GENE FLOW PATTERNS OF THE FIVE LINED EUMECES FASCIATUS IN THE FRAGMENTED LANDSCAPE OF NORTHEAST OHIO

A Thesis Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Tara Buk May, 2014

GENE FLOW PATTERNS OF THE FIVE LINED SKINK EUMECES FASCIATUS IN THE FRAGMENTED

LANDSCAPE OF NORTHEAST OHIO

Tara Buk

Thesis

Approved: Accepted:

Advisor Dean of the College Dr. Francisco Moore Dr. Chand K. Midha

Faculty Reader Dean of the Graduate School Dr. Randall Mitchell Dr. George R. Newkome

Faculty Reader Date Dr. Peter Niewiarowski

Department Chair Dr. Monte E. Turner

ii ABSTRACT

A major obstacle to the preservation of populations is habitat fragmentation. Fragmentation often results in the isolation and subsequent loss of subpopulations. Gene flow determines the extent to which populations remain separated as independent evolutionary units, and thus affects the evolution of a . Gene flow between small fragmented subpopulations can often have great effects on the species stability. If small populations are lost and there is no migration between subpopulations, recolonization of suitable habitat does not occur and the overall population declines. The loss of naturally occurring populations reduces gene flow, which may lead to genetic differentiation. This study investigated the population structure of the five-lined skink, Eumeces fasciatus, occupying what appear to be isolated sites in the fragmented landscape of Northeast

Ohio. Populations in Akron were of particular interest because they exist in highly urbanized locales, and these lizards have rarely been recorded in Summit County. Additionally, there is a large gap in distribution record of the species statewide. Five polymorphic microsatellite markers were used to evaluate the gene flow between 5 different locations in Northeast Ohio. The gene flow estimates indicated that there is a significant pattern of isolation by distance (IBD). However, even across very broad geographical scales (170km), the IBD did not lead to a consequential divergence of populations. This data offers information on the genetic divergence of this species and contributes to our understanding of the larger problem of animal conservation in urban areas, as well as its relation to anthropogenic habitat fragmentation and degradation.

iii ACKNOWLEDGEMENTS

iv TABLE OF CONTENTS

Page

LIST OF FIGURES vi LIST OF TABLES vii

CHAPTER

I. INTRODUCTION AND BACKGROUND 1 II. MATERIALS AND METHODS 6 Study system 6 Population sampling 6 Genotyping 8 Statistical analysis 8

III. RESULTS 10

FIT 10 F IS 10

FST 10 Isolation by distance 12

IV. DISCUSSION 18 Regional population structure 18 Local population structure 19

V. CONCLUSIONS 28 REFERENCES 30

v LIST OF FIGURES

Figure Page

1 Distribution Map of E.fasciatus populations samples for this study 5

2 The Mantel tests based on pairwise differentiation values indicated a significant pattern of isolation by distance when the two summit county populations were treated as one subpopulation rather than two 15 3 The Mantel tests based on pairwise differentiation values indicated a significant pattern of isolation by distance when the two Summit County populations were treated separately 16

vi LIST OF TABLES

Table Page

1 Populations name, county, sample size (N), GPS coordinates, and FIS values. FIS was significantly greater than zero in every population, using a randomization test with 25,000 randomizations for each of the sampled Eumeces fasciatus breeding populations. (P-value for FIS within samples. based on: 25000 randomizations. Indicative adjusted nominal level (5%) for one table is: 0.002) 4 2 Locus name, number of alleles, F , F ,and F values for each IT IS ST locus and over all loci. Bootstrapping was performed over all loci to determine 95% confidence interval. All values are significant p<.05 12

3 Matrix of geographical distances (km) between the populations

studied, above the diagonal, and F S values between pairs of E. fasciatus T populations of below the diagonal. All F S values were significantly greater than 0 (p<.005) 200 permutations).T 13

4 Matrix of Nm values between pairs of populations of E. fasciatus below the diagonal. All Nm values were significant (p <.005) 14

vii

CHAPTER I

INTRODUCTION AND BACKGROUND

Population connectivity plays a crucial role in species survivability, particularly in areas affected by habitat degradation and fragmentation. Considering the continual rise in anthropogenic fragmentation, it is not surprising that understanding population connectivity has become primary goal of conservation ecology. In particular, studies that investigate gene flow between subpopulations are needed to determine whether populations are isolated, or part of the connected metapopulation that is capable of recolonization.

Previous research indicates that frequently exist in a matrix of connected subpopulations, or metapopulations (Joyal 2001, Pianka 1996, Sarre 1995, Templeton

2011). Dispersal between subpopulations is needed for the persistence of the regional metapopulation and thus plays a fundamental role in population dynamics. However, directly measuring dispersal of individuals has proven to be fairly difficult and fails to reflect the reproductive success of migrants that determines their influence on a population’s persistence. Measurement of the gene flow between populations is a simpler and more useful way to infer dispersal rates, probability of recolonization, and thus regional connectivity within the metapopulation (Howes 2006). Gene flow is directly relevant to population connectivity because gene flow data can be used to interpret reproductive success of migrants between populations rather than just movement of individuals.

1 Understanding rates of gene flow between fragmented populations can help recognize populations under threat, and clarify the degree to which loss of local populations reduce overall genetic diversity within the taxon. Management of endangered groups therefore needs to treat most populations separately because of their genetic distinctiveness and low rates of genetic exchange (Dubey 2010). Differences in dispersal among subpopulations contribute to genetic differentiation; genetic patterns can then serve as a signal of disruptions in regional population connectivity due to the effect of demographic alterations. Isolated subpopulations may be subject to increased risk of local extinction

(Frankham 2005).

Landscape-level processes on the population biology of reptiles are critical, especially for species inhabiting anthropogenically modified landscapes (Purrenhage 2009). Many studies have clearly shown that gene flow between populations is often affected by anthropogenic habitat change causing patch isolation. This type of relationship is referred to as Isolation By Distance (IBD). IBD focuses on the genetic effect of geographic isolation among patches, that is to say, it focuses on the general landscape rather than the state of the habitat patches directly. Other factors can combine with IBD to determine the ultimate genetic structure of a population (Hoffman 2004). The focus this study is on urbanization effects rather than glacial advance and retreat as in previous studies.

Geologic changes such as glacial advance may alter the population structure of but they are a relatively slow process. This study focuses on anthropogenic habitat change that has occurred over a short period of time. A previous study using mtDNA showed that phylogeographic patterns for E. fasciatus were related to divergence that predates the

Pleistocene (Howes, 2006). There are no studies on this species that explore the impacts of urbanization in the last century.

Little is known about the population dynamics of Eumeces fasciatus in the fragmented landscape of Northeast Ohio. Although the species had not been recorded

2 in Summit County in the last 5 decades, a seemingly robust population of this species has recently been located in the city of Akron. Consequently, this species offers us an opportunity to investigate the current gene flow between populations that may have been isolated due to habitat fragmentation. In order to better understand the viability of the species in this region we must understand the dispersal between subpopulations. Here we run a genetic analysis on five E. fasciatus subpopulations in Northern Ohio using nuclear DNA microsatellite data to determine gene flow. Because gene flow is an indicator of connectivity between subpopulations, it allows us to infer the probability of recolonization. This study helps determine if the Akron populations are connected both within the city and across the region.

3

Table 1: Populations name, county, sample size (N), GPS coordinates, and FIS values. FIS was significantly greater than zero in every population, using a randomization test with 25,000 randomizations for each of the sampled Eumeces fasciatus breeding populations. (P-value for FIS within samples. based on: 25000 randomizations. Indicative adjusted nominal level (5%) for one table is: 0.002)

4

Figure 1: Distribution Map of E. fasciatus populations samples for this study

5

CHAPTER II

MATERIALS AND METHODS

Study system

Five-lined are small to medium size lizards growing to about 12.5 cm to 21.5 cm total in length. Young five-lined Skinks are dark brown to black with five distinctive white to yellow stripes running along the body and a bright blue tail. In females, the blue color fades to a light blue with age, and the stripes may also slowly disappear. As they age, both sexes become uniformly brown, with the exception of a red throat and cheeks in males. Eggs are laid between May and July. Females exhibit a high level of maternal care during gestation which typically lasts between 25 and 55 days.

Population sampling

In order to study patterns of movement in this species, capture, marking and sampling is necessary. Tissue samples are required for this genetic study. In order to cause as little harm to the animal as possible toe clipping is the preferred method. Toe clipping is recommended because it is minimally invasive, marks the animal, provides a tissue sample, and because normal toe loss is high enough in these lizard populations to suggest that little or no permanent harm is caused to the animal (Clemann et al. 2007, Beaupre et al. 2004). This method is preferable to a blood draw because a blood draw requires equal trauma and the individual to be taken back to lab rather than being done directly on site. 6 A local anesthesia was used since the relatively unpredictable and potentially delayed response to immobilants or anesthetics contra indicate their use under this type of field use (Beaupre et al. 2004). Specifically, inability to behavioral thermoregulation and risk of predation would create a high mortality risk. Overnight holding needed for general anesthesia presents additional risks because it causes unnecessary stress and increased mortality (Beaupre et al. 2004).

This study was conducted in an area spanning 4500 km² in northeastern Ohio. The sampling areas are located in a landscape fragmented by roads, agriculture, urban areas, and private residences. We investigated 5 study populations located in four counties

(Table 1). Ashtabula habitat is an open field used by locals for four wheeling and dirt biking that runs parallel to the Western Reserve Greenway, a 43 mile bike trail. It was a dry area with little to no tree cover. The Geauga habitat is a pristine reservation containing established upland woods, lowland woods, marsh habitats, and several ponds. The Sandusky habitat is a public wetland wildlife area with ponds totaling more than 400 acres of water as well as large remnant prairie. The Towpath is part of an 84 mile trail that runs parallel to the little Cuyahoga River and follows a historic trail from the 1800’s. The Stairs habitat is highly urbanized area on a historic set of steps built in the early 1900’s surrounded by roadways on all sides of the patch.

Sampling was conducted from late spring to late summer. Sites were first surveyed and identified in the first hours after sunrise. Lizards are easier to find when they are basking, however more difficult to capture. After population locations were established sampling was initiated. Individuals were hand-captured, generally on warm days with high precipitation. Collection did not occur unless at least 10 tissue samples could be taken since we considered five animals to be the minimum required for analysis. No more than 20 samples were taken from any site, as previous work indicated that this

7 sample size is adequate to provide statistical detection of even low levels of gene flow

(Purrenhage et al. 2009).

Genotyping

We genotyped 83 individuals at five microsatellite loci: EuFa1, EuFa7, Eufa15, Eufa21, Eufa27 (Howes 2004). Total DNA was extracted using the E.Z.N.A Tissue

DNA extraction kit (Omega Bio-tech) following manufacturer’s instructions, and stored at 20°C. DNA extracts (diluted to 100 ng/μL) were used for the amplification of the microsatellite markers (Purrenhage 2009). We used combined hot start and touchdown polymerase chain reaction (PCR) conditions for all loci , as follows: 94°C, 2 minutes followed by 10 cycles of +94°C, 30 minutes; annealing temperature step-downs every cycle of 1°C (from 65°C to +55°C); +72°C, 1 minute. The annealing temperature for the final 25 cycles was +55°C with denaturation and extension phases as previously stated.

Alleles were then scored using Peak Scanner Software (Applied Biosystems) with a size standard of GS500LIZ-3130.

Statistical analysis

F-statistics were generated with the computer program Fstat version 2.9.3. (Goudet 2001). F-statistics are used to investigate different levels of population structure. Bootstrapping generated 95% confidence limits for all F-statistics. We were particularly interested in F , F , and F . F is the inbreeding coefficient of an individual relative to IT IS ST IT

the total. F I is the inbreeding coefficient of an individual relative to the subpopulation.F I S S is used as a measure of inbreeding within populations. A F I of 0 indicates the populations S

8 are in hardy-weinburg equilibrium. Theoretically the closer F I is to 1 the more inbreeding S is occurring. F S is the effect of subpopulations compared to the total population. We T quantified genetic differentiation between populations by using pairwise F ST based on

m allele frequencies. We then used F S to calculate gene flow (N ). Measuring dispersal of T individuals directly is difficult with such an elusive species. For this reason we used Nm estimates rather than inferring individual migration rates. Nm was calculated from the level of genetic differentiation, F , with the equation Nm=((1-F )-1)÷4. We used Nei’s ST st estimation of heterozygosity to determine heterozygosity at each loci.

Microsatellite markers must be polymorphic in order to determine diversity between populations. Allelic Richness per locus and population was quantified and the markers were indeed polymorphic, the number of alleles present at each locus ranged from five to

15. To evaluate isolation-by-distance over populations, the correlation between the linear

FST estimates, which is measured as F S / (1 – F S ), and the natural log of geographic T T distances was tested by using Mantel’s test (10,000 permutations) with Passage2.

9

CHAPTER III

RESULTS

FIT

Combining data across all loci, a significant deviation (Bootstrap p<.05) from Hardy

Weinberg equilibrium was found across the populations with an F I = 0.317 (Table 2). T

FIS

Inbreeding (F I values significantly greater than zero) was found in all 5 populations. S

FI values per population ranged from ranged from 0.174 to 0.286 with an average S of 0.237 (Table 1). The two highest F I values are seen in the two Summit County. S When Summit Stairs population was combined with the Summit Towpath population

FI increased to 0.299. This maybe expected due location of the two Summit County S populations.

FST

Significant differentiation of demes were found between all pairwise comparisons

between demes (Table 3). F ST estimates ranged from 0.025 to 0.1655 with a significant

overall F S of 0.097 (Table 2). T

10 Isolation by distance

The lowest Nm estimate calculated from pairwise FST estimates was 1.26 between the Ashtabula and Summit Stairs Populations these two populations are 92,878 meters apart (Table3&4). The Highest Nm estimate was 9.75 between the two summit county populations which are only 274 meters apart.

Overall geographic distance was related to genetic differentiation. A Mantel tests based on pairwise differentiation measures indicated a significant pattern of isolation by distance when the two summit county populations were combined (r = 0.2538, P=0.0093)

(graph1). When Summit subpopulations were considered separately, a significant pattern of isolation by distance was also detected (r = 0.5469, P=0.0005)(graph 2). This indicates significant IBD . The two Akron populations fit the larger scale trend such that more of the variation (r2=0.5469 vs. r2 = 0.2538) is explained when the local structure is included than when it is left out.

11 Table 2. Locus name, number of alleles, F , F ,and F values for each locus and over all IT IS ST loci. Bootstrapping was performed over all loci to determine 95% confidence interval. All values are significant p<.05

# of Locus Name alleles FIT FIS FST EuFa1 13 0.251 0.171 0.097 EuFa7 15 0.519 0.464 0.102 EuFa15 11 0.29 0.19 0.123 EuFa21 11 0.343 0.275 0.094 EuFa27 11 0.188 0.093 0.105

Over All Loci 0.317 0.237 0.104

95% Confidence Interval. Upper Bound 0.232 0.144 0.097 Lower Bound 0.423 0.351 0.115

12 Table 3. Matrix of geographical distances (km) between the populations studied, above the diagonal, and F ST values between pairs of populations of E. fasciatus below the diagonal. All F values were significantly greater than 0 (p<.005) 200 permutations). ST

Populations* A G S SS TP A 0 31.22 168.49 92.88 92.52 G 0.0825 0 144.12 61.73 61.52 S 0.132 0.0826 0 113.81 114.09 SS 0.1655 0.1172 0.1414 0 0.27 TP 0.118 0.0959 0.1008 0.025 0

*Populations: A-Ashtabula; G-Geauga; S-Sandusky; SS- Stairs; TP- TowPath

13 Table 4. Matrix of Nm values between pairs of populations of E. fasciatus below the diagonal. All Nm values were significant (p <.005)

Populations A G S S T A 0 G 2.780303 0 S 1.643939 2.776634 0 SS 1.260574 1.883106 1.518034 0 TP 1.868644 2.356882 2.230159 9.75 0

14

0.16 LinFst = 0.023*ln(M) - 0.1411 0.15 R² = 0.2538

0.14 Mantel test Right- 0.13 tailed p=.00938

ST

F 0.12 Lin Fst

ear 0.11 Linear (Lin Fst) n

Li 0.1

0.09

0.08 10 10.5 11 11.5 12 12.5

Natural Log Distance (m) 15

Figure 2. The Mantel tests based on pairwise differentiation values indicated a significant pattern of isolation by distance when the two Summit County populations were treated as one subpopulation rather than two

0.2 LinFst = 0.0187*ln(M) - 0.0812 0.18 R² = 0.5469 0.16 Mantel test Right- 0.14 tailed p=.00057

0.12 ST F 0.1 linFST

ear Linear (linFST)

n 0.08

Li 0.06

0.04 0.02 4 6 8 10 12

16

Figure 3. The Mantel tests based on pairwise differentiation values indicated a significant pattern of isolation by distance when the two summit county populations were treated separately

CHAPTER IV

DISCUSSION

E.Fasciatus has not been reported in Summit county in recent decades. This in conjunction with the fact that the Summit Stairs population is found in a highly urbanized area lead us to hypothesize it may have been an isolated relic population rather than connected to the larger metapopulation. We expected to see these sub-populations in summit have drifted in their gene frequencies from surrounding populations. However this data indicated that there is functional connectivity (gene flow) between all northeast Ohio subpopulations. We found that the populations are not isolated which is counter intuitive based on the information known of anthropogenic fragmentations effect on reptile population connectivity. One reason this may have occurred is that historic areas and paths such as the Glendale steps and Metroparks towpath acting as refuges and connecting corridors in locals that would have otherwise been isolated by anthropogenic fragmentation.

Regional population structure

We found a significant pattern of genetic isolation by distance. This relationship between distance and genetic differentiation was significant when looked at across regional populations with distance explaining just over 25% of the genetic variation. When we included our two local Summit County populations separately, the pattern for distance became an even better predictor explaining almost 55% of the genetic variation

17 between demes. This consistency indicates that large scale isolation may mirror the buildup of smaller scale pattern. The pattern is one of highly significant genetic isolation by distance in E.fasciatus. Yet this isolation by distance was not so high that it indicates isolation of populations within this geographic scale. In terms of genetic variation it is clear that these populations are acting as one large population and that there is gene flow occurring between populations. Levels of gene flow among our populations were

high (Nm ranging from 1.52-9.75). This in combination with low pair-wise F ST values indicates significant connectivity between populations. The levels of gene flow indicate that these populations are part of the regional metapopulation and if one of these populations were lost they would be capable of recolonization. Therefore extirpation from any of these counties is unlikely. The highest amount of gene flow was seen between the two summit populations, which is expected given their proximity. Furthermore even populations that were furthest apart demonstrated enough gene flow to be considered connected. Clearly individuals from Sandusky are not directly migrating to Ashtabula. However these high levels of gene flow may indicate there are many other undiscovered populations of E.fasciatus throughout Northeast Ohio.

Local population structure

Although we see that there is not meaningful divergence between populations we did observe substructure within populations. Considerable inbreeding was observed within each population due to non-random mating. This is reflected by the F I values S that were significantly greater than zero. The highest F I values indicated that inbreeding S is most prevalent in the habitats that are fragmented by urbanization. This may be because the surrounding habitat is more variable and has more physical barriers to individual movement. This high F I in the PineBrook and Sandusky populations may S

18 be because samples were collected from individuals from several different sites on the reservations that may actually be sites of different subpopulations. The Ashtabula population demonstrated the lowest amount of inbreeding which may be explained by the homogeneous habitat of the Ashtabula field. In Ashtabula individuals were found in a uniformly flat 17 acre field hence there were not many physical impediment to dispersal within the population.

19

CHAPTER V

CONCLUSIONS

Now more than ever, conservation biologists need to be concerned with the difficult task of managing fragmented landscapes. As expansion of urban areas and thus anthropogenic habitat fragmentation continue to rise, it is expected that populations will have reduced survivability and connectivity. Therefore, studying functional connectivity is particularly valuable in evaluating population viability. If sub-populations exhibit gene flow after a fragmentation event, the population will be more likely to persist than one that has been functionally isolated. Given our unexpected results it is clear that making generalizations about particular fragmentation effects on gene flow can be difficult.

The level of connectivity between subpopulations has a massive influence on survival and persistence of the regional metapopulation. Connectivity is particularly critical in urban landscapes since urban patches are often of lower quality and smaller size they are less likely to maintain a species in isolation. The degree to which a patch is isolated often depends on the quality of landscape between patches, thus by increasing quality of land between patches the subpopulation may experience higher connectivity. One way that management can achieve this is by reinforcing the use of corridors for maintaining metapopulation connectivity. The corridors allow organisms to bypass urban habitats such as roads and buildings that would normally be impassible. This will result in increased gene flow between subpopulations and consequently increased survivability. The data has shown that although the towpath and stairs population are found within highly anthropogenically modified environments they still exhibit a high amount of

27 geneflow with all populations. Both of these populations are near the Metroparks Towpath, an 84 mile corridor that starts in Akron and heads north into Cleveland. It is our assumption that this historical trail may be acting as a connecting corridor for Eumeces fasciatus and possibly numerous other native species. Consequently, this data reinforces that by creating and maintaining connecting corridors between populations gene flow can be maintained between populations that would have otherwise been isolated by human development.

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REFERENCES

Beaupre S.J, E.R. Jacobson, H.B. Lillywhite, and K. Zamudio (2004). Guidelines for use of Live amphibians and reptiles in field and laboratory research. Second Edition, Report of the Herpetological Animal Care and Use Committee of the American Society of Ichthyologists and Herpetologists

Carr, L. W. (2001). Effect of road traffic on two amphibian species of differing vagility. Conservation Biology 15:1071.

Clemann N., T. Langkilde and E. Wapstra (2007). Australian Society of Herpetologists Position Statement No. 1: Toe clipping of lizards.

Dubey, S., and R. Shine. (2010). “Restricted Dispersal and Genetic Diversity in Populations of an Endangered Montane Lizard (Eulamprus Leuraensis, Scincidae).” Molecular Ecology 19.5: 886-97. Frankham R. (2005).”Genetics and extinction.” Biological Conservation : 131-40

Godinho, R., E. G. Crespo, and N. Ferrand (2008). “The Limits of MtDNA Phylogeography: Complex Patterns of Population History in a Highly Structured Iberian Lizard Are Only Revealed by the Use of Nuclear Markers.” Molecular Ecology 17.21: 4670-683

Goudet J (2001). FSTAT, a Program to Estimate and Test Gene Diversities and Fixation Indices (Version 2.9.3.) Available from http://www.unil.ch/izea/softwares/fstat.html. Updated from Goudet (1995).

Greenwald, K. R., J. L. Purrenhage, and W. K. Savage. (2009). Landcover predicts isolation in Ambystoma salamanders across region and species. Biological Conservation 142:2493-2500.

Hanski, I., Pakkala, T., Kuussaari, M., & Lei, G. (1995). Metapopulation persistence of an endangered butterfly in a fragmented landscape. Oikos,21-28.

Hitchings. (1997). Genetic substructuring as a result of barriers to gene flow in urban Rana temporaria (common frog) populations: implications for biodiversity conservation. Heredity 79:117.

Hoffman, E.A.; Blouin, M.S(2004). “Evolutionary history of the northern leopard frog: reconstruction of phylogeny, phylogeography, historical changes in population demography from mitochondrial DNA.” Evolution : 145–159.

29

Howes, B. J., B. Lindsey, and S. C. Lougheed.(2006). “Range-wide Phylogeography of a Temperate Lizard, the Five-lined Skink (Eumeces Fasciatus).” Molecular Phylogenetics and Evolution 40.1: 183-94.

Johansson. (2005). The influence of landscape structure on occurrence, abundance and genetic diversity of the common frog, Rana temporaria. Global Change Biology 11:1664.

Joyal, L. A., McCollough, M., & Hunter, M. L. (2001). Landscape ecology approaches to wetland species conservation: a case study of two turtle species in southern Maine. Conservation Biology, 15(6), 1755-1762.

Nichols, RA, and KL Freeman. (2004). “Using Molecular Markers with High Mutation Rates to Obtain Estimates of Relative Population Size and to Distinguish the Effects of Gene Flow and Mutation: a Demonstration Using Data from Endemic MauritianSkinks.” Molecular Ecology : 775-87.

.Pianka, E. R. (1996). Long-term changes in lizard assemblages in the Great Victoria Desert. Long-term studies of vertebrate communities (ML Cody and JA Smallwood, eds.). Academic Press, New York, 191-215.

Purrenhage, J. L., P. H. Niewiarowski, and F. B. Moore. (2009). “Population Structure of Spotted Salamanders (Ambystoma Maculatum) in a Fragmented Landscape.” Molecular Ecology :235-47.

Richmond, J.Q.; Reeder, T.W. (2002). “Evidence for parallel ecological speciation in scincid lizards of the Eumeces skiltonianus species group (: Scincidae).” Evolution. v. 56 p. 1498–1513.

Sarre, S., Smith, G. T., & Meyers, J. A. (1995). Persistence of two species of gecko (Oedura reticulata and Gehyra variegata) in remnant habitat. Biological conservation, 71(1), 25-33.

Templeton, A. R., Brazeal, H., & Neuwald, J. L. (2011). The transition from isolated patches to a metapopulation in the eastern collared lizard in response to prescribed fires. Ecology, 92(9), 1736-1747.

Wright, K. M. Whitaker, B. R. “Surgical techniques.” Amphibian Medicine and CaptiveHusbandry (2001): 273-47.

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