Cozy in the City: The Morphology and Spatial Ecology of Copperheads in an Urban Forest
Malle F. Carrasco-Harris1*, Judith A. Cole1, and Steve Reichling2
1Department of Biological Sciences, University of Memphis, 239 Ellington Hall 3700, Walker Ave Memphis, TN 38152, USA. 2Department of Conservation and Research, Memphis Zoo, 2000 Prentiss Place, Memphis, TN 38112, USA. *Corresponding author.
Urban Naturalist, No. 35 (2020)
Abstract
Anthropogenic environments alter behaviors in a wide variety of taxa. We examined the morphology and spatial ecology of Agkistrodon contortrix Linnaeus (Eastern Copperhead) within an urban forest and a rural forest in Tennessee. We captured snakes for morphological data and radio tracked 36 urban and 8 rural subjects to collect spatial data. We estimated home range size, core area, and movement parameters (total distance moved; daily, sampling, and monthly movement) using relocation data. Copperheads in the urban forest were smaller but did not differ in body condition compared to rural conspecifics. We found urban Copperheads had reduced home ranges, core areas, and movement parameters compared to rural subjects. Our study suggests urban snakes alter spatial behavior by decreasing overall movement.
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No. 35 Urban Naturalist 2020
Cozy in the City:
The Morphology and
Spatial Ecology of
Copperheads in an
Urban Forest
Malle F. Carrasco-Harris, Judith A. Cole,
and Steve Reichling
Urban Naturalist
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Cover Photograph: Peeking out is “Hooty”, a copperhead that remained in a root hole in a manicured section of Overton Park, Memphis,
Tennessee, for the month of July 2015. The hole afforded Hooty the opportunity to watch cyclists, runners, and walkers on the nearby pedestrian
road and a peek of the children’s playground. Hooty’s transmitter stopped sending signals the following spring, but he was once again
spotted in the same hole the following July. Park users seemed oblivious to his presence. Photograph © Melissa McMasters.
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2020 Urban Naturalist 35:1–19
Cozy in the City: The Morphology and Spatial
Ecology of Copperheads in an Urban Forest
Malle F. Carrasco-Harris1*, Judith A. Cole1, and Steve Reichling2
Abstract - Anthropogenic environments alter behaviors in a wide variety of taxa. We examined the
morphology and spatial ecology of Agkistrodon contortrix Linnaeus (Eastern Copperhead) within an
urban forest and a rural forest in Tennessee. We captured snakes for morphological data and radio
tracked 36 urban and 8 rural subjects to collect spatial data. We estimated home range size, core area,
and movement parameters (total distance moved; daily, sampling, and monthly movement) using
relocation data. Copperheads in the urban forest were smaller but did not differ in body condition
compared to rural conspecifics. We found urban Copperheads had reduced home ranges, core areas,
and movement parameters compared to rural subjects. Our study suggests urban snakes alter spatial
behavior by decreasing overall movement.
Introduction
Urban and suburban areas are growing, leading to increasingly isolated and fragmented
natural habitats surrounded by varying degrees of disturbance (Fischer and Lindenmayer
2007, United Nations 2018). Natural areas allocated for human recreation within urban settings
can function as refuges for a variety of species (Dickman 1987, Harden et al. 2009, Mahan
and O’Connell 2005). These habitats differ from continuous areas, as they experience the
consequences of surrounding anthropogenic disturbances, including impervious land cover,
exotic species introduction, wildlife subsidization, disease transfer, and human persecution
(Bar-Massada et al. 2014, Fischer et al. 2012, Mitchell and Jung Brown 2008). As urban
sprawl and human population density increase, native species richness and biodiversity decrease
(Haddad et al. 2015, McKinney 2008). Animals persisting in these environments often
have a degree of behavioral plasticity or traits that allow them to tolerate the disturbances
in urban environments, such as modifying spatial, breeding, or activity behavior (French et
al. 2018, Lowry et al. 2013). For example, research indicates mammals and birds decrease
home range size and occur at higher population densities in urban settings because of factors
such as resource availability, changes in competition, and habitat structure (Mannan and Boal
2000, Marks and Bloomfield 2006, Rutz 2006, Šálek et al. 2015, White et al. 2006).
Although mammals and birds are well-studied, less work has focused on snake behavior
and spatial ecology in urban environments, despite their sensitivity to habitat modification
(Burger et al. 2012), population decline (Reading et al. 2010), and human persecution
(Mitchell and Jung Brown 2008). Reptile species persist in urban areas if there are favorable
habitat conditions, such as connectivity between fragments, prey populations, appropriate
basking and shelter locations, and structures for hibernation (Ackley and Meylan 2010, Bonnet
et al. 2016, Zappalorti and Mitchell 2008). However, anthropogenic disturbances, such
as roads and railways, have effects on reptile movement and survival and limit dispersal
(Andrews et al. 2008, Rautsaw et al. 2018). Snakes and other reptiles in fragmented and
disturbed areas tend to have smaller home ranges (Breininger et al. 2011, Lomas et al. 2019),
1Department of Biological Sciences, University of Memphis, 239 Ellington Hall 3700, Walker Ave
Memphis, TN 38152, USA. 2Department of Conservation and Research, Memphis Zoo, 2000 Prentiss
Place, Memphis, TN 38112, USA. *Corresponding author: malle.fch@gmail.com
Manuscript Editor: Rachel Blakey
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2020 No. 35
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alter concealment and movement patterns (Beale et al. 2016, Ferronato et al. 2015, Martin et
al. 2017), and may exhibit lower body conditions (Lomas et al. 2015) compared to snakes in
undisturbed areas. Taken together, these consequences may come at a cost to growth, survivability,
and prey acquisition in reptiles persisting in human-disturbed environments.
Agkistrodon contortrix (Linnaeus) (Eastern Copperhead) are widespread across the
eastern United States (Ernst 1992), and their distribution overlaps with a variety of other
snake species that may be of greater conservation interest (Ernst and Ernst 2011). Copperheads
are relatively long-lived and exhibit fidelity to seasonal sites, which makes them
particularly susceptible to habitat modification (Burger et al. 2012, Fitch 1960). Hence,
this species could serve as a management indicator of environments suitable for snakes and
ecologically similar species (Caro and O’Doherty 1999, Levine 2013). To study the consequences
of urbanization on snake spatial ecology, we conducted a longitudinal radio telemetry
study on Copperheads within an urban forest. Copperhead home range and movement
patterns have been characterized by radio telemetry in less disturbed settings (Rodriguez
2010, Smith et al. 2009, Sutton et al. 2017), but their spatial ecology in urban fragments has
not been addressed. Understanding this common species will allow for better management
of this and related species in urban natural areas, and help elucidate the effects of urbanization
on herpetofauna. Our main objectives were to determine if there were differences in the
morphology and spatial ecology of Copperheads within an isolated urban natural fragment
and a rural forest. We expected subjects within the urban fragment would be smaller and
in poorer body condition, have reduced home range size, and move less than conspecifics
living in the rural forest. We also expected urban home range sizes to be smaller than previously
reported for this species.
Materials and Methods
Study Sites
We studied Copperheads in Overton Park (Overton; urban forest), Memphis, TN, and
Edward J. Meeman Biological Station (Meeman; rural forest), Shelby County, TN. Overton
(138 hectares [ha]) is a popular recreational area at the core of the community. Within the
park is a 57 ha old-growth mixed forest containing paved and unpaved trails, a golf course
and clubhouse, zoo, playgrounds, dog park, art gallery, and art school. The park has been
bordered by roads and residential and commercial areas for over a century (Bearden 2004).
The park and forest within it support a subset of native herpetofauna, including Copperheads
(Davis et al. 2012). Meeman (252 ha) is a University of Memphis property dedicated
to scientific study located 24 km north of Overton and composed of deciduous, evergreen,
and mixed forest, as well as some pastures. It is bordered by private and public forest and
woody wetlands. There are a few small buildings, and a low-traffic road bisects the property;
a state park and private land border the area. Meeman is not open to the public and
does not have an extensive trail network, making it relatively less disturbed than Overton.
Capture and Surgery
We captured 243 Copperheads (Table 1) by hand during visual searches, or when found
with focal subjects (tracked animals) and by using drift fences with funnel box traps. We
transported animals in a secured container to the Memphis Zoo veterinary hospital for morphological
data collection and surgical implantation of radio transmitters. All subjects were
included in the basic data collection, and a subset was included in radio telemetry research.
We safely restrained animals in an acrylic tube and injected a passive-integrated transponder
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(PIT) tag (134.2 kHz 8.4 mm Biomark, Boise, ID) ~10 cm anterior to the cloaca for individual
identification. We used the last 4 characters of the PIT tag identification number for all
records associated with a subject and noted recaptures when a previously caught individual
was identified. We photographed subjects with a standard for digital measurement of snoutvent
length (SVL; ± 0.01 cm) using ImageJ (National Institutes of Health, Bethesda, MD)
and recorded mass on a digital scale (± 0.01 g; HX-502 American Weigh Scales, Norcross,
GA). We determined sex by probing for the presence of hemipenes in males, and we palpated
adult females to detect ova.
We estimated body condition, an indicator of health, by calculating the scaled mass
index (SMI) for each animal following the methods of Peig and Green (2009, 2010). This
index incorporates allometric changes in scaling observed in many species and outperforms
other methods of determining body condition (Peig and Green 2010). Briefly, we used
standardized major axis (SMA) regression (Warton et al. 2012) to create a line of best fit
for the natural log-transformed mass and SVL of males and non-gravid females. The SMA
regression accounts for error in both variables (mass and length). We used the slope of the
SMA regression, mass, length, and mean population length to calculate the SMI for each
individual. Individual SMI can be compared between groups or to the population average.
We excluded gravid females from morphological analyses because they are expected to be
heavier for their length than predicted.
The senior zoo veterinarian and staff surgically implanted radio transmitters (R1680 3.6
g, Advanced Telemetry Systems, Isanti, MN) into selected adult subjects following methods
adapted from Reinert and Cundall (1982). Transmitters weighed less than 5% of body mass.
We monitored subjects at the hospital for 24 h post-implantation and assessed behavior and
the surgical site incision before release at their capture location. We surgically removed
transmitters from all animals that could be located after 1 year and returned the snakes to
their final relocation site.
Radio Telemetry and Spatial Analyses
From June 2015 to July 2018, we radio-tracked 44 subjects (25 males, 19 females)
twice per week during the active season (15 March–15 November). After implantation and
release, the snakes were located by using a hand-held 2-element RA-23K VHF antenna
(Telonics, Mesa, AZ) or 3-element folding Yagi antenna (Advanced Telemetry Systems,
Isanti, MN) with an R-1000 telemetry receiver (Communications Specialists, Orange, CA),
Table 1. Copperhead snakes captured at urban Overton Park and rural Meeman Biological Station. Trap
implies animal found in funnel trap array. Opportunistic animals were captured outside of traps by researcher.
Capture
Location Sex Trap Opportunistic Total
Meeman M 11 5 16
F 1 8 9
Overton M 44 65 109
F 30 78 108
NA* 1 0 1
87 156 243
*Unable to sex small animal.
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and their positions were identified (i.e., relocated). We separated consecutive relocations
by 3–4 days to reduce spatial autocorrelation (White and Garrott 1990) since snakes use
localized areas for extended periods of time (Row and Blouin-Demers 2006). The median
number of active season relocations was 51 (range 11–64). We obtained geographic coordinates
of the animal location using a hand-held global positioning system (±5 m; GPSmap
76Cx, Garmin, Olathe, KS) or triangulated the location if the animal could not be seen because
of dense vegetation. We recorded temperature and humidity at each relocation using
a psychrometer (Temperature Pen 800012, Sper Scientific, Scottsdale, AZ).
We estimated home range sizes using minimum convex polygons (MCP), kernel density
estimators (KDE), and local convex hull methods (LoCoH). We calculated home range
sizes using MCP (Fig. 1) with the R package adehabitatHR (Calenge 2006, Mohr 1947).
We calculated 100% and 95% MCPs to account for possible overestimation due to outliers
(White and Garrott 1990). We estimated utilization distributions using fixed kernel density
estimators (KDE; Fig. 1A) with the R package rhr (Signer and Balkenhol 2015, Worton
1989). Kernel utilization distributions model spatial use as a probability density function.
We estimated the KDE smoothing parameter using the bivariate plug-in method, as it is
robust at decreasing absolute error and is a preferable choice for studies with small-bodied
taxa, such as snakes (Bauder et al. 2015). We also calculated utilization distributions using
adaptive LoCoH (Fig. 1B) with the R package rhr (Getz et al. 2007, Getz and Wilmers 2004,
Signer and Balkenhol 2015). The LoCoH method is advantageous because of increasing accuracy
with sample size and better recognition of boundaries that are inaccessible, limiting
home range estimates accordingly. For both utilization distribution methods, we bounded
home ranges and core areas at 95% and 50% top use areas, respectively.
Figure 1. Home range model examples for a selection of 8 Copperhead snakes in the urban forest Overton
Park. Polygons represent active season minimum convex polygon (MCP) home ranges for males and
females. (A) Kernel density estimator home ranges and core areas shown within MCPs in gray. (B) Local
convex hull home ranges shown within MCPs in gray. Not all individuals in the study are shown in the
figure. Those displayed show a range of MCPs including the smallest and largest home ranges for both
sexes as well as intermediate individuals with minimal overlapping.
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We calculated movement metrics, including total distance, mean daily movement, mean
movement between sampling relocations, and mean monthly movement for each snake,
with the R package adehabitatLT (Calenge 2006). Total distance is the summation of the
Euclidian distance between relocations. Mean daily movement is the summation of the distance
between relocations divided by the number of days the animal was observed. Mean
movement between sampling relocations is the summation of the distance between relocations
divided by the number of observations. Mean monthly movement is the summation of
distance between relocations divided by the number of observations in a month.
Statistical Analyses
Prior to statistical analyses, we followed the data exploration protocol described in Zuur
et al. (2010). We assessed whether urban and rural Copperheads differed morphologically,
specifically by mass, length, and scaled mass index (SMI). We used linear models (ANOVA)
to determine if there were differences by location and included sex as a covariate to control
for size differences between males and females (Smith et al. 2009). We compared models
with and without interactions using the corrected Akaike information criterion (AICc) to
select the most parsimonious model given the data (Burnham and Anderson 2002). We
normalized morphological data by using the square root of mass and the natural logarithm
(ln) of SMI for the analyses. Common transformations did not enhance normality for SVL;
therefore, we used the raw data for analysis and verified model assumptions using residuals.
We found 100% and 95% MCP areas were highly correlated (r = 0.95, P < 0.001), and
we, therefore, conducted all analyses with 100% MCP for comparability between studies. We
estimated home range using 100% MCP and 95% KDE and LoCoH, and we estimated core
areas using 50% KDE and LoCoH. We used linear models to determine differences in home
range and core area by location and included year and sex as covariates to control for period
in study and home range differences between males and females, respectively (Smith et al.
2009). We ln-transformed all home range and core area response variables in our analyses.
Further, we compared our home range estimates to other rural Copperhead populations
using individual MCP home range estimates from Alabama (Sutton et al. 2017), Connecticut
(Smith et al. 2009), and Nebraska (Rodriguez 2010), using a linear model with sex,
location, and their interaction. We made pairwise comparisons between locations by sex
and corrected significance estimates using Holm-Bonferroni multiple comparison adjustments
to reduce type I error (Holm 1979). Although 2 of the studies were manipulative,
they did not find significant differences between control and treatment groups for home
range size (Rodriguez 2010, Sutton et al. 2017) and were, therefore, included for broader
comparison purposes.
We used linear models to assess total distance moved, mean daily movement, and
mean movement per sample by location and included year and sex as covariates to
control for period in study and movement differences between males and females. We
included the number of relocations for each individual in the analysis of total distance
moved since it would be positively related to how long the subject was tracked. To
determine differences in monthly movement, we used linear mixed models from the
lmerTest package in R (Kuznetsova et al. 2017) and included sex, location, month, and
year as fixed effects and individual as a random effect. We selected the most informative
and parsimonious nested model using AIC. We conducted pairwise comparisons by
consecutive months to determine if Copperhead movement differed throughout the active
season using Holm-Bonferroni multiple comparison adjustments (Holm 1979). Further,
we conducted pairwise comparisons of the sexes by month to determine if females and
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males differed in monthly movement. All movement metrics were ln-transformed to meet
assumptions of normality.
We verified linear model assumptions by plotting residuals versus fitted values and
each covariate in the model. If appropriate, we assessed residuals for temporal dependency
(Zuur and Ieno 2016). All statistical tests were 2-tailed and accepted as significant at P ≤
0.05. Statistical analyses were conducted using the R programming environment v. 3.3.3
(R Core Team 2017).
Results
Capture and Morphology
We captured snakes from May 2015–August 2018, totaling 217 unique individuals
out of 243 captures across both sites (Table 1). Opportunistic captures occurred at an
average temperature of 26.5 ± 0.3 ˚C and humidity of 62.5 ± 1.3%. One individual at
the rural forest and 25 at the urban forest were recaptured (captured and subsequently
identified using their PIT tags). Nearby conspecifics were most frequently found during
the breeding seasons, in particular April and July through October, but it was not
uncommon to find conspecifics of the same sex within the same area in the urban forest.
Of the instances where we found an urban focal (subject) female with another snake, 27
were with males, 8 were with other females, and 1 was undetermined. For focal males,
14 instances were with females, 14 with other males, and 3 were undetermined. In five
instances, 2 additional conspecifics were found with a focal snake (for a total of 3 seen
Copperheads). We did not find rural Copperheads with conspecifics frequently, because
there were fewer focal animals, and males spent a majority of the non-breeding active
season in dense vegetation. We observed focal females with a male conspecific 3 times
and never with other females. We found focal males with a female 4 times and another
male 1 time. In all instances, only 1 other conspecific was present.
Male snakes generally weighed more than non-gravid female snakes (Fig. 2A; Table 2),
and urban snakes weighed less than rural snakes. Similarly, male snakes were longer than
female snakes (Fig. 2B), and urban snakes were shorter than rural snakes. Males had lower
SMI than females (Fig. 2C), but there were no differences by location. Home range size
(MCP) was not related to body condition (F1, 32 = 0.06, P = 0.81), mass (F1, 38 = 0.93, P = 0.34),
or length (F1, 38 = 2.0, P = 0.17) when modeled with sex, location, and year. To maintain parsimonious
models, these morphological indices were not included in further analyses. Morphology
metrics are summarized in Supplemental Table 1 (in Supplemental File 1, available
online at: https://eaglehill.us/URNAonline2/suppl-files/urna-175-Carrasco-Harris-s1.pdf).
Home Range
We tracked 19 males and 17 females (n = 36) at the urban forest and 6 males and 2
females (n = 8) at the rural forest. Summary and spatial data for individuals tracked from
2015–2018 are provided in Supplemental Tables 2 and 3 (in Supplemental File 1). We did
not find differences in home range size (MCP) between non-gravid (n = 13) and gravid (n
= 6) females (F1, 17 = 1.26, P = 0.28), and we conducted all statistical analyses with females
pooled to improve balance. We found males had larger home range sizes using the 95%
LoCoH method, but not by the MCP or 95% KDE methods, and larger core areas by 50%
KDE and LoCoH methods (Fig. 3; Table 3; Supplemental Table 4, in Supplemental File 1).
Urban animals had significantly smaller home ranges and core areas than rural animals, and
estimates did not differ by year (Table 3).
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We compared home ranges (MCP) by sex and location with other rural Copperhead
population spatial ecology studies (Table 4). We found a significant difference between
home ranges by location (F4, 85 = 30.8, P < 0.001), sex (F1, 85 = 23.7, P < 0.001), and their
interaction (F4, 85 = 2.87, P < 0.05; Fig. 4). Pairwise comparisons between locations by sex
revealed urban Overton females had significantly smaller home ranges than rural female
snakes from Alabama, Connecticut, and Meeman (all pairwise comparisons P < 0.05) but
not Nebraska (P = 0.29). Urban Overton male snakes had significantly smaller home ranges
than rural males from Alabama, Connecticut, Meeman, and Nebraska (all pairwise comparisons
less than P < 0.001).
Table 2. Results of linear models of morphological metrics for Copperhead snakes at urban Overton Park and
rural Meeman Biological Station: mass, snout-vent length (SVL), and scaled mass index (SMI).
Effect F df P
Mass
Sex 4.23 1, 198 <0.05
Location 16.5 1, 198 <0.001
SVL
Sex 5.39 1, 197 <0.05
Location 12.6 1, 197 <0.001
SMI
Sex 5.48 1, 197 <0.05
Location 0.07 1, 197 0.78
Statistically significant values are indicated in bold.
Figure 2. Morphology metrics of Copperhead snakes at urban Overton Park and rural Meeman Biological
Station by location and sex. White diamonds denote means. (A) Mass in grams. (B) Snout-vent length in
centimeters. (C) Scaled mass index (SMI) in grams. Dashed line represents mean SMI (87.8 g).
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Figure 3. Home range models of Copperhead snakes at urban Overton Park and rural
Meeman Biological Station by location and sex. All home range area measurements in
hectares. White diamonds denote means. (A) 100% minimum convex polygon (MCP)
home range. (B) 95% kernel density estimator (KDE) utilization distribution. (C) 50%
KDE utilization distribution. (D) 95% local convex hull (LoCoH) utilization distribution.
(E) 50% LoCoH utilization distribution.
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Table 3. Results of linear models of home range and core area sizes.
Effect F df P
MCP
Sex 2.24 1, 39 0.14
Location 39.6 1, 39 <0.001
Year 1.74 2, 39 0.19
KDE 95%
Sex 3.76 1, 39 0.06
Location 33.8 1, 39 <0.001
Year 0.88 2, 38 0.42
KDE 50%
Sex 4.51 1, 39 <0.05
Location 22.7 1, 39 <0.001
Year 0.84 2, 39 0.44
LoCoH 95%
Sex 4.50 1, 39 <0.05
Location 21.1 1, 39 <0.001
Year 2.35 2, 39 0.11
LoCoH 50%
Sex 5.39 1, 39 <0.05
Location 19.7 1, 39 <0.001
Year 2.08 2, 39 0.14
Statistically significant values are indicated in bold.
Table 4. Minimum Convex Polygon (100% MCP) home range models by studies. Mean (SE) expressed in
hectares.
Location Sex N MCP
AlabamaA M 16 12.0 (1.9)
F 6 5.6 (1.7)
ConnecticutB M 10 17.5 (3.8)
F 8 5.0 (1.7)
Meeman M 6 12.1 (1.8)
F 2 7.4 (1.2)
NebraskaC M 5 9.3 (1.5)
F 6 2.7 (0.7)
Overton M 19 1.8 (0.3)
F 17 1.2 (0.2)
A Sutton et al. 2017, B Smith et al. 2009, C Rodriguez 2010
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Movement
We summarized movement by total distance moved, daily movement, and movement
per relocation sampling (MPS; Supplemental Table 5, in Supplemental File 1). Non-gravid
and gravid females did not differ in total distance moved and were kept as 1 group (F1, 17 =
3.11, P = 0.10). As anticipated, the number of relocations per individual partially explained
total distance moved (Table 5). Our analyses found male snakes moved more overall (total
distance), per day, and per sampling than female snakes (Fig. 5; Table 5). Rural snakes also
generally moved more than urban snakes. We found a year effect on daily movement and
MPS. Pairwise comparisons showed a difference in daily movement between all years (P <
0.05) and less MPS in 2015 compared to 2016 (P < 0.05; other pairwise differences > 0.05).
We suggest this finding is probably an artifact of not having subjects from the rural forest
during 2015 (Fig. 5).
We analyzed monthly movement by sex, location, and month, controlling for year and
individual. Non-gravid and gravid females were kept as 1 group (F1, 15 = 1.62, P = 0.22). We
found male individuals moved more than females (F1, 37.1 = 7.8, P < 0.01), and urban snakes
moved less than rural snakes per month (F1, 35.5 = 30.8, P < 0.001). The effect of month (F8,
289.5 = 7.7, P < 0.001) and its interaction with sex were also significant (F8, 289.8 = 2.7, P <
0.01). Pairwise comparisons between consecutive months indicated there were significant
differences in movement between the months of April–May, May–June, August–September,
September–October, and October–November (all pairwise comparisons P < 0.05). April–
May and August–September are important breeding months for Copperheads in this area.
Pairwise comparisons of month and sex suggested that males moved more than females in
August and September (P < 0.05). We also found a year effect (F2, 36.5 = 4.2, P < 0.05), and
pairwise comparisons showed less movement in 2015 compared to 2016 (P < 0.05; other
pairwise differences > 0.05). We believe this finding is due to the lack of rural snakes during
the 2015 season.
Figure 4. Differences in Copperhead snake mean minimum convex polygon (MCP) home range with 95%
confidence intervals by study location (urban Overton Park and rural Meeman Biological Station) and
sex. Home ranges were natural log transformed. Rural NE – Nebraska; CT – Connecticut; AL – Alabama.
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Table 5. Results of linear models of movement metrics: total distance moved, daily movement, and average
movement per sampling.
Effect F df P
Total Distance
Number of relocations 89.1 1, 38 <0.001
Sex 9.65 1, 38 <0.01
Location 51.8 1, 38 <0.001
Year 2.88 2, 38 0.07
Daily Movement
Sex 5.26 1, 39 <0.05
Location 21.5 1, 39 <0.001
Year 23.3 2, 39 <0.001
Movement per Sampling
Sex 7.87 1, 39 <0.01
Location 38.0 1, 39 <0.001
Year 3.84 2, 39 <0.05
Statistically significant values are indicated in bold.
Figure 5. Movement metrics of Copperhead snakes at urban Overton Park and rural Meeman Biological
Station by location and sex. White diamonds denote means. (A) Average total distance moved. (B) Average
daily movement and (C) average movement per sampling (MPS) also represented by year, as effect
was significant.
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Discussion
We conducted a longitudinal radio telemetry study comparing the morphology and spatial
ecology of Copperhead snakes living within an urban forest fragment and a rural forest.
To our knowledge, this is the first detailed radio telemetry study conducted with Copperhead
snakes in an urban forest remnant. Because of their widespread distribution, habitat specificity,
and observed sensitivity to human disturbance, Copperheads may be a valuable and
accessible model reptile species (Caro and O’Doherty 1999). This new understanding of
their spatial ecology in an urban forest fragment provides a baseline for future urban reptile
studies.
Morphology
We did not find lower body condition (scaled mass index) for snakes in the urban forest
compared to those in the rural forest. Body condition is a non-destructive measure of
the energy capital of an animal and, therefore, an indicator of health and ability to obtain
resources (Peig and Green 2009). Further, body condition is a predictor for reproductive
effort in male snakes and ability in females (Aubret et al. 2002, Lind and Beaupre 2015,
Lind et al. 2016, Naulleau and Bonnet 1996). We did not find evidence suggesting that the
urban Copperheads were experiencing nutritional deficiencies. Some studies have shown
decreased body condition in animals living in or near disturbed environments (Lazic et al.
2017, Lomas et al. 2015, Prange et al. 2003). Other studies have shown animals in disturbed
areas exhibit similar or increased body condition compared to rural conspecifics, an effect
perhaps attributable to resource availability (Bókony et al. 2012, Laverty et al. 2016, Martin
et al. 2017, Meillère et al. 2015, Wright and Fokidis 2016). This explanation is likely
the case in our research, but it warrants further study on available food sources within the
urban site. Broadly, these differences suggest some animals are better able to cope with urban
environments, although the nature of the disturbance is not uniform in all urbanization
studies (Meillère et al. 2015). However, studies that use condition indices from ordinary
least-squares residuals may not be as reliable as those using scaled mass indices (Peig and
Green 2010). In fact, results can be contradictory within the same dataset depending on
index (Bókony et al. 2012, Liker et al. 2008), confounding generalizations about the effects
of urban disturbance when body conditions are measured using different metrics. Multiple
behavioral and physiological metrics are important to develop a holistic understanding of
the organism.
Although the relative ratio between mass and length (SVL) did not differ between the
Copperhead populations, we did find the urban snakes were smaller in both of those metrics.
Previous studies have shown urban animals tend to be smaller than their non-urban counterparts
(Lomas et al. 2015, Wolfe et al. 2018a), with some exhibiting no difference in body
condition (Bókony et al. 2012, Meillère et al. 2015). In vipers, body length is a predictor
for male reproductive success (Levine et al. 2015, Schuett 1997) and for female reproductive
maturity and litter size (Ernst 1992, Holycross and Goldberg 2006, Lind et al. 2016).
Copperheads are viviparous, and fat storage and length (SVL) are important indicators of
frequency of female reproduction (Aubret et al. 2002, Fitch 2003, Holycross and Goldberg
2006). Hence, smaller body size could decrease lifetime reproductive ability (Halliday and
Verrell 1988) and should be investigated in future urban population studies.
There are several potential, non-mutually exclusive explanations for why our urban
snakes were smaller than rural conspecifics. First, diets may differ between the populations.
Copperheads are generalists and will eat a variety of animals, including ecto- and endoUrban
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thermic prey (Ernst and Ernst 2011). The Copperheads at our locations may have different
available prey (Fischer et al. 2012) or feed at different frequencies (Wolfe et al. 2018a).
Furthermore, Copperheads at the urban forest may not grow as quickly as their rural counterparts
(Hokit and Branch 2003, Moreno-Arias and Urbina-Cardona 2013), or population
demographics may be skewed toward younger age classes (Holland and Bennett 2010).
Without extensive survey work of animals followed since birth, it is difficult to determine
if the urban population is composed of younger snakes (Halliday and Verrell 1988). Finally,
genetic differences between the populations may be a contributing factor. In a concurrent
study, we found evidence for lower genetic diversity within the urban population (Carrasco-
Harris et al. 2020). Future work may consider the relationship between genetic diversity and
fitness metrics in urban populations (Szulkin et al. 2010).
Spatial Analyses
We found snakes at the urban forest had smaller home ranges and core areas than those
from the rural forest, as well as other previously studied populations of Copperheads. Further,
urban snakes moved less in all movement metrics compared to rural snakes. One possibility
is that snakes in the urban forest (57 ha) had smaller home ranges than snakes in the rural
forest (252 ha) because there is less area in which to have a typical home range. However, the
MCPs of Meeman rural snakes ranged from 4.7–16.7 ha. The urban home range could have
been as large as that of a rural snake and still fit within the suitable habitat of Overton. This
finding suggests the urban snakes may modify spatial behavior in this forest, tolerating human
disturbances to succeed in this environment (Lowry et al. 2013). Sex-based differences
for home ranges and movement patterns were anticipated (Smith et al. 2009, Sutton et al.
2017), although the differences between males and female were less pronounced at the urban
forest. Seasonal changes in activity in the spring and late summer were also expected, as it
has been previously noted that southeastern Copperheads mate twice a year (Aldridge and
Duvall 2002, Ernst and Ernst 2011). Urban subjects may have smaller home ranges and core
areas because of denser food availability (Wasko and Sasa 2012), predator release (Steen et
al. 2014), human disturbance (Beale et al. 2016), or a combination of circumstances.
Our results align with other studies in disturbed or fragmented environments. Studies
have shown snakes adjust to human disturbance by altering movement patterns and remaining
concealed more frequently (Beale et al. 2016, Lomas et al. 2019, Pattishall and Cundall
2008). Others have shown snakes decrease home range size in fragmented areas, including
those that interface with human development (Breininger et al. 2011, Mitrovich et al. 2009).
In contrast, some snakes and other reptiles do not exhibit movement differences in smaller
fragments surrounded by urban areas, in particular if these fragments meet the minimum size
required for persistence, the species is not territorial, or the animal is able to use urban or
edge habitats (Anguiano and Diffendorfer 2015, Kwiatkowski et al. 2008, Row et al. 2012).
These findings suggest that some urban-persisting reptiles with limited dispersal capacity
exhibit behavioral plasticity in modified environments and others may not. Although a
translocation study would be useful to test behavioral plasticity, translocated snakes often increase
movement compared to residents and may have greater mortality (Wolfe et al. 2018b).
Further research should investigate the costs and benefits of plasticity in animals that persist
within or near the urban interface (French et al. 2018, Lomas et al. 2015, Mitchell 1998).
Limitations
Some limitations of our study are having a smaller sample size at the rural forest than
at the urban forest and having only 2 years of data for rural snakes compared to 3 years for
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2020 No. 35
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urban snakes. Movement differences by year were most likely an artifact of the addition of
the rural site in 2016. Because of the cryptic nature of Copperheads, we had difficulty finding
suitable adults at this location. When tracking in the urban forest, it was not uncommon
to find adult conspecifics near the focal subject. At our rural site, focal males were found
primarily during the spring breeding season. During the summer, males were tracked in a
field of native Ambrosia trifida Linnaeus (Giant Ragweed) and invasive Pueraria montana
(Loureiro) Merrill (Kudzu), and a trail system had to be blazed to triangulate the animals
during relocations. It was very unlikely we were going to capture new snakes in these conditions.
Unequal sample sizes are often unavoidable in observational ecological studies.
Differences by sex depended on the model, but there are limitations in these comparisons
because of the small female sample size at the rural forest. Differences by reproductive
status have been previously noted but were not found to be significant in our study. First, the
limited sample size of females at the rural forest (1 gravid, 1 non-gravid at capture) hindered
our ability to determine if differences exist between reproductive and non-reproductive
females within and between locations. Further, reproductive females may have been falsely
identified as non-gravid if caught early in the season. Checking reproductive status by palpating
would mean regular handling of all snakes. We avoided intrusive handling that may
have led to physiological responses (Bailey et al. 2009, Schuett et al. 2004) and potential
behavior changes in focal subjects. After transmitter implantation, animals were only captured
to remove the transmitter or if there was an apparent medical reason related to the
surgery (Supplemental Table 2, in Supplemental File 1).
We acknowledge the study is limited by having 1 urban forest and 1 rural comparison
site with fewer individuals. If resources permit, research on the relationship between urbanization
and behavior should include more urban forests, allowing for greater generalizations.
However, urban forests may differ in degree of recreational usage and trails, fragment
size, surrounding urbanization density, and climate zones. Studies that include multiple
urban sites should standardize for location differences and acknowledge each fragment’s
unique characteristics (Moll et al. 2019). Our results should be taken as a case study and in
consideration with previous research on urban snake populations.
Conclusions
Our study provides detailed analysis of the morphology and spatial ecology of a persisting
Copperhead population isolated in an urban forest fragment. As urbanization continues,
it is likely that natural areas will become surrounded by development and possibly set
aside for human recreation. Natural areas that maintain structural complexity harbor native
reptiles that would otherwise be excluded from the urban matrix (Alvey 2006, Hamer and
McDonnell 2010, Harden et al. 2009, Vanegas-Guerrero et al. 2016). Research aimed at
understanding urban forests is important for understanding how animals in these fragments
persist and how land managers can best maintain habitats for both human recreation and
biodiversity (Bonnet et al. 2016, Garden et al. 2010).
Acknowledgements
We are grateful for field assistance from Chris Baker; the Memphis Zoo herpetarium staff; undergraduate
assistants from the University of Memphis, Christian Brothers University, and Rhodes
College; and Jeremy Harris. We thank Dr. Felicia Knightley and the Memphis Zoo veterinary staff for
conducting all surgeries on subjects. We also wish to acknowledge the Overton Park Conservancy and
Meeman Biological Station for their cooperation throughout this research. This work was supported
by a grant from the Memphis Zoological Society Conservation Action Network awarded to SR and
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MCH and a National Science Foundation Graduate Research Fellowship to MCH. All research was
conducted under the Tennessee Wildlife Resources Agency Permit #3852 and Memphis Zoo Institutional
Animal Care and Use Committee #15201. All data analyzed for this study are available through
the Movebank Repository available at: https://doi.org/10.5441/001/1.1rs3j824
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