Rowland 4N

Pike

6

1078.90

0.000

1759.40

0.000

1319.4

0

1.000

Shohola 1N

Pike

5

212.60

0.000

2718.50

0.000

51.5

0

0.945

Shohola 2

Pike

0

409.60

0.000

1788.40

0.000

389.0

0

1.000

Shohola 2N

Pike

4

32.60

0.005

3442.60

0.000

379.2

0

0.700

Shohola 3

Pike

0

157.60

0.000

6371.50

0.000

98.7

0

0.860

Shohola 4

Pike

3

1319.30

0.000

1319.30

0.000

1019.5

0

1.000

Shohola 4N

Pike

3

589.60

0.000

2076.00

0.000

1166.5

0

0.869

Shohola 5

Pike

3

1244.30

0.000

1246.50

0.000

1322.7

0

1.000

Shohola 3N

Pike

2

604.20

0.000

4604.30

0.000

623.9

0

0.883

Twelvemile Pond 1N

Pike

2

507.30

0.000

1232.70

0.000

505.9

0

0.621

Great Bend 1

Susquehanna

0

640.70

0.000

2560.10

0.000

800.1

0

1.000

89

Starrucca 1

Susquehanna

0

251.40

0.000

251.40

0.000

273.1

0

1.000

Susquehanna 1N

Susquehanna

2

510.90

0.000

867.80

0.000

482.5

0

0.999

White Mills 1

Wayne

3

252.20

0.000

4747.60

0.000

889.6

0

1.000

White Mills 1N

Wayne

3

106.70

0.000

4904.10

0.000

1117.4

0

0.417

White Mills 2

Wayne

3

573.20

0.000

6118.60

0.000

607.3

0

1.000

Dutch Mountain 1

Wyoming

3

534.50

0.000

12447.34

0.000

561.0

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.000

14033.38

0.000

1430.0

0

0.997

Dutch Mountain 2

Wyoming

0

1231.58

0.000

14548.48

0.000

1018.2

0

1.000

Dutch Mountain 2N

Wyoming

7

618.80

0.000

14517.34

0.000

557.8

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.000

12580.00

0.000

353.6

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.000

13554.38

0.000

1157.6

0

1.000

Dutch Mountain 4

Wyoming

3

444.90

0.000

7862.37

0.000

1932.7

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.000

8452.92

0.000

946.9

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.000

13997.25

0.000

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.000

12393.23

0.000

2026.7

0

0.878

Jenningsville 2N

Wyoming

3

1502.40

0.000

12400.73

0.000

1335.3

0

0.741

Meshoppen 1

Wyoming

0

414.20

0.000

8617.82

0.000

426.6

0

1.000

Meshoppen 1N

Wyoming

2

831.80

0.000

8763.22

0.000

414.5

0

1.000

Meshoppen 2N

Wyoming

6

202.60

0.000

10486.80

0.000

261.4

0

1.000

Noxen

Wyoming

0

2203.10

0.000

13030.57

0.000

2108.5

0

0.976

Noxen 1

Wyoming

4

1328.50

0.000

9656.14

0.000

1428.6

0

1.000

Noxen 10

Wyoming

6

1025.90

0.000

10649.31

0.000

911.2

0

1.000

Noxen 10N

Wyoming

4

1702.40

0.000

11205.63

0.000

1716.0

0

1.000

Noxen 1N

Wyoming

3

1273.90

0.000

12692.77

0.000

1318.2

0

1.000

Noxen 2

Wyoming

4

911.60

0.000

13087.59

0.000

558.0

0

1.000

Noxen 2N

Wyoming

3

1317.10

0.000

12992.57

0.000

1312.3

0

1.000

90

Noxen 3

Wyoming

0

1320.80

0.000

13011.71

0.000

1328.3

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.000

12391.78

0.000

1343.5

0

1.000

Noxen 4

Wyoming

2

711.20

0.000

9559.28

0.000

593.5

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.000

14165.07

0.000

1704.5

0

1.000

Noxen 5

Wyoming

0

2445.70

0.000

14364.49

0.000

1497.4

0

1.000

Noxen 5N

Wyoming

4

955.30

0.000

12570.92

0.000

925.9

0

1.000

Noxen 6N

Wyoming

2

934.80

0.000

10707.81

0.000

521.0

0

1.000

Noxen 7

Wyoming

0

1649.60

0.000

12814.95

0.000

1535.8

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.000

11145.25

0.000

1575.3

0

1.000

Noxen 8

Wyoming

8

1280.70

0.000

12783.07

0.000

1249.5

0

0.934

Noxen 8N

Wyoming

4

299.40

0.000

8074.57

0.000

1071.0

0

1.000

Noxen 9

Wyoming

0

1746.90

0.000

13753.02

0.000

1800.8

0

1.000

Noxen 9N

Wyoming

2

296.00

0.000

12346.09

0.000

358.8

0

1.000

Tunkannock 1N

Wyoming

2

244.80

0.000

3519.70

0.000

364.5

0

0.721

Appendix II. Raw data for Model 1 at the 400m buffer zone.

91

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 1

Carbon

0

279.10

0.0006

197.70

0.0047

222.55

2

0.819

Christman 10

Carbon

0

151.90

0.0019

1062.20

0.0000

146.76

10

0.975

Christman 11

Carbon

29

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

2

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0045

158.52

2

0.925

Christman 4

Carbon

0

316.90

0.0003

252.60

0.0028

315.33

2

0.929

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

0.994

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0023

458.56

0

0.951

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0035

350.89

2

0.896

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0006

489.78

0

0.929

Hell Creek

Carbon

73

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Nesquehoning 1

Carbon

0

297.40

0.0016

2154.20

0.0000

319.82

13

0.799

Tamaqua 1

Carbon

0

247.57

0.0003

3289.00

0.0000

978.90

0

0.930

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

0.741

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

0.996

Weatherly 1N-Ribello

Carbon

2

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

92

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0031

387.50

1

0.898

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 5

Carbon

0

217.40

0.0013

162.80

0.0053

320.73

6

0.868

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

6

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Dutch Mountain 6

Luzerne

0

320.70

0.0009

6494.40

0.0000

2013.90

0

0.997

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0000

606.10

0

0.889

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Pittston 1

Luzerne

0

363.80

0.0007

4098.00

0.0000

151.60

16

0.927

Pittston 2

Luzerne

0

258.00

0.0016

3557.40

0.0000

158.40

9

0.791

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.829

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.902

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0024

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0018

767.40

0

1.000

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0022

87.30

0.0016

1945.00

0

0.994

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

0.938

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0017

Lake Maskenozha 1N

Pike

3

0.0000

2424.60

0.0000

504.80

0.984
472.50

0

0.990

Milford 1N

Pike

3

377.60

0.0003

377.60

93

0

0.990

Narrowsburg 1N

Pike

21

0

1.000

Narrowsburg 2

Pike

3

390.80

0.0002

6085.00

0.0000

269.90

1

0.961

Narrowsburg 2N

Pike

5

367.30

0.0009

8573.00

0.0000

1115.10

0

0.971

Narrowsburg 3

Pike

1

59.10

0.0026

6611.90

0.0000

1522.10

0

0.825

Pecks Pond 1N

Pike

2

286.10

Pond Eddy 1N

Pike

8

764.00

0.0006

3.40

0.0042

195.00

8

0.940

0.0000

5170.00

0.0000

703.80

0

0.998

Pond Eddy 2N

Pike

2

174.50

0.0012

5259.00

0.0000

179.70

5

0.937

Pond Eddy 3N

Pike

3

554.20

0.0000

5595.00

0.0000

369.50

1

0.991

Port Jervis North 1

Pike

2

507.00

0.0000

6698.00

0.0000

421.10

0

1.000

Promised Land 1

Pike

9

108.20

0.0012

109.10

0.0013

2184.00

0

0.956

Promised Land 2N

Pike

16

546.60

0.0000

547.90

0.0000

1350.90

0

0.927

Promised Land 3N

Pike

5

1275.80

0.0000

691.70

0.0000

1973.00

0

0.999

0.0000

0.0003

491.50

0.0000

Rowland 1

Pike

4

122.60

0.0024

257.40

0.0008

95.20

6

0.937

Rowland 1N

Pike

5

959.07

0.0000

959.07

0.0000

876.20

0

0.978

Rowland 2N

Pike

3

1181.50

0.0000

1600.20

0.0000

745.20

0

0.976

Rowland 3N

Pike

6

928.30

0.0000

1657.50

0.0000

1367.70

0

0.997

Rowland 4N

Pike

6

1078.90

0.0000

1759.40

0.0000

1319.40

0

0.998

Shohola 1N

Pike

5

212.60

0.0019

2718.50

0.0000

51.50

12

0.928

Shohola 2

Pike

0

409.60

0.0000

1788.40

0.0000

389.00

1

0.995

Shohola 2N

Pike

4

32.60

0.0011

3442.60

0.0000

379.20

2

0.953

Shohola 3

Pike

0

157.60

0.0036

6371.50

0.0000

98.70

14

0.638

Shohola 4

Pike

3

1319.30

0.0000

1319.30

0.0000

1019.50

0

0.984

Shohola 4N

Pike

3

589.60

0.0000

2076.00

0.0000

1166.50

0

0.995

Shohola 5

Pike

3

1244.30

0.0000

1246.50

0.0000

1322.70

0

0.998

Shohola 3N

Pike

2

604.20

0.0000

4604.30

0.0000

623.90

0

0.981

94

Twelvemile Pond 1N

Pike

2

507.30

0.0000

1232.70

0.0000

505.90

0

0.938

Great Bend 1

Susquehanna

0

640.70

0.0000

2560.10

0.0000

800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0010

251.40

0.0010

273.10

3

0.900

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.735

White Mills 1

Wayne

3

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

3

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0014

12580.00

0.0000

353.60

1

0.981

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0004

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0010

13997.25

0.0000

0

0.995

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

0.989

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

6

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.992

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

95

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

4

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

0.996

Noxen 9N

Wyoming

2

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

2

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

Appendix III. Raw data for Model 1 at the 5000m buffer zone.

96

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 1

Carbon

0

279.10

0.0013

197.70

0.0014

222.50

512

0.882

Christman 10

Carbon

0

151.90

0.0022

1062.20

0.0002

146.76

2601

0.833

Christman 11

Carbon

29

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

10

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

2

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

4

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 3

Carbon

0

854.40

0.0010

88.20

0.0009

158.50

471

0.862

Christman 4

Carbon

0

316.90

0.0016

252.60

0.0008

315.33

1238

0.884

Christman 5

Carbon

0

1224.10

0.0009

595.70

0.0008

624.19

606

0.930

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Christman 7

Carbon

0

436.60

0.0016

302.80

0.0006

458.56

2298

0.928

Christman 8

Carbon

0

401.50

0.0016

192.05

0.0016

350.89

2683

0.933

Christman 9

Carbon

0

588.30

0.0016

393.40

0.0007

489.78

2738

0.929

Hell Creek

Carbon

73

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

11

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

16

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

2

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Nesquehoning 1

Carbon

0

297.40

0.0021

2154.20

0.0001

319.82

5193

0.818

Tamaqua 1

Carbon

0

247.57

0.0021

3289.00

0.0000

0.802

Tamaqua 1N

Carbon

0

415.50

0.0021

2830.20

0.0000

0.808

Weatherly 1

Carbon

0

1437.60

0.0009

854.90

0.0007

884.28

518

0.927

Weatherly 1N-Ribello

Carbon

2

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

97

Weatherly 2

Carbon

0

398.30

0.0016

229.10

0.0006

387.50

2682

0.933

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 5

Carbon

0

217.40

0.0020

162.80

0.0007

320.73

3917

0.908

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

2

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

6

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Dutch Mountain 6

Luzerne

0

320.70

0.0006

6494.40

0.0000

2013.90

121

0.963

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0004

606.10

1021

0.875

Hickory Run 2- Koval

Luzerne

31

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

2

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

4

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Pittston 1

Luzerne

0

363.80

0.0040

4098.00

0.0000

151.60

15706

0.584

Pittston 2

Luzerne

0

258.00

0.0030

3557.40

0.0001

158.40

9643

0.621

Pittston 3

Luzerne

0

632.70

0.0025

5916.00

0.0000

858.00

3735

0.704

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0014

3289.90

0.0001

1312.70

934

0.902

Red Rock 2

Luzerne

0

1116.90

0.0008

194.80

0.0005

0.920

Red Rock 3

Luzerne

0

766.10

0.0011

89.30

0.0004

0.905

Sweet Valley 1

Luzerne

0

430.60

0.0006

6257.30

0.0000

2253.40

118

0.964

Sweet Valley 2

Luzerne

0

88.50

0.0006

87.30

0.0004

1945.00

84

0.944

Wilkes Barre East 1

Luzerne

0

811.20

0.0030

5878.10

0.0000

733.10

9805

0.711

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

4

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

3

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

5

0.0018

51.20

0.0003

Lake Maskenozha 1N

Pike

3

0.0027

2424.60

0.0001

504.80

0.795
472.50

3967

0.874

98

Milford 1N

Pike

3

377.60

0.0023

377.60

0.0001

491.50

2105

0.879

Pecks Pond 1N

Pike

2

286.10

0.0021

3.40

0.0005

195.00

3395

0.870

Promised Land 1

Pike

9

108.20

0.0007

109.10

0.0006

2184.00

397

0.921

Promised Land 2N

Pike

16

546.60

0.0007

547.90

0.0007

1350.90

427

0.919

Promised Land 3N

Pike

5

1275.80

0.0010

691.70

0.0011

1973.00

561

0.886

Rowland 3N

Pike

6

928.30

0.0011

1657.50

0.0001

1367.70

683

0.903

Rowland 4N

Pike

6

1078.90

0.0011

1759.40

0.0001

1319.40

675

0.902

Shohola 4

Pike

3

1319.30

0.0018

1319.30

0.0001

1019.50

1314

0.879

Shohola 4N

Pike

3

589.60

0.0018

2076.00

0.0001

1166.50

1309

0.892

Shohola 5

Pike

3

1244.30

0.0018

1246.50

0.0001

1322.70

1378

0.878

Shohola 3N

Pike

2

604.20

0.0016

4604.30

0.0000

623.90

1217

0.917

Twelvemile Pond 1N

Pike

2

507.30

0.0018

1232.70

0.0002

505.90

4167

0.898

Great Bend 1

Susquehanna

0

640.70

0.0021

2560.10

0.0001

800.10

1850

0.807

Starrucca 1

Susquehanna

0

251.40

0.0014

251.40

0.0003

273.10

588

0.770

White Mills 1

Wayne

3

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

3

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

3

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

Dutch Mountain 1

Wyoming

3

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2

Wyoming

0

1231.58

0.0004

14548.48

0.0000

1018.17

151

0.976

Dutch Mountain 2N

Wyoming

7

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3

Wyoming

0

163.60

0.0003

12580.00

0.0000

353.60

94

0.978

Dutch Mountain 3N

Wyoming

3

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

3

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Dutch Mountain 5

Wyoming

0

385.50

0.0006

8452.92

0.0000

946.90

88

0.965

Jenningsville 1

Wyoming

0

259.10

0.0007

13997.25

0.0000

0.904

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

318

0.925

Jenningsville 2N

Wyoming

3

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1

Wyoming

0

414.20

0.0013

8617.82

0.0000

426.60

402

0.798

Meshoppen 1N

Wyoming

2

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

6

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

0.913

99

Noxen

Wyoming

0

2203.10

0.0007

13030.57

0.0000

2108.50

655

0.937

Noxen 1

Wyoming

4

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

Noxen 10

Wyoming

6

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

4

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

3

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

4

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

3

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

Noxen 3

Wyoming

0

1320.80

0.0005

13011.71

0.0000

1328.30

216

0.961

Noxen 3N

Wyoming

2

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

2

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5

Wyoming

0

2445.70

0.0004

14364.49

0.0000

1497.40

183

0.976

Noxen 5N

Wyoming

4

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

2

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7

Wyoming

0

1649.60

0.0008

12814.95

0.0000

1535.80

738

0.914

Noxen 7N

Wyoming

3

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

8

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

4

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9

Wyoming

0

1746.90

0.0007

13753.02

0.0000

1800.80

597

0.936

Noxen 9N

Wyoming

2

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

2

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

Appendix IV. Raw data for Model 2 at the 50m buffer zone.

100

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.584

Christman 11

Carbon

29

397.10

0.0000

21.60

0.0228

78.16

0

0.662

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0000

194.96

0

1.000

Christman 1N

Carbon

2

165.70

0.0000

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0000

227.90

0.0000

414.20

0

1.000

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Hell Creek

Carbon

73

145.00

0.0000

3037.30

0.0000

1582.90

0

1.000

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

1.000

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0000

89.18

0

1.000

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0000

244.48

0

0.932

Weatherly 1N-Ribello

Carbon

2

348.80

0.0000

2379.90

0.0000

1126.11

0

0.973

Weatherly 1N-Stan

Carbon

1

219.30

0.0000

162.60

0.0000

322.65

0

1.000

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0000

440.40

0

1.000

Weatherly 4

Carbon

1

29.90

0.0090

2393.90

0.0000

1101.32

0

0.980

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.998

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

1.000

Avoca 7

Luzerne

6

265.90

0.0000

4099.60

0.0000

463.70

0

1.000

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

1.000

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.912

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0000

694.10

0

1.000

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0097

700.70

0

0.880

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0000

0

1.000

Lake Maskenozha 1N

Pike

3

504.80

0.0000

2424.60

0.0000

472.50

0

0.912

Milford 1N

Pike

3

377.60

0.0000

377.60

0.0000

491.50

0

1.000

Narrowsburg 1N

Pike

21

0

1.000

Narrowsburg 2

Pike

3

390.80

0.0000

6085.00

0.0000

269.90

0

0.925

Narrowsburg 2N

Pike

5

367.30

0.0000

8573.00

0.0000

1115.10

0

1.000

0.0000

0.0000

101

Narrowsburg 3

Pike

1

59.10

0.0000

6611.90

0.0000

1522.10

0

0.864

Pecks Pond 1N

Pike

2

286.10

0.0000

3.40

0.0285

195.00

0

0.715

Pond Eddy 1N

Pike

8

764.00

0.0000

5170.00

0.0000

703.80

0

0.961

Pond Eddy 2N

Pike

2

174.50

0.0000

5259.00

0.0000

179.70

0

0.898

Pond Eddy 3N

Pike

3

554.20

0.0000

5595.00

0.0000

369.50

0

0.898

Port Jervis North 1

Pike

2

507.00

0.0000

6698.00

0.0000

421.10

0

1.000

Promised Land 1

Pike

9

108.20

0.0000

109.10

0.0000

2184.00

0

1.000

Promised Land 2N

Pike

16

546.60

0.0000

547.90

0.0000

1350.90

0

0.513

Promised Land 3N

Pike

5

1275.80

0.0000

691.70

0.0000

1973.00

0

1.000

Rowland 1

Pike

4

122.60

0.0000

257.40

0.0000

95.20

0

1.000

Rowland 1N

Pike

5

959.07

0.0000

959.07

0.0000

876.20

0

0.815

Rowland 2N

Pike

3

1181.50

0.0000

1600.20

0.0000

745.20

0

0.838

Rowland 3N

Pike

6

928.30

0.0000

1657.50

0.0000

1367.70

0

0.916

Rowland 4N

Pike

6

1078.90

0.0000

1759.40

0.0000

1319.40

0

1.000

Shohola 1N

Pike

5

212.60

0.0000

2718.50

0.0000

51.50

0

0.945

Shohola 2N

Pike

4

32.60

0.0051

3442.60

0.0000

379.20

0

0.700

Shohola 4

Pike

3

1319.30

0.0000

1319.30

0.0000

1019.50

0

1.000

Shohola 4N

Pike

3

589.60

0.0000

2076.00

0.0000

1166.50

0

0.869

Shohola 5

Pike

3

1244.30

0.0000

1246.50

0.0000

1322.70

0

1.000

Shohola 3N

Pike

2

604.20

0.0000

4604.30

0.0000

623.90

0

0.883

Twelvemile Pond 1N

Pike

2

507.30

0.0000

1232.70

0.0000

505.90

0

0.621

102

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.999

White Mills 1

Wayne

3

252.20

0.0000

4747.60

0.0000

889.60

0

1.000

White Mills 1N

Wayne

3

106.70

0.0000

4904.10

0.0000

1117.40

0

0.417

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

1.000

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.997

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

1.000

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.878

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.741

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

1.000

Meshoppen 2N

Wyoming

6

202.60

0.0000

10486.80

0.0000

261.40

0

1.000

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

1.000

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

1.000

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

1.000

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

1.000

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

1.000

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

1.000

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

1.000

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.934

Noxen 8N

Wyoming

4

299.40

0.0000

8074.57

0.0000

1071.00

0

1.000

Noxen 9N

Wyoming

2

296.00

0.0000

12346.09

0.0000

358.80

0

1.000

Tunkannock 1N

Wyoming

2

244.80

0.0000

3519.70

0.0000

364.50

0

0.721

103

Appendix V. Raw data for Model 2 at the 400m buffer zone.

104

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 11

Carbon

29

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

2

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Hell Creek

Carbon

73

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Weatherly 1N-Ribello

Carbon

2

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

6

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0017

0.984

Lake Maskenozha 1N

Pike

3

504.80

0.0000

2424.60

0.0000

472.50

0

0.990

Milford 1N

Pike

3

377.60

0.0003

377.60

0.0003

491.50

0

0.990

Narrowsburg 1N

Pike

21

0

1.000

Narrowsburg 2

Pike

3

390.80

0.0002

6085.00

0.0000

269.90

1

0.961

Narrowsburg 2N

Pike

5

367.30

0.0009

8573.00

0.0000

1115.10

0

0.971

0.0000

0.0000

105

Narrowsburg 3

Pike

1

59.10

0.0026

6611.90

0.0000

1522.10

0

0.825

Pecks Pond 1N

Pike

2

286.10

0.0006

3.40

0.0042

195.00

8

0.940

Pond Eddy 1N

Pike

8

764.00

0.0000

5170.00

0.0000

703.80

0

0.998

Pond Eddy 2N

Pike

2

174.50

0.0012

5259.00

0.0000

179.70

5

0.937

Pond Eddy 3N

Pike

3

554.20

0.0000

5595.00

0.0000

369.50

1

0.991

Port Jervis North 1

Pike

2

507.00

0.0000

6698.00

0.0000

421.10

0

1.000

Promised Land 1

Pike

9

108.20

0.0012

109.10

0.0013

2184.00

0

0.956

Promised Land 2N

Pike

16

546.60

0.0000

547.90

0.0000

1350.90

0

0.927

Promised Land 3N

Pike

5

1275.80

0.0000

691.70

0.0000

1973.00

0

0.999

Rowland 1

Pike

4

122.60

0.0024

257.40

0.0008

95.20

6

0.937

Rowland 1N

Pike

5

959.07

0.0000

959.07

0.0000

876.20

0

0.978

Rowland 2N

Pike

3

1181.50

0.0000

1600.20

0.0000

745.20

0

0.976

Rowland 3N

Pike

6

928.30

0.0000

1657.50

0.0000

1367.70

0

0.997

Rowland 4N

Pike

6

1078.90

0.0000

1759.40

0.0000

1319.40

0

0.998

Shohola 1N

Pike

5

212.60

0.0019

2718.50

0.0000

51.50

12

0.928

Shohola 2N

Pike

4

32.60

0.0011

3442.60

0.0000

379.20

2

0.953

Shohola 4

Pike

3

1319.30

0.0000

1319.30

0.0000

1019.50

0

0.984

Shohola 4N

Pike

3

589.60

0.0000

2076.00

0.0000

1166.50

0

0.995

Shohola 5

Pike

3

1244.30

0.0000

1246.50

0.0000

1322.70

0

0.998

Shohola 3N

Pike

2

604.20

0.0000

4604.30

0.0000

623.90

0

0.981

Twelvemile Pond 1N

Pike

2

507.30

0.0000

1232.70

0.0000

505.90

0

0.938

106

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.735

White Mills 1

Wayne

3

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

3

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

6

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

4

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9N

Wyoming

2

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

2

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

107

Appendix VI. Raw data for Model 2 at the 5000m buffer zone.

108

Site

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 11

Carbon

29

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

10

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

2

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

4

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Hell Creek

Carbon

73

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

11

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

16

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

2

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Weatherly 1N-Ribello

Carbon

2

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

2

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

6

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Hickory Run 2- Koval

Luzerne

31

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

2

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

4

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

4

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

3

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

5

0.0018

51.20

0.0003

0.795

109

Lake Maskenozha 1N

Pike

3

504.80

0.0027

2424.60

0.0001

472.50

3967

0.874

Milford 1N

Pike

3

377.60

0.0023

377.60

0.0001

491.50

2105

0.879

Pecks Pond 1N

Pike

2

286.10

0.0021

3.40

0.0005

195.00

3395

0.870

Promised Land 1

Pike

9

108.20

0.0007

109.10

0.0006

2184.00

397

0.921

Promised Land 2N

Pike

16

546.60

0.0007

547.90

0.0007

1350.90

427

0.919

Promised Land 3N

Pike

5

1275.80

0.0010

691.70

0.0011

1973.00

561

0.886

Rowland 3N

Pike

6

928.30

0.0011

1657.50

0.0001

1367.70

683

0.903

Rowland 4N

Pike

6

1078.90

0.0011

1759.40

0.0001

1319.40

675

0.902

Shohola 4

Pike

3

1319.30

0.0018

1319.30

0.0001

1019.50

1314

0.879

Shohola 4N

Pike

3

589.60

0.0018

2076.00

0.0001

1166.50

1309

0.892

Shohola 5

Pike

3

1244.30

0.0018

1246.50

0.0001

1322.70

1378

0.878

Shohola 3N

Pike

2

604.20

0.0016

4604.30

0.0000

623.90

1217

0.917

Twelvemile Pond 1N

Pike

2

507.30

0.0018

1232.70

0.0002

505.90

4167

0.898

White Mills 1

Wayne

3

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

3

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

3

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

Dutch Mountain 1

Wyoming

3

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2N

Wyoming

7

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3N

Wyoming

3

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

3

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

318

0.925

Jenningsville 2N

Wyoming

3

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1N

Wyoming

2

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

6

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

Noxen 1

Wyoming

4

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

0.913

110

Noxen 10

Wyoming

6

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

4

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

3

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

4

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

3

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

Noxen 3N

Wyoming

2

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

2

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5N

Wyoming

4

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

2

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7N

Wyoming

3

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

8

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

4

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9N

Wyoming

2

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

2

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

Appendix VII. Raw data for Model 3 at the 50m buffer zone where Number of Snakes (Population) has been changed to presence (1) absence(0) data.

111

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0000

2124.90

0.0000

451.14

0

0.584

Christman 1

Carbon

0

279.10

0.0000

197.70

0.0000

222.55

0

0.990

Christman 10

Carbon

0

151.90

0.0000

1062.20

0.0000

146.76

0

1.000

Christman 11

Carbon

1

397.10

0.0000

21.60

0.0228

78.16

0

0.662

Christman 12

Carbon

1

408.70

0.0000

58.00

0.0000

194.96

0

1.000

Christman 1N

Carbon

1

165.70

0.0000

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

1

186.80

0.0000

227.90

0.0000

414.20

0

1.000

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0000

158.52

0

0.931

Christman 4

Carbon

0

316.90

0.0000

252.60

0.0000

315.33

0

1.000

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

1.000

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0000

458.56

0

1.000

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0000

350.89

0

1.000

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0000

489.78

0

1.000

Hell Creek

Carbon

1

145.00

0.0000

3037.30

0.0000

1582.90

0

1.000

Hickory Run 4

Carbon

1

1544.20

0.0000

552.50

0.0000

2021.82

0

1.000

Hickory Run 5

Carbon

1

1101.90

0.0000

86.40

0.0000

89.18

0

1.000

Lehighton 1N

Carbon

1

475.30

0.0000

240.90

0.0000

244.48

0

0.932

Nesquehoning 1

Carbon

0

297.40

0.0000

2154.20

0.0000

319.82

0

0.956

Tamaqua 1

Carbon

0

247.57

0.0000

3289.00

0.0000

978.90

0

1.000

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

1.000

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

1.000

Weatherly 1N-Ribello

Carbon

1

348.80

0.0000

2379.90

0.0000

1126.11

0

0.973

112

Weatherly 1N-Stan

Carbon

1

219.30

0.0000

162.60

0.0000

322.65

0

1.000

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0000

387.50

0

1.000

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0000

440.40

0

1.000

Weatherly 4

Carbon

1

29.90

0.0090

2393.90

0.0000

1101.32

0

0.980

Weatherly 5

Carbon

0

217.40

0.0000

162.80

0.0000

320.73

0

1.000

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.998

Weatherly 7

Carbon

1

1466.50

0.0000

4823.60

0.0000

2034.26

0

1.000

Avoca 7

Luzerne

1

265.90

0.0000

4099.60

0.0000

463.70

0

1.000

Dutch Mountain 6

Luzerne

0

320.70

0.0000

6494.40

0.0000

2013.90

0

1.000

Hickory Run 1-Koval

Luzerne

0

238.80

0.0000

1199.50

0.0000

606.10

0

1.000

Hickory Run 2- Koval

Luzerne

1

966.60

0.0000

1260.40

0.0000

1114.20

0

1.000

Hickory Run 3- Koval

Luzerne

1

583.00

0.0000

944.50

0.0000

525.80

0

0.912

Nanticoke 1N

Luzerne

1

1110.80

0.0000

2009.10

0.0000

1253.60

0

1.000

Pittston 1

Luzerne

0

363.80

0.0000

4098.00

0.0000

151.60

0

1.000

Pittston 2

Luzerne

0

258.00

0.0000

3557.40

0.0000

158.40

0

1.000

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.960

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.286

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0000

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0000

767.40

0

0.985

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0000

87.30

0.0000

1945.00

0

1.000

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0000

694.10

0

1.000

Mount Pocono 2N

Monroe

1

827.40

0.0000

25.00

0.0097

700.70

0

0.880

Pocono Pines 1N

Monroe

1

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

1

0.0000

51.20

0.0000

0

1.000

Lake Maskenozha 1N

Pike

1

504.80

0.0000

2424.60

0.0000

472.50

0

0.912

Milford 1N

Pike

1

377.60

0.0000

377.60

0.0000

491.50

0

1.000

Narrowsburg 1N

Pike

1

0

1.000

Narrowsburg 2

Pike

1

390.80

0.0000

6085.00

0.0000

269.90

0

0.925

Narrowsburg 2N

Pike

1

367.30

0.0000

8573.00

0.0000

1115.10

0

1.000

0.0000

0.0000

113

Narrowsburg 3

Pike

1

59.10

0.0000

6611.90

0.0000

1522.10

0

0.864

Pecks Pond 1N

Pike

1

286.10

0.0000

3.40

0.0285

195.00

0

0.715

Pond Eddy 1N

Pike

1

764.00

0.0000

5170.00

0.0000

703.80

0

0.961

Pond Eddy 2N

Pike

1

174.50

0.0000

5259.00

0.0000

179.70

0

0.898

Pond Eddy 3N

Pike

1

554.20

0.0000

5595.00

0.0000

369.50

0

0.898

Port Jervis North 1

Pike

1

507.00

0.0000

6698.00

0.0000

421.10

0

1.000

Promised Land 1

Pike

1

108.20

0.0000

109.10

0.0000

2184.00

0

1.000

Promised Land 2N

Pike

1

546.60

0.0000

547.90

0.0000

1350.90

0

0.513

Promised Land 3N

Pike

1

1275.80

0.0000

691.70

0.0000

1973.00

0

1.000

Rowland 1

Pike

1

122.60

0.0000

257.40

0.0000

95.20

0

1.000

Rowland 1N

Pike

1

959.07

0.0000

959.07

0.0000

876.20

0

0.815

Rowland 2N

Pike

1

1181.50

0.0000

1600.20

0.0000

745.20

0

0.838

Rowland 3N

Pike

1

928.30

0.0000

1657.50

0.0000

1367.70

0

0.916

Rowland 4N

Pike

1

1078.90

0.0000

1759.40

0.0000

1319.40

0

1.000

Shohola 1N

Pike

1

212.60

0.0000

2718.50

0.0000

51.50

0

0.945

Shohola 2

Pike

0

409.60

0.0000

1788.40

0.0000

389.00

0

1.000

Shohola 2N

Pike

1

32.60

0.0051

3442.60

0.0000

379.20

0

0.700

Shohola 3

Pike

0

157.60

0.0000

6371.50

0.0000

98.70

0

0.860

Shohola 4

Pike

1

1319.30

0.0000

1319.30

0.0000

1019.50

0

1.000

Shohola 4N

Pike

1

589.60

0.0000

2076.00

0.0000

1166.50

0

0.869

Shohola 5

Pike

1

1244.30

0.0000

1246.50

0.0000

1322.70

0

1.000

Shohola 3N

Pike

1

604.20

0.0000

4604.30

0.0000

623.90

0

0.883

Twelvemile Pond 1N

Pike

1

507.30

0.0000

1232.70

0.0000

505.90

0

0.621

Great Bend 1

Susquehanna

0

640.70

0.0000

2560.10

0.0000

800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0000

251.40

0.0000

273.10

0

1.000

Susquehanna 1N

Susquehanna

1

510.90

0.0000

867.80

0.0000

482.50

0

0.999

114

White Mills 1

Wayne

1

252.20

0.0000

4747.60

0.0000

889.60

0

1.000

White Mills 1N

Wayne

1

106.70

0.0000

4904.10

0.0000

1117.40

0

0.417

White Mills 2

Wayne

1

573.20

0.0000

6118.60

0.0000

607.30

0

1.000

Dutch Mountain 1

Wyoming

1

534.50

0.0000

12447.34

0.0000

561.00

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.997

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

1

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0000

12580.00

0.0000

353.60

0

1.000

Dutch Mountain 3N

Wyoming

1

1119.80

0.0000

13554.38

0.0000

1157.60

0

1.000

Dutch Mountain 4

Wyoming

1

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0000

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0000

13997.25

0.0000

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.878

Jenningsville 2N

Wyoming

1

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.741

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

1.000

Meshoppen 1N

Wyoming

1

831.80

0.0000

8763.22

0.0000

414.50

0

1.000

Meshoppen 2N

Wyoming

1

202.60

0.0000

10486.80

0.0000

261.40

0

1.000

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.976

Noxen 1

Wyoming

1

1328.50

0.0000

9656.14

0.0000

1428.60

0

1.000

Noxen 10

Wyoming

1

1025.90

0.0000

10649.31

0.0000

911.20

0

1.000

Noxen 10N

Wyoming

1

1702.40

0.0000

11205.63

0.0000

1716.00

0

1.000

Noxen 1N

Wyoming

1

1273.90

0.0000

12692.77

0.0000

1318.20

0

1.000

Noxen 2

Wyoming

1

911.60

0.0000

13087.59

0.0000

558.00

0

1.000

Noxen 2N

Wyoming

1

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

1

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

115

Noxen 4

Wyoming

1

711.20

0.0000

9559.28

0.0000

593.50

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

1.000

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

1

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

1

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

1

1625.90

0.0000

11145.25

0.0000

1575.30

0

1.000

Noxen 8

Wyoming

1

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.934

Noxen 8N

Wyoming

1

299.40

0.0000

8074.57

0.0000

1071.00

0

1.000

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

1.000

Noxen 9N

Wyoming

1

296.00

0.0000

12346.09

0.0000

358.80

0

1.000

Tunkannock 1N

Wyoming

1

244.80

0.0000

3519.70

0.0000

364.50

0

0.721

Appendix VIII. Raw data for Model 3 at the 400m buffer zone where Number of Snakes (Population) has been changed to presence
(1) - absence(0) data.

116

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 1

Carbon

0

279.10

0.0006

197.70

0.0047

222.55

2

0.819

Christman 10

Carbon

0

151.90

0.0019

1062.20

0.0000

146.76

10

0.975

Christman 11

Carbon

1

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

1

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

1

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

1

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0045

158.52

2

0.925

Christman 4

Carbon

0

316.90

0.0003

252.60

0.0028

315.33

2

0.929

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

0.994

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0023

458.56

0

0.951

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0035

350.89

2

0.896

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0006

489.78

0

0.929

Hell Creek

Carbon

1

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

1

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

1

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

1

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Nesquehoning 1

Carbon

0

297.40

0.0016

2154.20

0.0000

319.82

13

0.799

Tamaqua 1

Carbon

0

247.57

0.0003

3289.00

0.0000

978.90

0

0.930

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

0.741

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

0.996

Weatherly 1N-Ribello

Carbon

1

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

117

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0031

387.50

1

0.898

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 5

Carbon

0

217.40

0.0013

162.80

0.0053

320.73

6

0.868

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

1

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

1

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Dutch Mountain 6

Luzerne

0

320.70

0.0009

6494.40

0.0000

2013.90

0

0.997

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0000

606.10

0

0.889

Hickory Run 2- Koval

Luzerne

1

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

1

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

1

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Pittston 1

Luzerne

0

363.80

0.0007

4098.00

0.0000

151.60

16

0.927

Pittston 2

Luzerne

0

258.00

0.0016

3557.40

0.0000

158.40

9

0.791

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.829

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.902

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0024

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0018

767.40

0

1.000

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0022

87.30

0.0016

1945.00

0

0.994

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

0.938

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

1

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

1

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

1

0.0000

51.20

0.0017

0.984

Lake Maskenozha 1N

Pike

1

504.80

0.0000

2424.60

0.0000

472.50

0

0.990

Milford 1N

Pike

1

377.60

0.0003

377.60

0.0003

491.50

0

0.990

Narrowsburg 1N

Pike

1

0

1.000

Narrowsburg 2

Pike

1

390.80

0.0002

6085.00

0.0000

269.90

1

0.961

Narrowsburg 2N

Pike

1

367.30

0.0009

8573.00

0.0000

1115.10

0

0.971

0.0000

0.0000

118

Narrowsburg 3

Pike

1

59.10

0.0026

6611.90

0.0000

1522.10

0

0.825

Pecks Pond 1N

Pike

1

286.10

0.0006

3.40

0.0042

195.00

8

0.940

Pond Eddy 1N

Pike

1

764.00

0.0000

5170.00

0.0000

703.80

0

0.998

Pond Eddy 2N

Pike

1

174.50

0.0012

5259.00

0.0000

179.70

5

0.937

Pond Eddy 3N

Pike

1

554.20

0.0000

5595.00

0.0000

369.50

1

0.991

Port Jervis North 1

Pike

1

507.00

0.0000

6698.00

0.0000

421.10

0

1.000

Promised Land 1

Pike

1

108.20

0.0012

109.10

0.0013

2184.00

0

0.956

Promised Land 2N

Pike

1

546.60

0.0000

547.90

0.0000

1350.90

0

0.927

Promised Land 3N

Pike

1

1275.80

0.0000

691.70

0.0000

1973.00

0

0.999

Rowland 1

Pike

1

122.60

0.0024

257.40

0.0008

95.20

6

0.937

Rowland 1N

Pike

1

959.07

0.0000

959.07

0.0000

876.20

0

0.978

Rowland 2N

Pike

1

1181.50

0.0000

1600.20

0.0000

745.20

0

0.976

Rowland 3N

Pike

1

928.30

0.0000

1657.50

0.0000

1367.70

0

0.997

Rowland 4N

Pike

1

1078.90

0.0000

1759.40

0.0000

1319.40

0

0.998

Shohola 1N

Pike

1

212.60

0.0019

2718.50

0.0000

51.50

12

0.928

Shohola 2

Pike

0

409.60

0.0000

1788.40

0.0000

389.00

1

0.995

Shohola 2N

Pike

1

32.60

0.0011

3442.60

0.0000

379.20

2

0.953

Shohola 3

Pike

0

157.60

0.0036

6371.50

0.0000

98.70

14

0.638

Shohola 4

Pike

1

1319.30

0.0000

1319.30

0.0000

1019.50

0

0.984

Shohola 4N

Pike

1

589.60

0.0000

2076.00

0.0000

1166.50

0

0.995

Shohola 5

Pike

1

1244.30

0.0000

1246.50

0.0000

1322.70

0

0.998

Shohola 3N

Pike

1

604.20

0.0000

4604.30

0.0000

623.90

0

0.981

Twelvemile Pond 1N

Pike

1

507.30

0.0000

1232.70

0.0000

505.90

0

0.938

Great Bend 1

Susquehanna

0

640.70

0.0000

2560.10

0.0000

800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0010

251.40

0.0010

273.10

3

0.900

Susquehanna 1N

Susquehanna

1

510.90

0.0000

867.80

0.0000

482.50

0

0.735

119

White Mills 1

Wayne

1

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

1

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

White Mills 2

Wayne

1

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

Dutch Mountain 1

Wyoming

1

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

1

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0014

12580.00

0.0000

353.60

1

0.981

Dutch Mountain 3N

Wyoming

1

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

1

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0004

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0010

13997.25

0.0000

0

0.995

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

1

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

0.989

Meshoppen 1N

Wyoming

1

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

1

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.992

Noxen 1

Wyoming

1

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

1

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

1

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

1

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

Noxen 2

Wyoming

1

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

1

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

1

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

120

Noxen 4

Wyoming

1

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

1

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

1

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

1

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

1

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

1

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

0.996

Noxen 9N

Wyoming

1

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

1

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

Appendix IX. Raw data for Model 3 at the 5000m buffer zone where Number of Snakes (Population) has been changed to presence (1)
- absence(0) data.

121

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 1

Carbon

0

279.10

0.0013

197.70

0.0014

222.50

512

0.882

Christman 10

Carbon

0

151.90

0.0022

1062.20

0.0002

146.76

2601

0.833

Christman 11

Carbon

1

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

1

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

1

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

1

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 3

Carbon

0

854.40

0.0010

88.20

0.0009

158.50

471

0.862

Christman 4

Carbon

0

316.90

0.0016

252.60

0.0008

315.33

1238

0.884

Christman 5

Carbon

0

1224.10

0.0009

595.70

0.0008

624.19

606

0.930

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Christman 7

Carbon

0

436.60

0.0016

302.80

0.0006

458.56

2298

0.928

Christman 8

Carbon

0

401.50

0.0016

192.05

0.0016

350.89

2683

0.933

Christman 9

Carbon

0

588.30

0.0016

393.40

0.0007

489.78

2738

0.929

Hell Creek

Carbon

1

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

1

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

1

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

1

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Nesquehoning 1

Carbon

0

297.40

0.0021

2154.20

0.0001

319.82

5193

0.818

Tamaqua 1

Carbon

0

247.57

0.0021

3289.00

0.0000

0.802

Tamaqua 1N

Carbon

0

415.50

0.0021

2830.20

0.0000

0.808

Weatherly 1

Carbon

0

1437.60

0.0009

854.90

0.0007

884.28

518

0.927

Weatherly 1N-Ribello

Carbon

1

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

122

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

Weatherly 2

Carbon

0

398.30

0.0016

229.10

0.0006

387.50

2682

0.933

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 5

Carbon

0

217.40

0.0020

162.80

0.0007

320.73

3917

0.908

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

1

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

1

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Dutch Mountain 6

Luzerne

0

320.70

0.0006

6494.40

0.0000

2013.90

121

0.963

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0004

606.10

1021

0.875

Hickory Run 2- Koval

Luzerne

1

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

1

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

1

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Pittston 1

Luzerne

0

363.80

0.0040

4098.00

0.0000

151.60

15706

0.584

Pittston 2

Luzerne

0

258.00

0.0030

3557.40

0.0001

158.40

9643

0.621

Pittston 3

Luzerne

0

632.70

0.0025

5916.00

0.0000

858.00

3735

0.704

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0014

3289.90

0.0001

1312.70

934

0.902

Red Rock 2

Luzerne

0

1116.90

0.0008

194.80

0.0005

0.920

Red Rock 3

Luzerne

0

766.10

0.0011

89.30

0.0004

0.905

Sweet Valley 1

Luzerne

0

430.60

0.0006

6257.30

0.0000

2253.40

118

0.964

Sweet Valley 2

Luzerne

0

88.50

0.0006

87.30

0.0004

1945.00

84

0.944

Wilkes Barre East 1

Luzerne

0

811.20

0.0030

5878.10

0.0000

733.10

9805

0.711

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

1

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

1

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

1

0.0018

51.20

0.0003

0.795

123

Lake Maskenozha 1N

Pike

1

504.80

0.0027

2424.60

0.0001

472.50

3967

0.874

Milford 1N

Pike

1

377.60

0.0023

377.60

0.0001

491.50

2105

0.879

Pecks Pond 1N

Pike

1

286.10

0.0021

3.40

0.0005

195.00

3395

0.870

Promised Land 1

Pike

1

108.20

0.0007

109.10

0.0006

2184.00

397

0.921

Promised Land 2N

Pike

1

546.60

0.0007

547.90

0.0007

1350.90

427

0.919

Promised Land 3N

Pike

1

1275.80

0.0010

691.70

0.0011

1973.00

561

0.886

Rowland 3N

Pike

1

928.30

0.0011

1657.50

0.0001

1367.70

683

0.903

Rowland 4N

Pike

1

1078.90

0.0011

1759.40

0.0001

1319.40

675

0.902

Shohola 4

Pike

1

1319.30

0.0018

1319.30

0.0001

1019.50

1314

0.879

Shohola 4N

Pike

1

589.60

0.0018

2076.00

0.0001

1166.50

1309

0.892

Shohola 5

Pike

1

1244.30

0.0018

1246.50

0.0001

1322.70

1378

0.878

Shohola 3N

Pike

1

604.20

0.0016

4604.30

0.0000

623.90

1217

0.917

Twelvemile Pond 1N

Pike

1

507.30

0.0018

1232.70

0.0002

505.90

4167

0.898

Great Bend 1

Susquehanna

0

640.70

0.0021

2560.10

0.0001

800.10

1850

0.807

Starrucca 1

Susquehanna

0

251.40

0.0014

251.40

0.0003

273.10

588

0.770

White Mills 1

Wayne

1

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

1

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

1

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

Dutch Mountain 1

Wyoming

1

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2

Wyoming

0

1231.58

0.0004

14548.48

0.0000

1018.17

151

0.976

Dutch Mountain 2N

Wyoming

1

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3

Wyoming

0

163.60

0.0003

12580.00

0.0000

353.60

94

0.978

Dutch Mountain 3N

Wyoming

1

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

1

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Dutch Mountain 5

Wyoming

0

385.50

0.0006

8452.92

0.0000

946.90

88

0.965

124

Jenningsville 1

Wyoming

0

259.10

0.0007

13997.25

0.0000

0.904

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

Jenningsville 2N

Wyoming

1

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1

Wyoming

0

414.20

0.0013

8617.82

0.0000

426.60

402

0.798

Meshoppen 1N

Wyoming

1

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

1

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

Noxen

Wyoming

0

2203.10

0.0007

13030.57

0.0000

2108.50

655

0.937

Noxen 1

Wyoming

1

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

Noxen 10

Wyoming

1

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

1

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

1

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

1

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

1

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

318

0.925
0.913

Noxen 3

Wyoming

0

1320.80

0.0005

13011.71

0.0000

1328.30

216

0.961

Noxen 3N

Wyoming

1

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

1

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5

Wyoming

0

2445.70

0.0004

14364.49

0.0000

1497.40

183

0.976

Noxen 5N

Wyoming

1

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

1

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7

Wyoming

0

1649.60

0.0008

12814.95

0.0000

1535.80

738

0.914

Noxen 7N

Wyoming

1

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

1

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

1

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9

Wyoming

0

1746.90

0.0007

13753.02

0.0000

1800.80

597

0.936

Noxen 9N

Wyoming

1

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

1

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

125

Appendix X. Raw data for Model 4 at the 50m buffer zone.
Site

126

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.584

Christman 1

Carbon

0

279.10

0.0000

197.70

0.0000

222.55

0

0.990

Christman 10

Carbon

0

151.90

0.0000

1062.20

0.0000

146.76

0

1.000

Christman 11

Carbon

29

397.10

0.0000

21.60

0.0228

78.16

0

0.662

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0000

194.96

0

1.000

Christman 1N

Carbon

2

165.70

0.0000

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0000

227.90

0.0000

414.20

0

1.000

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0000

158.52

0

0.931

Christman 4

Carbon

0

316.90

0.0000

252.60

0.0000

315.33

0

1.000

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

1.000

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0000

458.56

0

1.000

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0000

350.89

0

1.000

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0000

489.78

0

1.000

Hell Creek

Carbon

73

145.00

0.0000

3037.30

0.0000

1582.90

0

1.000

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

1.000

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0000

89.18

0

1.000

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0000

244.48

0

0.932

Nesquehoning 1

Carbon

0

297.40

0.0000

2154.20

0.0000

319.82

0

0.956

Tamaqua 1

Carbon

0

247.57

0.0000

3289.00

0.0000

978.90

0

1.000

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

1.000

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

1.000

Weatherly 1N-Ribello

Carbon

2

348.80

0.0000

2379.90

0.0000

1126.11

0

0.973

Weatherly 1N-Stan

Carbon

1

219.30

0.0000

162.60

0.0000

322.65

0

1.000

127

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0000

387.50

0

1.000

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0000

440.40

0

1.000

Weatherly 4

Carbon

1

29.90

0.0090

2393.90

0.0000

1101.32

0

0.980

Weatherly 5

Carbon

0

217.40

0.0000

162.80

0.0000

320.73

0

1.000

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.998

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

1.000

Avoca 7

Luzerne

6

265.90

0.0000

4099.60

0.0000

463.70

0

1.000

Dutch Mountain 6

Luzerne

0

320.70

0.0000

6494.40

0.0000

2013.90

0

1.000

Hickory Run 1-Koval

Luzerne

0

238.80

0.0000

1199.50

0.0000

606.10

0

1.000

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

1.000

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.912

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

1.000

Pittston 1

Luzerne

0

363.80

0.0000

4098.00

0.0000

151.60

0

1.000

Pittston 2

Luzerne

0

258.00

0.0000

3557.40

0.0000

158.40

0

1.000

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.960

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.286

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0000

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0000

767.40

0

0.985

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0000

87.30

0.0000

1945.00

0

1.000

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0000

694.10

0

1.000

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0097

700.70

0

0.880

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0000

Great Bend 1

Susquehanna

0

0.0000

2560.10

0.0000

640.70

800.10

0

1.000

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0000

251.40

0.0000

273.10

0

1.000

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.999

White Mills 1

Wayne

3

252.20

0.0000

4747.60

0.0000

889.60

0

1.000

White Mills 1N

Wayne

3

106.70

0.0000

4904.10

0.0000

1117.40

0

0.417

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

1.000

128

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.997

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0000

12580.00

0.0000

353.60

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

1.000

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0000

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0000

13997.25

0.0000

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.878

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.741

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

1.000

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

1.000

Meshoppen 2N

Wyoming

6

202.60

0.0000

10486.80

0.0000

261.40

0

1.000

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.976

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

1.000

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

1.000

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

1.000

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

1.000

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

1.000

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

129

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

1.000

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

1.000

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.934

Noxen 8N

Wyoming

4

299.40

0.0000

8074.57

0.0000

1071.00

0

1.000

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

1.000

Noxen 9N

Wyoming

2

296.00

0.0000

12346.09

0.0000

358.80

0

1.000

Tunkannock 1N

Wyoming

2

244.80

0.0000

3519.70

0.0000

364.50

0

0.721

Appendix XI. Raw data for Model 4 at the 400m buffer zone.
Site

130

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 1

Carbon

0

279.10

0.0006

197.70

0.0047

222.55

2

0.819

Christman 10

Carbon

0

151.90

0.0019

1062.20

0.0000

146.76

10

0.975

Christman 11

Carbon

29

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

2

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0045

158.52

2

0.925

Christman 4

Carbon

0

316.90

0.0003

252.60

0.0028

315.33

2

0.929

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

0.994

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0023

458.56

0

0.951

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0035

350.89

2

0.896

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0006

489.78

0

0.929

Hell Creek

Carbon

73

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Nesquehoning 1

Carbon

0

297.40

0.0016

2154.20

0.0000

319.82

13

0.799

Tamaqua 1

Carbon

0

247.57

0.0003

3289.00

0.0000

978.90

0

0.930

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

0.741

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

0.996

Weatherly 1N-Ribello

Carbon

2

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

131

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0031

387.50

1

0.898

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 5

Carbon

0

217.40

0.0013

162.80

0.0053

320.73

6

0.868

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

6

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Dutch Mountain 6

Luzerne

0

320.70

0.0009

6494.40

0.0000

2013.90

0

0.997

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0000

606.10

0

0.889

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Pittston 1

Luzerne

0

363.80

0.0007

4098.00

0.0000

151.60

16

0.927

Pittston 2

Luzerne

0

258.00

0.0016

3557.40

0.0000

158.40

9

0.791

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.829

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.902

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0024

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0018

767.40

0

1.000

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0022

87.30

0.0016

1945.00

0

0.994

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

0.938

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0017

Great Bend 1

Susquehanna

0

0.0000

2560.10

0.0000

640.70

0.984
800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0010

251.40

0.0010

273.10

3

0.900

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.735

White Mills 1

Wayne

3

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

3

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

132

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0014

12580.00

0.0000

353.60

1

0.981

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0004

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0010

13997.25

0.0000

0

0.995

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

0.989

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

6

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.992

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

133

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

4

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

0.996

Noxen 9N

Wyoming

2

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

2

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

Appendix XII. Raw data for Model 4 at the 5000m buffer zone.
Site

134

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 1

Carbon

0

279.10

0.0013

197.70

0.0014

222.50

512

0.882

Christman 10

Carbon

0

151.90

0.0022

1062.20

0.0002

146.76

2601

0.833

Christman 11

Carbon

29

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

10

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

2

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

4

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 3

Carbon

0

854.40

0.0010

88.20

0.0009

158.50

471

0.862

Christman 4

Carbon

0

316.90

0.0016

252.60

0.0008

315.33

1238

0.884

Christman 5

Carbon

0

1224.10

0.0009

595.70

0.0008

624.19

606

0.930

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Christman 7

Carbon

0

436.60

0.0016

302.80

0.0006

458.56

2298

0.928

Christman 8

Carbon

0

401.50

0.0016

192.05

0.0016

350.89

2683

0.933

Christman 9

Carbon

0

588.30

0.0016

393.40

0.0007

489.78

2738

0.929

Hell Creek

Carbon

73

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

11

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

16

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

2

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Nesquehoning 1

Carbon

0

297.40

0.0021

2154.20

0.0001

319.82

5193

0.818

Tamaqua 1

Carbon

0

247.57

0.0021

3289.00

0.0000

0.802

Tamaqua 1N

Carbon

0

415.50

0.0021

2830.20

0.0000

0.808

Weatherly 1

Carbon

0

1437.60

0.0009

854.90

0.0007

884.28

518

0.927

Weatherly 1N-Ribello

Carbon

2

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

135

Weatherly 2

Carbon

0

398.30

0.0016

229.10

0.0006

387.50

2682

0.933

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 5

Carbon

0

217.40

0.0020

162.80

0.0007

320.73

3917

0.908

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

2

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

6

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Dutch Mountain 6

Luzerne

0

320.70

0.0006

6494.40

0.0000

2013.90

121

0.963

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0004

606.10

1021

0.875

Hickory Run 2- Koval

Luzerne

31

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

2

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

4

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Pittston 1

Luzerne

0

363.80

0.0040

4098.00

0.0000

151.60

15706

0.584

Pittston 2

Luzerne

0

258.00

0.0030

3557.40

0.0001

158.40

9643

0.621

Pittston 3

Luzerne

0

632.70

0.0025

5916.00

0.0000

858.00

3735

0.704

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0014

3289.90

0.0001

1312.70

934

0.902

Red Rock 2

Luzerne

0

1116.90

0.0008

194.80

0.0005

0.920

Red Rock 3

Luzerne

0

766.10

0.0011

89.30

0.0004

0.905

Sweet Valley 1

Luzerne

0

430.60

0.0006

6257.30

0.0000

2253.40

118

0.964

Sweet Valley 2

Luzerne

0

88.50

0.0006

87.30

0.0004

1945.00

84

0.944

Wilkes Barre East 1

Luzerne

0

811.20

0.0030

5878.10

0.0000

733.10

9805

0.711

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

4

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

3

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

5

0.0018

51.20

0.0003

Great Bend 1

Susquehanna

0

0.0021

2560.10

0.0001

640.70

0.795
800.10

1850

0.807

136

Starrucca 1

Susquehanna

0

251.40

0.0014

251.40

0.0003

273.10

588

0.770

White Mills 1

Wayne

3

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

3

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

3

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

Dutch Mountain 1

Wyoming

3

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2

Wyoming

0

1231.58

0.0004

14548.48

0.0000

1018.17

151

0.976

Dutch Mountain 2N

Wyoming

7

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3

Wyoming

0

163.60

0.0003

12580.00

0.0000

353.60

94

0.978

Dutch Mountain 3N

Wyoming

3

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

3

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Dutch Mountain 5

Wyoming

0

385.50

0.0006

8452.92

0.0000

946.90

88

0.965

Jenningsville 1

Wyoming

0

259.10

0.0007

13997.25

0.0000

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

Jenningsville 2N

Wyoming

3

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1

Wyoming

0

414.20

0.0013

8617.82

0.0000

426.60

402

0.798

Meshoppen 1N

Wyoming

2

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

6

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

Noxen

Wyoming

0

2203.10

0.0007

13030.57

0.0000

2108.50

655

0.937

Noxen 1

Wyoming

4

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

Noxen 10

Wyoming

6

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

4

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

3

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

4

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

3

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

Noxen 3

Wyoming

0

1320.80

0.0005

13011.71

0.0000

1328.30

216

0.961

0.904
318

0.925
0.913

137

Noxen 3N

Wyoming

2

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

2

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5

Wyoming

0

2445.70

0.0004

14364.49

0.0000

1497.40

183

0.976

Noxen 5N

Wyoming

4

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

2

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7

Wyoming

0

1649.60

0.0008

12814.95

0.0000

1535.80

738

0.914

Noxen 7N

Wyoming

3

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

8

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

4

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9

Wyoming

0

1746.90

0.0007

13753.02

0.0000

1800.80

597

0.936

Noxen 9N

Wyoming

2

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

2

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

Appendix XIII. Raw data for Model 5 at the 50m buffer zone.
Site

138

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.584

Christman 11

Carbon

29

397.10

0.0000

21.60

0.0228

78.16

0

0.662

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0000

194.96

0

1.000

Christman 1N

Carbon

2

165.70

0.0000

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0000

227.90

0.0000

414.20

0

1.000

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Hell Creek

Carbon

73

145.00

0.0000

3037.30

0.0000

1582.90

0

1.000

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

1.000

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0000

89.18

0

1.000

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0000

244.48

0

0.932

Weatherly 1N-Ribello

Carbon

2

348.80

0.0000

2379.90

0.0000

1126.11

0

0.973

Weatherly 1N-Stan

Carbon

1

219.30

0.0000

162.60

0.0000

322.65

0

1.000

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0000

440.40

0

1.000

Weatherly 4

Carbon

1

29.90

0.0090

2393.90

0.0000

1101.32

0

0.980

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.998

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

1.000

Avoca 7

Luzerne

6

265.90

0.0000

4099.60

0.0000

463.70

0

1.000

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

1.000

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.912

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0000

694.10

0

1.000

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0097

700.70

0

0.880

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0000

0

1.000

139

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.999

White Mills 1

Wayne

3

252.20

0.0000

4747.60

0.0000

889.60

0

1.000

White Mills 1N

Wayne

3

106.70

0.0000

4904.10

0.0000

1117.40

0

0.417

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

1.000

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.997

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

1.000

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.878

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.741

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

1.000

Meshoppen 2N

Wyoming

6

202.60

0.0000

10486.80

0.0000

261.40

0

1.000

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

1.000

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

1.000

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

1.000

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

1.000

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

1.000

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

1.000

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

1.000

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.934

Noxen 8N

Wyoming

4

299.40

0.0000

8074.57

0.0000

1071.00

0

1.000

Noxen 9N

Wyoming

2

296.00

0.0000

12346.09

0.0000

358.80

0

1.000

Tunkannock 1N

Wyoming

2

244.80

0.0000

3519.70

0.0000

364.50

0

0.721

140

Appendix XIV. Raw data for Model 5 at the 400m buffer zone.
Site

141

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 11

Carbon

29

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

10

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

2

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

4

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Hell Creek

Carbon

73

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

11

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

16

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

2

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Weatherly 1N-Ribello

Carbon

2

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

2

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

6

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Hickory Run 2- Koval

Luzerne

31

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

2

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

4

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

4

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

3

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

5

0.0000

51.20

0.0017

0.984

142

Susquehanna 1N

Susquehanna

2

510.90

0.0000

867.80

0.0000

482.50

0

0.735

White Mills 1

Wayne

3

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

3

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

White Mills 2

Wayne

3

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

Dutch Mountain 1

Wyoming

3

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2N

Wyoming

7

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3N

Wyoming

3

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

3

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

3

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1N

Wyoming

2

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

6

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen 1

Wyoming

4

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

6

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

4

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

3

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

Noxen 2

Wyoming

4

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

3

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3N

Wyoming

2

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

2

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

Noxen 5N

Wyoming

4

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

2

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7N

Wyoming

3

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

8

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

4

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9N

Wyoming

2

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

2

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

143

Appendix XV. Raw data for Model 5 at the 5000m buffer zone.
Site

144

County

Num. of Snakes

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

12

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 11

Carbon

29

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

10

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

2

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

4

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Hell Creek

Carbon

73

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

11

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

16

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

2

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Weatherly 1N-Ribello

Carbon

2

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

2

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

6

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Hickory Run 2- Koval

Luzerne

31

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

2

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

4

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

4

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

3

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

5

0.0018

51.20

0.0003

0.795

145

White Mills 1

Wayne

3

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

3

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

3

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

Dutch Mountain 1

Wyoming

3

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2N

Wyoming

7

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3N

Wyoming

3

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

3

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

318

0.925

Jenningsville 2N

Wyoming

3

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1N

Wyoming

2

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

6

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

Noxen 1

Wyoming

4

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

0.913

Noxen 10

Wyoming

6

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

4

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

3

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

4

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

3

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

Noxen 3N

Wyoming

2

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

2

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5N

Wyoming

4

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

2

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7N

Wyoming

3

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

8

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

4

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9N

Wyoming

2

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

2

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

146

Appendix XVI. Raw data for Model 6 at the 50m buffer zone where Number of Snakes (Population) has been changed to presence (1)
- absence(0) data.

147

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0000

2124.90

0.0000

451.14

0

0.584

Christman 1

Carbon

0

279.10

0.0000

197.70

0.0000

222.55

0

0.990

Christman 10

Carbon

0

151.90

0.0000

1062.20

0.0000

146.76

0

1.000

Christman 11

Carbon

1

397.10

0.0000

21.60

0.0228

78.16

0

0.662

Christman 12

Carbon

1

408.70

0.0000

58.00

0.0000

194.96

0

1.000

Christman 1N

Carbon

1

165.70

0.0000

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

1

186.80

0.0000

227.90

0.0000

414.20

0

1.000

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0000

158.52

0

0.931

Christman 4

Carbon

0

316.90

0.0000

252.60

0.0000

315.33

0

1.000

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

1.000

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0000

458.56

0

1.000

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0000

350.89

0

1.000

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0000

489.78

0

1.000

Hell Creek

Carbon

1

145.00

0.0000

3037.30

0.0000

1582.90

0

1.000

Hickory Run 4

Carbon

1

1544.20

0.0000

552.50

0.0000

2021.82

0

1.000

Hickory Run 5

Carbon

1

1101.90

0.0000

86.40

0.0000

89.18

0

1.000

Lehighton 1N

Carbon

1

475.30

0.0000

240.90

0.0000

244.48

0

0.932

Nesquehoning 1

Carbon

0

297.40

0.0000

2154.20

0.0000

319.82

0

0.956

Tamaqua 1

Carbon

0

247.57

0.0000

3289.00

0.0000

978.90

0

1.000

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

1.000

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

1.000

Weatherly 1N-Ribello

Carbon

1

348.80

0.0000

2379.90

0.0000

1126.11

0

0.973

148

Weatherly 1N-Stan

Carbon

1

219.30

0.0000

162.60

0.0000

322.65

0

1.000

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0000

387.50

0

1.000

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0000

440.40

0

1.000

Weatherly 4

Carbon

1

29.90

0.0090

2393.90

0.0000

1101.32

0

0.980

Weatherly 5

Carbon

0

217.40

0.0000

162.80

0.0000

320.73

0

1.000

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.998

Weatherly 7

Carbon

1

1466.50

0.0000

4823.60

0.0000

2034.26

0

1.000

Avoca 7

Luzerne

1

265.90

0.0000

4099.60

0.0000

463.70

0

1.000

Dutch Mountain 6

Luzerne

0

320.70

0.0000

6494.40

0.0000

2013.90

0

1.000

Hickory Run 1-Koval

Luzerne

0

238.80

0.0000

1199.50

0.0000

606.10

0

1.000

Hickory Run 2- Koval

Luzerne

1

966.60

0.0000

1260.40

0.0000

1114.20

0

1.000

Hickory Run 3- Koval

Luzerne

1

583.00

0.0000

944.50

0.0000

525.80

0

0.912

Nanticoke 1N

Luzerne

1

1110.80

0.0000

2009.10

0.0000

1253.60

0

1.000

Pittston 1

Luzerne

0

363.80

0.0000

4098.00

0.0000

151.60

0

1.000

Pittston 2

Luzerne

0

258.00

0.0000

3557.40

0.0000

158.40

0

1.000

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.960

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.286

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0000

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0000

767.40

0

0.985

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0000

87.30

0.0000

1945.00

0

1.000

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

1.000

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0000

694.10

0

1.000

Mount Pocono 2N

Monroe

1

827.40

0.0000

25.00

0.0097

700.70

0

0.880

Pocono Pines 1N

Monroe

1

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

1

0.0000

51.20

0.0000

0

1.000

Great Bend 1

Susquehanna

0

640.70

0.0000

2560.10

0.0000

800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0000

251.40

0.0000

273.10

0

1.000

Susquehanna 1N

Susquehanna

1

510.90

0.0000

867.80

0.0000

482.50

0

0.999

White Mills 1

Wayne

1

252.20

0.0000

4747.60

0.0000

889.60

0

1.000

White Mills 1N

Wayne

1

106.70

0.0000

4904.10

0.0000

1117.40

0

0.417

149

White Mills 2

Wayne

1

573.20

0.0000

6118.60

0.0000

607.30

0

1.000

Dutch Mountain 1

Wyoming

1

534.50

0.0000

12447.34

0.0000

561.00

0

1.000

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.997

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

1

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0000

12580.00

0.0000

353.60

0

1.000

Dutch Mountain 3N

Wyoming

1

1119.80

0.0000

13554.38

0.0000

1157.60

0

1.000

Dutch Mountain 4

Wyoming

1

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0000

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0000

13997.25

0.0000

0

1.000

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.878

Jenningsville 2N

Wyoming

1

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.741

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

1.000

Meshoppen 1N

Wyoming

1

831.80

0.0000

8763.22

0.0000

414.50

0

1.000

Meshoppen 2N

Wyoming

1

202.60

0.0000

10486.80

0.0000

261.40

0

1.000

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.976

Noxen 1

Wyoming

1

1328.50

0.0000

9656.14

0.0000

1428.60

0

1.000

Noxen 10

Wyoming

1

1025.90

0.0000

10649.31

0.0000

911.20

0

1.000

Noxen 10N

Wyoming

1

1702.40

0.0000

11205.63

0.0000

1716.00

0

1.000

Noxen 1N

Wyoming

1

1273.90

0.0000

12692.77

0.0000

1318.20

0

1.000

Noxen 2

Wyoming

1

911.60

0.0000

13087.59

0.0000

558.00

0

1.000

Noxen 2N

Wyoming

1

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

1

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

1

711.20

0.0000

9559.28

0.0000

593.50

0

1.000

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

1.000

150

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

1

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

1

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

1

1625.90

0.0000

11145.25

0.0000

1575.30

0

1.000

Noxen 8

Wyoming

1

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.934

Noxen 8N

Wyoming

1

299.40

0.0000

8074.57

0.0000

1071.00

0

1.000

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

1.000

Noxen 9N

Wyoming

1

296.00

0.0000

12346.09

0.0000

358.80

0

1.000

Tunkannock 1N

Wyoming

1

244.80

0.0000

3519.70

0.0000

364.50

0

0.721

Appendix XVII. Raw data for Model 6 at the 400m buffer zone where Number of Snakes (Population) has been changed to presence
(1) – absence (0) data.

151

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0000

2124.90

0.0000

451.14

0

0.929

Christman 1

Carbon

0

279.10

0.0006

197.70

0.0047

222.55

2

0.819

Christman 10

Carbon

0

151.90

0.0019

1062.20

0.0000

146.76

10

0.975

Christman 11

Carbon

1

397.10

0.0001

21.60

0.0048

78.16

3

0.902

Christman 12

Carbon

1

408.70

0.0000

58.00

0.0047

194.96

2

0.915

Christman 1N

Carbon

1

165.70

0.0028

569.10

0.0000

614.94

0

1.000

Christman 2

Carbon

1

186.80

0.0015

227.90

0.0011

414.20

0

0.932

Christman 3

Carbon

0

854.40

0.0000

88.20

0.0045

158.52

2

0.925

Christman 4

Carbon

0

316.90

0.0003

252.60

0.0028

315.33

2

0.929

Christman 5

Carbon

0

1224.10

0.0000

595.70

0.0000

624.19

0

0.994

Christman 6

Carbon

1

1126.70

0.0000

411.50

0.0000

423.00

0

1.000

Christman 7

Carbon

0

436.60

0.0000

302.80

0.0023

458.56

0

0.951

Christman 8

Carbon

0

401.50

0.0000

192.05

0.0035

350.89

2

0.896

Christman 9

Carbon

0

588.30

0.0000

393.40

0.0006

489.78

0

0.929

Hell Creek

Carbon

1

145.00

0.0006

3037.30

0.0000

1582.90

0

0.991

Hickory Run 4

Carbon

1

1544.20

0.0000

552.50

0.0000

2021.82

0

0.951

Hickory Run 5

Carbon

1

1101.90

0.0000

86.40

0.0052

89.18

2

0.908

Lehighton 1N

Carbon

1

475.30

0.0000

240.90

0.0039

244.48

1

0.932

Nesquehoning 1

Carbon

0

297.40

0.0016

2154.20

0.0000

319.82

13

0.799

Tamaqua 1

Carbon

0

247.57

0.0003

3289.00

0.0000

978.90

0

0.930

Tamaqua 1N

Carbon

0

415.50

0.0000

2830.20

0.0000

600.60

0

0.741

Weatherly 1

Carbon

0

1437.60

0.0000

854.90

0.0000

884.28

0

0.996

Weatherly 1N-Ribello

Carbon

1

348.80

0.0006

2379.90

0.0000

1126.11

0

0.997

152

Weatherly 1N-Stan

Carbon

1

219.30

0.0013

162.60

0.0053

322.65

6

0.869

Weatherly 2

Carbon

0

398.30

0.0000

229.10

0.0031

387.50

1

0.898

Weatherly 3

Carbon

1

544.20

0.0000

316.30

0.0019

440.40

0

0.926

Weatherly 4

Carbon

1

29.90

0.0018

2393.90

0.0000

1101.32

0

0.988

Weatherly 5

Carbon

0

217.40

0.0013

162.80

0.0053

320.73

6

0.868

Weatherly 6

Carbon

1

732.90

0.0000

3411.40

0.0000

660.86

0

0.999

Weatherly 7

Carbon

1

1466.50

0.0000

4823.60

0.0000

2034.26

0

0.999

Avoca 7

Luzerne

1

265.90

0.0014

4099.60

0.0000

463.70

0

0.883

Dutch Mountain 6

Luzerne

0

320.70

0.0009

6494.40

0.0000

2013.90

0

0.997

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0000

606.10

0

0.889

Hickory Run 2- Koval

Luzerne

1

966.60

0.0000

1260.40

0.0000

1114.20

0

0.796

Hickory Run 3- Koval

Luzerne

1

583.00

0.0000

944.50

0.0000

525.80

0

0.677

Nanticoke 1N

Luzerne

1

1110.80

0.0000

2009.10

0.0000

1253.60

0

0.888

Pittston 1

Luzerne

0

363.80

0.0007

4098.00

0.0000

151.60

16

0.927

Pittston 2

Luzerne

0

258.00

0.0016

3557.40

0.0000

158.40

9

0.791

Pittston 3

Luzerne

0

632.70

0.0000

5916.00

0.0000

858.00

0

0.829

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0000

3289.90

0.0000

1312.70

0

0.902

Red Rock 2

Luzerne

0

1116.90

0.0000

194.80

0.0024

1637.00

0

1.000

Red Rock 3

Luzerne

0

766.10

0.0000

89.30

0.0018

767.40

0

1.000

Sweet Valley 1

Luzerne

0

430.60

0.0000

6257.30

0.0000

2253.40

0

1.000

Sweet Valley 2

Luzerne

0

88.50

0.0022

87.30

0.0016

1945.00

0

0.994

Wilkes Barre East 1

Luzerne

0

811.20

0.0000

5878.10

0.0000

733.10

0

0.938

Mount Pocono 1N

Monroe

1

620.80

0.0000

64.80

0.0053

694.10

0

0.998

Mount Pocono 2N

Monroe

1

827.40

0.0000

25.00

0.0035

700.70

0

0.995

Pocono Pines 1N

Monroe

1

907.56

0.0000

3311.77

0.0000

3311.77

0

Stroudsburg 2N

Monroe

1

0.0000

51.20

0.0017

0.984

Great Bend 1

Susquehanna

0

640.70

0.0000

2560.10

0.0000

800.10

0

1.000

Starrucca 1

Susquehanna

0

251.40

0.0010

251.40

0.0010

273.10

3

0.900

Susquehanna 1N

Susquehanna

1

510.90

0.0000

867.80

0.0000

482.50

0

0.735

White Mills 1

Wayne

1

252.20

0.0027

4747.60

0.0000

889.60

0

0.923

White Mills 1N

Wayne

1

106.70

0.0031

4904.10

0.0000

1117.40

0

0.772

153

White Mills 2

Wayne

1

573.20

0.0000

6118.60

0.0000

607.30

0

0.993

Dutch Mountain 1

Wyoming

1

534.50

0.0000

12447.34

0.0000

561.00

0

0.964

Dutch Mountain 1N

Wyoming

1

1508.54

0.0000

14033.38

0.0000

1430.01

0

0.976

Dutch Mountain 2

Wyoming

0

1231.58

0.0000

14548.48

0.0000

1018.17

0

1.000

Dutch Mountain 2N

Wyoming

1

618.80

0.0000

14517.34

0.0000

557.80

0

1.000

Dutch Mountain 3

Wyoming

0

163.60

0.0014

12580.00

0.0000

353.60

1

0.981

Dutch Mountain 3N

Wyoming

1

1119.80

0.0000

13554.38

0.0000

1157.60

0

0.992

Dutch Mountain 4

Wyoming

1

444.90

0.0000

7862.37

0.0000

1932.70

0

1.000

Dutch Mountain 5

Wyoming

0

385.50

0.0004

8452.92

0.0000

946.90

0

1.000

Jenningsville 1

Wyoming

0

259.10

0.0010

13997.25

0.0000

0

0.995

Jenningsville 1N

Wyoming

1

2061.80

0.0000

12393.23

0.0000

2026.70

0

0.983

Jenningsville 2N

Wyoming

1

1502.40

0.0000

12400.73

0.0000

1335.30

0

0.987

Meshoppen 1

Wyoming

0

414.20

0.0000

8617.82

0.0000

426.60

0

0.989

Meshoppen 1N

Wyoming

1

831.80

0.0000

8763.22

0.0000

414.50

0

0.968

Meshoppen 2N

Wyoming

1

202.60

0.0027

10486.80

0.0000

261.40

1

0.988

Noxen

Wyoming

0

2203.10

0.0000

13030.57

0.0000

2108.50

0

0.992

Noxen 1

Wyoming

1

1328.50

0.0000

9656.14

0.0000

1428.60

0

0.990

Noxen 10

Wyoming

1

1025.90

0.0000

10649.31

0.0000

911.20

0

0.998

Noxen 10N

Wyoming

1

1702.40

0.0000

11205.63

0.0000

1716.00

0

0.999

Noxen 1N

Wyoming

1

1273.90

0.0000

12692.77

0.0000

1318.20

0

0.988

Noxen 2

Wyoming

1

911.60

0.0000

13087.59

0.0000

558.00

0

0.998

Noxen 2N

Wyoming

1

1317.10

0.0000

12992.57

0.0000

1312.30

0

1.000

Noxen 3

Wyoming

0

1320.80

0.0000

13011.71

0.0000

1328.30

0

1.000

Noxen 3N

Wyoming

1

1335.40

0.0000

12391.78

0.0000

1343.50

0

1.000

Noxen 4

Wyoming

1

711.20

0.0000

9559.28

0.0000

593.50

0

0.996

Noxen 4N

Wyoming

1

1882.00

0.0000

14165.07

0.0000

1704.50

0

0.998

154

Noxen 5

Wyoming

0

2445.70

0.0000

14364.49

0.0000

1497.40

0

1.000

Noxen 5N

Wyoming

1

955.30

0.0000

12570.92

0.0000

925.90

0

1.000

Noxen 6N

Wyoming

1

934.80

0.0000

10707.81

0.0000

521.00

0

1.000

Noxen 7

Wyoming

0

1649.60

0.0000

12814.95

0.0000

1535.80

0

1.000

Noxen 7N

Wyoming

1

1625.90

0.0000

11145.25

0.0000

1575.30

0

0.984

Noxen 8

Wyoming

1

1280.70

0.0000

12783.07

0.0000

1249.50

0

0.911

Noxen 8N

Wyoming

1

299.40

0.0011

8074.57

0.0000

1071.00

0

0.901

Noxen 9

Wyoming

0

1746.90

0.0000

13753.02

0.0000

1800.80

0

0.996

Noxen 9N

Wyoming

1

296.00

0.0002

12346.09

0.0000

358.80

1

0.907

Tunkannock 1N

Wyoming

1

244.80

0.0011

3519.70

0.0000

364.50

1

0.878

Appendix XVIII. Raw data for Model 6 at the 5000m buffer zone where Number of Snakes (Population) has been changed to presence
(1) - absence

155

Site

County

Population

Nearest Road

Road Density

Nearest Trail

Trail Density

Nearest Building

Buildings Within

Canopy Percent

Blakeslee 1N

Carbon

1

523.70

0.0026

2124.90

0.0005

451.14

4034

0.872

Christman 1

Carbon

0

279.10

0.0013

197.70

0.0014

222.50

512

0.882

Christman 10

Carbon

0

151.90

0.0022

1062.20

0.0002

146.76

2601

0.833

Christman 11

Carbon

1

397.10

0.0018

21.60

0.0007

78.16

3167

0.921

Christman 12

Carbon

1

408.70

0.0011

58.00

0.0008

194.96

581

0.890

Christman 1N

Carbon

1

165.70

0.0009

569.10

0.0009

614.90

787

0.893

Christman 2

Carbon

1

186.80

0.0013

227.90

0.0006

414.20

726

0.887

Christman 3

Carbon

0

854.40

0.0010

88.20

0.0009

158.50

471

0.862

Christman 4

Carbon

0

316.90

0.0016

252.60

0.0008

315.33

1238

0.884

Christman 5

Carbon

0

1224.10

0.0009

595.70

0.0008

624.19

606

0.930

Christman 6

Carbon

1

1126.70

0.0016

411.50

0.0007

423.00

2195

0.918

Christman 7

Carbon

0

436.60

0.0016

302.80

0.0006

458.56

2298

0.928

Christman 8

Carbon

0

401.50

0.0016

192.05

0.0016

350.89

2683

0.933

Christman 9

Carbon

0

588.30

0.0016

393.40

0.0007

489.78

2738

0.929

Hell Creek

Carbon

1

145.00

0.0036

3037.30

0.0001

1582.90

5239

0.850

Hickory Run 4

Carbon

1

1544.20

0.0007

552.50

0.0003

2021.80

554

0.901

Hickory Run 5

Carbon

1

1101.90

0.0013

86.40

0.0013

89.10

424

0.884

Lehighton 1N

Carbon

1

475.30

0.0032

240.90

0.0008

244.48

7373

0.741

Nesquehoning 1

Carbon

0

297.40

0.0021

2154.20

0.0001

319.82

5193

0.818

Tamaqua 1

Carbon

0

247.57

0.0021

3289.00

0.0000

0.802

Tamaqua 1N

Carbon

0

415.50

0.0021

2830.20

0.0000

0.808

Weatherly 1

Carbon

0

1437.60

0.0009

854.90

0.0007

884.28

518

0.927

Weatherly 1N-Ribello

Carbon

1

348.80

0.0016

2379.90

0.0005

1126.11

2764

0.922

156

Weatherly 1N-Stan

Carbon

1

219.30

0.0020

162.60

0.0007

322.65

3921

0.908

Weatherly 2

Carbon

0

398.30

0.0016

229.10

0.0006

387.50

2682

0.933

Weatherly 3

Carbon

1

544.20

0.0016

316.30

0.0007

440.40

2723

0.930

Weatherly 4

Carbon

1

29.90

0.0017

2393.90

0.0005

1101.32

2734

0.909

Weatherly 5

Carbon

0

217.40

0.0020

162.80

0.0007

320.73

3917

0.908

Weatherly 6

Carbon

1

732.90

0.0015

3411.40

0.0002

660.86

1585

0.893

Weatherly 7

Carbon

1

1466.50

0.0014

4823.60

0.0000

2034.26

1701

0.853

Avoca 7

Luzerne

1

265.90

0.0006

4099.60

0.0001

463.70

483

0.905

Dutch Mountain 6

Luzerne

0

320.70

0.0006

6494.40

0.0000

2013.90

121

0.963

Hickory Run 1-Koval

Luzerne

0

238.80

0.0013

1199.50

0.0004

606.10

1021

0.875

Hickory Run 2- Koval

Luzerne

1

966.60

0.0008

1260.40

0.0002

1114.20

812

0.909

Hickory Run 3- Koval

Luzerne

1

583.00

0.0008

944.50

0.0002

525.80

574

0.908

Nanticoke 1N

Luzerne

1

1110.80

0.0023

2009.10

0.0001

1253.60

5986

0.726

Pittston 1

Luzerne

0

363.80

0.0040

4098.00

0.0000

151.60

15706

0.584

Pittston 2

Luzerne

0

258.00

0.0030

3557.40

0.0001

158.40

9643

0.621

Pittston 3

Luzerne

0

632.70

0.0025

5916.00

0.0000

858.00

3735

0.704

Pleasant View Summit 1- Koval

Luzerne

0

1247.00

0.0014

3289.90

0.0001

1312.70

934

0.902

Red Rock 2

Luzerne

0

1116.90

0.0008

194.80

0.0005

0.920

Red Rock 3

Luzerne

0

766.10

0.0011

89.30

0.0004

0.905

Sweet Valley 1

Luzerne

0

430.60

0.0006

6257.30

0.0000

2253.40

118

0.964

Sweet Valley 2

Luzerne

0

88.50

0.0006

87.30

0.0004

1945.00

84

0.944

Wilkes Barre East 1

Luzerne

0

811.20

0.0030

5878.10

0.0000

733.10

9805

0.711

Mount Pocono 1N

Monroe

1

620.80

0.0034

64.80

0.0001

694.10

7057

0.820

Mount Pocono 2N

Monroe

1

827.40

0.0035

25.00

0.0001

700.70

7591

0.818

Pocono Pines 1N

Monroe

1

907.56

0.0027

3311.77

0.0000

3311.77

4727

Stroudsburg 2N

Monroe

1

0.0018

51.20

0.0003

0.795

Great Bend 1

Susquehanna

0

640.70

0.0021

2560.10

0.0001

800.10

1850

0.807

Starrucca 1

Susquehanna

0

251.40

0.0014

251.40

0.0003

273.10

588

0.770

White Mills 1

Wayne

1

252.20

0.0016

4747.60

0.0000

889.60

1654

0.798

White Mills 1N

Wayne

1

106.70

0.0016

4904.10

0.0000

1117.40

1554

0.814

White Mills 2

Wayne

1

573.20

0.0015

6118.60

0.0000

607.30

1469

0.849

157

Dutch Mountain 1

Wyoming

1

534.50

0.0006

12447.34

0.0000

561.00

271

0.934

Dutch Mountain 1N

Wyoming

1

1508.54

0.0004

14033.38

0.0000

1430.01

142

0.968

Dutch Mountain 2

Wyoming

0

1231.58

0.0004

14548.48

0.0000

1018.17

151

0.976

Dutch Mountain 2N

Wyoming

1

618.80

0.0004

14517.34

0.0000

557.80

156

0.973

Dutch Mountain 3

Wyoming

0

163.60

0.0003

12580.00

0.0000

353.60

94

0.978

Dutch Mountain 3N

Wyoming

1

1119.80

0.0005

13554.38

0.0000

1157.60

218

0.956

Dutch Mountain 4

Wyoming

1

444.90

0.0005

7862.37

0.0000

1932.70

42

0.964

Dutch Mountain 5

Wyoming

0

385.50

0.0006

8452.92

0.0000

946.90

88

0.965

318

Jenningsville 1

Wyoming

0

259.10

0.0007

13997.25

0.0000

Jenningsville 1N

Wyoming

1

2061.80

0.0007

12393.23

0.0000

2026.70

0.904

Jenningsville 2N

Wyoming

1

1502.40

0.0006

12400.73

0.0000

1335.30

Meshoppen 1

Wyoming

0

414.20

0.0013

8617.82

0.0000

426.60

402

0.798

Meshoppen 1N

Wyoming

1

831.80

0.0013

8763.22

0.0000

414.50

455

0.778

Meshoppen 2N

Wyoming

1

202.60

0.0009

10486.80

0.0000

261.40

334

0.870

Noxen

Wyoming

0

2203.10

0.0007

13030.57

0.0000

2108.50

655

0.937

Noxen 1

Wyoming

1

1328.50

0.0007

9656.14

0.0000

1428.60

247

0.925

Noxen 10

Wyoming

1

1025.90

0.0008

10649.31

0.0000

911.20

268

0.958

Noxen 10N

Wyoming

1

1702.40

0.0008

11205.63

0.0000

1716.00

344

0.961

Noxen 1N

Wyoming

1

1273.90

0.0008

12692.77

0.0000

1318.20

439

0.955

Noxen 2

Wyoming

1

911.60

0.0005

13087.59

0.0000

558.00

243

0.949

Noxen 2N

Wyoming

1

1317.10

0.0008

12992.57

0.0000

1312.30

624

0.929

0.925
0.913

158

Noxen 3

Wyoming

0

1320.80

0.0005

13011.71

0.0000

1328.30

216

0.961

Noxen 3N

Wyoming

1

1335.40

0.0005

12391.78

0.0000

1343.50

208

0.968

Noxen 4

Wyoming

1

711.20

0.0008

9559.28

0.0000

593.50

477

0.914

Noxen 4N

Wyoming

1

1882.00

0.0004

14165.07

0.0000

1704.50

154

0.977

Noxen 5

Wyoming

0

2445.70

0.0004

14364.49

0.0000

1497.40

183

0.976

Noxen 5N

Wyoming

1

955.30

0.0012

12570.92

0.0000

925.90

912

0.881

Noxen 6N

Wyoming

1

934.80

0.0005

10707.81

0.0000

521.00

224

0.947

Noxen 7

Wyoming

0

1649.60

0.0008

12814.95

0.0000

1535.80

738

0.914

Noxen 7N

Wyoming

1

1625.90

0.0008

11145.25

0.0000

1575.30

363

0.959

Noxen 8

Wyoming

1

1280.70

0.0010

12783.07

0.0000

1249.50

865

0.897

Noxen 8N

Wyoming

1

299.40

0.0010

8074.57

0.0000

1071.00

427

0.894

Noxen 9

Wyoming

0

1746.90

0.0007

13753.02

0.0000

1800.80

597

0.936

Noxen 9N

Wyoming

1

296.00

0.0014

12346.09

0.0000

358.80

1152

0.832

Tunkannock 1N

Wyoming

1

244.80

0.0024

3519.70

0.0001

364.50

2669

0.701

Appendix B: Descriptive Statistics
Appendix XIX. Descriptive statistics of factors at the 50m buffer zone for Model 1.
Min.

Max.

Mean

Count

29.9

2445.7

720.7

116

Road Density (m/m )

0.000

0.0090

0.0001

118

Nearest Trail (m)

3.40

14548.48

5043.22

117

Trail Density (m/m )

0.0000

0.0284

0.0005

118

Nearest Building (m)

51.50

3311.77

883.32

115

Total Buildings

0

0

0

118

Canopy Cover

0.286

1

0.947

117

Nearest Road (m)
2

2

Appendix XX. Descriptive statistics of factors at the 400m buffer zone for Model 1.
Min.

Max.

Mean

Count

29.90

2445.70

720.76

116

Road Density (m/m )

0.0000

0.0036

0.0004

118

Nearest Trail (m)

3.40

14548.48

5043.22

117

Trail Density (m/m )

0.0000

0.0053

0.0006

118

Nearest Building (m)

51.50

3311.77

883.32

115

Total Buildings

0

16

1.14

115

Canopy Cover

0.638

1.000

0.947

117

Nearest Road (m)
2

2

159

Appendix XXI. Descriptive statistics of factors at the 5000m buffer zone for Model 1.
Min.

Max.

Mean

Count

29.9

2445.7

764.4

101

Road Density (m/m )

0.0003

0.0040

0.0013

102

Nearest Trail (m)

3.40

14548.48

5177.06

102

Trail Density (m/m2)

0.0000

0.0015

0.0002

102

Nearest Building (m)

78.10

3311.77

936.45

96

Total Buildings

42

15706

1871.03

95

Canopy Cover

0.584

0.977

0.885

101

Nearest Road (m)
2

Appendix XXII. Descriptive statistics of factors at the 50m buffer zone for Model 2.
Min.

Max.

Mean

Count

29.9

2061.8

737.5

77

Road Density (m/m )

0.0000

0.0090

0.0001

79

Nearest Trail (m)

3.40

14517.33

5182.67

78

Trail Density (m/m2)

0.0000

0.0284

0.0007

79

Nearest Building (m)

51.50

3311.77

913.12

77

Nearest Road (m)
2

Total Buildings

0

0

0

79

Canopy Cover

0.4167

1.000

0.934

78

160

Appendix XXIII. Descriptive statistics of factors at the 400m buffer zone for Model 2.
Min.

Max.

Mean

Count

29.9

2061.8

737.5

77

Road Density (m/m )

0.0000

0.0031

0.0004

79

Nearest Trail (m)

3.40

14517.33

5182.67

78

Trail Density (m/m2)

0.0000

0.0053

0.0005

79

Nearest Building (m)

51.50

3311.77

913.12

77

Nearest Road (m)
2

Total Buildings

0

12

0.666

78

Canopy Cover

0.677

1.000

0.954

78

Appendix XXIV. Descriptive statistics of factors at the 5000m buffer zone for Model 2.
Min.

Max.

Mean

Count

29.9

2061.8

796.1

64

Road Density (m/m )

0.0004

0.0035

0.0013

65

Nearest Trail (m)

3.40

14517.33

5390.93

65

Trail Density (m/m2)

0.0000

0.0013

0.0002

65

Nearest Building (m)

78.16

3311.77

985.90

64

Nearest Road (m)
2

Total Buildings

42

7591

1675.58

63

Canopy Cover

0.701

0.976

0.891

64

161

Appendix XXV. Descriptive statistics of factors at the 50m buffer zone for Model 3.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

737.5

77

88.5

2445.7

687.69

39

Road Density

0.0000

0.0090

0.0001

79

0.0000

0.0000

0.0000

39

Nearest Trail

3.4

14517.34

5182.67

78

87.3

14548.48

4764.34

39

Trail Density

0.0000

0.2849

0.0007

79

0.0000

0.0000

0.0000

39

Nearest Building

51.50

3311.77

913.12

77

98.70

2253.40

822.94

38

Total Buildings

0

0

0

79

0

0

0

39

Canopy Cover

0.416

1.000

0.934

78

0.286

1.000

0.972

39

Appendix XXVI. Descriptive statistics of factors at the 400m buffer zone for Model 3.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

737.5

77

88.5

2445.7

687.6

39

Road Density

0.0000

0.0031

0.0004

79

0.0000

0.0036

0.0005

39

Nearest Trail

3.40

14517.34

5182.67

78

87.30

14548.48

4764.34

39

Trail Density

0.0000

0.0053

0.0005

79

0.0000

0.0052

0.0008

39

Nearest Building

51.50

3311.77

913.12

77

98.70

2253.40

822.94

38

Total Buildings

0

12

0.667

78

0

16

2.102

39

Canopy Cover

0.677

1.000

0.954

78

0.638

1.000

0.933

39

162

Appendix XXVII. Descriptive statistics of factors at the 5000m buffer zone for Model 3.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

796.12

64

88.5

2445.7

709.54

37

Road Density

0.0004

0.0035

0.0013

65

0.0003

0.0040

0.0013

37

Nearest Trail

3.40

14517.34

5390.93

65

87.30

14548.48

4801.33

37

Trail Density

0.0000

0.0013

0.0002

65

0.0000

0.0015

0.0003

37

Nearest Building

78.16

3311.77

985.93

64

146.76

2253.40

837.50

32

Total Buildings

42

7591

1675.58

63

84

15706

2255.81

32

Canopy Cover

0.701

0.976

0.891

64

0.584

0.977

0.875

37

Appendix XXVIII. Descriptive statistics of factors at the 50m buffer zone for Model 4.
Min.

Max.

Mean

Count

29.9

2445.7

767.9

89

Road Density (m/m )

0.0000

0.0090

0.0001

90

Nearest Trail (m)

21.60

14548.47

5676.42

90

Trail Density (m/m2)

0.0000

0.0227

0.0003

90

Nearest Building (m)

78.16

3311.77

913.34

88

Total Buildings

0

0

0

90

Canopy Cover

0.286

1.000

0.962

89

Nearest Road (m)
2

163

Appendix XXIX. Descriptive statistics of factors at the 400m buffer zone for Model 4.
Min.

Max.

Mean

Count

29.9

2445.7

767.9

89

Road Density (m/m )

0.0000

0.0031

0.0004

90

Nearest Trail (m)

21.6

14548.4756

5676.423

90

Trail Density (m/m2)

0.0000

0.0053

0.0007

90

Nearest Building (m)

78.16

3311.77

913.34

88

Nearest Road (m)
2

Total Buildings

0

16

0.9438

89

Canopy Cover

0.677

1.000

0.944

89

Appendix XXX. Descriptive statistics of factors at the 5000m buffer zone for Model 4.
Min.

Max.

Mean

Count

29.9

2445.7

770.8

88

Road Density (m/m )

0.0003

0.0040

0.0013

89

Nearest Trail (m)

21.60

14548.47

530.45

89

Trail Density (m/m2)

0.0000

0.0015

0.0002

89

Nearest Building (m)

78.16

3311.77

914.54

83

Total Buildings

42

15706

1904.3048

82

Canopy Cover

0.584

0.977

0.884

88

Nearest Road (m)
2

164

Appendix XXXI. Descriptive statistics of factors at the 50m buffer zone for Model 5.
Min.

Max.

Mean

Count

29.9

2061.8

809.4

52

Road Density (m/m )

0.000

0.0090

0.0001

53

Nearest Trail (m)

21.60

14517.33

6287.33

53

Trail Density (m/m2)

0.0000

0.0227

0.0006

53

Nearest Building (m)

78.16

3311.77

953.65

52

Nearest Road (m)
2

Total Buildings

0

0

0

53

Canopy Cover

0.416

1.000

0.953

52

Appendix XXXII. Descriptive statistics of factors at the 400m buffer zone for Model 5.
Min.

Max.

Mean

Count

29.9

2061.8

809.4

52

Road Density (m/m )

0.0000

0.0031

0.0003

53

Nearest Trail (m)

21.60

14517.33

6287.33

53

Trail Density (m/m2)

0.0000

0.0053

0.0007

53

Nearest Building (m)

78.16

3311.77

953.65

52

Nearest Road (m)
2

Total Buildings

0

6

0.3269

52

Canopy Cover

0.677

1.000

0.947

52

165

Appendix XXXIII. Descriptive statistics of factors at the 5000m buffer zone for Model 5.
Min.

Max.

Mean

Count

29.9

2061.8

815.3

51

Road Density (m/m )

0.0004

0.0035

0.0013

52

Nearest Trail (m)

21.60

14517.33

6391.55

52

Trail Density (m/m2)

0.0000

0.0013

0.0002

52

Nearest Building (m)

78.16

3311.77

962.88

51

Nearest Road (m)
2

Total Buildings

42

7591

1679.34

50

Canopy Cover

0.701

0.976

0.890

51

Appendix XXXIV. Descriptive statistics of factors at the 50m buffer zone for Model 6.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

809.4

52

88.5

2445.7

709.5

37

Road Density

0.0000

0.0090

0.0001

53

0.0000

0.0000

0.0000

37

Nearest Trail

21.60

14517.34

6287.33

53

87.30

14548.48

4801.33

37

Trail Density

0.0000

0.0227

0.0006

53

0.0000

0.0000

0.0000

37

Nearest Building

78.16

3311.77

953.65

52

146.76

2253.40

855.11

36

Total Buildings

0

0

0

53

0

0

0

37

Canopy Cover

0.416

1.000

0.953

52

0.286

1.000

0.975

37

166

Appendix XXXV. Descriptive statistics of factors at the 400m buffer zone for Model 6.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

809.4

52

88.5

2445.7

709.5

37

Road Density

0.0000

0.0031

0.0003

53

0.0000

0.0022

0.0004

37

Nearest Trail

21.60

14517.34

6287.33

53

87.30

14548.48

4801.33

37

Trail Density

0.0000

0.0053

0.0007

53

0.0000

0.0052

0.0009

37

Nearest Building

78.16

3311.77

953.65

52

146.76

2253.40

885.11

36

Total Buildings

0

6

0.3269

52

0

16

1.8108

37

Canopy Cover

0.677

1.000

0.947

52

0.740

1.000

0.939

37

Appendix XXXVI. Descriptive statistics of factors at the 5000m buffer zone for Model 6.
Present

Absent

Min

Max

Mean

Count

Min

Max

Mean

Count

Nearest Road

29.9

2061.8

815.3

51

88.5

2445.7

709.5

37

Road Density

0.0004

0.0035

0.0013

52

0.0003

0.0040

0.0013

37

Nearest Trail

21.60

14517.34

6391.55

52

87.30

14548.48

4801.33

37

Trail Density

0.0000

0.0013

0.0002

52

0.0000

0.0015

0.0003

37

Nearest Building

78.16

3311.77

962.88

51

146.76

2253.40

837.50

32

Total Buildings

42

7591

1679.34

50

84

15706

2255.81

32

Canopy Cover

0.701

0.976

0.890

51

0.584

0.977

0.875

37

167

Appendix C: Raw Data for Random Points
Appendix XXXVII. Raw data at the 50m buffer zone for the one-hundred random points.
OID

Near Road (m)

Road Density (m/m2)

Near Trail (m)

Trail Density (m/m2)

Canopy

1

317.611

0.0000

7002.931

0.0000

1

2

281.638

0.0000

2318.486

0.0000

0

3

200.433

0.0000

1465.068

0.0000

0

4

208.680

0.0000

864.769

0.0000

1

5

362.259

0.0000

6441.596

0.0000

1

6

6.572

0.0260

5170.337

0.0000

0

7

609.840

0.0000

3475.755

0.0000

1

8

65.323

0.0000

688.438

0.0000

1

9

262.126

0.0000

5682.931

0.0000

1

10

191.663

0.0000

5230.337

0.0000

0

11

164.866

0.0000

1609.948

0.0000

1

12

19.987

0.0103

2119.352

0.0000

1

13

807.379

0.0000

851.974

0.0000

1

14

250.808

0.0000

4806.914

0.0000

1

15

955.744

0.0000

2162.231

0.0000

1

16

230.234

0.0000

3270.166

0.0000

1

17

231.544

0.0000

4674.978

0.0000

1

18

134.333

0.0000

7106.927

0.0000

1

19

8.777

0.0169

610.497

0.0000

0

20

224.096

0.0000

2229.744

0.0000

1

21

309.330

0.0000

2038.842

0.0000

1

22

165.948

0.0000

4816.098

0.0000

0

23

247.073

0.0000

4266.310

0.0000

0

24

611.067

0.0000

3021.257

0.0000

1

25

287.561

0.0000

8414.501

0.0000

1

26

23.488

0.0121

2923.158

0.0000

1

27

152.254

0.0000

1015.181

0.0000

1

28

192.126

0.0000

9418.221

0.0000

0

29

389.770

0.0000

8962.951

0.0000

1

30

369.355

0.0000

948.005

0.0000

0

31

77.358

0.0000

2180.727

0.0000

0

32

224.258

0.0000

6500.430

0.0000

0

33

160.333

0.0000

0.0000

0

34

1266.637

0.0000

3477.072

0.0000

1

35

376.449

0.0000

1894.005

0.0000

1

36

13.570

0.0209

977.777

0.0000

1

168

37

279.946

0.0000

7562.989

0.0000

1

38

183.525

0.0000

4203.417

0.0000

0

39

103.438

0.0000

2775.681

0.0000

1

40

29.224

0.0096

5991.501

0.0000

1

41

16.358

0.0118

5765.601

0.0000

1

42

1214.028

0.0000

1214.028

0.0000

1

43

573.185

0.0000

6396.252

0.0000

0

44

0.848

0.0127

4740.591

0.0000

0

45

1.449

0.0127

11844.386

0.0000

1

46

509.851

0.0000

7186.755

0.0000

1

47

521.752

0.0000

1517.770

0.0000

1

48

58.684

0.0000

1656.206

0.0000

1

49

10.742

0.0124

8.401

0.0124

1

50

111.226

0.0000

4457.615

0.0000

0

51

382.102

0.0000

3502.248

0.0000

0

52

898.659

0.0000

1803.675

0.0000

1

53

121.305

0.0000

3947.865

0.0000

0

54

1209.785

0.0000

344.456

0.0000

0

55

24.228

0.0111

746.917

0.0000

1

56

335.662

0.0000

0.0000

1

57

419.114

0.0000

4345.209

0.0000

1

58

32.037

0.0097

9483.457

0.0000

0

59

46.982

0.0044

182.839

0.0000

0

60

16.420

0.0238

1478.742

0.0000

0

61

40.983

0.0073

976.086

0.0000

1

62

642.378

0.0000

2178.282

0.0000

1

63

324.034

0.0000

2161.443

0.0000

0

64

194.685

0.0000

1936.630

0.0000

0

65

51.827

0.0000

1912.481

0.0000

0

66

5.480

0.0085

6491.087

0.0000

1

67

1021.497

0.0000

3439.948

0.0000

1

68

64.451

0.0000

2748.798

0.0000

1

69

226.200

0.0000

12526.513

0.0000

0

70

37.215

0.0056

9499.331

0.0000

1

71

67.434

0.0000

1969.470

0.0000

1

72

125.081

0.0000

478.536

0.0000

0

73

280.816

0.0000

656.508

0.0000

1

74

370.852

0.0000

3611.278

0.0000

1

75

65.894

0.0000

11529.944

0.0000

1

76

313.173

0.0000

4014.770

0.0000

0

169

77

382.552

0.0000

6297.893

0.0000

0

78

8.830

0.0231

2213.728

0.0000

0

79

159.744

0.0000

13125.969

0.0000

0

80

883.685

0.0000

46.622

0.0091

1

81

305.096

0.0000

3053.198

0.0000

0

82

11.684

0.0122

9710.952

0.0000

0

83

31.891

0.0170

1318.368

0.0000

1

84

357.126

0.0000

3688.058

0.0000

1

85

178.547

0.0000

4806.953

0.0000

1

86

619.812

0.0000

2527.002

0.0000

1

87

421.248

0.0000

548.340

0.0000

1

88

6.779

0.0247

6.779

0.0126

0

89

325.472

0.0000

7321.144

0.0000

1

90

54.077

0.0000

4441.603

0.0000

1

91

105.965

0.0000

6302.265

0.0000

0

92

134.047

0.0000

1814.767

0.0000

1

93

361.517

0.0000

3344.854

0.0000

1

94

264.575

0.0000

5818.811

0.0000

1

95

205.869

0.0000

935.916

0.0000

1

96

172.915

0.0000

2059.987

0.0000

0

97

56.489

0.0000

167.100

0.0000

1

98

78.242

0.0000

4876.436

0.0000

1

99

379.066

0.0000

4619.210

0.0000

1

100

65.529

0.0000

8899.716

0.0000

1

170

Appendix XXXVIII. Raw data at the 400m buffer zone for the one-hundred random
points.
OID

Near Road (m)

Road Density (m/m2)

Near Trail (m)

Trail Density (m/m2)

Canopy

1

317.611

0.00193

7002.931

0.00000

1

2

281.638

0.00035

2318.486

0.00000

0

3

200.433

0.00399

1465.068

0.00000

0

4

208.680

0.00156

864.769

0.00000

1

5

362.259

0.00076

6441.596

0.00000

1

6

6.572

0.00325

5170.337

0.00000

0

7

609.840

0.00000

3475.755

0.00000

1

8

65.323

0.00779

688.438

0.00000

1

9

262.126

0.00201

5682.931

0.00000

1

10

191.663

0.00220

5230.337

0.00000

0

11

164.866

0.00452

1609.948

0.00000

1

12

19.987

0.00902

2119.352

0.00000

1

13

807.379

0.00000

851.974

0.00000

1

14

250.808

0.00230

4806.914

0.00000

1

15

955.744

0.00000

2162.231

0.00000

1

16

230.234

0.00076

3270.166

0.00000

1

17

231.544

0.00131

4674.978

0.00000

1

18

134.333

0.00306

7106.927

0.00000

1

19

8.777

0.01183

610.497

0.00000

0

20

224.096

0.00151

2229.744

0.00000

1

21

309.330

0.00100

2038.842

0.00000

1

22

165.948

0.00220

4816.098

0.00000

0

23

247.073

0.00422

4266.310

0.00000

0

24

611.067

0.00000

3021.257

0.00000

1

25

287.561

0.00084

8414.501

0.00000

1

26

23.488

0.00410

2923.158

0.00000

1

27

152.254

0.00158

1015.181

0.00000

1

28

192.126

0.00176

9418.221

0.00000

0

171

29

389.770

0.00037

8962.951

0.00000

1

30

369.355

0.00056

948.005

0.00000

0

31

77.358

0.00501

2180.727

0.00000

0

32

224.258

0.00243

6500.430

0.00000

0

33

160.333

0.00333

0.00000

0

34

1266.637

0.00000

3477.072

0.00000

1

35

376.449

0.00093

1894.005

0.00000

1

36

13.570

0.01188

977.777

0.00000

1

37

279.946

0.00229

7562.989

0.00000

1

38

183.525

0.00206

4203.417

0.00000

0

39

103.438

0.00195

2775.681

0.00000

1

40

29.224

0.00414

5991.501

0.00000

1

41

16.358

0.00626

5765.601

0.00000

1

42

1214.028

0.00000

1214.028

0.00000

1

43

573.185

0.00000

6396.252

0.00000

0

44

0.848

0.00259

4740.591

0.00000

0

45

1.449

0.00165

11844.386

0.00000

1

46

509.851

0.00000

7186.755

0.00000

1

47

521.752

0.00000

1517.770

0.00000

1

48

58.684

0.00387

1656.206

0.00000

1

49

10.742

0.00486

8.401

0.00171

1

50

111.226

0.00436

4457.615

0.00000

0

51

382.102

0.00047

3502.248

0.00000

0

52

898.659

0.00000

1803.675

0.00000

1

53

121.305

0.00241

3947.865

0.00000

0

54

1209.785

0.00000

344.456

0.00033

0

55

24.228

0.00496

746.917

0.00000

1

56

335.662

0.00086

0.00000

1

57

419.114

0.00000

4345.209

0.00000

1

58

32.037

0.00654

9483.457

0.00000

0

59

46.982

0.00646

182.839

0.00111

0

172

60

16.420

0.01007

1478.742

0.00000

0

61

40.983

0.01008

976.086

0.00000

1

62

642.378

0.00000

2178.282

0.00000

1

63

324.034

0.00121

2161.443

0.00000

0

64

194.685

0.00461

1936.630

0.00000

0

65

51.827

0.00724

1912.481

0.00000

0

66

5.480

0.00424

6491.087

0.00000

1

67

1021.497

0.00000

3439.948

0.00000

1

68

64.451

0.00732

2748.798

0.00000

1

69

226.200

0.00174

12526.513

0.00000

0

70

37.215

0.00081

9499.331

0.00000

1

71

67.434

0.00290

1969.470

0.00000

1

72

125.081

0.00145

478.536

0.00000

0

73

280.816

0.00122

656.508

0.00000

1

74

370.852

0.00041

3611.278

0.00000

1

75

65.894

0.00312

11529.944

0.00000

1

76

313.173

0.00140

4014.770

0.00000

0

77

382.552

0.00007

6297.893

0.00000

0

78

8.830

0.02131

2213.728

0.00000

0

79

159.744

0.00176

13125.969

0.00000

0

80

883.685

0.00000

46.622

0.00347

1

81

305.096

0.00199

3053.198

0.00000

0

82

11.684

0.00265

9710.952

0.00000

0

83

31.891

0.00452

1318.368

0.00000

1

84

357.126

0.00060

3688.058

0.00000

1

85

178.547

0.00260

4806.953

0.00000

1

86

619.812

0.00000

2527.002

0.00000

1

87

421.248

0.00000

548.340

0.00000

1

88

6.779

0.00507

6.779

0.00159

0

89

325.472

0.00015

7321.144

0.00000

1

90

54.077

0.00356

4441.603

0.00000

1

173

91

105.965

0.00211

6302.265

0.00000

0

92

134.047

0.00156

1814.767

0.00000

1

93

361.517

0.00011

3344.854

0.00000

1

94

264.575

0.00289

5818.811

0.00000

1

95

205.869

0.00547

935.916

0.00000

1

96

172.915

0.00642

2059.987

0.00000

0

97

56.489

0.00500

167.100

0.00126

1

98

78.242

0.00224

4876.436

0.00000

1

99

379.066

0.00005

4619.210

0.00000

1

100

65.529

0.00311

8899.716

0.00000

1

174

Appendix XXXIX. Raw data at the 5000m buffer zone for the one-hundred random
points.
OID

Near Road (m)

Road Density (m/m2)

Near Trail (m)

Trail Density (m/m2)

Canopy

1

317.611

0.00306

7002.931

0.00000

1

2

281.638

0.00367

2318.486

0.00017

0

3

200.433

0.01199

1465.068

0.00017

0

4

208.680

0.00498

864.769

0.00048

1

5

362.259

0.00459

6441.596

0.00000

1

6

6.572

0.00390

5170.337

0.00000

0

7

609.840

0.00746

3475.755

0.00040

1

8

65.323

0.00163

688.438

0.00017

1

9

262.126

0.00745

5682.931

0.00000

1

10

191.663

0.00388

5230.337

0.00000

0

11

164.866

0.00455

1609.948

0.00014

1

12

19.987

0.00484

2119.352

0.00011

1

13

807.379

0.00256

851.974

0.00112

1

14

250.808

0.00414

4806.914

0.00004

1

15

955.744

0.00874

2162.231

0.00045

1

16

230.234

0.00220

3270.166

0.00018

1

17

231.544

0.00677

4674.978

0.00026

1

18

134.333

0.00245

7106.927

0.00000

1

19

8.777

0.00656

610.497

0.00016

0

20

224.096

0.00319

2229.744

0.00173

1

21

309.330

0.00233

2038.842

0.00010

1

22

165.948

0.00368

4816.098

0.00001

0

23

247.073

0.00341

4266.310

0.00019

0

24

611.067

0.00444

3021.257

0.00017

1

25

287.561

0.00277

8414.501

0.00000

1

26

23.488

0.00488

2923.158

0.00031

1

27

152.254

0.00117

1015.181

0.00115

1

28

192.126

0.00529

9418.221

0.00000

0

29

389.770

0.00433

8962.951

0.00000

1

30

369.355

0.00454

948.005

0.00038

0

31

77.358

0.00283

2180.727

0.00011

0

32

224.258

0.00640

6500.430

0.00000

0

33

160.333

0.00215

0.00000

0

34

1266.637

0.00103

3477.072

0.00007

1

35

376.449

0.00617

1894.005

0.00093

1

36

13.570

0.00662

977.777

0.00019

1

37

279.946

0.00282

7562.989

0.00000

1

175

38

183.525

0.00873

4203.417

0.00003

0

39

103.438

0.00503

2775.681

0.00030

1

40

29.224

0.00744

5991.501

0.00000

1

41

16.358

0.01018

5765.601

0.00000

1

42

1214.028

0.00172

1214.028

0.00039

1

43

573.185

0.00772

6396.252

0.00000

0

44

0.848

0.00351

4740.591

0.00007

0

45

1.449

0.00040

11844.386

0.00000

1

46

509.851

0.00225

7186.755

0.00000

1

47

521.752

0.00733

1517.770

0.00071

1

48

58.684

0.00329

1656.206

0.00034

1

49

10.742

0.00312

8.401

0.00018

1

50

111.226

0.00280

4457.615

0.00005

0

51

382.102

0.00411

3502.248

0.00012

0

52

898.659

0.00310

1803.675

0.00165

1

53

121.305

0.00426

3947.865

0.00025

0

54

1209.785

0.00474

344.456

0.00117

0

55

24.228

0.00588

746.917

0.00093

1

56

335.662

0.00292

0.00000

1

57

419.114

0.00107

4345.209

0.00007

1

58

32.037

0.00335

9483.457

0.00000

0

59

46.982

0.00613

182.839

0.00042

0

60

16.420

0.01428

1478.742

0.00017

0

61

40.983

0.00404

976.086

0.00106

1

62

642.378

0.00277

2178.282

0.00038

1

63

324.034

0.00214

2161.443

0.00024

0

64

194.685

0.01295

1936.630

0.00020

0

65

51.827

0.00662

1912.481

0.00003

0

66

5.480

0.00388

6491.087

0.00000

1

67

1021.497

0.00219

3439.948

0.00005

1

68

64.451

0.00237

2748.798

0.00017

1

69

226.200

0.00296

12526.513

0.00000

0

70

37.215

0.00177

9499.331

0.00000

1

71

67.434

0.00359

1969.470

0.00043

1

72

125.081

0.00404

478.536

0.00025

0

73

280.816

0.00689

656.508

0.00088

1

74

370.852

0.01000

3611.278

0.00012

1

75

65.894

0.00433

11529.944

0.00000

1

76

313.173

0.00445

4014.770

0.00022

0

77

382.552

0.00339

6297.893

0.00000

0

176

78

8.830

0.00551

2213.728

0.00050

0

79

159.744

0.00291

13125.969

0.00000

0

80

883.685

0.00336

46.622

0.00093

1

81

305.096

0.00341

3053.198

0.00048

0

82

11.684

0.00266

9710.952

0.00000

0

83

31.891

0.00564

1318.368

0.00013

1

84

357.126

0.00350

3688.058

0.00022

1

85

178.547

0.00330

4806.953

0.00001

1

86

619.812

0.00202

2527.002

0.00026

1

87

421.248

0.00134

548.340

0.00033

1

88

6.779

0.00238

6.779

0.00016

0

89

325.472

0.00225

7321.144

0.00000

1

90

54.077

0.00306

4441.603

0.00022

1

91

105.965

0.00190

6302.265

0.00000

0

92

134.047

0.00435

1814.767

0.00008

1

93

361.517

0.00945

3344.854

0.00056

1

94

264.575

0.00750

5818.811

0.00000

1

95

205.869

0.00397

935.916

0.00049

1

96

172.915

0.00547

2059.987

0.00016

0

97

56.489

0.00309

167.100

0.00046

1

98

78.242

0.00286

4876.436

0.00005

1

99

379.066

0.00283

4619.210

0.00019

1

100

65.529

0.00323

8899.716

0.00000

1

177

Appendix D: Descriptive Statistics for Random Points
Appendix XL. Descriptive statistics of factors at the 50m buffer zone for the random
points.
Min

Max

Mean

Count

Nearest Road

0.8484

1266.63

269.03

100

Road Density

0

0.026

0.0029

100

Nearest Trail

6.779

13125.97

3917.05

98

Trail Density

0

0.0125

0.000341

100

Canopy

0

1

0.64

100

Appendix XLI. Descriptive statistics of factors at the 400m buffer zone for the random
points.
Min

Max

Mean

Count

Nearest Road

0.8484

1266.63

269.03

100

Road Density

0

0.0213

0.00285

100

Nearest Trail

6.779

13125.97

3917.05

98

Trail Density

0

0.00347

0.00009468

100

Canopy

0

1

0.64

100

Appendix XLII. Descriptive statistics of factors at the 5000m buffer zone for the random
points.
Min

Max

Mean

Count

Nearest Road

0.8484

1266.63

269.03

100

Road Density

0.000398

0.0142

0.00441

100

Nearest Trail

6.779

13125.97

3917.05

98

Trail Density

0

0.00173

0.000253

100

Canopy

0

1

0.64

100

178

Appendix E: R-Squared and AIC Values
Appendix XLIII. R-Squared and AIC values for all models, sorted by model number,
then by spatial scale. Note that GLMs do not give an R-squared value.
Model 1 50m
Model 1 400m
Model 1 5000m
Model 2 50m
Model 2 400m
Model 2 5000m
Model 3 50m
Model 3 400m
Model 3 5000m
Model 4 50m
Model 4 400m
Model 4 5000m
Model 5 50m
Model 5 400m
Model 5 5000m
Model 6 50m
Model 6 400m
Model 6 5000m

R- Squared
0.0234
-0.0050
0.0879
0.0302
0.0348
0.1097
0.0557
-0.0337
0.1220
0.1000
0.0385
0.2210
-

AIC
806.53
810.73
677.678
562.81
563.34
468.03
128.75
152.33
128.75
648.38
643.89
592.02
394.96
399.19
375.34
124.15
121.16
118.15

Appendix XLIV. R-Squared and AIC Values for all models sorted by spatial scale
followed by model number. Note that GLMs do not give an R-squared value.
Model 1 50m
Model 2 50m
Model 3 50m
Model 4 50m
Model 5 50m
Model 6 50m
Model 1 400m
Model 2 400m
Model 3 400m
Model 4 400m
Model 5 400m
Model 6 400m
Model 1 5000m
Model 2 5000m
Model 3 5000m
Model 4 5000m
Model 5 5000m
Model 6 5000m

R- Squared
0.0234
0.0302
0.0557
0.1000
-0.0050
0.0348
-0.0337
0.0385
0.0879
0.1097
0.1220
0.2210
-

179

AIC
806.53
562.81
128.75
648.38
394.96
124.15
810.73
563.34
152.33
643.89
399.19
121.16
677.67
468.03
128.75
592.02
375.34
118.15

180

Appendix F: Significant Factors
Appendix XLV. All models shown ordered by spatial scale with an 'X' indicating factors
that showed a significant relationship with population size.
Nearest
Road

Road
Density

Nearest
Trail

Trail
Density

Nearest
Building

Buildings
Within

X

-

Model 1
5000m

X

X

Model 2
50m

X

-

Model 2
400m

X

Model 2
5000m

X

Model 1
50m

Canopy
Percent

Model 1
400m

Model 3
50m

-

Model 3
400m

X

Model 3
5000m
Model 4
50m

X

-

Model 4
400m
Model 4
5000m

X

Model 5
50m

X

Model 5
400m

X

Model 5
5000m

X

-

X

Model 6
50m

-

Model 6
400m
Model 6
5000m

181

X

X

Appendix XLVI. All models shown ordered by model number with an 'X' indicating
factors that showed a significant relationship with population size.
Nearest
Road

Road
Density

Nearest
Trail

Trail
Density

Nearest
Building

Buildings
Within

Model 1
50m

X

-

Model 2
50m

X

-

Model 3
50m

Canopy
Percent

-

Model 4
50m

X

Model 5
50m

X

Model 6
50m

-

Model 1
400m
Model 2
400m

X

Model 3
400m

X

Model 4
400m
Model 5
400m

X

Model 6
400m
Model 1
5000m

X

Model 2
5000m

X

X

Model 3
5000m
Model 4
5000m
Model 5
5000m

X

Model 6
5000m

182

X

X

X

X

Appendix G: TRAP Sites

Appendix XLVII. Rattlesnake sites in the Northeast produced by TRAP through the
PFBC. Sites are randomly offset from actual locations by up to 5000m to minimize the
potential of poaching activity from this work.
183