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Genetic diversity and population structure of non-indigenous burmese pythons (Python MolurusBivittatus) in Everglades National Park, FloridaBarbara L. FreemanFlorida International University

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Recommended CitationFreeman, Barbara L., "Genetic diversity and population structure of non-indigenous burmese pythons (Python Molurus Bivittatus) inEverglades National Park, Florida" (2008). FIU Electronic Theses and Dissertations. 3415.https://digitalcommons.fiu.edu/etd/3415

FLORIDA INTERNATIONAL UNIVERSITY

Miami, Florida

GENETIC DIVERSITY AND POPULATION STRUCTURE OF NON-

INDIGENOUS BURMESE PYTHONS (PYTHON MOLURUS BIVITTATUS) IN

EVERGLADES NATIONAL PARK, FLORIDA

A thesis submitted in partial fulfillment of the

requirements for the degree of

MASTER OF SCIENCE

in

BIOLOGY

by

Barbara L. Freeman

2008

To: Dean Kenneth FurtonCollege of Arts and Sciences

This thesis, written by Barbara L. Freeman, and entitled Genetic Diversity and PopulationStructure of Non-Indigenous Burmese Pythons (Python molurus bivittatus) in EvergladesNational Park, Florida, having been approved in respect to style and intellectual content,is referred to you for judgment.

We have read this thesis and recommend that it be approved

Maureen A. Donnelly

Javier Francisco-Ortega

Timothy M. Collins, Major Professor

Date of Defense: May 9, 2008

The thesis of Barbara L. Freeman is approved.

Dean Kenneth FurtonCollege of Arts and Sciences

Dean George WalkerUniversity Graduate School

Florida International University, 2008

ii

ACKNOWLEDGMENTS

I would like to thank Dr. Timothy Collins for being my supervisor, and my

committee members Dr. Maureen Donnelly and Dr. Javier Francisco-Ortega. I extend my

thanks to Dr. Matthew Osentoski for his assistance with lab research and manuscript

preparation. This research is in cooperation with Skip Snow and Everglades National

Park who provided all Everglades National Park and Vietnam snake samples. I would

like to thank Dr. Timothy Rawlings, Paul Sharp, Duane Choquette, Oriana Perez, and

Cindy Chan for their assistance in the lab and acquiring samples. Also thanks to Sunset

Reptiles for providing a shed skin from their Burmese python. This research has been

funded with a grant that has been provided by the South Florida Water Management

District, and augmented by a Teaching assistant scholarship, a General Scholarship, and

an Adolfo Henriques Scholarship from FlU. Finally I would like to thank my family,

especially my husband, for their support.

iii

ABSTRACT OF THE THESIS

GENETIC DIVERSITY AND POPULATION STRUCTURE OF NON-INDIGENOUS

BURMESE PYTHONS (PYTHON MOL UR US BIVITTATUS) IN EVERGLADES

NATIONAL PARK, FLORIDA

by

Barbara L. Freeman

Florida International University, 2008

Miami, Florida

Professor Timothy Collins, Major Professor

One of the more recent vertebrate introductions to South Florida's Everglades is

the Burmese Python, Python molurus bivittatus. These pythons prey on and may compete

with native species for habitat and prey. Molecular data including rnitochondrial DNA

sequences and microsatellite loci was used to examine the genetic diversity of Burmese

pythons sampled from Everglades National Park, determine whether this diversity

suggests that the populations are distinct or part of a single large population, and

determine if there is genetic evidence for parthenogenetic reproduction in P. m. bivittatus

in ENP. Multiple population analyses revealed that the ENP Burmese pythons display

low genetic differentiation suggesting no significant substructure. One cause for this low

differentiation may be that the pythons are interbreeding and spread throughout the park.

There is no evidence of parthenogenetic reproduction in the sampled ENP pythons.

Management strategies should focus on controlling a large established population.

iv

TABLE OF CONTENTS

CHAPTER PAGE

I. INTRODUCTION.................................................................... 1Invasive species......................... ........... ............................... 1

Burmese pythons in Everglades National Park.................................. 3

Analyses of population structure 7................................................ 7

II. METHODS 2......................................................................... 12Sample collection .................................................................... 12Mitochondrial DNA...... ............ . ..... .......... ......... 12Microsatellite genotyping............................................................ 13Population analyses ................................................................ 15

III. R E SU L T S 8.................................................................... ....... 1Mitochondrial DNA.... ............................................................ 18Number of populations .......................................................... 18Population assignment............................................................. 21F-statistics and Hardy Weinberg equilibrium ................................... 21

Geneotyping errors ................................................................ 23

IV. DISCUSSION ............................................................... 24

LIST OF REFERENCES ................. ................ .......- . . 58

APPENDICES 67

v

LIST OF TABLES

TABLE PAGE

1. Inferred ancestry of individuals from STRUCTURE, K2............................ 32

2. Inferred ancestry of individuals from STRUCTURE (data set without Vietnampythons) K =4................................................................................... 34

3. Population assignm ents from H ...................................................... 38

4. Observed and expected heterozygosity..- - ................................ 42

5. Tests for Hardy Weinberg equilibrium .................................................. 43

6. Fst and migrants per generation between ENP and Vietnam populations..... 44

7. Fst and migrants per generation among all ENP subpopulations .................... 45

8. Pairwise Fst and Nm for four ENP populations from STRUCTURE............... 46

9. Alleles at each locus for embryos and their mothers ...................-.. . 47

vi

LIST OF FIGURES

FIGURE PAGE

1. Collection sites in Everglades National Park........................................... 48

2. Primers used for amplifying and sequencing the mitochondrial control region inPython molurus bivittatus ..................................................................... 50

3. Two of six microsatellite regions, PM1 and PM2 ...................................... 51

4. Results from STRUCTURE with the entire data set.......... ...... .... ...... 52

5. Results from STRUCTURE for the data set without the Vietnam pythons ...... 53

6. Results from STRUCTURE, K=2, cluster assignment ................................. 54

7. Results from STRUCTURE for data set without Vietnam pythons, K=4, clusterassignment ...................................................................................... 55

8. Results from TESS with entire data set ................................................ 56

9. Results from TESS for the data set without the Vietnam pythons ................... 57

vii

I. INTRODUCTION

The Burmese python, Python molurus bivittatus, has been introduced to

Everglades National Park (ENP), and has the potential to be an invasive species that

threatens the native ecosystem. Ascertaining the population genetic structure of these

introduced pythons can help to reveal the extent and spread of the introduction, as well as

facilitate management strategies.

Invasive species

Invasive species are increasingly recognized as a growing environmental and

economic problem (Pimentel et al., 2000; Mooney, 2001; Clavero and Garcia-Berthou,

2005). Once an invasive species becomes established it is difficult to eradicate (Myers et

al., 2000; Ricciardi et al., 2000; Simberloff, 2001; Simberloff, 2003), so control measures

should focus on preventing introductions. Genetics and phylogenetics provide valuable

information needed for the study, management, and prevention of invasive species. This

is especially true with the development of microsatellites, single nucleotide

polymorphisms (SNPs), and high-throughput DNA sequencing, which facilitate the

acquisition of high-resolution data on the genetic structure of populations. Population

genetics can provide information on dispersal, breeding, and migration patterns (Scribner

et al., 2005; Abdelkrim et al., 2007; Herborg et al., 2007). Genetic data can also be

informative about the possible success of an invasion. For example, an increase in genetic

diversity may increase an introduced population's ability to adapt to and therefore invade

a new environment, while limited genetic diversity may impede adaptation and

establishment of a population (Garcia-Ramos and Rodriguez, 2002; Roman, 2006;

1

Stepien and Tumeo, 2006). Understanding the genetics and population structure of an

introduced species can help determine the best strategies for management, such as

immunocontraception (Boyle, 1994; Committee, 1996; Ylonen, 2001), eradication of

isolated subpopulations, and control of dispersal boundaries (Sharov and Liebhold, 1998;

Myers et al., 2000; Cowled et al., 2007). Phylogenetics can provide information on the

taxonomy of the introduced species and the relatedness among introduced populations, as

well as link the introduced population(s) to their source (Baker and Moeed, 1987; Collins

et al., 2002; Hufbauer et al., 2004; Stepien and Tumeo, 2006).

Reptile invasive species contribute to the ongoing problem of declining

biodiversity. Introduced reptiles are often new predators. Impacts from these

introductions can be extreme, as in the case of the brown tree snake on Guam, which

eliminated native vertebrate populations (Savidge, 1987; Rodda et al., 1997; Fritts and

Rodda, 1998; Perry et al., 1998). Reptile species may introduce new parasites to an area,

affecting native fauna, and directly affecting humans. Many reptile species bring

introduced ticks with them, and the chance for the spread of new diseases (Burridge,

2001, Simmons and Burridge, 2002). Some introduced species can pose a direct health

risk to humans, for example, in Sio Paulo City, Brazil, sixteen exotic snake species,

many of them venomous, were reported in 2002 (Eterovic and Duarte, 2002). The

introduction of these species was most likely due to the release of imported exotic pets.

The United States is a major importer of live reptiles, any of which enter through

Florida (Burridge, 2001; Simmons and Burridge, 2002).

The problem of invasive species is especially pressing in South Florida

(Simberloff et al., 1997). Examples of problematic introductions in the southeastern

United States include Brazilian Pepper, Schinus terebinthifolius, which has already taken

over many regions of South and Central Florida, displacing native plant species and

eliminating food sources for native vertebrate species (Ferriter and Clark, 1997). This

invasive plant provides food for birds, which in turn facilitate dispersal, complicating

control. Invasive vertebrates are also problematic in the southeastern U.S. The brown

anole, Anolis sagrei, introduced to Florida is a generalist in diet and habitat use, and is

successfully competing with and consuming native lizards (Campbell and Echternacht,

2003). Another recent and alarming introduction to the southeastern US is the

amphibious swamp eel (Monopterus spp.), with populations from different sources

threatening ecosystems in Florida and Georgia (Collins et al., 2002).

Burmese pythons in Everglades National Park

One of the more recent vertebrate introductions to South Florida's Everglades is

the Burmese Python, Python molurus bivittatus. Burmese pythons have been found in

Everglades National Park (ENP) since the early 1980's (Meshaka et al., 2000) but have

shown a dramatic increase in numbers since 1995 (Snow, 2006). Because pythons have

been sampled from geographically disparate locations in ENP (Snow, 2006), it is

believed that this introduction is a result of several instances of pet release. Python

molurus is a constrictor with a general diet. In its native range of Southeast Asia this

python can reach up to six meters in length and over 90 kilograms in weight, with a

lifespan of up to 25 years (Ernst and Zug, 1996). Effects of this invasion have not yet

been studied extensively, but preliminary evidence suggests that pythons compete with

native species for habitat and prey (Snow, 2006). In ENP the pythons prey on native

species, including the gray squirrel, opossum, cotton rat, black rat, raccoons, bobcat,

3

house wren, pied-billed grebe, limpkin, and white ibis (latter two are species of special

concern) (Snow et al., 2007). Other species of special concern such as the native

mangrove fox squirrel could also provide a suitable food item for pythons in ENP. Gut

content analysis of a Burmese python found in Key Largo revealed endangered wood rats

(Scott Hardin, personal communication). Endangered birds such as the wood stork are at

risk as the python diet generally includes birds. Pythons have been spotted in close

proximity to birding "hot spots" like Mrazek Pond, Eco Pond, Paurotis Pond and the

Tamiami West wood stork rookery (Snow, 2006).

The Burmese python possesses several characteristics of a successful invader.

Burmese pythons are diet generalists, sometimes killing prey so large it cannot be

swallowed, as seen in tragic accounts of pet pythons killing children and even adolescents

(Chiszar et al., 1993; Herszenhorn, 1996). They are considered terrestrial, but are fully

capable of climbing trees and swimming. With its general diet and ability to swim and

climb, the Burmese python is a novel predator to the Everglades. The alligator is the only

possible predator of the introduced python in the Everglades, but Burmese pythons may

also prey on alligators, as witnessed in October 2005 in ENP (Snow et al., 2007). In that

case the alligator that the python swallowed was too large and the snake did not survive.

Altercations between large pythons and alligators that have ended in a "draw" have also

been witnessed (Lovgren, 2004). In summary, the potential impact of Burmese pythons

on the native fauna of the Florida Everglades is unknown, but the possibilities are

sobering.

The extent of the invasion of Python molurus bivittatus in ENP is unknown.

Young snakes as well as female snakes with eggs and broods have been captured,

4

providing evidence of reproduction. Pythons have been captured and sighted in different

geographical areas of Everglades National Park. It is unclear whether this distribution

results from separate introductions, or a single population that has become established in

ENP. Molecular evidence can determine if the population consists of one or several

different genetic units, and whether the distribution is patchy or uniform. Knowledge of

population structure is fundamental for developing a control and management plan for an

invasive species (Cowled et al., 2006; Abdelkrim et al., 2007; Cowled et al., 2007; Scalici

and Gherardi, 2007), but the size, geographical extent, or degree of connectedness among

populations in ENP is not known. In this project, I examine the parentage and

relationships among individual pythons captured in various areas of the park using

molecular techniques to address the following questions. What is the genetic diversity

and population structure of Python molurus bivittatus in ENP? Does the distribution of

genetic diversity suggest that the populations sampled to date are distinct, to be managed

separately, or are they likely part of a single large population. Finally, is there genetic

evidence for parthenogenetic reproduction in Python molurus bivittatus in ENP?

Molecular evidence for parthenogenesis has been observed in a study of captive

Python molurus bivittatus in the Artis Zoo in Amsterdam (Groot et al., 2003) but has not

been demonstrated in wild populations. In that study, comparisons of microsatellite and

AFLP markers showed that a female who had been separated from males had offspring

that were all genetically identical. Limited genetic variation may suggest that this python

species has the ability to develop parthenogenetically in their introduced habitat.

Parthenogenesis should result in an excess of homozygotic and female individuals.

Parthenogenesis has not been verified in Burmese Pythons in Florida; among the snakes

5

collected for this study there does not seem to be a shortage of males, however the snakes

were mostly collected on or near roads and do not represent a random sample. Female

snakes captured with eggs provide an opportunity to explore this phenomenon, as

offspring should be genetically identical females if parthenogenetically produced. This

mode of reproduction may have important implications for the establishment and spread

of populations of this species.

Population structure can be tested by studying the distribution of multi-locus

genotypes within ENP. The Burmese pythons in Everglades National Park may be one

interbreeding population that is spread throughout the park (panmictic), or distinct

subpopulations that are isolated in breeding and geographical area (subdivision). If there

is significant differentiation within the sampled ENP pythons then the population is not

panmictic and there may be multiple subpopulations. Multiple independent introductions

in different geographical areas of the park could produce genetically isolated populations

with little to no interbreeding and gene flow. If the genetic differentiation is moderate the

population most likely is not panmictic, but may display limited substructure. If there is

very little to no genetic differentiation, then the ENP pythons are most likely a panmictic

population. This possibility could be a result of interbreeding pythons that are spread

throughout the park. However there are other possible reasons for low levels of genetic

differentiation in the ENP pythons. These snakes may be the result of introductions of a

few individuals into a new environment with resulting founder effects. Founder effects

reduce genetic variation including a decrease in number of alleles and heterozygosity,

and a loss of rare alleles (Baker and Moeed, 1987; Hufbauer et al., 2004; Rasner et al.,

2004; Hawley et al., 2006). Limited genetic variation can impede adaptation to novel

environments and the evolution of genetic differentiation. Furthermore these pythons are

most likely not from a wild, native source population, but their source is likely a captive

bred population, which may have very little genetic variation as a result of extensive

inbreeding. Given that the majority of the introductions of Burmese pythons to ENP were

most likely pets from the captive bred reptile trade, snake populations in ENP could

display a lack of genetic variation, and therefore lack differentiation. Low genetic

differentiation along with an excess of females and homozygotes, and genetically

identical offspring would suggest that the Burmese pythons in ENP are reproducing

parthenogenetically.

Analyses of population structure

Most tests for substructure involve testing the allelic frequencies of a population

for Hardy-Weinberg equilibrium (HWE), and assigning individuals to subdivisions based

on the distribution of alleles in the total population. A population is in Hardy Weinberg

equilibrium when expected and observed genotype frequencies are not significantly

different, This can be calculated by the Chi-square test where

[(observed - expected)2 I expected] (Hartl, 2000)

Observed heterozygosity can be low and the total population not in HWE if the

population consists of subpopulations in HWE but with differing allelic frequencies

(Wahlund, 1928). Wright's fixation indices (F-statistics) can evaluate population

subdivision by measuring heterozygosity (Wright, 1931; Wright, 1965; Weir and

Cockerham, 1984). Of the three indices FST is the most useful for evaluating population

7

substructure, and compares the heterozygosity within subpopulations (Hs) to the

heterozygosity within the total population (HT):

FsT = HT - Hs / HT (Hartl, 2000)

FST measures genetic differentiation where FsT= 0 when the population is panmictic with

no subdivision or differentiation and EsT = 1 when there is complete isolation with great

differentiation between subdivisions (Hartl and Clarck, 1997). FsT values from 0 to 0.05

are considered to represent little genetic differentiation, 0.05 to 0.15 moderate genetic

differentiation, 0.15 to 0.25 great genetic differentiation, and over 0.25 very great genetic

differentiation (Wright, 1978). Linkage disequilibrium (LD or D), where genes are not in

random association, can be measured as the difference between the observed and

expected frequency of a genotype in a population. LD can also reveal departure from

HWE and may be the result of an admixture of subpopulations with differing allelic

frequencies (Hartl, 2000). Using these methods to compare alleles for multiple unlinked

loci can reveal the presence and the structure of population subdivision.

Mitochondrial DNA sequences have been used in many studies of non-indigenous

populations (Collins et al, 2002; Downie, 2002; Facon et al., 2003; Mun et al., 2003;

Bachelet et al., 2004; Roman and Palumbi, 2004; Cognato et al., 2005) because of useful

attributes such as ease of amplification and both conserved and highly divergent regions.

The control region is a non-coding, variable segment of the mitochondrial genome with a

high mutation rate making it ideal for comparing relationships among more recently

diverged taxa, such as populations within a species. Microsatellite markers possess

features such as high mutation rates and Mendelian inheritance profiles (Zhang and

Hewitt, 2003) and are often used for intraspecific population studies (Escorza-Trevino

and Dizon, 2000; Tsutsui et al., 2000; Diniz-Filho and de-Campos-Telles, 2002; Kaeuffer

et al., 2004; Sacks et al., 2004; Rowe and Beebee, 2007; Zamudio and Wieczorek, 2007)

including studies of introduced populations (Hufbauer et al., 2004; Cowled et al., 2006;

Hawley et al., 2006; Spencer et al., 2006; Vargo et al., 2006; Abdelkrim et al., 2007;

Cowled et al., 2007; Webly et al., 2007) and species under non-equilibrium conditions

(van der Strate et al., 2003; Gilchrist et al., 2006; Pearse et al., 2006). The Python

molurus bivittatus individuals in Everglades National Park are relatively recently

introduced and therefore may be under non-equilibrium conditions associated with

founder effects, which often result in low genetic variation, loss of alleles, and decrease

in heterozygosity in the introduced population (Baker and Moeed, 1987; Rasner et al.,

2004; Hawley et al., 2006). The ENP pythons may also be primarily from a captive bred

reptile trade population possessing little genetic variation as a result of inbreeding. This

lack of variation would also cause a departure from Hardy Weinberg and linkage

equilibrium. Most tests for population substructure define subpopulations as groups of

individuals that are in Hardy-Weinberg equilibrium (HWE). However, HWE makes

multiple assumptions about a population such as a large population size and random

mating. Because the ENP Burmese python population may not be in equilibrium,

comparing multiple analyses employing differing genetic and statistical methods may

help to reduce the effect of violation of equilibrium assumptions (Pearse et al., 2006).

There are many methods available for population genetic analysis of

microsatellite allele data (Pearse and Crandall, 2004; Excoffier and Heckel, 2006).

Classic F-statistics, particularly FsT, can be used to measure population subdivision with

9

values that indicate the genetic differentiation within the total population analyzed.

Programs such as GENALEX (Peakall and Smouse, 2006) and GENEPOP (Raymond

and Rousset, 1995) provide tests for HWE, allele patterns, heterozygosity, F-statistics,

and population assignment. Both programs use exact tests for HWE, however,

GENEALEX uses a Chi-squared test while GENEPOP, the more exact program, uses the

Markov chain method and provides standard error for each estimate of probability.

While still informative, Fs-r based analyses assume that populations are in HWE

and should not be used alone as they may not be best suited for microsatellite loci with

multiple alleles or high mutation rates, which violate the assumption of mutation

equilibrium (Weir and Cockerham, 1984; Pearse and Crandall, 2004). Newer methods

employing Bayesian and maximum likelihood approaches such as assignment methods

and tests may be more appropriate, as these use the concept of coalescence that infers the

evolutionary history of the population and not simply the current allele distribution

(Pearse and Crandall, 2004; Manel et al., 2005). Clustering methods that determine how

many subpopulations are present within the total population of genotypes analyzed and

assign individuals to subpopulations will be used to analyze the microsatellite alleles. For

example, STRUCTURE (Pritchard et al., 2000) uses a Bayesian approach with a Markov

chain Monte Carlo estimation to cluster individuals into subpopulations that approach

Hardy-Weinberg equilibrium (HWE) and linkage equilibrium, and provides an estimate

for the most likely number of clusters or subpopulations (log probability of K where K is

the number of clusters) while assigning individuals to those clusters. STRUCTURE also

calculates allele frequencies and the proportion of an individual's genome that originated

from its assigned cluster (Q). However, it has been observed that log probability of K

10

does not always define the real number of clusters (K) (Pritchard et al., 2000; Evanno et

al., 2005; Latch et al., 2006), but a second order rate change with respect to K (AK as

defined in Evanno et al., 2005) will show the true value of K.

TESS (Francois et al., 2006; Chen et al., 2007) is a Bayesian model that

additionally incorporates spatial or geographical locations of the individuals to assess

number of clusters and assignment. TESS uses a hidden Markov random field, which

uses the geographical coordinates as prior distributions on cluster assignment, in other

words it states that allele frequencies are more likely to be closely related to those from

neighboring sites as opposed to those from distant sites.

Assignment tests assign individuals based on their genotypes to their population

of origin. Populations must be defined by the user, so these tests can only be done when

the number of populations in the data set is known. DOH (Paetkau et al., 1995) assigns

individuals of unknown populations to user-determined candidate populations by

calculating the likelihood that an individual's genotype belongs in a certain population

based on HWE and linkage equilibrium. DOH will also reassign any individuals that are

not in their nominal (sampled) population. The majority of the aforementioned programs

calculate allele frequencies within populations. These analyses will help determine

genetic diversity and population structure of the Burmese Pythons in Everglades National

Park.

11

II. METHODS

Sample collection

Python molurus bivittatus tissue samples from 156 individuals were collected

from various regions of Everglades National Park (Figure 1). The sample included two

mothers with their broods (one with six and one with fourteen embryos). Python

individuals were usually collected at night on or along park roads. UTM and/or a

description of geographic location were recorded for all but six individuals. When

possible information on sex, size, and reproductive condition such as testis size in males

and number and size of oviductal eggs in females was recorded. These data provided

information on sex ratio, estimated age and reproductive status to indicate breeding

patterns. I also sampled thirteen snake skins from Python molurus bivittatus from their

native range in Vietnam, assumed to be from a wild population, as well as a skin shed by

a Burmese python for sale at a local pet store (see Appendix I and Figure 1 for collection

details). DNA was isolated from muscle tissue from the head and "neck", tail, mid-body

ribs; the entire embryo; or snake skin using standard phenol chloroform extraction

methods (Saghai-Maroof et al., 1984).

Mitochondrial DNA

In a subset of sixteen Burmese pythons from different regions of ENP a 360 base

pair region of the mitochondrial cytochrome b gene was amplified with the polymerase

chain reaction (PCR) with an initial denaturation step of 5 minutes at 94°C, 37 cycles at

94°C for 1 minute, 50°C for 1:30 minutes and 72°C for 1 minute, followed by an

extension step at 49°C for 1 minute and 72°C for 4 minutes. Reactions were performed in

12

an MJ Research PTC-200 thermal cycler in 25 or 50ul volumes with 10-100ng genomic

DNA, 1.5uM MgCl 2, each dNTP at 10mM, 1X Promega B buffer, 0.5 units Promega Taq,

and 1 uM of each primer. I used primers that were originally developed for catfish, but

were found to be similar to primers previously developed for snake species (Wong et al.,

2004). Cycle-sequencing used Big Dye version 3.1 chemistry (PE-ABI) with conditions

at 10 seconds at 96°C, 5 seconds at 50°C, and 4 minutes at 60°C through thirty cycles.

Cytochrome b regions were sequenced with an ABI Prism 3100 Genetic Analyzer with a

50cm capillary and compared in MacClade 4.03 (Maddison and Maddison, 2001). Two

sets of primers for the control region previously used for snakes (Kumazawa and Nishida,

1993; Kumazawa and Nishida, 1995; Kumazawa et al., 1996) did not yield specific

amplification products, so external and internal primers were designed specifically for the

ENP Python molorus bivittatus individuals (Figure 2). In a subset of the sampled snakes

including eleven ENP pythons from different regions, a skin from a Burmese python for

sale at a local reptile store, and two of the Vietnam skins, mitochondrial control region

sequences were isolated using the new species-specific primers in PCR reactions and

cycle sequencing reactions similar to the methods mentioned above (annealing

temperature for external primers was 57-620C), and were sequenced with an ABI Prism

3100 Genetic Analyzer and compared in MacClade 4.03 (Maddison and Maddison,

2001).

Microsatellite genotyping

Six microsatellite regions previously designed for Python molurus bivittatus to

study parthenogenetic reproduction (Burns and Houlden, 1999; Prosser et al., 1999;

13

Groot et al., 2003) were amplified with PCR reactions in 10ul volumes with

approximately 50ng genomic DNA, 2-3uM MgCl 2, each dNTP at 10mM, 1X Promega

buffer B, 0.5 units Promega Taq, and 1 uM of each primer. PCR conditions included an

initial denaturation step at 94°C for 5 minutes, and 36 cycles at 94°C for 30 seconds,

50.5°C for 45 seconds, and 72°C for 1 minute. Microsatellite alleles were compared

visually with gel electrophoresis. Variation was limited with one locus displaying only

two alleles while the remaining five loci were homozygous for one allele (Figure 3)

making these loci unsuitable for detailed population structure studies.

Jordan et al. (2002) developed 27 microsatellite loci conserved across 13 different

Australian python species, which were tested on the ENP Python molurus bivittatus. Ten

of these loci were suitable for population analysis, displaying clean amplification and

polymorphism, and were amplified with PCR reactions in 10ul volumes with

approximately 50ng genomic DNA, 2uM MgCl 2 , each dNTP at 10mM, 1X Promega

buffer B, 0.5 units Promega Taq, and 1 uM of each primer. PCR conditions included an

initial denaturation step at 94°C for 5 minutes, and 36 cycles at 94°C for 30 seconds, 56

or 58°C depending on primer pair (Table 4) for 45 seconds, and 72°C for 1 minute, with

an additional extension at 72°C for 8 minutes. Microsatellite alleles were compared

visually with gel electrophoresis, and each locus was sequenced to confirm correct

amplification of the expected repeat sequence. Microsatellite PCR products were run for

fragment analysis on the ABI Prism 3100 or 3130 Genetic Analyzer using POP4 polymer

in both machines to result in consistent allele sizes between them, and fragment sizes

were analyzed with GeneScan3.1 and 3.7 or GeneMapper4 software (Applied

Biosystems).

14

Population analyses

Microsatellite data for both the entire data set (170 individual Burmese pythons)

and the data set without the Vietnam pythons (157 individuals) were analyzed using

STRUCTURE (Pritchard et al., 2000) to determine the number of populations and

assignment of individuals, as well as FsT for each cluster (population). Each run included

1 million iterations with a burnin of 10,000. Pritchard et al. (2000) used 1,000,000

iterations in simulation studies to test their program. While various studies have used

different burnin values for STRUCTURE, Evanno et al (2005) found that burnins longer

than 10,000 did not change results significantly, and I observed that results did not vary

greatly over separate, independent runs. I set values for K (number of populations) equal

to 1-15, with 10 runs for each K, using the admixture model with allele frequencies

correlated. It has been observed that the admixture model and correlated allele

frequencies is best suited for populations that may have similar frequencies due to

migration or common ancestry, and therefore have low differentiation and subtle

population structure (Falush et al., 2003; Latch et al., 2006; Rowe and Beebee, 2007). A

second order rate change with respect to K (AK) as defined in Evanno et aL, 2005 was

calculated.

The entire data set was examined using the program TESS (Francois et al., 2006;

Chen et al., 2007) adding UTM coordinates for each individual where possible, using the

admixture model, 100,000 iterations with a burnin of 10,000 for each run for maximal

number of clusters (K) equal to 1-15, 10 runs for each K. The entire data set was also run

in TESS not using the admixture model also for values of K equal to 1-15, 10 runs for

15

each K, 100,000 iterations with a burnin of 15,000. These initial runs without the

admixture model resulted in estimated population numbers of 2, 3, and 4, so 100 more

runs with the same parameters and with the maximum value for K set to 4 were

performed. The TESS manual recommends a burnin of 10,000 and 50,000 iterations,

starting at a maximal number of 2 clusters. After examining the point of stabilization in

the log likelihood history of preliminary runs, a burnin value of 15,000 seemed more

appropriate for the non-admixture runs. Again variation was minimal across different,

independent runs for the same K. The data set without the Vietnam pythons was also run

in TESS using the same parameters for non-admixture runs, K equal to 1-15, 10 runs for

each K.

Using the value of K and the assignments determined by the first three programs

the data were analyzed in DOH (Paetkau et al., 1995) treating any outlier individuals or

those with probabilities of assignment less than 0.9 as having unknown population origin

to confirm their correct assignment. The data were analyzed in GENALEX6 (Peakall and

Smouse, 2006) and GENEPOP 3.4 (Raymond and Rousset, 1995) also using the number

of populations and assignments from previous analyses to test for Hardy Weinberg

equilibrium and determine observed and expected heterozygosity, allele patterns, number

of migrants per generation (Nm) and FST. Embryos were omitted from these analyses

because their presence would violate assumptions of HWE.

MICRO-CHECKER (Van Oosterhout et al., 2004) analyses were performed to

check for genotyping errors in the ENP and Vietnam subpopulations determined by the

previous analyses, using a 99% confidence interval. These errors commonly result in

incorrect scoring, and include null alleles (an allele fails to amplify during PCR), stutter

16

(a product created from slip strand amplification in PCR), and large allele dropout (large

alleles fail to or do not amplify efficiently compared to small alleles) (Bonin et al., 2004;

Hoffman and Amos, 2005; Selkoe and Toonen, 2006).

17

111. RESULTS

Mitochondrial DNA

Data from the subset of Burmese Python individuals captured in various areas of

the park showed that there was no variation within the cytochrome b sequences among

the Everglades National Park individuals, but some variation was present between the

ENP pythons and Python molurus sequences downloaded from GenBank (Slowinski and

Lawson, 2002). SS127 and 5224 were the only individuals collected from ENP that

differed within the approximately 1300 base pair control region sequence. SS127 and

SS224 displayed 6 and 2 differences respectively from the other ENP pythons. There

were only 3 differences between the ENP pythons and a python from a local pet store and

4 between the ENP pythons and the Vietnam pythons (DNA extracted from snake skin).

The lack of variation in these two regions among the ENP pythons suggests that

mitochondrial DNA is not a useful molecular marker to assess genetic structure within

this particular population. However, three of the differences seen in the control region

were parsimony informative. One difference linked the two Vietnam pythons, one linked

SS127 and the store python, and the third linked the Vietnam pythons, SS127, the store

python, and SS224 together. I discuss the possible significance of these results below.

Number of populations

The average number of alleles for each microsatellite locus was eleven with a

range from seven to sixteen (Appendix II). Of 170 individuals thirteen had missing data,

the majority only missing one or two loci and one individual missing five loci. The

estimated number of populations (K) determined by STRUCTURE based on highest log

18

probability of K, was five, with a log probability of -4363.07. The log probability of K

reached a plateau at two after which standard deviation increased (Figure 4a). These data

are consistent with observations that the log probability of K tends to plateau at the true

number of populations and climb slightly while variance among runs increases (Pritchard

et al., 2000; Evanno et al., 2005; Latch et al., 2006). It has been suggested that Evanno et

al's (2005) second order rate change (AK) is a better indicator of the true value of K in

this situation. The calculation of AK for this data set revealed two clusters (Figure 4b).

The probability of assignment or Q, also described as the estimated membership

coefficient of an individual to or proportion of individual's genome originating from a

cluster (Pritchard et al., 2000), was less than 0.9 in only two snakes (Table 1, Figure 6).

One cluster included the majority of the Everglades National Park pythons (ENP cluster)

while the other cluster included all of the Vietnam pythons, the store snake, and three of

the ENP pythons: SS127, SS224, and SS384 (Vietnam cluster). However SS384's

assignment is not definite as the average Q values were 0.4299 to the ENP cluster and

0.5701 to the Vietnam cluster. Q values from analyses where K is set to three show that

SS127, SS224, SS384, and the store python would not group with either the ENP or

Vietnam clusters.

When the data was run without the Vietnam pythons STRUCTURE grouped the

remaining pythons (ENP samples and store sample) into four clusters with an average log

probability of K of -3884. This was the highest log probability of K, but also had the

greatest standard deviation (Figure 5a). AK also indicates four as the number of clusters

(Figure 5b). However, individuals do not have decidedly large proportions of their

19

genotypes belonging to their cluster (average Q value was 0.5888) and the clusters divide

up SS006 and her set of embryos and distribute them into all four clusters (Table 2,

Figure 7). The four clusters show no geographic pattern.

Using the geographical coordinates as an a priori parameter, and when using the

admixture model, the program TESS always estimated number of clusters to be equal to

the maximal number of clusters input for each run. When run without the admixture

model, the estimated number of clusters was two, three, or four (excluding runs where

maximum cluster number was 1) with the majority of the runs displaying two clusters.

When the entire data set was rerun with the maximal number of clusters equal to four, the

estimated number of clusters was two in 76% of the runs with an average log-likelihood

of -4384, and three in 24% of the runs with an average log-likelihood of -4383. The

majority of one cluster represented an Everglades National Park (ENP) cluster and the

other a Vietnam cluster including the store snake and ENP pythons SS127 and SS224.

The intermittent third cluster represented five outliers. Two of these outliers, SS127 from

the East Everglades Ranger Station and SS224 from the L-67 Ext. Canal Levee (see

Figure ib), have probabilities of 0.178 and 0.004 respectively of their genotype

belonging to the Vietnam cluster. Each has zero probability of belonging to the ENP

cluster and a greater probability of belonging to neither of the two clusters. Two other

outliers, SS369 from Coptic Hammock, ENP and SS384 from Main Park Rd., Rock Reef

Pass, have probabilities of 0.190 and 0.155 respectively of their genotype belonging to

the ENP cluster and 0 probability of belonging to the Vietnam cluster. Each also has a

greater probability of belonging to neither of the two clusters. The final outlier is the

Burmese python from a local reptile store that has a probability of only 0.010 of their

20

genotype belonging to the Vietnam cluster and zero probability of belonging to the ENP

cluster with a greater probability of belonging to neither of the two clusters. In the 10

runs where the maximal number of clusters was set to two, SS 127, SS224, and the store

python were grouped with the Vietnam cluster and SS369 and SS384 were grouped with

the ENP cluster (Figure 8). TESS grouped the data set without the Vietnam pythons into

1 cluster in 13% of the runs with an average log-likelihood of -3936 and into 2 clusters in

87% of the runs with an average log-likelihood of -3276. SS006 and her embryos were

separated between these two clusters, and the clusters show no geographical pattern

(Figure 9).

Population assignment

While each of these programs assigns individuals to clusters (subpopulations) the

assignment test DOH was used to confirm the assignment of outliers and individuals that

had a Q value of less then 0.9 (according to STRUCTURE, see Table 1) of belonging to

their cluster, and ensure all other individuals were assigned correctly. Individuals that had

Q values higher than 0.9 were assigned to populations 1 (ENP) or 2 (Vietnam) as

determined from STRUCTURE and TESS analyses, while the others were not assigned a

population. DOH confirmed all the individual assignments from STRUCTURE and

TESS (Table 3) except SS384's uncertain assignment from STRUCTURE, grouping

SS127 and SS224 with the Vietnam cluster, and SS369 and SS384 with the ENP cluster.

F-statistics and Hardy Weinberg equilibrium

Populations determined from STRUCTURE, TESS, and DOH were analyzed with

GENEALEX6, which revealed an average FSr between the ENP and Vietnam populations

of 0.088, representing moderate genetic differentiation, and an average migrants per

21

generation (Nm) of 2.589 (Table 6). In population 1 (ENP) average expected

heterozygosity (He) = 0.657 and average observed heterozygosity (H") = 0.634 and for

population 2 (Vietnam) He= 0.805 and H0 = 0.735 (Table 4). GENEPOP generated an

average FsT of 0.1824 between the two populations (Table 6), which represents great

genetic differentiation. Tests for Hardy Weinberg equilibrium are only reported from

GENEPOP as it offers a more exact test with standard error provided. These analyses

show that two out of ten loci (MS 16 and MS22) in the ENP population and four out of

ten loci (MS06, MS 16, MS22, MS24) in the Vietnam population were not in Hardy

Weinberg equilibrium at P<0.05 level of significance (Table 5). In the ENP population,

five loci show heterozygote deficiency while one locus shows an excess of heterozygotes,

and in the Vietnam population four loci show heterozygote deficiency while one locus

shows an excess of heterozygotes.

GENEALEX average FST among all four populations from STRUCTURE results

for the data set without Vietnam pythons was 0.060 and average Nm was 3.924 (Table 7).

Average pairwise EsT was 0.04 (Table 8). GENEPOP average FsT among all four

populations was 0.0646 (Table 7) and average pairwise FST was 0.0595 (Table 8).

Between the two populations from TESS results for the data set without Vietnam

pythons, GENEALEX average FsT was 0.027 and average Nm was 8.941, and GENEPOP

average FST was 0.0453 (Table 7). It has been observed that STRUCTURE and Evanno et

al's (2005) second order rate change (AK) can correctly identify the true number of

populations only when FsT is greater than 0.03 (Latch et al., 2006). Although not one of

the programs previously tested, TESS uses similar statistics to STRUCTURE and may

22

exhibit the same limitations, therefore the two populations generated by TESS with an

average FsT of 0.027 between them should not be considered true populations. While the

average FST among the four ENP STRUCTURE populations was low, and average

pairwise FsT was even lower, it was not below 0.03. However, these subpopulations

divide up a mother and her embryos, as do the TESS populations, which defies the

definition of an interbreeding population or a population of a group of organisms with

reproductive continuity (Hartl and Clarck, 1988; Harl and Clarck, 1997; Futuyma, 1998;

Hartl, 2000; Hendrick, 2000), therefore these four populations should not be considered

true populations. Neither of these groups of subpopulations from STRUCTURE or TESS

show any geographical pattern so also defy a population of individuals within a restricted

geographical area (Lapedes, 1978; Futuyma, 1998).

Genotyping errors

Results from MICRO-CHECKER showed no evidence for large allele dropout or

scoring error due to stutter in any of the loci for either subpopulation. According to

MICRO-CHECKER null alleles may be present in locus MS22 in the ENP population

based on an excess of homozygotes (expected homozygotes = 51.452, observed

homozygotes = 72). In the Vietnam population null alleles may be present in locus MS09

(expected homozygotes = 2.156, observed homozygotes = 9) and MS24 (expected

homozygotes = 3.25, observed homozygotes = 9). However, homozygous excess may be

due to a departure from HWE as opposed to the presence of null alleles. A departure from

HWE is likely in both populations because the ENP population may be from an inbred

captive bred source and the Vietnam population consists of a very small sample size.

23

IV. DISCUSSION

Based on the majority of results generated from these data, the Python molurus

bivittatus population in Everglades National Park displays low levels of genetic

differentiation. This indicates a lack of significant substructure suggesting the majority of

the ENP Burmese pythons are a genetically panmictic population. There is more than one

possible explanation for this low level of genetic differentiation. It is possible that the

pythons are truly panmictic and are interbreeding and spread throughout the park. There

are no significant geographical barriers in ENP to this species as the Burmese pythons are

adept swimmers and climbers, and radio tracking of individual snakes has revealed

movement across large distances in the park (Mazzotti et al., 2007). Yet, genetic

differentiation may be minimal because the population is introduced and may exhibit

founder effects. A population with a small number of founders may have limited genetic

variation with few alleles, limited heterozygosity, and no private or rare alleles (Baker

and Moeed, 1987; Hufbauer et al., 2004; Rasner et al., 2004; Hawley et al., 2006),

Nevertheless, the ENP pythons only show a loss in number of alleles at one locus, and

only a moderate decrease in heterozygosity (H0 = 0.634 for ENP population versus Ho=

0.735 for Vietnam population) relative to the Vietnam population. Although there are

more alleles only found in the Vietnam population (private alleles) many of which are

rare alleles not seen in the introduced ENP population. The exact geographic coordinates

are not know for the individuals collected from Vietnam, and there is no way to know if

they were from the same area and were part of the same population. Also the sample size

is very small (N = 13). Therefore population statistics for the Vietnam population in this

24

data set, such as number of private alleles, and a deviation from HWE, are not very

robust.

The Burmese pythons sampled from part of their native range in Vietnam are

genetically distinct from the ENP population. This distinction may be the result of the

fact that introduced populations, such as the ENP population, tend to undergo genetic

evolution and differentiation from their source population (Baker and Moeed, 1987;

Rasner et al., 2004). It is more likely that this distinction is a result of ENP pythons being

released into the wild from the pet trade, not the native source. The pythons in ENP were

most likely introduced by pet release and the majority of Burmese pythons in the reptile

trade in the USA are part of a captive bred population, not imported from their native

range. However, there are some native born Burmese pythons sold in the USA. Even

though native Burmese python populations are considered threatened and are CITES II

listed, as are all snakes form the family Boidae, it is legal to import native caught

pythons. For example over 12,000 Burmese pythons were imported between 1989-2000

(Reed, 2005), and were sold by breeders or reptile suppliers.

P. m. bivittatus captive bred populations originally came from the native

population, but may have had time to genetically differentiate, most likely losing alleles.

Although it is difficult to know how long ago the captive bred populations were first

introduced from the native and how many subsequent introductions have occurred. The

differentiation of the captive bred from the native populations is the result of artificial

selection (docility, breeding schedule, color morphs) and extensive inbreeding

(http://www.anapsid.org/conserv.html). These factors most likely contribute to the ENP

population's deviation from Hardy Weinberg equilibrium. Pythons from the captive bred

25

population should show low levels of genetic variation, significant homozygote excess,

and a marked deviation from Hardy Weinberg equilibrium. Therefore it is surprising that

there is not a significant excess of homozygotic individuals or decrease in heterozygosity.

The lack of significant homozygote excess in the ENP pythons may be a result of

adequate time and sufficient breeding success to increase genetic diversity in their new

environment. Because these snakes were introduced relatively recently, it is more likely

that subsequent introductions, especially native, imported snakes, increased genetic

diversity by adding new genotypes. Introducing new genotypes reduces the affects of

inbreeding and artificial selection in captive bred animals (Williams and Osentoski,

2007). In the future an extensive comparison of the genetic structuring and composition

of the captive bred populations and the introduced ENP population could further

elucidate the genetic structure and evolution of the ENP pythons, though the availability

of samples would depend on the cooperation of reptile breeders and vendors.

The single representative of a Burmese python from a reptile store in this study is

genetically distinct from the ENP pythons, but like the other four outliers (SS127, SS224,

SS369, SS384) the majority of its genotype does not belong to either the ENP or Vietnam

cluster. The mitochondrial control region data that groups these five pythons separate

from the other ENP pythons confirms the microsatellite data. While it is not possible to

determine from my data whether each individual snake is a recent introduction or a snake

from subsequent generations born in the park, SS127, SS224, SS369, and SS384 may be

recent introductions to ENP. If these snakes were purchased from the captive bred source

then these recent introductions may illustrate further genetic differentiation in the ENP

pythons from their captive bred source. It may also reflect recent introductions of snakes

26

purchased from breeders who imported them from a region of their native range other

than Vietnam.

Limited genetic variation in the ENP Burmese pythons in mitochondrial DNA,

especially the highly variable control region, and in some microsatellite loci may suggest

that the captive bred population of Burmese pythons from which the ENP pythons

originated has very limited genetic variation. Other possible reasons for limited variation

include extensive dispersal and interbreeding throughout the park, or reduced rates of

evolution in the control region for this species. Limited variation may also be an

indication that this python species has reproduced parthenogenetically, however there

was not an excess of females (55% male, 45% female) or homozygotic individuals

(observed heterozygosity = 0.634) in my sample. Among the 10 microsatellite loci used

for population analyses the two sets of embryos showed variation within them and with

their mothers (Table 9). These results indicate that the female Burmese pythons sampled

in ENP were not reproducing parthenogenetically. Nevertheless, the Amsterdam zoo

python study demonstrated parthenogenesis in this species (Groot et al., 2003). If a stress

such as removal or sterilization of males occurs it is possible that Burmese pythons can

adjust to this mode of reproduction. This may be an important consideration if attempting

to implement strategies for management that include removal or sterilization of males.

High levels of genetic diversity may enable an introduced population to adapt to

and invade a new environment (Garcia-Ramos and Rodriguez, 2002; Stepien and Tumeo,

2006) but most introduced populations experience a founder event and have reduced

genetic diversity relative to source populations (Baker and Moeed, 1987; Rasner et al.,

2004; Hawley et al., 2006). While the ENP population displays a lack of variation at

27

some loci, at the ten microsatellite loci used in this study it does not seem that the

population has suffered a marked loss in genetic diversity. Repeated introductions over

the past few years may add new variation to the ENP population, and increase the number

and diversity of the founding group, which will dilute the founder effect and facilitate

successful establishment (Roman, 2006; Stepien and Tumeo, 2006). Sightings of

Burmese pythons in Everglades National Park have been reported as early as the 1980's

(Meshaka et al., 2000) and sightings have greatly increased over the past decade

suggesting more recent introduction events. Burmese pythons in ENP usually only have

one brood per year, with the eggs hatching in July or August (slightly later than captive

pythons who lay their eggs in March or April that hatch in May or June) (Snow, 2006),

however the mean clutch size of the ENP pythons has been recorded as 35.75 (Brien et

al., 2007) and most Burmese pythons display a behavior to facilitate embryo survival.

After laying her eggs a female Burmese will wrap around them for the duration of their

gestation (about two months) and shiver her muscles to create an incubated environment,

as well as to protect the eggs from predators (Zug and Ernst, 2004). These facts illustrate

the opportunity for successful and prolific breeding in P. m. bivittatus in Everglades

National Park.

An introduced species' rate of adaptation is directly related to its invasion success

(Garcia-Ramos and Rodriguez, 2002). Burmese pythons seem to have adapted very well

to their new environment in the Everglades, probably because of an absence of predators

and competitors, a copious food source, and a mild, subtropical climate (Reznick and

Ghalambor, 2001). If it is true that the ENP pythons are one panmictic population, then

they are interbreeding and in all probability are spread throughout the park. This most

28

likely includes areas in which they have not yet been sited or collected such as all regions

away from park roads. Most Burmese python individuals have been collected on or near

roads possibly because humans, both those that released snakes and those collecting

snakes, access the park on roads. If the ENP pythons were composed of distinct

populations those populations may have been constrained to areas around their likely

sites of introduction (roads) and could be handled separately with a higher probability of

eradication (Liebhold and Bascompte, 2003), yet this does not seem to be the case.

Python sampling has been largely limited to roads because roads allow one to cover a

large area rapidly. In addition, the cryptic coloring of Burmese pythons makes them

difficult to spot in dense vegetation. They are ambush predators and are often hidden in

vegetation.

Eradication strategies may not be possible in such a large panmictic population

and managers may need to focus on control strategies, such as slowing population spread

and preventing further introductions (Sharov and Liebhold, 1998; Myers et al., 2000).

Effective January 1, 2008, regulations by the Florida Fish and Wildlife Conservation

Commission (hp -w oa R Res htm) have included the Burmese

python in a newly designated category Reptiles of Concern, which includes non-native

reptile species that have the potential to become established in Florida and may threaten

the native wildlife or humans. Reptiles in this category require a $100 permit to own and

if larger than 2 inches must be implanted with a microchip. Establishment of new

regulations such as this on snakes such as the Burmese python, as well as importer,

breeder, and/or owner accountability for the final destination of these exotic reptiles may

help the control of this species.

29

The Burmese python is a high-profile introduction in a well-known park that has

captured the public imagination. Determining the nature of this introduction may increase

public awareness of the problem of well-meaning, but careless introductions that may

have profound ecological consequences. Various news articles have featured encounters

as well as exciting python-alligator altercations in ENP

(http;//news.nationalgeographic.com/news/2004/06/0603 040603 invasivespecieshtrnl),

and in late October of 2004 ENP wildlife biologist Skip Snow was discussing the python

invaders on CNN

(http://www.cnn.com/2004/TECH/science/1.0/22/predators.in.paradise/index.html).

Successful studies with this high profile invasive species may encourage future

investigations and attempts for management of other destructive invasive species. Once

an invasive species is recognized in the ecosystem, eradication methods should be

implemented as soon as possible. Unfortunately, the importance of this has just been

realized relatively recently, and policy and funding are not readily available. New

introductions of reptile as well as other invasive species are continually documented, and

the need for control and preventative measures is critical.

In conclusion, my results indicate that there is limited genetic differentiation

among the Python molurus bivittatus in Everglades National Park, suggesting that the

Burmese pythons in the park are not genetically differentiated populations. This lack of

genetic differentiation could be a result of a freely interbreeding panmictic population,

supported by the lack of geographic barriers and the large distances traversed by

individuals seen through radio tracking. Alternatively, the lack of genetic differentiation

could be a result of isolated populations separately introduced from a genetically uniform

30

captive-bred source population. Further studies of genetic variation among native range

Burmese pythons as well as those in the reptile trade could further clarify provenance an

genetic heritage of the ENP pythons. Additional investigations should also include

samples from pythons now occurring throughout South Florida on the periphery of the

"core" distribution of Everglades National Park. Management strategies should focus on

control, such as slowing population spread and preventing further introductions, rather

than eradication.

31

Table 1: Inferred ancestry of individuals from STRUCTURE K=2: percent missing data and average Q,estimated membership coefficient to assigned cluster for each individual (Cluster 1 = ENP cluster, Cluster2 = Vietnam cluster)

Field ID %Ms Clus I Clus 2 Field ID %Ms Clus 1 Clus 2

1 SS006 0 0.996 0.004 48 SS141 0 0.996 0.0042 SSO06ae 0 0.981 0.019 49 SS142 0 0.996 0.0043 SS0O6be 0 0.9814 0.0186 50 SS143 20 0.8597 0.14034 5S006ce 0 0.996 0.004 51 SS144 0 0.996 0.0045 SSOO6de 0 0.996 0.004 52 S5145 0 0.993 0.0076 SS006ee 10 0.996 0.004 53 SS146 0 0.9571 0.04297 SS006fe 0 0.996 0.004 54 SS147 0 0.996 0.0048 SS006ge 20 0.996 0.004 55 SS149 0 0.993 0.0079 SS006he 0 0.996 0.004 56 SS157 0 0.994 0.00610 SS016 0 0.996 0.004 57 SS165 0 0.9947 0.005311 SS026e 0 0.994 0.006 58 SS166 0 0.996 0.00412 SS027e 0 0.994 0.006 59 S5168 0 0.9937 0.006313 SSO3Oe 0 0.9879 0.0121 60 SS172 0 0.994 0.00614 SSO31e 0 0.994 0.006 61 SS174 0 0.8976 0.102415 SS032e 0 0.996 0.004 62 SS176 0 0.995 0.00516 SS033e 0 0.996 0.004 63 SS178 0 0.9718 0.028217 SSO35e 0 0.996 0.004 64 SS182 0 0.9945 0.005518 SS036e 0 0.9961 0.0039 65 SS183 0 0.9929 0.007119 SS037e 0 0.996 0.004 66 SS187 0 0.9959 0.004120 SS038e 0 0.997 0.003 67 SS188 0 0.9942 0.005821 SS039e 0 0.996 0.004 68 SS190 0 0.996 0.00422 S040e 0 0.989 0.011 69 SS195 0 0.993 0.00723 SS041e 10 0.9859 0.0141 70 SS196 0 0.9933 0.006724 SS043e 0 0.996 0.004 71 SS200 0 0.995 0.00525 SS082 0 0.996 0.004 72 SS201 0 0.8157 0.1843

26 SS084 0 0.995 0.005 73 SS202 0 0.995 0.00527 SS092 0 0.9935 0.0065 74 SS206 0 0.9016 0.098428 SS093 0 0.993 0.007 75 SS208 0 0.9546 0.045429 SS108 0 0.996 0.004 76 SS209 0 0.996 0.00430 SS111 10 0.995 0.005 77 SS210 0 0.996 0.00431 SS112 0 0.996 0.004 78 SS217 0 0.996 0.00432 SS114 0 0.9881 0.0119 79 SS220 0 0.9114 0.0886

33 SS120 0 0.9949 0.0051 80 SS221 0 0.9032 0.0968

34 SS121 0 0.995 0.005 81 SS222 0 0.995 0.005

35 SS122 0 0.9955 0.0045 82 SS224 0 0.1463 0.8537

36 SS123 0 0.994 0.006 83 SS274 40 0.993 0.007

37 SS124 0 0.996 0.004 84 SS278 30 0.993 0.007

38 SS125 0 0.994 0.006 85 SS284 0 0.9948 0.0052

39 SS126 0 0.9961 0.0039 86 SS287 30 0.9902 0.0098

40 SS127 0 0.008 0.992 87 SS289 0 0.8603 0.1397

41 SS128 0 0.996 0.004 88 SS293 20 0.995 0.005

42 SS129 0 0.9901 0.0099 89 SS294 20 0.994 0.00643 SS130 0 0.996 0.004 90 SS295 30 0.994 0.00644 SS131 0 0.996 0.004 91 SS296 0 0.9961 0.003945 SS132 0 0.996 0.004 92 SS300 0 0.996 0.00446 SS139 10 0.994 0.006 93 SS304 0 0.9269 0.073147 SSI40 0 0.9942 0.0058 94 SS305 0 0.996 0.004

32

Table 1: continued

Field ID %Ms Clus I Clus 2 Field ID %Ms Clus 1 Clus 2

95 SS306 0 0.9633 0.0367 143 SS400 0 0.9185 0.081596 SS308 0 0.9963 0.0037 144 SS401 0 0.995 0.00597 SS309 0 0.9584 0.0416 145 SS407 0 0.995 0.00598 SS310 0 0.9938 0.0062 146 SS408 0 0.995 0.00599 SS311 0 0.9802 0.0198 147 SS411 0 0.9968 0.0032100 SS312 50 0.992 0.008 148 SS420 0 0.9252 0.0748101 SS313 0 0.8712 0.1288 149 SS422 0 0.996 0.004102 SS314 0 0.996 0.004 150 SS425 0 0.9806 0.0194103 SS325 0 0.9956 0.0044 151 SS426 0 0.996 0.004104 SS327 0 0.9944 0.0056 152 SS427 0 0.9554 0.0446105 SS333 0 0.996 0.004 153 SS428 0 0.993 0.007106 SS337 0 0.996 0.004 154 SS429 0 0.8004 0.1996107 SS339 0 0.996 0.004 155 SS430 0 0.995 0.005108 SS340 0 0.995 0.005 156 SS432 0 0.995 0.005109 SS341 0 0.9786 0.0214 157 Store01 0 0.0189 0.9811110 SS342 0 0.9768 0.0232 158 Vietnam0l 0 0.004 0.996111 SS347 0 0.996 0.004 159 Vietnam02 0 0.0101 0.9899112 SS348 0 0.9956 0.0044 160 Vietnam03 0 0.004 0.996113 SS350 0 0.996 0.004 161 Vietnam05 0 0.0113 0.9887114 SS351 0 0.994 0.006 162 Vietnam06 0 0.0055 0.9945115 SS352 0 0.996 0.004 163 Vietnam07 0 0.0087 0.9913116 SS354 0.996 0.004 164 Vietnam08 0 0.005 0.995117 SS355 0 0.942 0.058 165 Vietnam09 0 0.003 0.997118 SS360 10 0.7066 0.2934 166 Vietnaml0 0 0.005 0.995119 SS361 0 0.995 0.005 167 Vietnaml1 0 0.0088 0.9912120 SS362 0 0.994 0.006 168 Vietnam12 0 0.004 0.996121 SS363 0 0.948 0.052 169 Vietnaml3 0 0.005 0.995122 SS364 0 0.7332 0.2668 170 Vietnaml4 0 0.005 0.995123 SS365 0 0.994 0.006 169 Vietnaml3 0 0.005 0.995124 SS366 0 0.996 0.004 170 Vietnaml4 0 0.005 0.995125 SS367 0 0.9951 0.0049126 SS368 0 0.996 0.004127 SS369 0 0.5898 0.4102128 SS372 0 0.9901 0.0099129 SS373 0 0.995 0.005130 SS374 0 0.995 0.005131 SS375 0 0.995 0.005132 SS376 0 0.996 0.004133 SS377 0 0.996 0.004134 SS379 0 0.996 0.004135 SS380 0 0.993 0.007136 SS384 0 0.4299 0.5701137 SS388 0 0.9821 0.0179138 SS389 0 0.8727 0.1273139 SS395 0 0.993 0.007140 SS396 0 0.9663 0.0337141 SS397 0 0.9615 0.0385142 SS399 0 0.996 0.004

33

Table 2: Inferred ancestry of individuals from STRUCTURE (data set without Vietnam pythons) K=4:percent missing data and average Q, estimated membership coefficient to assigned cluster for eachindividual

Field ID %Ms Clus 1 Clus 2 Clus 3 Clus 4

1 SS006 0 0.2587 0.3321 0.1018 0.30772 SS006ae 0 0.7393 0.0608 0.1282 0.0723 SS006be 0 0.6809 0.0796 0.1369 0.10274 SS006ce 0 0.1751 0.3951 0.0744 0.35545 SS006de 0 0.6191 0.0784 0.0699 0.23276 SS006ee 10 0.5046 0.1509 0.0751 0.26967 SS006fe 0 0.3581 0.102 0.076 0.46398 SS006ge 20 0.3581 0.631 0.0759 0.1299 SS006he 0 0.4788 0.3827 0.0747 0.063810 SSO16 0 0.4112 0.2429 0.0972 0.248511 SSO26e 0 0.0917 0.0549 0.1183 0.735612 SSO27e 0 0.0519 0.049 0.0395 0.859713 SSO30e 0 0.1704 0.0446 0.1105 0.674514 SSO3le 0 0.094 0.0398 0.0457 0.820415 SSO32e 0 0.0744 0.0409 0.047 0.837816 SSO33e 0 0.0712 0.0431 0.0414 0.844117 SSO35e 0 0.0869 0.0381 0.0456 0.82918 SSO36e 0 0.0499 0.0497 0.0367 0.863619 SSO37e 0 0.1071 0.0504 0.0506 0.792120 SSO38e 0 0.0432 0.035 0.0382 0.883421 SSO39e 0 0.0516 0.0432 0.0446 0.860622 SS040e 0 0.0582 0.0369 0.0886 0.8162

23 SSO41e 10 0.0854 0.0413 0.0993 0.773924 SSO43e 0 0.0701 0.0655 0.049 0.815425 SS082 0 0.0546 0.323 0.0538 0.568526 |S084 0 0.2425 0.3987 0.1029 0.255927 SSO92 0 0.4475 0.2238 0.253 0.075728 SS093 0 0.1797 0.1637 0.3603 0.296429 SS108 0 0.2983 0.0898 0.1222 0.489530 SS111 10 0.7949 0.0556 0.0609 0.088531 SS112 0 0.3613 0.0974 0.0872 0.454232 SS 114 0 0.6931 0.0502 0.1738 0.082933 SS120 0 0.4251 0.3516 0.1382 0.08534 SS121 0 0.3596 0.118 0.2275 0.294835 SS122 0 0.1466 0.1465 0.1859 0.521236 SS123 0 0.1381 0.3855 0.1911 0.2852

37 SS124 0 0.1584 0.6402 0.0755 0.12638 SS125 0 0.7326 0.0496 0.1011 0.1166

39 SS126 0 0.1325 0.4456 0.0828 0.33940 SS127 0 0.0257 0.026 0.9225 0.025641 SS128 0 0.2291 0.043 0.058 0.6742 SS129 0 0.194 0.5451 0.2113 0.049843 SS130 0 0.1211 0.7124 0.0752 0.091344 SS131 0 0.7516 0.0655 0.0693 0.113645 SS132 0 0.2539 0.442 0.1089 0.195446 SS139 10 0.1886 0.5056 0.2022 0.103747 SS140 0 0.0594 0.804 0.0567 0.0799

34

Table 2: continued

Field ID %Ms Clus 1 Clus 2 Clus 3 Clus 4

48 SS141 0 0.7772 0.098 0.0561 0.0684

49 SS142 0 0.1418 0.2305 0.169 0.458850 SS143 20 0.05 0.0589 0.3254 0.565451 SS144 0 0.263 0.0639 0.136 0.537152 SS145 0 0.2748 0.2023 0.3979 0.125153 SS146 0 0.0662 0.6148 0.1678 0.151454 SS147 0 0.2647 0.5246 0.1027 0.107755 SS149 0 0.2682 0.1604 0.3806 0.190956 SS157 0 0.5413 0.0806 0.1982 0.180357 SS165 0 0.4086 0.1553 0.1492 0.286858 SS166 0 0.7235 0.0802 0.0857 0.110659 SS168 0 0.4915 0.2211 0.2186 0.068860 SS172 0 0.3804 0,2714 0.2234 0.12561 SS174 0 0.1289 0.1229 0.6466 0.101762 SS176 0 0.2245 0.6179 0.0817 0.075863 SS178 0 0.3677 0.0406 0.4388 0.15364 SS182 0 0.1321 0.5448 0.1684 0.154765 SS183 0 0.0584 0.7757 0.1314 0.034666 SS187 0 0.1891 0.181 0.2289 0.400667 SS188 0 0.5794 0.2006 0.0982 0.121968 SS190 0 0.7926 0.0947 0.0584 0.054769 SS195 0 0.4332 0.141 0.2672 0.158570 SS196 0 0.2185 0.1797 0.4198 0.182171 SS200 0 0.0697 0.7163 0.1258 0.088372 SS201 0 0.2037 0.0689 0.6354 0.092273 SS202 0 0.3012 0.4373 0.1797 0.0816

74 SS206 0 0.0771 0.2781 0.5578 0.08775 SS208 0 0.0472 0.4579 0.3858 0.108976 SS209 0 0.1354 0.0472 0.0562 0.76177 SS210 0 0.1203 0.7896 0.0571 0.032978 SS217 0 0.707 0.0713 0.0742 0.147479 SS220 0 0.2857 0.11 0.5447 0.059580 SS221 0 0.3822 0.147 0.3682 0.102881 SS222 0 0.0633 0.5488 0.0862 0.301682 SS224 0 0.0416 0.0221 0.8768 0.059383 SS274 40 0.537 0.0613 0.1166 0.2851

84 SS278 30 0.1581 0.6142 0.1567 0.071

85 SS284 0 0.0722 0.7783 0.0929 0.056586 SS287 30 0.1196 0.3884 0.2077 0.2842

87 SS289 0 0.1441 0.3763 0.4161 0.0638

88 SS293 20 0.3724 0.2602 0.1286 0.2387

89 SS294 20 0.1141 0.7643 0.0576 0.064

90 SS295 30 0.1056 0.4195 0.125 0.349991 SS296 0 0.575 0.0747 0.0754 0.2749

92 SS300 0 0.0385 0.8476 0.0494 0.064693 SS304 0 0.1016 0.2295 0.418 0.2507

94 SS305 0 0.5332 0.1126 0.0721 0.282395 SS306 0 0.153 0.4869 0.2067 0.153296 SS308 0 0.225 0.4634 0.0596 0.2517

35

Table 2: continued

Field ID %Ms Clus 1 Clus 2 Clus 3 Clus 4

97 SS309 0 0.1571 0.044 0.367 0.431798 SS310 0 0.7187 0.0517 0.1124 0.117199 SS311 0 0.1902 0.3146 0.4045 0.0906100 SS312 50 0.1541 0.6024 0.1323 0.111101 SS313 0 0.179 0.202 0.5187 0.1002102 SS314 0 0.2569 0.1291 0.1144 04998103 SS325 0 0.6172 0.0789 0.1016 0.2025104 SS327 0 0.4552 0.1348 0.1913 0.2182105 SS333 0 0.0846 0.4965 0.1388 0.2804106 SS337 0 0.8018 0.0902 0.0579 0.0499107 SS339 0 0.5457 0.0833 0.0938 0.2773108 SS340 0 0.6542 0.1495 0.1092 0.0872109 SS341 0 0.1137 0.6444 0.1895 0.0521110 SS342 0 0.401 0.2033 0.2638 0.132111 SS347 0 0.4669 0.0915 0.0824 0.3594112 SS348 0 0.3796 0.4253 0.1039 0.0913113 SS350 0 0.1773 0.6656 0.0706 0.0864114 SS351 0 0.0715 0.8258 0.0613 0.0414115 SS352 0 0.18 0.4479 0.1329 0.2392116 SS354 0 0.139 0.0579 0.0515 0.7514117 SS355 0 0.1278 0.0969 0.6041 0.1711118 SS360 10 0.1602 0.0544 0.6752 0.1104119 SS361 0 0.2041 0.3245 0.2466 0.2249120 SS362 0 0.3947 0.1785 0.3357 0.091121 SS363 0 0.2264 0.3525 0.2903 0.131122 SS364 0 0.1042 0.1531 0.6877 0.055123 SS365 0 0.398 0.0812 0.3515 0.1693124 SS366 0 0.4406 0.1071 0.138 0.3142125 SS367 0 0.1599 0.7244 0.0584 0.0575126 SS368 0 0.8008 0.0466 0.0516 0.101127 SS369 0 0.1163 0.0481 0.7891 0.0462128 SS372 0 0.4395 0.1387 0.3704 0.0511129 SS373 0 0.2311 0.6093 0.111 0.0485130 SS374 0 0.1553 0.391 0.2238 0.2299131 SS375 0 0.6511 0.0703 0.0869 0.1919132 SS376 0 0.2811 0.3285 0.1255 0.2652

133 SS377 0 0.7149 0.0851 0.0619 0.1382134 SS379 0 0.6552 0.0604 0.0691 0.2154135 SS380 0 0.0626 0.5547 0.1268 0.256

136 SS384 0 0.0531 0.044 0.8492 0.0539137 SS388 0 0.1538 0.3011 0.363 0.182138 SS389 0 0.0632 0.6546 0.2257 0.056139 SS395 0 0.0356 0.8933 0.0384 0.0328140 SS396 0 0.0937 0.3171 0.3394 0.2501141 SS397 0 0.0665 0.3211 0.4418 0.1707142 SS399 0 0.3573 0.4376 0.0812 0.124143 SS400 0 0.1018 0.283 0.4586 0.1565144 SS401 0 0.0478 0.8814 0.0372 0.0338145 SS407 0 0.1213 0.6775 0.1148 0.0864

36

Table 2: continued

Field ID %Ms Clus 1 Clus 2 Clus 3 Clus 4

146 SS408 0 0.4877 0.1398 0.0975 0.2752

147 SS411 0 0.1921 0.617 0.0623 0.1284148 SS420 0 0.0939 0.223 0.55 0.1326149 SS422 0 0.1439 0.3346 0.1274 0.3939150 SS425 0 0.1729 0.156 0.5339 0.1371151 SS426 0 0.8338 0.0559 0.0531 0.0571152 SS427 0 0.2625 0.126 0.4539 0.1575153 SS428 0 0.3396 0.4535 0.1581 0.0488154 SS429 0 0.1305 0.4614 0.3617 0.0463155 SS430 0 0.1178 0.4409 0.1431 0.2981156 SS432 0 0.3242 0.0792 0.0748 0.5217157 Store0l 0 0.0307 0.029 0.9189 0.022

37

Table 3: Population assignments from DOH: Nominal population (sample site), assigned population,probability of genotype belonging to assigned pop, probability of genotype belonging to each pop

Ind. NomPop AssnPop AssnPrb | PopL Pop288006 1 1 1.30E-07 1.30E-07 1.04E-30SS006ae ? 1 2.37E-10 2.37E-10 2,211E-26SS006be ? 1 2.98E-10 2.98E-10 1.43E-28SS006ce ? 5.43E-09 5.43E-09 6.63E-33SS006de ? 1 3.18E-07 3.18E-07 1.29E-27SS006ee ? 1 2.82E-07 2.82E-07 5.86E-30SS006fe ? 1 2.90E-08 2.90E-08 4.62E-32SS006ge | ? 1 2.60E-06 2.60E-06 1.29E-24SS006he ? 1 3.42E-08 3.42E-08 4.09E-30SS016 1 1 8.30E-08 8.30E-08 2.26E-29SS026e ? 1 2.24E-08 2.24E-08 5.62E-30SSO27e ? 1 6.33E-12 6.33E-12 1.50E-26SS030e ? 1 3.42E-13 3.42E-13 1.96E-29SS031e |_?_ | 1 5.30E-11 5.30E-11 5.00E-26SS032e | ? | I 5.53E-09 5.53E-09 6.98E-31

SS033e ? 1 1.44E-08 1.44E-08 2.12E-31SS035e ? 1 3.53E-08 3.53E-08 3.86E-33SS036e ? I 1.31E- 9 1.31E-09 5.52E-32SS037e ? 1 1.66E-09 1.66E-09 7.23E-29SS038e ? 1.65E-09 1.65E-09 7.63E-34SS039e ? 1 7.17E-09 7.17E-09 7.22E-29SSO40e ? 1 2.77E-13 2.77E-13 1.02E-28SSO41e ? 1 5.99E-12 5.99E-12 5.96E-24SS043e ? 1 2.96E-08 2.96E-08 8.73E-29SS082 1 1 6.88E-09 6.88E-09 4.46E-34SS084 1 1 3.42E-08 3.42E-08 1.10E-24SS092 1 1 2.04E-10 2.04E-10 1.78E-27SS093 1 | 1.92E-09 1.92E-09 3.71E-28SS108 | 1 1.34E-08 1.34E-08 3.36E-24SS1II 1 1 4.37E-08 4.37E-08 5.35E-24SS 112 I 1 1.11E-07 1.11E-07 2.39E-28SS114 1 1 1.25E-10 1.25E-10 4.27E-30SS120 1 1 1.22E-08 1.22E-08 3.53E-26SS121 | 1 1 5.94E-09 5.94E-09 7.02E-28SS122 1 1 7.07E-09 7.07E-09 3.24E-31SS123 1 1 1.13E-09 1.13E-09 1.23E-29SS124 1 1 6.17E-08 6.17E-08 2.86E-30SS125 I___ 1 1.94E-09 1.94E-09 2.42E-29SS126 1 1 1.00E-07 1.00E-07 1.51E-32SS127 ? ?_| 2 1.71E-25 2.48E-44 1.71E-25SS128 1 | 1 3.76E-08 3.76E-08 2.34E-27SS129 1 1 6.54E-11 6.54E-11 2.311E-28SS130 1 1 2.05E-08 2.05E-08 2.05E-30SS131 | 1 | 1 | 5.86E-09 5.86E-09 4.09E-29SS132 1 1 4.45E-08 4.45E-08 1.01E-29SS139 | 1 9.113-0 9 9.141E-09 4.61E-25SS140 1 1 8.77E-10 8.77E-10 2.69E-28SS141 1 I 2.59E-07 2.59E-07 2.36E-28

38

Table 3: continued

Ind. Nomop Alssn'op AssnPrb Popi Pop2 oS S142 1 1 1.45E-08 1.45E-08 1.25E-28SS143 1 .60E 12 1.60E-12 4.71E-25SS144 1 1 2.28E-09 2.28E-09 1.11E-30SS145 1 1 5.66E-09 5.66E-09 2.66E-27SS146 1 1 5.12E 11 5.12E-11 2.61E-27SS147 1 2.43E-08 2.43E-08 1.O4E-30SS149 1 1 197E-09 1.97E-09 1.38E-25SS157 1 I 4.24E-10 4,24E- 10 3.66E-29SS165 I 1 7.25E-09 7.25E-09 5.91E-28SS166 1 1 4.61E-08 4.61E-08 1.75E-26SS168 1 I 3.59E-10 3.59E-10 1.43E-29SS172 1 1 2.24E-09 2.24E-09 4.01E-29SS174 ? 5.34E-14 5.34E-14 2.33E-27SS176 1 8.92E-08 8.92E-08 2.24E-28SS178 I I 1.52E-12 1.52E-12 1.46E-27SS182 I 1 5.75E-09 5.75E-09 2.76E-33SS183 I 1 5.95E-1 5.95E-1I 4.70E-31SS187 _ 1 1.46E-08 1.46E-08 1.07E-26

SS188 1 1 4.28E-9 4.28E-09 1.91E-29SS190 1 1 4.78E-08 4.78E-08 5.64E-26SS195 1 1 7.00E-10 7.00E-10 4.24E-28SS196 1 I 6.44E-09 6.44E-09 1.36E-25SS200 1 1.64E-09 1.64E-09 8.18E33

SS201 ?1 7.64E- 15 7.64E-15 2.59E-29

SS202 I I 2.78E-10 2.78E-10 2.75E-29SS206 1 1 2.96E-12 2.96E-12 1.53E-26SS208 1 1 9.92E-14 9.92E-14 1.43E-30SS209 1 1.82E-09 1.82E-09 6.08E-32SS210 I I 2.53E-10 2.53E-10 1.19E-34SS217 1 1 7.01E-08 7.01E-08 7.68E-28SS220 1 1 4.21E-13 4.21E-13 9.35E-28SS221 1 1 547E-14 5.47E-14 5.38E-27SS222 1 1 9.65E-11 9.65E-11 3.29E-32SS224 ? 2 8.09E-28 1.77E-29 8.09E-28SS274 1 1 2.58E-05 2.58E-05 2.69E-18SS278 1 1 7.04E-06 7.04E-06 1.50E-16SS284 1 1 9.82E-09 9.82E-09 1.46E-28SS287 1 I 7.68E-07 768E-07 1.96E-20SS289 1 6.75E-14 6.75E-14 1.60E28SS293 I 1 3.05E-06 3.05E-06 1.04E-23SS294 1 5.55E-08 5.55E-08 3.60E-21SS295 1 1 3.81E-06 3.81E-06 8.80E-18SS296 1 1.l19E-08 .19E-08 188E-5SS300 1 1 9.74E-10 9.74E-10 7.47E-32SS304 1 1 2.00E-13 2.00E-13 7.14E-31SS305 1 I 1.20E-08 1.20E-08 2.01E-33SS306 1 1 3.18E-10 3.18E-10 2.03E-28SS308 1 1 1.89E-08 1.89E-08 2.63E-28SS309 1 1 3.23E-11 3.23E-11 6.15E-28

39

Table 3: continued

Ind. NoPop AssnPop AssnPrb | opi Pop2SS310 1 1 2.49E-10 2.49E-10 9.91E-28SS311 1 1 3.98E-10 |3.98E-10 1.45E-26SS312 1 1 6.64E-05 6.64E-05 6.54E-14

SS313 ? I 2.62E-14 2.62E-14 7.04E-33SS314 1 1 3.60E-08 3.60E-08 5.46E-31SS325 1 1 |186E-07 1.86E-07 2.64E-26SS327 1 1 3.14E-08 3.14E-08 1.37E-24SS333 1 1 1.52E-10 1.52E-10 4.19E-35SS337 1 1 1.34E-09 1.34E-09 3.25E-3188339 1 1 4.96E-08 4.96E-08 9.19E-28SS340 1 1 3.38E-08 3.38E-08 1.82E-25SS341 1 1 1.98E-09 1.98E-09 7.42E-28SS342 1 1 1.27E-10 1.27E-10 9.53E-31SS347 1 1 4.51E-08 4.51E-08 5.44E-30SS348 1 1 8.33E-09 8.33E-09 4.51E-29SS350 1 1 1.26E-07 1.26E-07 5.98E-30S351 1 1 7.29E-10 7.29E-10 9.85E-30SS352 1 1 1.16E-08 1.16E-08 1.79E-32SS354 I 1 5.57E-08 5.57E-08 8.84E-30SS355 1 1 1.21E-11 1.21E-11 6.35E-26SS360 ? I 1.82E-15 1.82E-15 3.21E-27SS361 1 1 2.30E-08 2.30E-08 2.28E-25SS362 1 1 1.06E-09 1.06E-09 1.82E-27SS363 1 I 5.42E-11 5.42E-11 2.44E-27SS364 ? 1 5.40E-15 5.40E-15 3.54E-25SS365 I _I 5.47E-10 5.47E-10 1.83E-29SS366 1 1 1.79E-08 1.79E-08 1.27E-28SS367 1 1 1.02E-07 1.02E-07 3.06E-27SS368 1 1 2.59E-08 2.59E-08 4.35E-27SS369 ? 1 2.17E-22 2.17E-22 3.18E-33SS372 1 I 4.52E-11 4.52E-11 3.71E-26SS373 1 1 4.10E-09 4.10E-09 3.34E-25SS374 1 1 1.02E-08 1.02E-08 1.93E-28SS375 1 1 7.49E-08 7.49E-08 1.01E-24SS376 1 1 9.47E-08 9.47E-08 1.61E-25SS377 1 1 1.86E-07 1.86E-07 4.23E-29SS379 | 1 I 2.98E-08 2.98E-08 1.51E-27SS380 I 1 1.34E-10 1.34E-10 7.30E-26SS384 ?1 5.34E-21 5.34E-21 2.18E-2888388 1 1 6.58E-11 6.58E-11 2.27E-28SS389 ? 1 6.11E-13 6.111E-13 6.811E-29SS395 1 1 3.68E-10 3.68E-10 7.60E-28SS396 1 1 3.30E-10 3.30E-10 7.51E-30SS397 1 1 4.88E-12 4.88E-12 7.61E-29SS399 1 1 9.20E-09 9.20E-09 2.63E-29SS400 1 1 4.93E-14 4.93E-14 2.87E-36SS401 1 1 2.33E-10 2.33E-10 1.01E-34SS407 1 1 1.79E-10 1.79E-10 3.05E-31SS408 1 1 9.57E-08 9.57E-08 8.32F-26

40

Table 3: continued

Ind. NomPo AssnPop AssnPrb Po 1 Pop2SS411 1 1 2.81 E-08 2.81E-08 8. 46E-32SS420 1 1 4.32E-12 4.32E-12 1.24E-28SS422 I 8.32E-10 832E-10 1.98E36SS425 1 1 5.62E-12 5.62E-12 5.27E-27SS426 1 1 2.48E-09 2.48E-09 1.lOE-31

SS427 _ 1 1.94E-11 1.94E-11 1.i3E-29SS428 _ 1 6.00E-09 6.00E-09 1.27E-28SS429 ? 1 2.55E-13 2.55E-13 2.15E-23SS430 1 1 8.35E-09 8.35E-09 6.94E-30SS432 1 1 6.55E-13 6.55E-13 5.56E-34StoreOl ? 2 6.06E-30 2.44E-38 6.06E-30Vtnam0l 2 2 2.48E-19 4.86E-52 2.48E-19Vtnam02 2 2 4.11E-19 3.85E-42 4.11E-19Vtnam03 2 2 3.86E-12 1.07E-39 3.86E-12Vtnam05 2 2 5.68E-24 1.33E-39 5.68E-24Vtnam06 2 2 1.07E-21 8.94E-47 1.07E-21Vtnam07 2 2 7.86E-12 4.12E-41 7.86E-12Vtnam08 2 2 3.43E-11 7.48E-38 343E-11Vtnam09 2 2 1.21E-12 8.83E-52 1.211E-12Vtnam10 2 2 8.40E-21 7.25E-46 8.40E-21Vtnaml1 2 2 2.51E-19 1.92E-39 2.51E-19Vtnaml2 2 2 3.65E-12 1.31E-41 3.65E-12Vtnam13 2 2 1.51E-20 5.65E-45 1.51E-20Vtnaml4 2 2 3.43E-11 7.48E-38 3.43E-11

41

Table 4: Observed and expected heterozygosity: Loci Id from Jordan et al., 2002, annealing temperature(TA) used for Burmese pythons, sample number (N), observed (Ho) and expected (He) heterozygosity,(GENEALEX) and expected and observed homozygotes and heterozygotes (GENEPOP).

GENEALEX GENEPOP

Hor Hor Het H eePo L ocus# LocusID TA(°C) N Ho He

ENP 1 MSO5 58 130 0.762 0.749 32.2162 31 977838 99ENP 2 MS06 56 126 0.770 0.761 297769 29 96.2231 97ENP 3 MSO9 56 130 0.654 0.654 447066 45 85.2934 85ENP 4 MS10 58 130 0.515 0.534 60.3321 63 69.6680 67ENP 5 MS11 58 127 0.677 0.602 50.2332 41 767668 86ENP 6 MS13 58 129 0,566 0.565 55.8677 56 73.1323 73ENP 7 MS16 58 131 0.656 0.701 38.7816 45 92.2184 86ENP 8 MS19 58 130 0.731 0.746 32.6139 35 97.3861 95ENP 9 MS22 58 129 0.512 0.625 48.0817 63 80.9183 66ENP 10 MS24 56 131 0.550 0.634 47.6284 59 83.3717 72

GENEALEX GENEPOP

Hom Hor Het HetPop Locus# LocusID TA(°C) N Ho He Ex Obs Exp OhsVietnam 1 MS05 58 16 0.750 0.734 3.8710 4 12.1290 12Vietnam 2 MS06 56 16 0.438 0.865 1.7097 9 14.2903 7Vietnam 3 MSO9 56 16 1.000 0.758 3.4839 0 12.5161 16Vietnam 4 MSIO 58 16 0.813 0.791 2.9355 3 13.0645 13Vietnam 5 MS11 58 16 0.875 0.848 2.0000 2 14.0000 14Vietnam 6 MS13 58 16 0.813 0.738 3.8065 3 12.1935 13Vietnam 7 MS16 58 16 0.750 0.852 1.9355 4 14.0645 12Vietnam 8 MS19 58 16 0.750 0.764 3.3871 4 12.6129 12Vietnam 9 MS22 58 16 0.750 0.799 2.8065 4 13.1935 12Vietnam 10 MS24 56 16 0.438 0.797 2.8387 9 13.1613 7

42

Table 5: Tests for Hardy Weinberg equilibrium from GENEPOP: p-values and standard error (SE) forprobability, heterozygote deficiency, and heterozygote excess tests.

HePop Locus Prob SE deficit SE He excess SEENP MSO5 0.8302 0.0009 0.4327 0.0020 0.5631 0.0021ENP MS06 0.9147 0.0012 0.5300 0.0044 0.4685 0.0044ENP MSO9 0.0541 0.0010 0.1093 0.0019 0.8902 0.0018ENP MS10 0.0692 0.0013 0.3252 0.0064 0.7017 0.0061ENP MS11 0.3319 0.0029 0.9753 0.0013 0.0272* 0.0014ENP MS13 0.0645 0.0022 0.0136* 0.0007 0.9873 0.0006ENP MS16 0.0069** 0.0003 0.0037** 0.0002 0.9963 0.0002ENP MS19 0.1664 0.0012 0.0477* 0.0006 0.9534 0.0006ENP MS22 0.0028** 0.0002 0.0157* 0.0006 0.9839 0.0006ENP MS24 0.1511 0.0009 0.0216* / 0.9786 /

HePop Locus Prob SE deficit SE He excess SEVietnam MSO5 0.3180 0.0122 0.2329 0.0094 0.7809 0.0107Vietnam MS06 0.0000*** 0.0000 0.0000*** 0.0000 1 0.0000Vietnam MSO9 0.1513 0.0079 1 0.0000 0.0155* 0.0033Vietnam MS10 0.7104 0.0090 0.3857 0.0117 0.6557 0.0116Vietnam MS11 0.4043 0.0225 0.5867 0.0253 0.5091 0.0243Vietnam MS13 0.2073 0.0288 0.1029 0.0140 0.9026 0.0147Vietnam MS16 0.0288* 0.0069 0.0048** 0.0017 0.9953 0.0016Vietnam MS19 0.1454 0.0074 0.5220 0.0119 0.6128 0.0122Vietnam MS22 0.2045 0.0186 0.0307* 0.0062 0.9718 0.0052Vietnam MS24 0.0000*** 0.0000 0.0022** 0.0011 0.9986 0.0042

Key: * P<0.05, ** P<0.01, *** P<0.001

43

Table 6: Fst and migrants per generation (Nm) between ENP and Vietnam populations

GENEALEX

MSO5 MSO6 MSO9 MS1O MS11 MS13 MS16 MS19 MS22 MS24 MeanFst 0.020 0.082 0.075 0.090 0.068 0.173 0.062 0.092 0.127 0.093 0.088Nm 12.326 2.814 3.090 2.541 3.412 1.192 3.815 2.479 1.726 2.427 2.589

GENEPOP

MSO5 MS06 MSO9 MS10 MS11 MS13 MS16 MS19 MS22 MS24 MeanFst 0.0424 0.1659 0.1583 0.1915 0.1503 0.3151 0.1390 0.1777 0.2727 0.1913 0.1824

44

Table 7: Fst and migrants per generation (Nm) among all ENP subpopulations from STRUCTURE andTESS for data set without Vietnam pythons.

GENEA LEX

STRUCTURE results (4 subpopulations)

MSO5 MSO6 MS09 MS1O MS11 MS13 MS16 MS19 MS22 MS24 MeanFst 0.037 0.039 0.058 0.092 0.025 0.089 0.038 0.091 0.079 0.051 0.060Nm 6.576 6.178 4.041 2.454 9.817 2.571 6.375 2.486 2.916 4.639 3.924

TESS results (2 subpopulation)

MSOS MS06 MSO9 MS1O MSil MS13 MS16 MS19 MS22 MS24 MeanFst 0.022 0.006 0.021 0.007 0.002 0.092 0.002 0.078 0.021 0.021 0.027Nm 10.926 40.302 11.590 33.094 154.400 2.461 160.048 2.974 11.572 11.796 8.941GENEPOP

STRUCTURE results (4 subpopulations)

MSO5 MS06 MSO9 MS1O MS11 MS13 MS16 MS19 MS22 MS24 MeanFst 0.0315 0.0233 0.078 0.1112 0.0205 0.1279 0.0231 0.1308 0.0597 0.0522 0.0646

TESS results (2 subpopulation)

MSO5 MSO6 MSO9 MS1 11 MS13 MS16 MS19 MS22 MS24 MeanFst 0.0367 0.0044 0.0342 0.007 -0.0037 0.1617 -0.0051 0.1374 0.0327 0.0324 0.0453

45

Table 8: Pairwise Fst and Nm for four ENP populations from STRUCTURE results for data set withoutVietnam pythons.

GENEALEX

Pop1 Pop2 Fst (via Frequency) Nm #Pop1 #Pop2PopI Pop2 0.052 4.521 15 51

Popi Pop3 0.045 5.281 15 41Pop2 Pop3 0.055 4.265 51 41

Pop1 Pop4 0.029 8.353 15 28Pop2 Pop4 0.028 8.747 51 28

Pop3 Pop4 0.031 7.717 41 28

Ave: 0.040 6.481GENEPOP

Popi Pop2 Fst (via Frequency) #Popl #Pop2Pop1 Pop2 0.0829 15 51

PopI Pop3 0.0644 15 41

Pop2 Pop3 0.0915 51 41

Popi Pop4 0.0302 15 28Pop2 Pop4 0.0428 51 28

Pop3 Pop4 0.0453 41 28

Ave: 0.0595

46

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0 50,000 100,000 200,000 Feet

aFigure 1: Collection sites in Everglades National Park; a - GIS satellite photo of maincollection sites (with field Ids) in ENP

48

EVERGLADES, NATIONAL PARK

- u

bb - approximate collection sites on ENP map from the National Park Servicedownloadable at http://www.nps.gov/ever/planyourvisit/maps.htm (blue diamondsrepresent outliers SS127 and SS224).

49

PmbIle_F

CR379F CR720F

tRNA Ile tRNA Pro Control Region tRNA Leu

CR439R CR861R

PmbLeu_R

Figure 2: Primers used for amplifying and sequencing the mitochondrial control region inPython molurus bivittatus. External primers 5'-3': PmbIle_F - TAG ACA CAG GACCGC CGA, PmbLeu_R - GGC CTG ACT TTG CTA CCT. Internal primers 5' -3':CR379F - CGT CCA TAA GTG CTA CCC, CR720F - ATA TAA TGA GAC TCCGAA, CR439R - CTT GAG AGT GTA ACC AGC, CR861R - ATT CTT GTA TTTGGT GGA

50

Figure 3: Two of six microsatellite regions, PM1 (top) and PM2 (bottom) in 16 Pythonmolurus bivitattus individuals from Everglades National Park (negative control in lastwell, first well from degraded tissue which did not amplify). Two alleles can be seen inPM1 and only one allele in PM2

51

K vs in prob of K

-40001 2 3 4 5 6 7 8 9 10 11 12 13 14 15

-4100

-4200

-4300

-44000

C -4500

-4700

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-4700

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a K

K vs deltaK

700 - -

600

500

400

x 300

200

y 100

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

K

b

Figure 4: Results from STRUCTURE with the entire data set (ENP and Vietnam); a -plot of the mean log probability of K (population number) for number of populations 1-15 (±SD) over 10 runs for each K. b - plot of Evanno et al's (2005) delta K for number of

populations 2-15.

52

K vs Inprob of K

-3800

2 4 6 8 10 12 14 16-3850

-3900

-3950

o -4000

-4050-

-4100-

-4150-

-4200

-4250

a K

K vs deltaK

250 - -

200

150

-100)

50

50

Kb

Figure 5: Results from STRUCTURE for the data set without the Vietnam pythons; a -plot of the mean log probability of K (population number) for number of populations 1-

15 (±SD) over 10 runs for each K. b - plot of Evanno et al's (2005) delta K for number of

populations 2-15.

53

1.00

0.80

0.60

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a

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b

Figure 6: Results from STRUCTURE,K=2;a - cluster assignment, probability ofbelonging to a cluster on vertical axis,individuals on horizontal axis seen in a

single line or; b - multiple lines.Colors represent different clusters(green=ENP cluster 1, red=Vietnamcluster 2). Individual numbers refer toorder of individuals in STRUCTUREdata, see appendix I for corresponding

cluste11 cluste,2 field Ids; c - triangle plot showingclustering of individuals.

C

54

1.00

0F40 7 R f R

020

000

99 _

9 52i 24 1

for data set without Vietnam pythons,

K=4;•.a - cluster assignment, probability of

u'~I belonging to a cluster on vertical axis,* ~ m *individuals on horizontal axis seen in a

• ,••• single line or; b -multiple lines.* • asColors represent different clusters.

° "*, Individual numbers refer to order ofindividuals in STRUCTURE data, see

class esosappendix I for corresponding field Ids;c - triangle plot showing clustering ofindividuals.

C

55

a

Figure 8: Results from TESS withentire data set (ENP andVietnam), number of clusters=2;a - cluster assignment,individuals along horizontal axis(see Appendix I for correspondingfield Ids) probability theindividual is in a cluster onvertical axis, colors representdifferent clusters (green=ENP,red=Vietnam);b - clusters showing geographicaldistance, group of individuals(black dots) at the top in greenrepresent pythons caught in ENPand the store sample (in red),individuals in the middle in redare Vietnam pythons, andindividuals at the bottom in greenare ENP pythons missingcoordinates or geographicaldescription (Appendix 1).

b

56

III . I[.i[ ~ Id1.II 1111 |I . AJ 11Ih1 lHi.LJJIHih.ba

Figure 9: Results from TESS forthe data set without the Vietnampythons, number of clusters=2;a - cluster assignment,individuals along horizontal axis(see Appendix I for correspondingfield Ids) probability theindividual is in a cluster onvertical axis, colors representdifferent clusters;b - clusters showing geographicaldistance, group of individuals(black dots) at the top representpythons caught in ENP and thestore sample (in red), andindividuals at the bottom (in blue)are ENP pythons missingcoordinates or geographicaldescription (Appendix 1).

b

57

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Appendix II: Number of Alleles and Allele Frequencies by Populations For Each Locus(GENEALEX)

Locus No. alleles Allele Pop1 (ENP) Pop2 (Vietnam)

MSO5 7 316 0.033 0.147

318 0.129 0.029

320 0.295 0.382

324 0.023 0.059328 0.315 0.147

332 0.205 0.206

340 0.000 0.029

Locus No. alleles Allele PopI Pop2

MS06 16 385 0.000 0.059391 0.007 0.000

395 0.000 0.118397 0.265 0.059401 0.231 0.000403 0.000 0.029

405 0.003 0.000407 0.000 0.118409 0.248 0.059

411 0.003 0.235413 0.003 0.000415 0.000 0.176417 0.007 0.000419 0.000 0.088421 0.228 0.059435 0.003 0.000

Locus No. alleles Allele Pop1 Pop2MSO9 8 165 0.000 0.088

173 0.003 0.206177 0.258 0.353181 0.192 0.265185 0.036 0.000187 0.003 0.000189 0.500 0.088193 0.007 0.000

Locus No. alleles Allele Pop1 Pop2MS10 8 211 0.000 0.265

215 0.010 0.118219 0.417 0.176221 0.003 0.000

77

223 0.017 0.147

227 0.543 0.265

231 0.003 0.000

235 0.007 0.029

Locus No. alleles Allele Pop1 Pop2

MS11 14 353 0.000 0.029

357 0.000 0.029

361 0.000 0.235

365 0.179 0.147

367 0.007 0.000

369 0.584 0.235371 0.003 0.000

373 0.014 0.029375 0.007 0.000

377 0.199 0.176383 0.000 0.059385 0.000 0.029403 0.003 0.000

409 0.003 0.029

Locus No. alleles Allele Popi Pop2

MS13 14 166 0.003 0.029168 0.007 0.412

172 0.160 0.000

174 0.033 0.000182 0.007 0.059

184 0.050 0.176

186 0.630 0.118

190 0.003 0.029

192 0.003 0.000

194 0.027 0.088

196 0.073 0.000

200 0.003 0.000

210 0.000 0.029

212 0.000 0.059

Locus No. alleles Allele Pop1 Pop2

MS16 12 356 0.007 0.000364 0.000 0.029368 0.007 0.000370 0.016 0.029372 0.270 0.118374 0.007 0.088376 0.000 0.147

78

378 0.000 0.147

380 0.372 0.176

382 0.039 0.176

384 0.283 0.059400 0.000 0.029

Locus No. alleles Allele Popi Pop2

MS19 9 532 0.119 0.235540 0.311 0.088

544 0.007 0.000

546 0.003 0.059

548 0.003 0.324

550 0.000 0.176

552 0.020 0.029

554 0.344 0.088

556 0.192 0.000

Locus No. alleles Allele Popi Pop2

MS22 12 394 0.262 0.029398 0.000 0.118400 0.000 0.029

402 0.007 0.265406 0.007 0.147410 0.463 0.118412 0.242 0.059414 0.007 0.176

416 0.007 0.000418 0.003 0.029426 0.003 0.000434 0.000 0.029

Locus No. alleles Allele Popi Pop2MS24 11 176 0.000 0.029

192 0.007 0.118

200 0.010 0.088204 0.467 0.059

208 0.355 0.088212 0.000 0.029216 0.161 0.412224 0.000 0.088228 0.000 0.029236 0.000 0.029248 0.000 0.029

79