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2014 Aspects of the Trophic Ecology of an Invertivorous Snake Community Meagan Amanda Thomas Eastern Illinois University This research is a product of the graduate program in Biological Sciences at Eastern Illinois University. Find out more about the program.

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Please submit in duplicate. ASPECTS OF THE TROPHIC ECOLOGY OF AN INVERTNOROUS SNAKE COMMUNITY

BY

Meagan Amanda Thomas

THESIS

Submitted in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE in BIOLOGICAL SCIENCES

In the Graduate School, Eastern Illinois University

Charleston, Illinois

2014

We hereby recommend that this thesis be accepted as fulfilling this part of the graduate degree

cited above

Date

Date

Date 2014 Copyright by Meagan A. Thomas ABSTRACT

Understanding the significance of trophic links has been of interest to ecologists

for decades, likely because food web studies have the potential to reveal a considerable

amount of information in the fields of ecosystem and community ecology. Despite the intrinsic benefits that come from elucidating food web structures, doing so is often problematic because of the complex and dynamic nature of ecological communities. The dietary ecology of small-bodied invertivorous snakes remains relatively understudied

compared to other snake species. Many of these species are abundant throughout their range, making them ideal organisms for studying community-level questions. I

employed a combination of stable isotope analyses as well as gut and fecal material

analyses to quantify the trophic niche width of five species of invertivorous snakes

(genera: Coluber, Diadophis, Opheodrys, and Storeria) occurring in central Illinois. I

investigated seasonal differences in capture rates and quantified morphometric and isotopic differences among species. I used Bayesian mixing models to determine the

potential sources ofC13 and N 15 in scale, red blood cell, and plasmatissue samples. The

stable isotope data, supported by the gut and fecal analyses, revealed differences in the

levels of dietary specialization within the community. High levels of trophic niche

overlap were detected, however, indicating that snake dietary preferences are more likely

a product of taxonomic affinity and species specific life-history, rather than interspecific

competition. Further studies that involve a combination of techniques can provide a more

comprehensive understanding of dietary ecology within snake communities. DEDICATION

This thesis is dedicated to my amazing mother, Amanda Mary Schenning-for all those hours she spent at the kitchen table helping me with my chemistry homework. I would not be half the person I am today without her guidance and unwavering support.

ii ACKNOWLEDGMENTS

The completion of this thesis is, by no means, the result of my work alone.

Throughout the course of my time at Eastern Illinois University I have been lucky enough to be constantly surrounded with a fervent network of support. First and foremost, I would like to thank my committee members, Drs. Scott Meiners and Ann Fritz, as well as my advisor Dr. Stephen Mullin. I'm grateful to Dr. Meiners for awarding me unwavering patience, guidance, and time- which he always seemed to make for me, despite his busy

schedule. I'm also grateful to Dr. Ann Fritz, her knowledge of insect communities is

_extensive, and I greatly respect her work in behavioral ecology. In addition, this thesis would not be of the caliber it is without the help of my advisor Dr. Stephen Mullin. I have undoubtedly grown as a writer thanks to his unfaltering editorial eye, and as a researcher because of his constant encouragement to think outside my comfort zone. In addition to my committee members, I owe Dr. Richard Seigel an enormous amount of thanks for

identifying a passion for research within me throughout my undergraduate career, and

fostering my development as a scientist even to this day. I whole-heartedly thank all the

individuals who helped with field and lab work throughout this project- Elizabeth

Bauman, Sarah Baxter, Cynthia Carter, Anndria Cluster, Kylee Gochanour, Danelle

Grochocinski, Iwo Gross, Corissa Mantooth, Emily McCallen, Murphy Walters, and

Joseph Zigler. In particular, Joeseph Zigler and Kylee Gochanour dedicated dozens of hours of their free time to helping me process snakes, and prepare samples. Similarly,

Cynthia Carter, Iwo Gross, Corissa Mantooth, and Emily McCallen helped me not only

with research, but also kept me sane (relatively speaking, of course) throughout this

process, all of whom I consider lifelong friends. I must also thank Andrew Durso for the

iii help and inspiration he has provided me with in the past two years, without him I never would have considered pursuing stable isotope analyses for my thesis. I'm thankful for the faculty of the Biological Sciences Department at Eastern Illinois University and all of their logistical support. In particular, Sandra Baumgartner, Deborah Endsley, Marschelle

McCoy, and Megan Przygoda, who simplified my life with their generous help. I owe a

special thanks to Mike Masters of the Energy Biosciences Institute at the University of

Illinois for his collaboration, and for completing stable isotope analyses on my samples.

This study would not have been possible without permission from the Illinois Department of Natural Resources, specifically the personnel Fox Ridge State Park, who also assisted with construction and maintenance of drift fences. Funding was graciously awarded to me through teaching and research assistantships from Eastern Illinois University (EIU),

and a Graduate Student Investigator Award and two Research and Creative Activity

Grants from the Graduate School at EIU. Finally, I would like to thank my loving

boyfriend Clinton Morgeson, my parents, Amanda and Craig Schenning, and the

remainder of my family for their constant support, and never failing to let me lose sight

of the light at the end of the tunnel.

iv TABLE OF CONTENTS

List of Tables ...... vi

List of Figures ...... vii

Introduction ...... !

Natural History of Select Invertivorous Snakes ...... 3

Studying Snake Dietary Ecology ...... 6

Methods ...... 10

Study Site ...... 10

Field Methods ...... 10

Sample Preparation and Analyses ...... 13

Statistical Analyses ...... 13

Results ...... 16

Snake Collection ...... 16

Prey Collection ...... ,...... 17

Stable Isotope Analyses ...... 18

Discussion ...... 20

Natural History of the Community ...... 20

Gut and Fecal Surveys ...... 21

Stable Isotope Analyses ...... 23

Conclusions ...... 28

Tables ...... 31

Figures ...... 35

References ...... 48

v LIST OF TABLES

Table 1. Sex ratios of snakes collected from Fox Ridge State Park (Coles County,

Illinois) in 2012 and 2013. Activity season 1 contains individuals captured from 2 April to 26 October 2012, and activity season 2 contains individuals captured from 3 March to

30 October 2013 ...... 3 l

Table 2. Morphological characteristics (means ± 1 standard error) of snakes collected

from Fox Ridge State Park (Coles County, Illinois) in 2012 and 2013. Because there was

an insufficient number of juvenile snakes (other than Coluber constrictor), juveniles were

excluded from calculations involving snout-vent length, tail length, and mass ...... 32

Table 3. Morphological measurements for each sex of five species of colubrid snakes

collected at Fox Ridge State Park (Coles County, Illinois). Snout-vent length (SVL) and

tail length (TL) are reported in mm, whereas mass is reported in g; all values are means

±1 standard error. *denotes sexual· size dimorphism for that trait within the species

(ANqyA; p < 0.05) ...... 33

Table 4. Results of separate analyses of variance assessing differences in mean C13 values

(±1 standard error) between tissue samples for each of five species of species of colubrid

snakes collected from Fox Ridge State Park (Coles County, Illinois).

Different letters indicate significant differences in tissue type within each species; RBC =

red blood cell...... 34

vi LIST OF FIGURES

Figure 1. Relationship between Coluber constrictor snout-vent length (SVL) and isotopic

N 15 values from scale tissue samples. Hollow circles were excluded from all analyses, because these individuals were likely hatchlings reflecting maternal isotopic signatures ...... 35

Figure 2. Results of the gut content and fecal sample dissection surveys; (A) percentage of prey items detected in Coluber constrictor samples (Stde = Storeria dekayi); (B) percentage of prey items detected in Diadophis punctatus samples, (C) percentage of prey items detected in Opheodrys aestivus samples, (D) percentage of prey items detected in Storeria occipitomaculata samples and (E) percentage of prey items detected in

Storeria dekayi samples ...... 36

Figure 3. Mean stable isotope values(± 1 standard error) for N15 (A) and C13 (B) for

Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae),

Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc). Different lowercase letters

within each panel indicate significant differences between species ...... 3 7

Figure 4. Mean C13 and N15 isotopic values for scale, red-blood cell (RBC), and plasma

tissue in five species of snakes found at Fox Ridge State Park (Coles County, Illinois),

between 2012 and 2013. Bars represent ±1 standard error; Coluber constrictor means are

shown in blue, Diadophis punctatus means are shown in orange, Opheodrys aestivus

vii means are shown in green, Storeria dekayi means are shown in brown, and S. occipitomaculata means are shown in red ...... 38

Figure 5. Polygons depicting the isotopic space (C 13 and N 15 values) for scale tissue collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc) ...... 39

Figure 6. Polygons depicting the isotopic space (C 13 and N 15 values) for plasma tissue collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc) ...... 40

Figure 7. Polygons depicting the isotopic space (C 13 and N 15 values) for red blood cells collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde), and Storeria occipitomaculata (Stoc) ...... 41

Figure 8. Mean C13 and N 15 isotopic values for prey items compromising 2: 3% of the diet of five colubrid snakes (Coluber constrictor, Diadophis punctatus, Opheodrys aestivus,

Storeria dekayi, and Storeria occipitomaculata) sampled in Fox Ridge State Park (Coles

Co., Illinois) during the 2012 and 2013 activity seasons. Bars represent± 1 standard error ...... •...... 42

Figure 9. Posterior probabilities that eight prey types contribute to the diet of Co Zuber constrictor at Fox Ridge State Park (Coles County, Illinois), based on plasma (A), red

viii blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix as a percentage ...... 43

Figure 10. Posterior probabilities that eight prey types contribute to the diet of Diadophis punctatus at Fox Ridge State Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix as a percentage ...... 44

Figure 11. Posterior probabilities that eight prey types contribute to the diet of Opheodrys aestivus at Fox Ridge State Park (Coles County, Illinois), based on scale samples (sample sizes were not high enough to run models on plasma and red-blood cell samples). X-axis represents source contribution to the mix as a percentage ...... 45

Figure 12. Posterior probabilities that eight prey types contribute to the diet of Storeria dekayi at Fox Ridge State Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix as a percentage...... :.. 46

Figure 13. Posterior probabilities that eight prey types contribute to the diet of Storeria

occipitomaculata at Fox Ridge State Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix

as a percentage...... 47

ix INTRODUCTION

It was the Law of the Sea, they said. Civilization ends at the waterline. Beyond that, we all enter the food chain, and not always right at the top. -Hunter S. Thompson

A primary driving force of all animals is the necessity of finding the right kind of food and enough of it (Elton 1927). It is this driving force that leads every animal to consume and potentially be consumed, creating a linked array of species, otherwise known as a food web, based on their trophic interactions. All organisms are embedded within these food webs, creating a series of trophic links that can identify the pathways of energy and matter transfer within communities (Paine 1988). Untangling and understanding the meaning of these links has been of interest to ecologists for decades, likely because food web studies have the potential to reveal a considerable amount of information, particularly in the fields of ecosystem and community ecology. As examples, by deciphering food web dynamics, ecologists have been able to study the mechanisms of energy flow (Polis and Hurd 1995), biodiversity (Thebault and Loreau

2003), inter and intraspecific relationships (Connell 1961; Smith 1990), invasive species dynamics (Dorcas et al. 2012), efficacy of wildlife management protocols (McShea and

Rappole 2001), and even landscape dynamics (Polis et al. 1997).

Despite the intrinsic benefits that come from elucidating food web structure in ecological communities, the task itself is not one to be taken lightly. By their very nature, food webs are complex, dynamic, sensitive to environmental change, and difficult to scale both temporally and spatially. As a consequence, they present challenges when assessing the importance of a particular species or trophic link relative to the energy flow

1 of an entire community (Paine 1980, 1988; Polis et al. 1989). Despite these limitations, studies examining the dietary composition of species within a community are nevertheless important, as they can provide insight into potential community structure mechanisms (e.g., resource partitioning).

Traditionally, resource dimensions have been divided into three categories (i.e., habitat, food, and time), all of which can potentially be partitioned by organisms within a community (Pianka 1975). Numerous studies of resource partitioning have considered multiple taxonomic groups, including invertebrates (Abrams 1987), fish (Ross 1986), amphibians (Lawler and Morin 1993), reptiles (Tucker et al. 1995), birds (Holm and

Burger 2002), and mammals (Emmons 1980). Among reptiles, snakes are particularly ideal for questions related to food-resource partitioning for a variety ofreasons: (1) the entire group is carnivorous with no known species feeding on any type of vegetative matter; (2) they are gape-limited, making prey size an important dietary constraint; (3) because of their limbless morphology, they are considerably more limited than other vertebrates in terms of prey capture and handling; and, (4) because they often eat large prey items relative to their body size, and are capable of fasting for long periods of time, and might be exempt from many of the energy acquisition problems that many other predatory vertebrates face (Vitt 1987). These reasons, along with others, have provided the motivation for documenting the dietary preferences and feeding ecology of a wide range of snake species. With that being said, the ecology of smaller-bodied, invertivorous species is woefully under-represented.

In some areas, invertivorous snakes, particularly smaller bodied ones, can occur in astonishingly high densities constituting a large portion of the vertebrate biomass. An

2 impressive example of this occurrence is Fitch's (1975) estimation that Ring-necked

Snakes (Diadophis punctatus) occur at densities greater than 1000 individuals per hectare in Kansas. Several other semi-fossorial species, such as Common Wormsnakes

(Carphophis amoenus) and Southeastern Crowned Snakes (Tantilla coronata), are also reported as very abundant in areas of their range (Todd et al. 2008; Wilson and Dorcas

2004). For this reason, they can be valuable components within communities as both predators and prey (Willson and Dorcas 2004). Nevertheless, studies detailing the foraging ecology and dietary preferences of these species are few (but see Clark 1970;

Fitch 1975; Todd et al. 2008; Weaver 2010; Willson and Dorcas 2004), and none of these examined dietary overlap in a solely invertivorous community of snakes.

Natural History ofSelect lnvertivorous Snakes

Coluber constrictor (North American Racer)

Coluber constrictor is a large (adults average 150 cm in total length), diurnal species. Adults have a uniformly black dorsal surface, and white to cream ventral surface, juveniles are blue-grey in color, with red to brown blotches extending the length of the body (Phillips et al. 1999). The species is widespread across North America, and exhibits significant phenotypic variation throughout the country (Ernst and Ernst 2003). Coluber constrictor is abundant throughout its range and thrives in both open and woodland habitats. While adults are often described as opportunistic feeders, juveniles feed primarily on invertebrates, likely because they are gape-limited (Ernst and Ernst 2003).

Diadophis punctatus (Ring-necked Snake)

Diadophis punctatus is a small (most adults are smaller than 40 cm) semi­ fossorial species, characterized by a bluish-grey to black dorsal surface with a yellow to

3 red band around the neck. The ventral surface is yellow to red and may have black spots running the length of the body (Phillips et al. 1999). The species ranges over much of

North America, from southeastern Canada to central Mexico, with individuals displaying considerable phenotypic variation across the range (Ernst and Ernst 2003). Eastern populations are typically found in woodlands, while Midwestern and Western populations seem to prefer edge habitat. The species is secretive, and is typically encountered under some type of debris. Throughout its range, D. punctatus exhibits variation in diet ranging from generalist to specialist foraging strategies, and has been known to feed on amphibians, reptiles, arthropods, insects, and earthworms (Ernst and

Ernst 2003).

Opheodrvs aestivus (Rough Greensnake)

Opheodrys aestivus is aptly named for its vibrant green dorsal surface, and keeled dorsal body scales. The ventral surface ranges from white to cream colored. The body is slender, and adults typically do not exceed 80 cm in total length (Phillips et al. 1999).

The species ranges from southern New Jersey south through Florida and central Texas, and west to eastern Kansas. Isolated populations can be found in Missouri and Mexico

(Ernst and Ernst 2003). Greensnakes are arboreal, usually found in trees along waterways. The species is oviparous and has been reported to feed primarily on insects

(i.e., beetles, damselflies, mayflies, moth and butterfly larvae, dragonflies, crickets, grasshoppers, katydids, wood roaches, mantids, and walking sticks), but has also been known to take millipedes, isopods, spiders, snails, and even small fish and frogs (Ernst and Ernst 2003).

4 Storeria dekayi (Dekay's Brownsnake)

Storeria dekayi is a small (i.e., up to 40 cm in total length), grayish brown to dark brown snake with a cream to pinkish ventral surface and two parallel rows of dark brown or black spots on the dorsal surface (Phillips et al. 1999). The species is found from southern Quebec through to Honduras, and west to the eastern Dakotas. Storeria dekayi is common throughout its range, occurring in: nearly all terrestrial, and marshland habitats, and especially along forest edges (Ernst and Ernst 2003). It most commonly feeds on earthworms and slugs, but has also been reported to consume snails, insects, isopods, mites, spiders, small fish, larval amphibians, and small frogs (Ernst and Ernst 2003).

Storeria occipitomaculata (Red-bellied Snake)

Storeria occipitomaculata is very similar in appearance and behavior to S. dekayi.

Adults can reach up to 35 cm in snout-vent length, and are characterized by a gray, brown, or black dorsal surface, light blotching behind their head, and a red to orange ventral surface (Phillips et al. 1999). The species ranges over across much of eastern

North America, with populations occurring from southeastern Canada to eastern Texas

(Ernst and Ernst 2003). The species is found commonly in moist woodland habitats, under rocks and logs, but is also occasionally seen in open fields and marshlands.

Descriptions of its dietary preferences are limited, but consist mostly of slugs and earthworms. Individuals have also been reported to predate insect larvae, isopods, and snails (Ernst and Ernst 2003).

Species co-occurrence

These species overlap in many portions of their range (e.g., central Illinois), and have all been documented within Fox Ridge State Park (FRSP) in Coles County, Illinois.

5 Despite high levels of range overlap, detection of all five species within individual study sites is uncommon, making FRSP a unique site in which to study resource partitioning. In addition to range overlap, these species, particularly Storeria spp. and Diadophis, might overlap in dietary preferences. If food resources are limited, individuals might be partitioning food resources within the park to minimize competition in areas of co- occurrence.

Studying Snake Dietary Ecology

Traditionally, researchers have been limited to only a few methods by which to study snake dietary ecology. By dissecting fecal samples, researchers can identify undigested remnants of prey items (e.g., exoskeletons and other hard parts). Obtaining these samples, however, often requires keeping individuals in captivity for some length of time. Gut content analyses can be performed by palpating the gut cavity of a snake to determine if it has recently fed, and then forcing the animal to regurgitate this prey item.

This technique can injure and potentially kill animals if not executed properly.

Alternatively, on animals that are already dead (either preserved in museum collections or as encountered in the field), dissections can identify any prey items that the snake contained at the time of death. Finally, direct observations of animals feeding in the field can be recorded, although events such as these are often rare and anecdotal.

Although these techniques have the potential to offer insight into the dietary preferences and feeding ecology of many snake species, they have limitations. By their very nature, snakes tend to be: (1) difficult to observe in their natural habitat; (2) prone to long periods of inactivity; and, (3) infrequent feeders (Parker and Plumber 1987). In addition, snakes typically swallow their prey whole and leave little identifiable material

6 in their fecal matter to help identify prey species. Because gut and fecal samples only provide information about what an animal had recently eaten, inferences about an animal's dietary preferences or trophic position within a community are based on a short time frame of activity (Hobson et al. 1994). Consequently, seasonal shifts in a snake's diet can be missed, and organisms can be mislabeled as having specialist or generalist tendencies. Additional biases can be incurred by not accurately measuring relative abundance and availability of prey taxa, or failure to account for variation in digestibility and assimilation rates (e.g., softer prey items are digested more rapidly; Bearhop et al.

2004; Votier et al. 2003). Finally, snakes can become stressed from being forced to regurgitate prey items or being held in captivity for extended periods of time (Tyrrell and

Cree 1998), and such stressors can alter either willingness to feed or physiological processes related to energy uptake.

Stable isotope analyses (SIA) have been used over the past few decades in fields of research such as geology, paleontology, chemistry, and plant physiology (Gannes et al.

1998). More recently, however, use of SIA has expanded into the fields of animal ecology and physiology, as researchers have begun to apply this technique to answer questions about dietary composition and isotopic components of consumer tissue (e.g.,

Bearhop et al. 2002; Inger and Bearhop 2008). When used for dietary studies, SIA compares the isotopic ratios of certain atoms (e.g., H, C, N, 0, S) within an organism to those found within that organism's biotic and abiotic environment to make predictions about diet composition (Gannes et al. 1998).

Most naturally-occurring elements have at least two stable isotopes, one of which is typically more abundant than the others (Ehleringer and Runde! 1989). The ratio of these

7 stable isotopes within tissue samples of a predator can be measured relative to a known standard (e.g., PeeDee cretaceous belemnite for C, atmospheric air for N), and compared values of potential prey items (Griffiths 1991 ). Relative to their prey, predator isotopic values are, on average, enriched by 1 part per thousand (%0) for C and 3 parts per thousand for N (Peterson and Fry 1987). Carbon isotopes are beneficial because they retain source information (e.g., C3 vs. C4 photosynthetic pathways in plants) throughout the trophic web, whereas nitrogen isotopes provide information about trophic level (Kelly

2000). The majority of dietary studies use carbon and nitrogen together, likely because they are the most affordable and accessible choices. There is, however, immense potential for other isotopes to be used as indicators in ecological systems (Connolly et al.

2004; Duxbury et al. 2003; Whitledge et al. 2007).

Stable isotope analysis offers researchers an alternative method to study the dietary preferences of snakes, while bypassing many of the difficulties associated with traditional methods (Pilgrim 2005; Rush et al. 2014; Willson et al. 2010). For example, SIA can identify dietary history regardless of whether or not an animal has recently fed, and allows researchers to examine diet over a much longer temporal scale than gut and fecal surveys. This helps to ensure that ontogenetic or seasonal shifts in diet will not go undetected. Finally, isotopic data is relatively easy to analyze, with multiple mixing model software applications available to determine the proportion of potential prey items contributing to consumer tissue. These isotopic models can be further strengthened by using a Bayesian approach that incorporates prior data (e.g., gut and fecal surveys).

In an effort to address the lack of information related to resource partitioning within invertivore snake communities, I used a combination of traditional methods (i.e.,

8 gut and fecal surveys) in concert with SIA of carbon and nitrogen to quantify the diet of five species of invertivorous snakes found in central Illinois ( Coluber constrictor,

Diadophis punctatus, Opheodrys aestivus, Storeria dekayi, and S. occipitomaculata).

Combining these techniques allowed me to determine: (1) the dietary preferences of the five species; (2) the degree to which the species of snakes are dietary generalists or specialists; and, (3) the degree to which any niche overlap occurs among the five species.

9 METHODS

Study Site

I sampled Coluber constrictor, Diadophis punctatus, Opheodrys aestivus,

Storeria dekayi, S. occipitomaculata, and potential prey items of these five species FRSP in Coles County, Illinois (39°24'9''N, 88°81 '4"W; 836 ha). This property contains both upland and lowland oak-hickory forest, along with a few hectares of short-grass prairie that are managed via controlled burn treatments. FRSP is bordered by the Embarrass

River to the West, and a mixture of forest habitat and agriculture production along its other borders. The specific areas surveyed for my five species of interest include a mixture of old field habitat and upland hardwood forest that are separated by a 2.6 km stretch ofroad (Ridge Lake Road). This road is unique in that it separate areas oflower elevation from potential hibernacula sites at higher elevations within the upland forest.

Field Methods

Snake Collection

All snakes were sampled by walking a 2400 m transect that runs parallel to Ridge

Lake Road in FRSP every day, during the activity season of two consecutive years (26

March to 11November2012, and 29 March to 5 November 2013). This transect consisted of nine 100 m long drift fences located east of the road, which were spaced approximately 170 m apart. These fences were installed in 2010 as part of a separate study. Fences were originally constructed out of 45 cm tall silt fabric, but were sporadically replaced with 45 cm tall aluminum flashing when repairs were needed. Each fence was originally paired with four 18 L pitfall traps, three 3.5 L pitfall traps, and three pairs of rubber cover mats averaging 60 x 107 cm in size, all evenly spaced. During the

10 second year of sampling each fence was outfitted with six 18 L pitfall traps and 4 pairs of rubber cover mats to more effectively sample the five species of interest. In addition to sampling this transect, visual encounter surveys were conducted for individuals in adjacent habitats. During the winter between sampling years, all large pitfall traps were sealed with lids, with at least one rubber mat placed on the lid to avoid trapping any target or non-target species.

Upon capture of one of my species of interest, I recorded the time, date, and location of the individual. To record the exact location of all specimens, I used a hand­ held global positioning system (Magellan eXplorist 310, ±5 m accuracy), and took additional notes on the orientation, trap type, and trap location if individuals were caught along drift fences. Captured snakes were then returned to the lab where I recorded the mass (±0.01 g), snout-vent length (SVL; ±1 mm), tail length (TL; ±1 mm), and gender for each individual (Fitch 1987). In the case of Coluber constrictor, only hatchling and juvenile individuals (SVL < 500 mm) were sampled, because of their tendency to feed primarily on invertebrates at these life history stages (Rosen 1991). All individuals were uniquely marked by branding of the ventral scales with a medical cautery unit (Winne et al. 2006). I collected 2-6ventral scale clips depending on the size of the snake and at least 0.20 ml of blood from each individual that had a mass :::: 2.5 g. Blood was drawn from the caudal vein of all individuals with a 27.5 gauge needle. Scales were immediately placed into individual aluminum tin capsules, while blood was centrifuged to separate plasma and red blood cells (RBC), with each tissue type being placed into its own tin capsule after separation.

11 For comparison with my stable isotope analyses, I palpated the gut cavity of all individuals and when possible, forced the snake to regurgitate any rece:IJ.tly ingested meal. ( In addition, individuals were housed in the lab for no more than 48 hr so that a fecal I sample could be obtained. All snakes were released at the site of cap e following defecation, or if they failed to defecate within the 48 hr period that the were in captivity.

Regurgitated prey and any prey material detected in fecal samples wer identified to the lowest possible taxonomic level, based on the quality of the prey sam le. All tissue, regurgitated prey, and fecal matter were stored at -20°C.

Prey Collection

All potential prey items were collected in the same time frame that snakes were sampled. Because invertebrate species make up such a high proportio of the global biomass, I attempted to filter potential invertebrate prey items to thos that appeared previously in dietary analyses of my species of interest, as well as spe ies that were similar in terms oflife-history, or taxonomic affinity.

The majority of invertebrate prey species were collected via o portunistic encounters under the coverboards or in pitfall traps along the arrays at were established to capture snakes. I also sampled potential invertebrate prey using sw ep-net collection, nocturnal spotlight surveys, and vacuum-suction collection (Bugzoo*™; Wyers \ Products Group Inc., Englewood, Colorado). Potential vertebrate prey \vere also collected opportunistically along drift fences and Ridge Lake Road. Upon capture, each prey item was sacrificed by freezing at temperatures below -20°C. Whole prey items were then wrapped in aluminum foil and stored at -20°C.

12 Sample Preparation and Analysis

Using a lyophilizer at the University of Illinois Institute for Genomic Biology, I

freeze-dried all prey and tissue samples for 24-48 hr to ensure complete dehydration.

Following removal of water, each whole prey item was ground until fully homogenized

in a vial with a magnetitezed impactor in a cryogrinder (Spex SamplePrep 6870

Freezer/Mill). The vial and impactor size varied depending on the size of the prey item.

Prey items that weighed between 0.5-4 g were ground using a small grinding vial set

(Spex SamplePrep Vial Set 6751), and samples that weighed below 0.5 g were ground in

a microvial set (Spex SamplePrep Microvial Set 6753). I weighed out 0.6-1.2 mg of each

sample (either homogenized prey item or snake tissue sample) and placed each

subsample individually into new tin caps. This mass is necessary for the detection of

nitrogen in tissues via stable isotope analysis (based on an approximate 10% content of

nitrogen for animal tissues). The C and N ratios of all samples were compared against

. PeeDee cretaceous belemnite and air standards, respectively, using an elemental

analyzer-isotope ratio mass spectrometer (Costech 4010 and Delta V Advantage) at the

University of Illinois Institute for Genomic Biology.

Statistical Analyses

Neonatal snakes have been shown to display biased isotopic values because of

retention of maternal isotopic signatures (Pilgrim 2007). This can be especially

problematic when interpreting the isotopic signatures of species whose life histories

involve ontogenetic shifts in diet (e.g., Coluber constrictor; Fitch 1963; Lennon 2013).

This phenomenon was likely documented in my study, with tissue samples from several

of the smallest Blue Racers displaying elevated isotopic values of nitrogen, similar to the

13 values seen in adult females at my study site. In order to avoid confounding diet-derived signals with retained maternal signals, I plotted the nitrogen values of all individuals as a function of SVL, which indicated the smallest individuals to have enriched signatures compared to the larger neonates and juveniles (Figure 1). Based on this distinction in signatures, I established an N-cutoffvalue of 10.18, and excluded all juvenile Blue

Racers (i.e., n = 3) whose nitrogen signatures were greater than this cutoff value from any analysis. I also plotted the N-values of my four other species of interest. I did not detect any evidence of ontogenetic shifts in these species, however, and included all sampled individuals of these remaining four species in my analyses.

All non-Bayesian statistical analyses were performed in SAS v9.2. I used chi­ squared tests to determine if capture rates of any species were different across seasons. I used analyses of variance (ANOVA) to detect any sexual differences among species in terms of SVL, tail length, and mass. I also used ANOVAs to detect differences in C13 and

N 15 ratios between the five species of interest, as well as the three tissue types sampled

(i.e., scale, RBC, and plasma). Bonferroni post-hoc tests were used to help protect against the occurrence of Type-1 errors.

In order to estimate the contributions of each potential prey item to the diets of the five snake species, I used the statistical package MixSIR for MATLAB to estimate how much of each species diet was made up of each potential prey item. This statistical package is based on a Bayesian framework, which uses varying degrees of posterior probabilities to make predictions about the subject being tested (in this manner, the technique differs from traditional hypothesis testing). I then incorporated the isotopic signatures of C and N from each individual, based on tissue type and species into each

14 model, along with the mean values of C and N for each of my potential prey groups resulting in a total of 20 different models. As a comparative basis for all of these models,

I used the average values of fractionation reported in the literature-that N is enriched by

3 %0 and C is enriched by 1 %0 with each increasing level in the trophic web (Peterson and Fry 1987). All models were then set to run to one million iterations. If any prey items were found to contribute < 3 % to the diet of the snake species, they were dropped from further analysis and the mixing models were repeated with five million iterations.

15 RESULTS

Snake Collection

The number of specimens obtained was not equal across species (Table 1). All individuals sampled were adults with the exception of the targeted juvenile C. constrictor, four S. occipitomaculata, one 0. aestivus, and one D. punctatus. Three neonate C. constrictor were excluded from all analyses because their isotopic signatures was likely biased by maternal isotopic signatures (Figure 1). Snakes were encountered from 2 April to 26 October 2012, and 3 March to 30 October 2013. In both years, species were encountered more frequ~tly in the Autumn (September-November), with the exception of Diadophis, which was encountered more in the Summer (June-August; i" =

20.17, df= 2, p < 0.0001).

Sex ratios were skewed for Coluber and Opheodrys, but approximately even for

Diadophis and both Storeria species (Table 1). Two of the females collected (one S. occipitomaculata and one Diadophis) were gravid at the time of tissue sample collection.

Opheodrys aestivus and juvenile Coluber constrictor had the greatest values for SVL, TL and mass, followed by Diadophis and the two Storeria species (Table 2). The two

Storeria species were the only species that exhibited sexual size dimorphism for any of the morphometric traits. Males of both species of Storeria had longer tails than female subjects, whereas female S. dekayi had larger values for SVL and mass than their male counterparts (Table 3).

Identifiable remnants of prey items were detected by either gut palpations or dissecting fecal samples in 76 individuals across all five species. Individuals had recently consumed between one to three prey items, resulting in a total of 96 partially digested

16 prey items. My ability to detect prey varied by method for each species (i.e., palpating the gut cavity vs. dissecting fecal samples). The majority of prey items consumed by

Diadophis, and Storeria spp. were recovered by palpating the gut cavity. Most of the items consumed by Opheodrys and Coluber were detected in fecal samples. Exceptions to these patterns included: (1) one wolf spider (Family Lycosidae) found in the gut cavity of an adult Opheodrys; (2) one S. dekayi and one butterfly (Suborder Rhopalocera) found in the gut cavity of two juvenile C. constrictor; and, (3) an unidentifiable non­ lepidopteran wing membrane found in a fecal sample from an adult S. dekayi. All of the prey items recovered from Diadophis and S. occipitomaculata were earthworms and slugs and/or snails, respectively. Because all prey items were partially digested, it was difficult to distinguish snails from slugs. I labeled specimens where a shell was detected within the sample as snails, whereas samples without shells were labeled as slug/snail.

The prey items consumed by Coluber consisted of crickets, katydids, butterflies, and

Brownsnakes. The prey items consumed by Opheodrys consisted of katydids, wolf spiders and crickets, and the prey items consumed by S. dekayi consisted of slugs and/or snails, earthworms, and the unidentified wing membrane (Figure 2).

Prey Collection

I collected samples (n 2: 6) of 20 groups of potential invertebrate prey, which were categorized to the lowest possible taxonomic level. These 20 types included: grasshoppers [Family Acridae (n = 33)], katJ:dids [Family Tettigonidae (n=8)], crickets

[Family Gryllidae (n= 33)], mantids [Family Mantidae (n= 7)], adult ants [Family

Formicidae (n=7), ant larvae [Family Formicidae (n=6)], butterflies [Order Lepidoptera

(n=14)], caterpillars [Order Lepidoptera (n= 12)], damselflies [Order Odonafa (n=6)],

17 dragon flies [Order Odonata (n=6)], wood roaches [Family Blattellidae (n=l O)], ground beetles [Family Carabidae (n=12)], sowbugs [Order Isopoda (n=13)], giant millipedes

[Family Spirobolidae (n=14)], centipedes [Family Cryptyopidae (n= 8)] harvestmen

[Family Opiliones (n=lO)] wolf spider [Family Lycosidae (n=8)], earthworms [Order

Megadrilacea (n=33)], slugs [Class Gastropoda (n=13)] and snails [Class Gastropoda

(n=28)].

Stable Isotope Analyses

Stable isotope readings were obtained for scale samples from 31 C. constrictor,

26 D. punctatus, 11 0. aestivus, 29 S. dekayi, and 16 S. occipitomaculata. Stable isotope readings for RBC and plasma samples were obtained from 31 C. constrictor, 23 D. punctatus, 4 0. aestivus, 29 S. dekayi, and 8 S. occipitomaculata. Isotopic signature varied significantly among the five species for nitrogen (F4, 298 = 16.26 p < 0.001; Figure

3A) and for carbon (F4, 298= 39.80 p < 0.001; Figure 3B), with no differences detected between the sexes of any of the snake species (p 2:: 0.26 for N, and p 2:: 0.48 for C).

Excepting C. constrictor and S. occipitomaculata, tissue types differed in their carbon signatures (Table 4). There were no differences in isotopic nitrogen between tissue types for any species (p 2::. 0.11 ). In order to visualize dietary niche width in isotopic space, I plotted all individual predator data points according to tissue type, with C13 on the x-axis, and N 15 on the y-axis (Figures 5-7).

In the initial mixing model analyses, several potential prey groups were predicted to contribute very little to each species diet (i.e., 0-3% with a positively skewed distribution). Because none of these prey items were detected in any gut or fecal samples they were dropped from further analyses. These eliminated prey groups include: mantids,

18 ants, ant larvae, caterpillars, damselflies, dragonflies, wood roaches, ground beetles, sow

bugs, giant millipedes, centipedes and harvestmen. The isotopic means of the remaining

prey items were plotted in a fashion similar to that used for the snake tissue samples

(Figure 8). When removed from the mixing model analyses, the posterior probabilities for

the remaining eight prey groups were smoothed at one million iterations.

The mixing models for C. constrictor tissues were similar, with snails

contributing the most to tissue composition, followed by crickets and butterflies (Figure

9). The mixing models for D. punctatus tissues were also in agreement that earthworms

were the main dietary component, potentially contributing over 80% to tissue

composition (Figure 10). However, the plasma and RBC models also predicted that snails

could contribute substantially to diet. Because sample sizes were low (n= 4) for 0.

aestivus blood samples, a mixing model analysis could only be performed on the isotopic

data obtained from scale tissue. This model predicted that grasshoppers, katydids,

crickets, wolf spiders, and butterflies potentially all contributed to the diet of this species,

with predictive values :S 20% for all prey types (Figure 11 ). The mixing models for S.

dekayi RBC and scale tissue were in agreement with earthworms, slugs, and snails

contributing substantially to tissue composition. However, the mixing model for plasma

indicated that grasshoppers, katydids, and crickets also contributed to tissue composition

,in this snake species (Figure 12). The mixing models for S. occipitomaculata tissue types

were in agreement that snails were the main dietary component, potentially contributing

over 90% to tissue composition (Figure 13).

19 DISCUSSION

Natural History ofthe Community

The snake community at Fox Ridge State Park (FRSP) in Coles County, Illinois

appears to be stable with 11 species detected in the park since research efforts started in

2010. Five species in particular, Coluber constrictor, Diadophis punctatus, Opheodrys aestivus, Storeria dekayi, and S. occipitomaculata, have been studied extensively relative to their dietary preferences.

Storeria dekayi and S. occipitomaculata populations both show signs of sexual

size dimorphism, similar to what has previously been reported for the genus, with S. dekayi females being heavier and longer than their male counterparts, and S. occipitomaculata males having longer tails (King 1997). In a review of sexual size

dimorphism among reptiles, Fitch (1981) documented a trend among snakes occurring in

temperate climates for females of viviparous species to obtain larger body size, relative to

conspecific males, when compared to oviparous species. This trend likely evolved as a

strategy to increase per-clutch fecundity in females, and as an adaptation to cold

environments that might cause high mortality among eggs (Fitch 1981; Shine 1985). The two Storeria species are the only viviparous species in my study, likely explaining why I

documented sexual size dimorphism in these species only. Unlike sexual size dimorphism

of SVL, which can be male- or female-biased, sexual size dimorphism of TL, when present, is almost always male-biased (King 1989). This pattern explains why male

Storeria had longer tails relative to female conspecifics, despite the trend for females of

the genus to have larger overall body size. Although the sex ratio for C. constrictor was male-biased, I suggest there is a healthy population of females inhabiting FRSP, based on

20 the large number ofhatchlings encountered each year. The sex ratio for 0. aestivus was

slightly female-biased, but because of low capture rates for this species, this might not be

a biologically-relevant finding.

In both years, I captured all species more frequently in the Autumn, with the

exception of D. punctatus that was captured more often in the Summer. Almost all of

these captures were made after detecting an individual under rubber cover mats. Fitch

(1982) found that D. punctatus at a study site in Kansas, preferred edge habitat with

abundant sources of cover and sunshine. Based on this, the rubber cover objects in place

at the park are likely ideal for detecting this species, because they are located along a

prairie-forest edge, and receive ample amounts of sunshine. In addition to finding snakes

under these rubber cover objects, I regularly found a variety of potential prey items on

which Diadophis could potentially feed (i.e., earthworms, slugs, snails, roaches, and

centipedes). Because these rubber cover mats are placed in ideal habitat for this species,

and provides multiple potential foraging opportunities, Diadophis is likely spending

extended periods of time during the activity season, before moving to hibernation sites in

the Autumn.

Gut and Fecal Surveys

Based on gut and fecal surveys, C. constrictor, D. punctatus, 0. aestivus, S.

dekayi, and S. occipitomaculata appear to have a diet similar to conspecifics within their

respective ranges (Ernst and Ernst 2003). Diadophis punctatus and S. occipitomaculata

appear to be dietary specialists, with 100% of samples containing earthworms and slugs

and/or snails, respectively. In comparison to these species, Storeria dekayi has generalist

tendencies, and appears to be feeding primarily on a combination of earthworms and

21 snails and/or slugs. Coluber constrictor and 0. aestivus appear to be dietary generalists relative to the other species I studied. Several segments of S. deka.yi ventral scales were found in C. constrictor fecal samples, in addition to katydids, crickets, and butterflies.

This indicates that, at this life-history stage, racers are feeding on a mixture of vertebrates and invertebrates. Based on gut and fecal surveys, 0. aestivus also appears to exhibit a generalist feeding style by depredating katydids, crickets, and wolf spiders.

The majority of prey items obtained from Diadophis or Storeria were found by palpating the gut cavity. Because these prey items are soft-bodied invertebrates (i.e., slugs, snails, and earth worms), they likely leave very little identifiable material in fecal samples. A wing membrane was found in a fecal sample produced by an adult male

Storeria dekayi, however the membrane was in poor condition and could not be identified. Reports of this species feeding on winged invertebrates are scarce, although

Judd (1954) found a wing membrane in a fecal sample obtained from an adult in Ontario.

Although the adult male in my study may have intentionally consumed this prey item, it is more likely that it was consumed inadvertently, potentially as by catch of attempting to feed on another prey item (e.g., earthworms, slugs, and snails). The majority of prey items obtained from Coluber or Opheodrys were found by dissecting fecal samples.

Many of these samples contained exoskeletons of heads and legs from butterflies, crickets, and katydids. Because these exoskeletons are composed of chitin, they may be energetically costly to digest, causing snakes to excrete them as opposed to assimilating them.

22 ...... ,,. Stable Isotope Analyses

Coluber constrictor and 0. aestivus were the most enriched in N 15, followed by S. dekayi, and then by D. punctatus and S. occipitomaculata. Because nitrogen isotopes are enriched by approximately 3 %0 as they are transferred up a food chain, they can be used as indicators of trophic position (Peterson and Fry 1987). This means that higher order ' predators will have more enriched values of isotopic nitrogen than lower order predators or consumers within a food web. The trophic positions of the focal snake species at FRSP are supported by prior reports of stomach content, with juvenile C. constrictor and 0. aestivus being reported to regularly consume higher order invertebrates (e.g., spiders, katydids, and crickets), relative to the soft-bodied invertebrates that typically make up the diets of Diadophis and Storeria. (Ernst and Ernst 2003).

As with N 15, C13 also varied among species, with D. punctatus and S. occipitomaculata representing the only two species that were not different from one another in terms of isotopic carbon. Carbon isotopes are typically used in dietary studies because they are enriched by only :::::1 %0 as they move up the food chain (Peterson and

Fry 1987). These small increments of enrichment provide information about the source of the carbon, such as the photosynthetic pathway utilized by a producer at the base of a food chain. By this logic, isotopic carbon values from predators within a food web should have different signatures, relative to how different their prey bases are. Earthworms, slugs, and snails were similar in terms of isotopic carbon and nitrogen, and both D. punctatus and S. occipitomaculata have been reported to feed heavily on these prey items

(Fitch 1975; Semlitsch and Moran 1984). My gut and fecal analyses corroborated these reports with earthworms, slugs, and snails representing the only prey items that these

23 species were found to be depredating. The lack of differences in isotopic carbon between

D. punctatus and S. occipitomaculata is best explained by a similarity of diet.

Plotting the isotopic values of the snake species separately for each tissue type revealed a significant amount of inter- and intra-individual variation in carbon and nitrogen for each species. Surprisingly, there was substantial overlap for each species, with at least one other species in the plots for each tissue type. This high level of overlap suggests that there is little to no interspecific competition for food resources occurring within the community at FRSP. Theoretically, high levels of interspecific competition would present a strong pattern ofresource partitioning among species (Pianka 1974). If snakes in this community were partitioning resources, it would be indicated by low levels of overlap between the polygons representing each species. Because of the high levels of invertebrate density within the park (personal observation), it is plausible that food resources are plentiful, and that partitioning resources would offer few advantages to a

species. Because of this, dietary preference is more likely to be a product of prey

availability coupled with life-history traits (e.g., semi-fossorial), than it is competition.

Although phylogenetic relatedness could also result in similarities in diet between species

(i.e., S. dekayi and S. occipitomaculata), other species such as D. punctatus (Dipsadinae)

appear to have similar diets to Storeria (Natricinae), despite belonging to two separate

subfamilies.

Species that are dietary specialists should have the smaller-sized polygons in the

predator plots, whereas generalist species would have larger polygons. Because a

specialist species would be depredating select prey items, little variation in isotopic

carbon and nitrogen between species is expected. Alternatively, a generalist predator

24 would have larger polygons, because they are depredating a variety of different prey items, resulting in higher amounts of intra-individual variation in isotopic values within a species. Opheodrys aestivus consistently had the smallest polygons, but this is likely because oflow sample size, not because the species is a specialist. The polygons for C. constrictor, D. punctatus, and S. dekayi were of simliar sizes for each tissue type, and the polygons representing S. occipitomaculata were consistently the largest among the focal species at FRSP. Based on the gut and fecal analyses, I expected D. punctatus and S. dekayi to have smaller polygons because they appeared to be dietary specialists. It is possible that the large amount of intraspecific variation in isotopic ratios within each of these species stems from feeding primarily on generalist detritivores/omnivores (i.e., snails and earthworms). There was substantial variation in isotopic ratios of earthworms, slugs, and snails relative to some of the other potential prey items in this study (e.g., butterflies and katydids), likely because these prey items are feeding on a wide variety of both live and decaying organic matter. Although D. punctatus and S. occipitomaculata both have large polygons, suggesting a generalist feeding strategy, it is likely that the large intra-individual variation among subjects can be explained less by variation in their own diet, and more by that of their prey.

The mixing model analyses for C. constrictor diet generally match the gut and fecal analyses, supporting the hypothesis that this species is an opportunistic generalist.

Mixing models of scale, RBC, and plasma tissue uniformly predicted that snails, crickets, and butterflies make up the bulk of this species diet. In all three models, snails were predicted to contribute the most (::; 60%) to diet, followed by butterflies (::; 50% ), and then crickets (::; 40%). Katydids were also shown to potentially contribute ::; 30% to diet,

25 although the majority of model iterations returned values between 0-20%, which is a more likely potential contribution.

Because no snails have ever been recovered from the gastrointestinal tract of C.

constrictor, and incidents of ophiophagy by this species are frequent in the literature

(e.g., Fitch 1963; Lennon 2013), it is more likely that C. constrictor is depredating S.

dekayi instead of snails. Given that there is a large population of S. dekayi inhabiting

FRSP, with> 1200 individuals marked to date, opportunistic encounters between these

two species are probable. Although the 3:1 fractionation ratio for nitrogen and carbon is

most common in terrestrial systems, this assumption has not been verified for S. dekayi.

If S. dekayi consumes large amounts of snails, values of isotopic carbon in snake tissue

would be similar to snails, and potentially indistinguishable to the modeling software.

The model predictions of the butterflies, crickets, and katydids contributing substantially

to diet of C. constrictor are supported by the gut and fecal surveys, although the model

predicts higher contributions of each prey item to the species diet than was detected in

either gut or fecal samples.

The mixing models generated for D. punctatus are also supported by analysis of

content from gut and fecal samples, which further substantiates my hypothesis that the

population at FRSP contains dietary specialists. The models generated for scale, RBC,

and plasma tissue all predict that earthworms contribute greatly to the diet of this species,

with the models based on RBC and scale tissue predicting that earthworms make up

approximately 70-90% of diet, and the model based on plasma tissue predicting that

earthworms account for~ 74% of this species diet. The models based on both of the

blood tissue types also predicted that pulmonate gastropods (i.e., slugs and snails) could

26 be a major component of diet, although there was more support for this generated by the plasma model.

Slugs were collected and subjected to SIA only in 2013. This sampling bias likely results from the Midwest drought of2012 (U.S. Drought Monitor 2012), which might have caused the slug community to crash, or spend long periods of time in aestivation.

This could make this prey item harder to find, causing D. punctatus to shift to a diet made up primarily of earthworms which appear to be more readily available in the park

(personal observation). Snails could also be affected by the drought, but would be at a lower risk of desiccation because of their shell, potentially explaining the lower number of snails that were detected in 2012. Scale tissue is replaced slower than blood tissue

(particularly in adult animals), and RBCs are typically replaced slower than plasma.

Because of these differences in tissue turnover time, if D. punctatus is reverting to feed on slugs and/or snails this change in diet would be reflected in blood tissue first.

Because oflow sample sizes for 0. ae.stivus, mixing models could only be performed on scale tissue. The results of this model were supported by gut and fecal content analyses, with grasshoppers, katydids, crickets, wolf spiders, and butterflies all predicted to contribute substantially to diet. Opheodrys aestivus appears to be an invertivorous generalist relative to the other species of interest. It appears to exhibit a preference for orthopterans, with grasshoppers and katydids each predicted to contribute

S 40%, and crickets S 50% of diet. Wolf spiders and butterflies could potentially contribute S 40% of diet, although the posterior probabilities for these items are low, making 15-30% a more biologically relevant estimate.

27 The mixing models for S. dekayi show the least amount of similarity between tissue types, and when compared to the gut and fecal surveys. The models based on blood samples predict earthworms, slugs, and snails, constitute the majority of the species' diet, which is similar to the gut and fecal surveys. The model based on scale tissue, however, predicts that earthworms, slugs, grasshoppers, katydids, and crickets, all contribute at least 20% to dietary composition. Based on the body size of S. dekayi, it is unlikely that this species is depredating adult grasshoppers and katydids. It is possible that the species is depredating smaller instar stages of these prey items, as these all commonly occur at

FRSP (personal observation). An alternative explanation is that the species is feeding on prey items that have similar isotopic signatures to these prey items that I was not able to sample.

The mixing models generated for S. occipitomaculata are supported by the results of the gut and fecal analyses, which further substantiates my hypothesis that this population is made up of dietary specialists. The mixing models for all tissue types agree that snails are the main dietary component, estimated to contribute approximately 70-

90% of the species diet. The model based on scale tissue also predicted that earthworms could potentially be included in the diet of S. occipitomaculata. Because the posterior probabilities for this prey item were so low, however and no other models showed the same result, this finding does not appear to be biologically relevant.

Conclusions

Quantifying the extent of an organism's trophic niche can offer valuable insight into food web dynamics within communities and ecosystems. Unfortunately, traditional techniques used to study dietary ecology result in interpretations which are often biased

28 by differences in assimilation rates of different prey items, and are limited to a very narrow window of foraging activity (Bearhop et al. 2004; Votier et al. 2003). When used in concert with traditional methods (e.g., gut and fecal dissection) stable isotope analyses have the potential to provide a more accurate estimation of trophic niche width, which can be reflected across multiple temporal scales. Combining SIA data with content from gut and fecal samples, I have added to a growing body of studies that utilize stable isotope analyses to examine dietary ecology of snake species. Of potentially greater impact is the insight that this study can offer into the dietary ecology of invertivorous snakes, a group of organisms that despite widespread abundance, has received little attention.

Like many techniques, SIA offers relatively little information with which to make biologically relevant conclusions when it is used alone. The robust snake community at

FRSP provided me with the opportunity to collect multiple gut and fecal samples, which were essential for verifying the success of the isotope mixing models. _Despite being technically very different, each method yielded similar conclusions, allowing me to confidently identify a combination of dietary specialists (i.e., D. punctatus and S. occipitomaculata), and generalists (i.e., C. constrictor, 0. aestivus, and S. dekayi).

Therefore, a combination of these field-based techniques is strongly recommended for future studies wishing to utilize stable isotope analyses to glean a more conclusive understanding of snake dietary ecology.

The inferences about trophic webs derived from stable isotope analyses can be strengthened by augmenting the various field-based techniques with precise laboratory­ based experiments. Researchers should consider the amount of natural isotopic variation

29 in a system, and quantify the spatial and temporal variation in prey availability and isotopic composition, before pursuing SIA as an appropriate technique for their studies.

Additionally, SIA is limited by communities that contain prey and predator taxa that deviate from the average 3: 1 N :C fractionation ratio, or that are prone to frequent diet shifts. Because of these potential sources of error, studies should elucidate the physiological and behavioral dynamics of organisms within a given community, prior to use of stable isotope analyses. When the technique is used alongside other approaches, however, it can serve as a powerful tool to elucidate the dynamics of trophic relationships within a given community.

30 TABLES

Table 1. Sex ratios of snakes collected from Fox Ridge State Park (Coles County,

Illinois) in 2012 and 2013. Activity season 1 contains individuals captured from 2 April to 26 October 2012, and activity season 2 contains individuals captured from 3 March to

30 October 2013.

Species Activitv season 1 Activity season 2 Sex ratio (M:F) Males Females Males Females Coluber constrictor 7 8 13 3 20:11

Diadophis punctatus 4 0 11 11 15:11

Opheodrys aestivus 3 4 1 3 4:7

Storeria dekayi 5 5 10 9 15:14

Storeria occipitomaculata 4 4 3 5 7:9

31 Table 2. Morphological characteristics (means ± 1 standard error) of snakes collected from Fox Ridge State Park (Coles County, Illinois) in 2012 and 2013. Because there was an insufficient number of juvenile snakes (other than Coluber constrictor), juveniles were excluded from calculations involving snout-vent length, tail length, and mass.

Species N Snout-vent Tail length Mass (g) length (mm) (mm) Coluber constrictor 31 303.12 ± 6.69 91.74 ± 2.48 10.97 ± 0.75

Diadophis punctatus 26 250.80 ± 8.89 61.68 ± 2.82 7.81±0.78

Opheodrys aestivus 11 480.80 ± 26.38 283.40 ± 16.59 28.46 ± 4.18

Storeria dekayi 29 242.34 ± 4.87 67.69 ± 1.93 6.12 ± 0.25

Storeria occipitomaculata 16 166.08 ± 6.64 44.67 ± 1.04 2.47 ± 0.13

32 Table 3. Morphological measurements for each sex of five species of colubrid snakes collected at Fox Ridge State Park (Coles County, Illinois). Snout-vent length (SVL) and tail length (TL) are reported in mm, whereas mass is reported in g; all values are means

±1 standard error. *denotes sexual size dimorphism for that trait within the species

(ANOV A; p < 0.05).

Species Male subjects Female subjects p value Coluber constrictor SVL 299.48 ± 7.14 309.00 ± 13.41 0.50 TL 91.19 ± 2.78 92.62 ± 4.85 0.79 Mass 10.42 ± 0.79 11.86 ±1.52 0.36 Diadophis punctatus SVL 241.00 ± 11.21 263.27 ± 13.98 0.22 TL 64.07 ± 4.42 68.64 ± 2.64 0.35 Mass 8.66 ± 0.80 7.16 ± 1.41 0.34 Opheodrys aestivus SVL 476.25 ± 42.16 483.83 ± 39.77 0.90 TL 292.50 ± 28.08 . 277.33 ± 23.98 0.69 Mass 25.64± 8.12 30.34 ± 5.46 0.63 Storeria dekayi SVL* 232.87 ± 6.38 252.57 ± 6.59 0.04 TL* 72.33 ± 2.29 62.71±2.64 0.01 Mass* 6.62 ± 0.34 5.65 ± 0.32 0.05 Storeria occipitomaculata SVL 181.80 ± 15.02 154.86 ± 15.02 0.20 TL* 54.00 ± 2.71 38.00 ± 2.71 0.04 Mass 2.95 ± 0.42 1.96 ± 0.42 0.24

33 Table 4. Results of separate analyses of variance assessing differences in mean C13 values

(± 1 standard error) between tissue samples for each of five species of species of colubrid snakes collected from Fox Ridge State Park (Coles County, Illinois). Different letters indicate significant differences in tissue type within each species; RBC = red blood cell.

S2ecies Scale RBC Plasma Coluber constrictor p:'.:: 0.20 -24.81 ±0.13A -24. 72 ± 0.09A -25.32 ± 0.09A Diadophis punctatus p:::; 0.0001 -24.11 ± 0.07A -24.42 ± 0.07B -24.98 ± O.Olc Opheodrys aestivus p:::; 0.01 -25.89 ± 0.18A -25.81±0.02A -26.89 ± 0.20B Storeria dekayi p:::; 0.0001 -24.97 ± 0.09A -25.32 ± o.o5B -26.17 ± 0.08c Storeria occipitomaculata p:'.:: 0.12 -24.13 ± 0.29A -24.27 ± 0.35A -25.08 ± 0.23A

34 FIGURES

14.00

ll.00 0 co 10.00 • •• • , • 8.00 .,..,z ..... • '°- 6.00 • • • .. • • • 4.00 • • • •

2.00

0.00 200 250 300 350 400 450 SVL

Figure 1. Relationship between Coluber constrictor snout-vent length (SVL) and isotopic

N 15 values from scale tissue samples. Hollow circles were excluded from all analyses, because these individuals were likely hatchlings reflecting maternal isotopic signatures.

35 33% Katydid

IOOo/o Earthworm

10% Katydid

A 40% Stde B c 50% Cricket 5% Snail

25% Earthworm

D E 65% Slug/Snail

Figure 2. Results of the gut content and fecal sample dissection surveys; (A) percentage of prey items detected in Coluber constrictor samples (Stde = Storeria dekayi); (B) percentage of prey items detected in Diadophis punctatus samples, (C) percentage of prey items detected in Opheodrys aestivus samples, (D) percentage of prey items detected in Storeria occipitomaculata samples and (E) percentage of prey items detected in

Storeria dekayi samples.

36 8 A a a 7 c

6 b b

5 I

c515N -I

3

2

0 Coco Dipu Opae Stde Stoc -23

B -23.:

-2-1

c513C -2-1.5 I

-25 b b -25.5 c

-26 a

-26.5 d

Figure 3. Mean stable isotope values(± 1 standard error) for N 15 (A) and C 13 (B) for

Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae ),

Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc). Different lowercase letters within each panel indicate significant differences between species.

37 8.5 8 + 7.5 7 +~ + 6.5 o15N 6 5.5 5 4.5 4 -27.5 -27 -26.5 -26 -25.5 -25 -24.5 -24 -23.5 o13C

• Scale tissue • RBC tissue ~ Plasma tissue

Figure 4. Mean C 13 and N 15 isotopic values for scale, red-blood cell (RBC), and plasma tissue in five species of snakes found at Fox Ridge State Park (Coles County, Illinois), between 2012 and 2013. Bars represent ±1 standard error; Coluber constrictor means are shown in blue, Diadophis punctatus means are shown in orange, Opheodrys aestivus means are shown in green, Storeria dekayi means are shown in brown, and S. occipitomaculata means are shown in red.

38 11.00

10.00

9.00

8.00 -.oo oL ' 6.00

5.00

-LOO

3.00

2.00 -2 .00 -26.00 -25.00 -2-1.00 -23.00 -22.00 -21.00 &13C

[Z] Coco Dipu IZJ Opae IZJ Stde [Z] Stoc

Figure 5. Polygons depicting the isotopic space (C13 and N 15 values) for scale tissue collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc).

39 10.00

9.00

8.00

7.00

6.00 O} T .00

.i.oo

3.00

1.00 -2 . 0 -2 .00 -26.50 -26.00 -25. 0 -25 .00 -24.50 -24.00 -23.50 o l 3C

0 coco Dipu 0 Opae 0 Stde 0 Stoc

Figure 6. Polygons depicting the isotopic space (C 13 and N 15 values) for plasma tissue collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde) and Storeria occipitomaculata (Stoc).

40 10.00

9.00

8.00

7.00

6.00 0 15 . :.oo

-l.00

3.00

2.00

1.00 ·26.50 -26.00 · 25 .50 ·25.00 -24.50 • 4.00 ·23.50 ·23 .00 ·22.50 ·22.00 813C

[Z] coco Dipu [ZJ Opae [ZJ Stde [Z] Stoc

Figure 7. Polygons depicting the isotopic space (C 13 and N 15 values) for red blood cells collected from Coluber constrictor (Coco), Diadophis punctatus (Dipu), Opheodrys aestivus (Opae), Storeria dekayi (Stde), and Storeria occipitomaculata (Stoc).

41 6

O Ea1thwo1m 5 O Katydid

O Wolf pider -l 8151\ • c1icket

,, O Slug 3 • Butterfly

e Snail

• Grasshopper

-29 -28 -r -26 -25 -24 -23 o13C

Figure 8. Mean C 13 and N 15 isotopic values for prey items compromising~ 3% of the diet of five colubrid snakes (Coluber constrictor, Diadophis punctatus, Opheodrys aestivus,

Storeria dekayi, and Storeria occipitomaculata) sampled in Fox Ridge State Park (Coles

Co., Illinois) during the 2012 and 2013 activity seasons. Bars represent± 1 standard error.

42 Earthworm l I 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Slug 02 0.3 0.4 0.5 0.6 0.7 0.8 0.9 I

Grasshopper I I I I 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Katydid I i 0.2 0.3 0.6 0.7 0.8 0.9 I Snail A 0.3 0.6 0.7 0.6 0.9

I I I I Cricket 0.3 0.4 0.5 0.6 0.7 0.8 0.9 i Wolf Spider 0.3 0.4 0.5 0.6 0.7 0.8 0.9

I Butterfly 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Earthworm 0.2 0.3 0.4 0.5 0.6 0.7 0.8 119

Slug I ' i 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Grasshopper i D.2 0.3 0.4 0.5 D.6 0.7 0.8 0.9

Katydid I I ! I I I 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 ~~.~.-~~~~3 B Snail 0.3 0.4 0.5 0.6 0.7 D.8 0.9 1

O I I I I I i Cricket 0.3 0.4 0.5 0.6 D.7 0.8 0.9 1

Wolf Spider : : I 1

Butterfly 0.1 0.2 0.3 0.4 05

: : I 1 Earthworm 0.2 0.3 0.5 0.6 0.7 D.8 0.9 1

Slug : I : : j 0.2 0.3 0.4 0.5 0.6 0.7 D.B 0.9 1

Grasshopper 1 I I I I I I j 0.2 0.3 0 4 0.5 0.6 0.7 Oil 0.9 1

Katydid : : o :. : : I 1 ~ U U U M V ~ M 1 .-----.---,----, ~.~... --,-·~:-r-:-r-:~3 c Snail 0.2 0.3 0.4 D.5 D.6 0.7 0.8 0.9 1 : l Cricket 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

I I Wolf Spider 0.3 0.4 0.5 0.7 0.B 0.9 1 I I

I I 1 Butterfly 03 0.4 0.5 0.6 0.7 0.8 0.9 Figure 9. Posterior probabilities ¢.at eight prey types contribute to the diet of Coluber constrictor at Fox ,, . Ridge State Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples.

X-axis represents source contribution to the mix as a percentage.

43 Earthworm Slug Grasshopper

Katydid A Snail Cricket

Wolf Spider

Butterfly

Earthworm

Slug Grasshopper

Katydid B oJJSI ' ' ' ; _. : : j Snail 0 0:0 0. t (J..2 0.3- tL4 -0..5 0.6 0.7 o.8 0,9 1 Cricket Wolf Spider

Butterfly

Earthworm

Slug Grasshopper : i 11.8 ll.9 Katydid c

Snail I I ' 0.A 05 0.7 0.9 Cricket 0.5 0.7 Wolf Spider 0.7

Butterfly ~l: I I f I I 1 0 ~ G U M U U V U U 1 _,,,_,,,,,,_,,, __ ~-----•- , -~---"-'··°''- - -~------••H•··---··----· •>• Figure 10. Posterior probabilities that eight prey types contribute to the diet of Diadophis punctatus at Fox Ridge State

Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix as a percentage.

44 I I I Earthworm OD : I : i ~' 0.1 82 IU DA 0.5 Q.6 D.7 lUl 0.9 1 Slug o.1li I : : I I I : : : 1 00 IU ll2 ll3 0,.4 05 ll.6 D.7 u tl.9 1 l I l Grasshopper • I I .... . L ...... L ...... 1....•..•...... ! ...... J om-0o 0.1 G.2 113 GA D.5 o.s 0.7 u tl.9 Q.Ol --,- Katydid om o, 0.1 G.2 ll3 GA 05 tl.& 6.1 u tl.9 1 I Snail ~ii : : I : : : I : i 00 IU ll2 11.3 DA 1'l.5 o.6 0.7 WI 1).9 1 j Cricket 04St j I : I : : : 00 0.1 G.2 G3 OA 1'l.5 11.6 D.7 u tl.9 1 l

Wolf Spider I I j - I I =lmllii·D . : : 0 IU 112 It! 1'l.5 o.6 0.7 O.i D.9 1 Butterfly °"' : I I I I : I 1 OAS-0o IU 112 0.3 OA U5 O.i lU' D.I 0.9 1

Figure 11. Posterior probabilities that eight prey types contribute to the diet of Opheodrys

aestivus at Fox Ridge State Park (Coles County, 'Illinois), based on scale samples (sample

sizes were not high enough to run models on plasma and red-blood cell samples). X-axis

represents source contribution to the mix as a percentage.

45 Earthworm J 0.2 0.3 0.4 0.5' 0.6 0.7' 0.8 0.9 ' 1 Slug 0.2 0.3 O.A 0.5 0.6 0.7 0.8 0.9 1 ' I j Grasshopper I 0.3 04 .---.--.--0.5 0.6 0.7 0.6 0.9 1 ' j Katydid ' ' I ' : 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9:--] 1 A I I I Snail 0.1 0.2 0.3 0.4 0.5 0.6' 0.7 ' 0.8 0.9 1 j Cricket ' ' ' ' 0.2 ••0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 j Wolf Spider I I I I I I 0.2' 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 j : I : : : Butterfly 0.2 0.3 0.5 0.6 0.7 0.8 0.9 1: : : : : j Earthworm 0.3 0.4 0.5 0.6 0.7 O.B 0.9 , I I I I Slug ] I 0.3 04 0.5' 0.6' 0.7' O.B' 0.9' 1 Grasshopper I I : ' I : J 01 0.2' 0.3 04 0.5 0.6 0.7 0.8 0.9 1 Katydid j ' I I I I I 0.1 0.3 04 0.5 0.6 0.7 O.B 0.9 1 B Snail j I ' I I 0.2 0.3 04' 0.5 0.6 0.7 0.8 0.9' 1 I I j Cricket ' ' I I 0.2 0.3 0.4 0.5 0.6' 0.7 ' 0.8 0.9 1

Wolf Spider I : I I I I J 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Butterfly I I I I I J 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 j Earthworm I I I 04 0.5' 0.6 0.7 0.8 0.9 1 Slug I I I I : I j 03 0.4 0.5 0.6 0.7 0.6 0.9 1

Grasshopper I I I I I I I 1 (l.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8' 0;9 1 Katydid I I I I I J 0.1 0.2 0.6 0.7 0.8 0.9 1 c Snail : : I I : : 1 0.1 0.2 0.3 0.5 0.6 0.7 0.6 0.9 1 I j Cricket I I I : I I I 0.1 0.2 . 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 i

Wolf Spider I I I I J 0.2 0.3' 0.4 ' 0.5' 0.6 0.7 0.8 0.9 1 j I I I I I Butterfly 0.2 0.3 0.4 0.5' 0.6 0.7 0.8 0.9' 1 Figure 12. Posterior probabilities that eight prey types contribute to the diet of Storeria dekayi at Fox Ridge State Park

(Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix ~centage.

46 Earthworm : : j D.2 0.3 O..t Q.5 0.6 o.7 0..9 1 Slug : : . : . . : ~ e;2 Q.3 0.4 0.5 o.s o::r 0.9 1 Grasshopper : : : . : ~ Q.2 Q.5: : 0.3 CA na 0.7 0.9 1 Katydid : : : . : : ~ A 0.2 0.3 DA 0.5 o.e 1 Snail : : : : : ] 0.2 0.3 t\.4. 0..5 0.6 0..9 1 Cricket : : : : j : (1..6: 0 ..2 o.a °'"' 0.5 0.9 1 Wolf Spider . : : : : j 0.2 0.3 OA 0.5 Q.;9 1 Butterfly ' : . : : . 3 0.2 0.$ OA 05 oJ5. 0,7 0.8 OJJ 1 0.1, I Earthworm : : : : : Ji 00 : : 0.1 G.2 o.s o.• QJi 0.6 ll.7 OS 1' Slug :;L: 00 : : : : : : : : 0.1 ll.2 113 O.• as 0.6 ll.7 OS 11. Grasshopper :;lb j. 00 : : : : : : : 0.1 G.2 n.s OA 0.6 0.6 ll.7 Q.9

Katydid ~L : : : : I : : "o 0.1 G.2 11.3 ... Wi' OJI o.7 OS ~ B I IW>f • ji : : : ' : : Snail Q.I G.2 n.s n.o: 0.5 O.B o.7 OS t "'o I Cricket ji 00 : : : : : : : 0.t' ru G.2 o.:a OA Wi OJI 0.7 OJJ t' I Wolf Spider a.1111L j1 OD : : : : : : : 0.1 G.2 n.s DA 0..6 o:s o.7 OS Butterfly ~IL ~! 00 : : : : : : : : QJi a.1 G.2 n.s OA o.s o.7 OS t'

• : I l Earthworm O.t'DO 0.1 0.2 llll IU o.s OJI D.7 ' D.9 Slug . . . . • ' HIL : • I : : I I : : 3 OD Ill 0.2 11.l! IU o.s ll.6 ll.7 a.e 119 1 Grasshopper :JL: : : : : : : : : : j 'o 0.1 D.2 llll o..c 0.5 u 0,7 e.e 0$ 1 Katydid 02L j I I : : I : : : : 'o 0.1 D.2 It! 0.4 o.s D.6 D.7 u OS 1 aa;t;;; I . i ' I I c Snail : __.______.... _,~,._J..._ ___ ~-l.--··'--- ....._] OD 0.1 0.2 llll DA tl.5 11.6 0.7 u ti 1 j Cricket :Jib : : : : I : : : : 00 0.1 D.2 llll IU u 11.6 o.; o.e u \ I Wolf Spider O.fh : : : : : : : : J OD 0.1 D.2 o.s DA o.s 11.0 0.7 u 00 1 Butterfly 02, : : : : : : : : : 3 °io 0.1 D.2 u QA o.s 0$ D.7 u u Figure 13. Posterior probabilities that eight prey types contribute to the diet of Storeria occipitomaculata' at Fox Ridge

State Park (Coles County, Illinois), based on plasma (A), red blood cell (B) and scale (C) samples. X-axis represents source contribution to the mix as a percentage.

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