Variation in Deuterium Levels of Non-migratory Eptesicus
fuscus (Big Brown Bat) along the Delmarva Peninsula
Brittany Elizabeth Sturgis, Armando Alberto Aispuro, and Kevina Vulinec
Northeastern Naturalist, Volume 26, Issue 1 (2019): 202–213
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B.E.Sturgis, A.A. Aispuro, and K. Vulinec
22001199 NORTHEASTERN NATURALIST 2V6(o1l). :2260,2 N–2o1. 31
Variation in Deuterium Levels of Non-migratory Eptesicus
fuscus (Big Brown Bat) along the Delmarva Peninsula
Brittany Elizabeth Sturgis1,2, Armando Alberto Aispuro1,3, and Kevina Vulinec1,*
Abstract - Stable-isotope analysis can address fundamental questions about the ecology
and life history of mobile organisms. The hydrogen isotope, deuterium (δ2H), follows
distinct and predictable patterns along environmental gradients, enabling migratory-origin
assignments in vagile animals such as bats. However, it is unclear to what degree deuterium
levels vary within non-migratory bat populations in fixed areas. To understand this, we compared
deuterium signatures among adult female bats in maternity colonies of non-migratory
Mid-Atlantic Eptesicus fuscus (Big Brown Bat). We sampled from 5 different locations
along the Delmarva Peninsula. We also compared differences in signatures between males
and females within colonies. Despite relative proximity to each other, deuterium signatures
of females among colony locations differed significantly. Deuterium signatures did not
differ among males and females or between 2010 and 2011. We suggest that variation in
foraging and roosting behavior, as well as changes in water sources along the peninsula
influence deuterium levels on a small geographic scale. These and other factors should be
considered when interpreting sampled deuterium levels.
Introduction
Bats play an integral role in the functioning of ecosystems in the northeastern
US, but face several threats including white-nose syndrome transmission and windturbine
collisions (Frick et al. 2010, Kunz et al. 2007). Because of these threats,
it is imperative to better understand bat-movement patterns (Sullivan et al. 2012)
and roosting ecology. Mark–recapture, radio-tracking, and indirect methods used to
study night-flying animals have primarily yielded an understanding of bat behavior
at local scales (Cryan et al. 2004, Limpert et al. 2007). Stable-isotope analysis can
be used to supplement these conventional techniques and provide a more precise
picture of regional bat ecology (Britzke et al. 2012, Cryan et al. 2012, Hobson and
Wassenaar 1997, Rubenstein et al. 2002).
Deuterium (δ2H), an isotope of hydrogen, is a particularly convenient tool for
assessing movement patterns. Rainwater concentrations (or signature) of δ2H vary
predictably across North America; rainwater in the Southeast is depleted of δ2H
relative to rainwater in the Northwest (reviewed in Hobson 1999). This pattern is
related to the clinal variation in growing-season precipitation across the landscape
1Department of Agriculture and Natural Resources, Delaware State University, Dover,
DE 19901-2277. 2Current address - Delaware Department of Natural Resources and Environmental
Control, 100 West Water Street, Suite 6B, Dover, DE 19904. 3Konrad Lorenz
Institute of Ethology, University of Veterinary Medicine Vienna, Savoyenstraße 1a, A-1160
Vienna, Austria. Corresponding author - kvulinec@desu.edu.
Manuscript Editor: Adrienne Kovach
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and the resulting patterns of hydrogen isotopes within the vegetation. These isotopes
are in turn detectable in animals at higher trophic levels (Cormie et al. 1994)
and can be used to infer relative geographic positions of sampled-tissue origins.
This technique has been widely and successfully used to elucidate breeding and
natal origins of migratory bats and birds sampled away from those sites (e.g., Cryan
et al 2004, Fraser et al. 2012, Hobson 2005, Popa-Lisseanu et al. 2012). However, it
remains unclear how much variation in δ2H isotopic signatures should be expected
within highly vagile but non-migratory animals. A potential confounding factor in
understanding life histories may exist if δ2H variation in migratory bats is different
from that of non-migratory bats.
Cryan et al. (2012) found that urban bats from proximate roosting sites in
Colorado had high within-species δ2H variation, though mean values for 2 maternal
nesting colonies were not significantly different. Voigt et al. (2013) also found
a high degree of within-species δ2H variation among bats in tropical Costa Rica,
though in addition they found significant differences in mean δ2H values between
maternal nesting colonies. These results came from a large city and tropical forest,
respectively, and they may not be representative of a semi-rural region in the Mid-
Atlantic states. Furthermore, it is unknown if the sources of this variation (such as
sex, age, year, or season) are similar between geographically distant populations.
Therefore, we investigated factors that may contribute to variation in δ2H concentrations
of non-migratory bats within the Delmarva Peninsula. Understanding
variation among colonies and among years may allow for better identification of
roosting sites or reveal the inability to determine sites if the variation among sites
or years is too large.
We analyzed the δ2H signatures of bat fur in Eptesicus fuscus (Palisot de
Beauvois) (Big Brown Bat), a non-migratory bat in Delaware, Maryland, and
Pennsylvania. In the US, Big Brown Bats do not travel far to their winter roosts
(usually not more than 80 km) and the species is considered non-migratory
(Neubaum et al. 2006). These bats go through an annual molt at their roosting
site in mid- to late summer (Fraser et al. 2013), when new fur is grown and local
δ2H signatures are incorporated (Britzke et al. 2009; Cryan et al. 2004, 2014).
We compared the δ2H signature of Big Brown Bat fur (1) between males and females,
(2) among females from 5 maternity colonies, and (3) between 2010 and
2011. Following Cryan et al. (2012), we expected to find differences between
males and females, but we did not expect substantial variation among the maternity
colonies or between years because of the non-migratory behavior of Big
Brown Bats. The δ2H signatures for individuals and maternity colonies may help
determine patterns in local variation in δ2H of a non-migratory but highly vagile
bat species. Understanding the extent of local δ2H variation in non-migratory
bats on the Delmarva Peninsula may improve the efficacy of using δ2H as an intrinsic
marker, especially in the context of migratory-origin assignments (Langin
et al. 2007, Voigt et al. 2013).
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Methods
Study sites
The Delmarva Peninsula is characterized as a low-lying, semi-rural landscape in
a matrix of abundant agricultural land with natural parks and few large population
centers. Study sites (Fig. 1, Appendix A) consisted of known bat maternity colonies
(K. Vulinec and B.E. Sturgis, pers. observ.; H. Niederriter, Delaware Department of
Natural Resources and Environmental Control [DNREC], Dover, DE, pers. comm.).
Field methods
We conducted our fieldwork during the 2010 and 2011 maternity season (April–
June) by netting bats from maternity colonies throughout Delaware and 1 location
in Pennsylvania (Fig. 1). We captured bats with mist nets or harp traps positioned at
colony egresses (Kunz and Fenton 2003). We erected nets or traps ~15 min prior to
dusk and left them operational for ~3 h, checking nets every 15 min. We followed
the protocol for capturing and handling live bats as established by the American
Society of Mammalogists (Sikes and Gannon 2011). The Delaware State University
Institutional Animal Care and Use Committee (IACUC) approved these methods
in 2010. We wore latex gloves during bat handling to reduce possible white-nose
syndrome contamination, according to the National White-Nose Syndrome Decontamination
Protocol (USFWS 2010).
Once bats were removed from the net, we placed individuals in separate, numbered,
brown paper bags. We recorded species, weight, age, sex, wing health, and
Figure 1. Big Brown Bat sampling locations in Delaware and Pennsylvania in 2010 and
2011. Appendix A identifies the labels and the corresponding location coordinate s.
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trapping location. We considered individuals that were born the year of sampling
to be juveniles, as determined by examining the metacarpal-phalangeal joint. Juvenile
joints are less calcified and more cartilaginous when compared to adults
(Brunet-Rossinni and Wilkinson 2009). We then cut a fur sample as close to the
skin as possible from the dorsal region between the scapulae, placed it in a labeled
plastic 1.5-ml microcentrifuge tube, and stored tubes in a dry location for further
laboratory processing.To avoid confusing molting periods and new fur growth on
juveniles, we excluded juveniles and all captures after the first week of July from
the analysis (Cryan et al 2012).
Stable-isotope analysis
Fur samples were analyzed at the Colorado Plateau Stable Isotope Laboratory
(CPSIL) at Northern Arizona University with an isotope mass-spectrometer using
standardized methods. All stable hydrogen-isotope (δ2Hfur) values from fur were
reported in parts per thousand (‰) relative to the internationally accepted Vienna
Standard Mean Ocean Water (VSMOW). Six in-house standards were used as part
of the quality-assurance protocol at the Colorado Plateau Stable Isotope Laboratory,
including Rangifer tarandus (L.) (Caribou) hoof, Tragelaphus strepsiceros
(Pallas) (Kudu) horn, Alces alces (L.) (Moose) hair, Cervus canadensis (Erxleben)
(Elk) hair, Urus arctos (L.) (Grizzly Bear) hair, and Meleagris gallopavo L. (Wild
Turkey) feathers. Our bat-fur samples were analyzed alongside these standards, and
their δ2Hfur signatures were standardized to VSMOW using comparative equilibration
techniques (Wassenar and Hobson 2003). The CPSIL lab uses keratin standards
throughout their sample runs as a measure of within-run precision. Samples that had
very little material were analyzed alongside a series of standards at similarly low
weights to determine if the chromatography was accurate (Britzke et al. 2009, 2012;
Cryan et al 2004; Fraser et al. 2012; Popa-Lisseanu et al. 2012).
Discrimination factors account for the observed difference between source and
tissue isotopic signatures (Del Rio et al. 2009). Discrimination factors have been
used to correct isotope data in order to make it comparable across groups. We analyzed
raw data because we do not have an experimental basis for discrimination
factors and because these values for Big Brown Bat on the Delmarva Peninsula are
not known (Cryan et al. 2012). This approach likely did not influence our results
because we sampled and analyzed the same tissue type from the same species.
Therefore, comparisons within this defined group are not influenced by correction.
Statistical analyses
We performed statistical analyses in version 25 of IBM SPSS Statistics software
(SPSS Inc. 2017). We fit a general linear model (GLM; UNIANOVA) to compare
adult female’s δ2Hfur signatures among locations and between years. Following Cryan
et al. (2012), we excluded from the location analysis juveniles, males, and bats
not caught at the maternity colonies’ egress in order to determine a more accurate
picture of the δ2Hfur levels of non-migratory Big Brown Bat maternity colonies. We
excluded outliers of less than 20‰ as samples with inadequate material. Data on other bats
and juvenile Big Brown Bats are available in Sturgis (2013).
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δ 2H values did not deviate from normal (Kolmogorov–Smirnov: P = 0.200) and
the variances were homogeneous (Levene’s test for mean and median = 0.750);
therefore, we used a generalized linear model (GLM) with a normal distribution to
examine differences of adult female δ2Hfur values among locations and years, with
location and year as fixed effects. The interaction of location*year was not significant
and so we removed this interaction from the model. We used Type III sum of
squares and pairwise comparisons of the estimated marginal means of locations
through least significant differences (LSD) for multiple comparisons. We assessed
effect sizes using the proportion of variation explained for a certain effect ([effect
SS] / [effect SS + error SS]). This statistic is analogous to R2 in multiple regression
and is used to examine effect size when there is more than 1 independent variable.
A partial Eta squared value >0.2 is considered a large effect (Fritz et al. 2012). We
employed a GLM to examine the difference between δ2Hfur values of males and
females captured from the same maternity colonies.
Results
We collected and analyzed 55 fur samples in 2010 and 54 fur samples in 2011
from females, for a total of 109 samples for both years (Appendix B). We also
collected and analyzed the fur from 16 males during 2010. No samples from
males were collected during 2011. A table of all sampled individuals is provided
in Supplemental File 1 (available online at http://www.eaglehill.us/NENAonline/
suppl-files/n26-1-N1644-Vulinec-s1, and, for BioOne subscribers, at https://
dx.doi.org/10.1656/N1664.s1).
The mean δ2Hfur for adult females caught at maternity colonies (-44.76‰, SD
= 9.67, n = 109) did not differ significantly from the mean for adult males at the
same maternity colonies (-42.82‰, SD = 6.20, n = 16) (Sex: F = 0.607, df = 1, P =
0.437).
δ 2Hfur values of Big Brown Bat adult females differed significantly among maternity-
colony sites located throughout the study area (F = 7.286, df = 4, P < 0.001;
partial Eta squared = 0.221; Table 1, Fig. 2). Pairwise comparisons of the estimated
marginal means by LSD procedure (Table 2) revealed no differences among Dover
and Georgetown, Killens Pond and White Clay Creek, and White Clay Creek and
Bellevue (Fig. 2). The greatest differences were between and White Clay Creek
and Georgetown (P < 0.001) and Bellevue and Georgetown (P < 0.001); the latter
2 sites were the farthest apart (Fig. 1).
Table 1. General linear model tests of between-subjects effects with the dependent variable, deuterium.
Test of effect size (partial Eta squared) is included.
Partial
Source Sum of squares df Mean square F P value Eta squared
Location 1788.035 4 447.009 7.286 less than 0.001 0.221
Year 0.750 1 0.750 0.012 0.912 0.000
Error 6319.317 103 61.353
Total 228524.620 109
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δ2Hfur values did not change significantly between both study seasons for Big
Brown Bat (F = 0.012, df = 1, P = 0.912). Mean δ2Hfur in 2010 was -49.02‰ (SD =
9.82; n = 55) and in 2011, mean δ2Hfur was -40.43‰ (SD = 7.40; n = 54).
Discussion
We compared the effect of sex, population location, and year on the δ2H signature
of Big Brown Bat fur on the Delmarva Peninsula. We collected fur in the same
general geographic region for all individuals and established a baseline for expected
variation of a non-migratory bat in the region. The variation in δ2H of a population
has been described by Cryan et al. (2012) for the same species in a western urban
center. Here we report similarly high levels of variation in a much different habitat
type.
Big Brown Bats are non-migratory, opportunistic and generalist feeders, and
rarely move farther than 80 km between their summer and winter roosting sites
(Mills et al. 1975, Sullivan et al. 2006). The generalist feeding style of Big Brown
Bats probably explains some of the variation in δ2H signatures of fur observed
in this study, as was also suggested by Cryan et al. (2012) in a Colorado urban
center. The δ2Hfur signatures for Big Brown Bats were within the range associated
with precipitation signatures in Delaware and the surrounding areas (Meehan et al.
2004), supporting the proposed relationship between the δ2H signatures of fur in an
Figure 2. δ2Hfur values of female Big Brown Bats in 5 locations sampled in 2010 and 2011.
Boxes enclose the 25th to 75th quartiles. Central line indicates median and whiskers encompass
the range of the data. The circle represents an outlier (extreme values that fall more
than 1.5 interquartile ranges beyond the 25th and 75th percentile). Boxes sharing a letter are
not significantly different. Sample sizes for each location are below the location n ame.
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insectivorous bat and local water sources (Popa-Lisseanu et al. 2012). Therefore,
while foraging behavior may cause high variation in δ2Hfur signatures for this species,
these values appear to be primarily influenced by local wa ter sources.
Big Brown Bat δ2Hfur values were very different from those reported by Cryan
et al. (2012), perhaps partially related to differences in geographic variation of δ2H.
Adult males captured in mid-Atlantic maternity colonies did not differ significantly
from females, contrary to findings of Cryan et al. (2012) of sex-related δ2Hfur patterns
in a western urban center that is likely more chemically complex than our
semi-rural mid-Atlantic sites. Our results showing no difference between males and
females may be due to small sample size of males or potentially because males and
females have similar foraging behaviors on the Delmarva Peninsula.
We found differences in the δ2Hfur signatures among maternity colonies within
the Delmarva Peninsula. This finding is in contrast to prior work showing that,
while there may be large differences in the δ2H levels among individual bats within
a relatively small geographical area (9.25 km maximum distance), there was no
significant difference in the mean level between 2 Colorado maternity colonies
(Cryan et al. 2012). Different results came from a study in Costa Rica by Voigt
et al. (2013), who found a large variation (20‰) in the δ2H makeup of sedentary
neotropical bats from 2 colonies 4 km apart. Our study sites were up to 100 km
apart (Fig. 1), therefore greater differences might be expected among our colonies
Table 2. Pairwise comparisons of female Big Brown Bat mean δ2Hfur values among 5 locations
sampled in Delaware and surrounding areas in 2010 and 2011, based on estimated marginal means.
An asterisk (*) indicates that the difference in mean δ2Hfur values is significant at the 0.05 alpha level..
95% CI = 95 % confidence interval for differrence.
Mean 95% CI
difference Std Lower Upper
Location I Location J (I - J) error P-value Bound Bound
Dover, DE Georgetown DE -7.951 4.070 0.053 -16.024 0.121
Killens Pond 7.190* 3.085 0.022 1.072 13.308
Bellevue 13.178* 2.656 0.001 7.911 18.445
White Clay Creek Preserve 9.301* 3.159 0.004 3.036 15.567
Georgetown DE Dover, DE 7.951 4.070 0.053 -0.121 16.024
Killens Pond 15.141* 5.091 0.004 5.045 25.238
Bellevue 21.129* 4.831 0.001 11.548 30.711
White Clay Creek Preserve 17.253* 5.136 0.001 7.066 27.440
Killens Pond Dover, DE -7.190* 3.085 0.022 -13.308 -1.072
Georgetown DE -15.141* 5.091 0.004 -25.238 -5.045
Bellevue 5.988* 2.863 0.039 0.311 11.665
White Clay Creek Preserve 2.111 3.270 0.520 -4.373 8.596
Bellevue Dover, DE -13.178* 2.656 0.001 -18.445 -7.911
Georgetown DE -21.129* 4.831 0.001 -30.711 -11.548
Killens Pond -5.988* 2.863 0.039 -11.665 -0.311
White Clay Creek Preserve -3.877 2.943 0.191 -9.712 1.959
White Clay Creek Dover, DE -9.301* 3.159 0.004 -15.567 -3.036
Preserve Georgetown DE -17.253* 5.136 0.001 -27.440 -7.066
Killens Pond -2.111 3.270 0.520 -8.596 4.373
Bellevue 3.877 2.943 0.191 -1.959 9.712
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than those in the study of Voigt et al. (2013); yet we found similar differentiation
of δ2Hfur values among colonies to those in Costa Rica (largest δ2Hfur differences approximately
20‰; Appendix B). The δ2Hfur variance may be attributed to 2 different
factors: the local water sources may have different δ2Hprecipitation levels because of
the surrounding landscape or maternity colonies may have different diets and food
preferences (Agosta 2002).
The Piedmont and Coastal Plain regions make up the 2 physiographic regions
found in Delaware and the surrounding areas. The Piedmont is found in the hilly
northernmost part of the state where the parent material is made up of metamorphic
and igneous rocks. Conversely, the Coastal Plain physiographic region covers
most of the state and is flatter and underlain with Appalachian sediments that are
relatively young (Polsky et al. 2000). The difference in the surrounding geology
may change the groundwater signatures (Bowen et al. 2005), and that may alter the
stable δ2H signatures of bat fur within the locales. Furthermore, water composition
changes because of runoff and leaching, which may cause differences among localities
(Good et al. 2015). Our study revealed δ2Hfur signatures among Big Brown Bat
that showed considerable variation within and among maternity colonies. Two of
the locations with similar δ2Hfur profiles were on the Piedmont portion of the peninsula
(Bellevue and White Clay Creek Preserve). The other 3 locations were on the
Coastal Plain (structure in Dover, Killens Pond, and a residence in Georgetown).
Only 2 of these Coastal Plain locations showed slightly similar δ2Hfur levels—Dover
and Georgetown (P = 0.053). Both of these sites are heavily urbanized, while Killens
Pond is a wooded park set within a matrix of agricultural land. We suggest that
there is a difference of the δ2Hfur mean among locations because of differences in
local water composition (Kendall and Coplan 2001). In addition, the opportunistic
feeding ecology and generalist diet of this species probably contributed to relatively
wide variation in δ2Hfur values. As mentioned above, influence δ2Hfur levels may be
influenced by local diet, but we did not analyze stable isotopes in food sources to
relate it to δ2Hfur levels. The difference in δ2Hfur from insect diet and surface water
would be important to examine in future studies in this area (V oigt et al. 2013).
While variation can be extensive, bats of the northeastern US are assumed to
molt once a year during mid- to late summer (Fraser et al. 2015). For this reason, we
excluded any bats caught after 3 July. We did not find differences in δ2Hfur between
2010 and 2011 in Big Brown Bat females from maternity colonies. We collected fur
samples from 1 May through 3 July in 2010 and 11 April through 23 June in 2011.
We hypothesized that the mean δ2Hfur level might vary throughout the year as the
bats (1) migrated from their winter roosting sites or other locations or (2) molted
during the summer. The δ2Hfur level did not change between years, suggesting that
our methods avoided confounding molting with fur from the previous year. Furthermore,
as there was no interaction between locations and years, our results indicate
that individual female bats may return to different maternity colonies in the summer,
as is suggested in Vonhof et al. (2008).
Big Brown Bats appear to molt and grow new fur while in the Mid-Atlantic region.
The process to grow new fur is not well understood (Fraser et al. 2015), and
the timing of fur replacement may differ among individuals as well as species.
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While collecting fur samples, we noticed an overall “fuzzy” appearance of bats
throughout August. The fur also pulled out more readily than earlier in the season;
it was particularly easy to remove fur follicles in August compared to the April–
July period.
In conclusion, our study showed that (1) Big Brown Bats differ in δ2Hfur signatures
depending on where they roost, and (2) there is high regional δ2Hfur variation
within a small rural peninsular region of the northeastern US. We suggest that diet,
sex, age, water sourcing, roosting ecology, molting patterns, and thermoregulation
strategies may contribute to variation in δ2Hfur signatures of bats even at a small
local scale (Cryan et al. 2012, Weller 2009). Microsatellite and mitochondrial DNA
analyses of colonies showed complex genetic structure, suggesting that females
may not be as philopatric as previously thought (Vonhof et al. 2008). Accordingly,
intercolony migration may account for the wide variation in δ2H. These and other
pertinent ecological factors should be considered when using δ2H values to inform
bat ecology, especially in the context of migratory and colonizing patterns. Further
sampling of these 5 colonies, local water sources, and local insects may parse out
specific factors that influence bat δ 2H values.
Acknowledgments
This project was funded by Delaware State University and a USDA Evans–Allen grant
to K. Vulinec (PROJ NO: DELX0029-10-03). We thank Virginia Balke, Richard Barczewski,
Christopher (Kitt) Heckscher, Lori Brown, and Kimmi Swift for providing input on
this project and the manuscript. We also thank Megan Wallrichs, Kesha Braunskill, Ileana
Mayes, and Dr. Virginia Balke’s crew at Delaware Technical Community College. We thank
Holly Niederriter, Erin Adams, and volunteers with the Bat Program of the Delaware Department
of Natural Resources and Environmental Control. We thank the biologists from
Bombay Hook National Wildlife Refuge and the managers within the Delaware State Parks
(Killens Pond, White Clay Creek State Park, Bellevue State Park), and homeowners. We
extend special thanks to Matt Sturgis and Dave Mellow for continual help and support.
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Appendix A. Locations and latitude and longitude of bat-trapping sites on Delmarva.
Location Latitude and Longitude
Structure, Bellevue, DE 39°46'42.0024''N, 75°30'20.7612''W
Industrial structure, Dover, DE 39°9'42.822''N, 75°32'2.7528''W
Killens Pond State Park, Felton, DE 38°59'17.2104''N, 75°32'41.8128''W
House, Georgetown, DE 38°41'26.5704''N, 75°23'1.4244''W
White Clay Creek Preserve, London Britain, PA 39°44'16.7568''N, 75°46'0.9696''W
Appendix B. The year, location, mean, standard deviation, and sample size of stable
hydrogen-isotope signature (δ2H) of Big Brown Bat female individuals (n = 109) sampled
and analyzed in 2010 and 2011 at various trapping locations in Delaware and Pennsylvania.
Year Location Mean Standard deviation n
2010 Dover, DE -40.75 9.19 13
Killens Pond -48.23 7.86 12
Bellevue -54.41 7.27 19
White Clay Creek Preserve -50.34 10.44 11
Total -49.02 9.82 55
2011 Dover, DE -40.85 7.14 49
Georgetown DE -32.83 6.40 4
Bellevue -50.20 - 1
Total -40.43 7.40 54
Total Dover, DE -40.83 7.53 62
Georgetown DE -32.83 6.40 4
Killens Pond -48.23 7.86 12
Bellevue -54.20 7.14 20
White Clay Creek Preserve -50.34 10.44 11
Total -44.76 9.68 109