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Schwartz, Tonia S.
Population structure of the gopher tortise (sic) (Gopherus polyphemus) in Florida, using microsatellites
h [electronic resource] /
by Tonia S. Schwartz.
Population structure of the gopher tortoise (Gopherus polyphemus) in Florida, using microsatellites
[Tampa, Fla.] :
b University of South Florida,
Thesis (M.S.)--University of South Florida, 2003.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
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ABSTRACT: Gopher tortoise (Gopherus polyphemus) population sizes have drastically declined in the past 100 years. Much of this decline has been attributed to past human predation, to habitat loss from human development, and potentially to the recently discovered upper respiratory tract disease. An understanding of the genetic structure among populations is critical for the long-term success of relocation and other management strategies. This research focuses on the development of a suite of genetic markers and the answers they provided to questions concerning present day population genetics and its use in management. In addition, this study provides inference on historical refugia and dispersal patterns of the gopher tortoise through the Pleistocene. Nine microsatellite loci were identified, optimized, and characterized from a G. polyphemus microsatellite-enriched DNA library.These loci are applicable for population level analysis along with parentage analysis in all Gopherus species. In addition, a few of the loci also work in other Testudinies. Application of these markers to eighteen Florida and two Georgia populations of gopher tortoises reveal considerable amount of genetic diversity within the species and substantial genetic subdivision among populations, especially in the northern part of the Florida peninsula and southern Georgia. Admixture and genetic homogenization in central Florida may be attributed to past human mitigation events as much of this area has been substantially developed. These data indicate a more conservative approach to relocation is necessary if the goal is to maintain the genetic distinctiveness of these areas. Lastly, these genetic data, in conjunction with historical geological, climactic, and fossil records, were used to identify gopher tortoise refugia, and dispersal patterns during the Pleistocene.Within Florida, four major genetic assemblages were determined that correspond to four Pleistocene ridges that would have been present at high sea levels: Lake Wales Ridge, Brooksville Ridge, Southern Atlantic Coastal Ridge, and Mt. Dora Ridge. In addition, these data indicate that tortoises that dispersed into southeastern Florida after the fall in sea level were most closely related to tortoises from the Brooksville Ridge. Likewise, tortoises in northwestern Florida and southern Georgia were most closely related to tortoises from the Mt. Dora Ridge.
Adviser: Karl, Stephen A.
t USF Electronic Theses and Dissertations.
POPULATION STRUCTURE OF THE GOPHER TORTISE ( GOPHERUS POLYPHEMUS ) IN FLORIDA, USING MICROSATELLITES by TONIA S. SCHWARTZ A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Biology College of Arts and Sciences University of South Florida Major Professor: Stephen A. Karl, Ph.D. Henry R. Mushinsky, Ph.D. Jonathan K. Lindzey, Ph.D. Date of Approval: April 7, 2003 Keywords: biogeography, conservation genetics, population genetics, simple-sequence repeats, turtle Copyright 2003, Tonia S. Schwartz
Photograph by Daniel A. Warner
DEDICATIONI am dedicating this thesis to my parents, Wayne and Cathy Schwartz. I am forever grateful for their continual love and encouragement that has set me free to explore this amazing world we live in, and for their trust in me that I will always remember where I came from and how to find my way back home. Youve flown so long. Youve flown so far. Remember home, Not a house, Or a town, Or a farm But us and them And hearts and dreams. Fly for a while Circle once and land home To waiting hearts, Helping hands, And silent songs Whispered beyond forever. ~Cathy Schwartz, 8 / 1998
ACKNOWLEDGEMENTSI would first like to thank my advisor Stephen A. Karl for accepting me to do research in his laboratory. He has been as a wonderful mentor and friend over the past four years. His continual encouragement and high expectations have made me a better scientist. Thank you to my committee members Henry R. Mushinsky and Jonathan K. Lindzey for putting up with me and all the paperwork I come with. I am especially grateful to my good friends in the Karl lab: Ken Hayes, Caitlin Curtis, Anna Bass, Emily Severance, Cecilia Puchuletegui, Andrey Castro, Maria Cattell, Kevin Jansen, Anne Jackson, and Mike Tringali. All of who have been extremely supportive and encouraging through the past four years. I have learned more from each of them than I ever could in a class. I wish them all the best in every aspect of their lives. This project would not have been half as successful without all the help I received collecting blood samples. I would like to thank the following field assistants for their sore feet, sunburnt faces, endless bug bites, and poison ivy that were suffered while helping me find tortoises: Cory Legler, Mindy Smith, Rebecca Brachmann, Caitlin Curtis, Anna Bass, Ken Hayes, Kristen Penney, and Dan Warner. People who have graciously shared their bloods sample include Tripp Lamb, Matt Osentoski, Ray Ashton, Lori Wendland (University of Florida ELISA lab), Roger Birkhead, Mitch Lockhart, Henry Mushinsky, Earl McCoy, Kate Stiles, and Susan Reidel. I would also like to thank Caitlin Curtis, Ken Hayes, Anna Bass, and Emily Severance for their useful comments while suffering through the first drafts of this thesis. Thank you to the Biology Department secretaries and staff who were always ready and willing to help. I would like to thank the following for financial support of this thesis: Arcadia National Wildlife Preserve Inc.; Sigma Delta Xi, Women in Science, Eloise Gerry Fellowship; Chelonian Research Foundation, Linnaeus Fund; University of South
Florida, Department of Biology Travel Grants and Tharpe Fellowship; and National Science Foundation Systematics Grant to Stephen A. Karl. Lastly, I would like to express my thanks to my darling fianc Daniel A. Warner for his never tiring love and encouragement, for patiently waiting for me to finish my thesis, and for putting up with me and my bad habits through the writing portion of this project. I look forward to our adventures together.
iTABLE OF CONTENTSList of Tables iii List of Figures iv Abstract v Overview 1 Chapter 1: The Development of Microsatellite Loci for the Genus Gopherus (Testudines: Testudinidae) and Their Applicability Towards Other Chelonian Species Introduction 8 Materials and Methods 9 Results 13 Discussion 15 References 20 Chapter 2: Population Genetics of the Gopher Tortoise: Implications for Conservation Introduction 31 Materials and Methods 34 Results 37 Discussion 40 References 50
ii Chapter 3: Using Microsatellite Data along with Geological, Climactic, and Fossil Records to Infer Movements of the Gopher Tortoise in Pleistocene Florida Introduction 71 Materials and Methods 72 Results 73 Discussion 74 References 78 Appendix A: Primers for Microsatellite Loci that were Non-variable or Unreliable in G. polyphemus 89 Appendix B: Characteristics of Alleles and Notes on Scoring 90 Appendix C: Characteristics of Individual Tortoises Sampled 98 Appendix D: Graphs of Allelic Frequencies by Locus 115 Appendix E: Table of Allelic Frequencies by Locus for Each Population 124
iiiLIST OF TABLESTable 1.1 Multiplexing microsatellite PCR and Genescan reactions protocol that was used in this study. 25 Table 1.2 Primer sequences and characteristics for Gopherus polyphemus microsatellites. 26 Table 1.3 Cross-species PCR amplification, Genescan, and sequences results. 27 Table 2.1 Population estimates for each locus and for all loci combined. 60 Table 2.2 Linkage disequilibrium P-values below 0.05 for locus-by-locus comparisons in each population in Genepop with 1000 dememorization steps, 100 batches with 1000 iterations per batch. 65 Table 2.3 Genetic distances among populations calculated in Arlequin. 66 Table 2.4 Genetic distances among assemblages calculated in Arlequin. 67 Table 2.5 Individual tortoises identified as migrants using Structure. 68 Table 3.1 Sampling locations and their two letter abbreviations that are used throughout the chapter. 84 Table 3.2 Population distances ( )2 estimated in Rst Calc are above the diagonal, and RST estimates calculated in Rst Calc below the diagonal. 85
ivLIST OF FIGURESFigure 1.1 The percentages of types of microsatellite sequences found in the 91 clones from the G. polyphemus sub-genomic microsatellite library. 28 Figure 1.2 The percentages of the types of microsatellites found in the 61 clones that contained microsatellite regions. 29 Figure 1.3 The percentages of microsatellites recovered that contained the repeat motifs targeted during the construction of the microsatellite library. 30 Figure 2.1 Locations sampled in this study overlaying the three genetic assemblages found by Osentoski and Lamb (1995) using RFLPs on mtDNA. 69 Figure 2.2 Groupings according to AMOVA based on RST and FST values. 70 Figure 3.1 The genetic assemblages identified by the Neighbor-Joining dendrogram based on pairwise RST, and the corresponding sand ridges that were present during the Pleistocene. 86 Figure 3.2 The colored shapes on the map represent highest ridges in Florida during the Pleistocene (modified from Cooke 1939; Schmidt 1997). 87
vPOPULATION STRUCTURE OF THE GOPHER TORTOISE ( GOPHERUS POLYPHEMUS) IN FLORIDA, USING MICROSATELLITESTonia S. Schwartz ABSTRACT Gopher tortoise ( Gopherus polyphemus ) population sizes have drastically declined in the past 100 years. Much of this decline has been attributed to past human predation, to habitat loss from human development, and potentially to the recently discovered upper respiratory tract disease. An understanding of the genetic structure among populations is critical for the long-term success of relocation and other management strategies. This research focuses on the development of a suite of genetic markers and the answers they provided to questions concerning present day population genetics and its use in management. In addition, this study provides inference on historical refugia and dispersal patterns of the gopher tortoise through the Pleistocene. Nine microsatellite loci were identified, optimized, and characterized from a G. polyphemus microsatellite-enriched DNA library. These loci are applicable for population level analysis along with parentage analysis in all Gopherus species. In addition, a few of the loci also work in other Testudinies. Application of these markers to eighteen Florida and two Georgia populations of gopher tortoises reveal considerable amount of genetic diversity within the species and substantial genetic subdivision among populations, especially in the northern part of the Florida peninsula and southern Georgia. Admixture and genetic homogenization in central Florida may be attributed to past human mitigation events as much of this area has been substantially developed. These data indicate a more conservative approach to relocation is necessary if the goal is to maintain the genetic distinctiveness of these areas.
vi Lastly, these genetic data, in conjunction with historical geological, climactic, and fossil records, were used to identify gopher tortoise refugia, and dispersal patterns during the Pleistocene. Within Florida, four major genetic assemblages were determined that correspond to four Pleistocene ridges that would have been present at high sea levels: Lake Wales Ridge, Brooksville Ridge, Southern Atlantic Coastal Ridge, and Mt. Dora Ridge. In addition, these data indicate that tortoises that dispersed into southeastern Florida after the fall in sea level were most closely related to tortoises from the Brooksville Ridge. Likewise, tortoises in northwestern Florida and southern Georgia were most closely related to tortoises from the Mt. Dora Ridge.
Tonia S. SchwartzOverview 1OVERVIEWThe gopher tortoise is an essential component of the sand hill and scrub habitat throughout the southeastern coastal plains of the United States including the states of Louisiana, Mississippi, Alabama, Florida, Georgia, and South Carolina (McCoy and Mushinsky 1992). The burrows constructed by tortoises provide refuge for numerous other species, which include approximately 60 vertebrate and 300 invertebrate species. Many of these species, such as the eastern indigo snake ( Prymarchon corais coupei ), the Florida mouse ( Permyscus floridanus ), and the gopher frog ( Rana aredata ) are in danger of extinction (Diemer 1986; Kent et al. 1997; Lips 1991; Witz et al. 1991). This tight interaction among species often results in interspecific dependence both physically and behaviorally such that the loss of a single species could drastically reduce the viability of the other species in the same habitat (Vida 1994). Because co-occurring species are dependent upon the gopher tortoise burrows, the loss or decline of the tortoise could potentially cause a cascade of negative effects leading to the extinction of a variety of species. Gopher tortoise population sizes are estimated to have declined 80% in the past 100 years (Auffenberg and Franz 1982). Presently this species is listed in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), and as threatened according to the Florida Committee for Rare and Endangered Plants and Animals (FCREPA) (Bury and Germano 1994; Diemer 1986; Levell 1995). Although protected by Florida law, it should not be assumed that Florida tortoise populations are not continuing to decline (McCoy and Mushinsky 1992). The severe
Tonia S. SchwartzOverview 2 decline in tortoise population numbers and sizes, especially in Florida, is primarily due to past human predation, and habitat degradation and destruction as result of increased urbanization. Life history characteristics of long life (60+ years), late sexual maturity (10-21 years), low fecundity (5-7 eggs/clutch/year), and poor and variable hatching success decrease the tortoises ability to quickly evolve and/or rebound from the habitat destruction (Diemer 1986). Furthermore, a growing number of populations have been found infected with the recently identified upper respiratory tract disease (URTD) (Auffenberg and Franz 1982; Diemer Berish et al. 2000; Diemer 1986; Jacobson et al. 1991). Ongoing habitat destruction displaces tortoises from suitable habitat, decreases the population size, and disrupts migratory corridors. This results in isolated populations that are only found in protected areas such as state and national parks. Small isolated populations have higher levels of inbreeding and the effects of genetic drift are more pronounced. Both of these processes have the potential to decrease the fitness of the population due to loss of genetic variability and accumulation of deleterious, recessive alleles (Gilpin and Soul 1986; Lande and Barrowchough 1987; Mueller 1964). Genetically depauperate populations may have a reduced ability to adapt to a changing environment and new diseases (Selander et al. 1991; Vida 1994). This is an exceptionally important consideration in light of the recent findings of URTD in many populations throughout Florida (Diemer Berish et al. 2000). Accompanying the habitat destruction are mitigation efforts to relocate individual tortoises or entire populations that interfere with human development. These tortoises are often dumped into preexisting populations. The mixing genetically divergent populations that may have been locally adapted to their different microhabitats may have a number of different effects on the future of the combined population. First, the mixing could benefit the population by introducing new genetic variability upon which natural selection can act. Inversely, if the mitigated population is locally adapted to its particular habitat, relocation events may be quite detrimental not only to the relocated tortoises, but also to the established population. The arbitrary mixing of potentially distinct genetic
Tonia S. SchwartzOverview 3 stocks of tortoises may lead to outbreeding depression in the receiving population such that mating with the relocated tortoises would disrupt the locally adapted gene complexes. The disruption of these naturally selected gene complexes could result in the overall decrease in population fitness at a genetic level (Diemer Berish 1989; Templeton 1986). The introduction of new individuals also provides a route of infection for disease causing and parasitic organisms including the bacterium causing URTD. URTD affects the upper respiratory tract of a number of tortoise species including the gopher tortoise. Clinical trials have indicated that the bacterium Mycoplasma agassizii is the likely etiological agent of URTD, although other Mycoplasma species also may be involved (Brown et al. 1999; Diemer Berish et al. 2000). The mode of infection is thought to be via direct contact with infected individuals. Currently there is no evidence that direct human to tortoise contact has contributed to the spread of the disease, although human mediate relocation of infected tortoises may be indirectly responsible. Although clinical signs of the disease may vary, they include mucopurulent discharge from the nares, excessive tearing to purulent ocular discharge, endema of the eyelids and ocular glands, and dullness of the skin and scutes (Jacobson et al. 1991). Clinical signs may be present within four weeks of infection (Brown et al. 1999). The disease was originally found in desert tortoises ( Gopherus agassizii ) and resulted in high mortality rates (Jacobson et al. 1991). Management plans addressing both the genetic and disease issues are essential for the preservation of gopher tortoise populations. In addressing the genetic issues, effective management decisions at the population level require information on life history traits and genetic population parameters. A large number of ecological studies on the tortoise exist but very little genetic research has been conducted on Florida tortoise populations. In one of the few studies published, Osentoski and Lamb (1995) detected three major genetic assemblages in Florida using restriction fragment length polymorphism (RFLP) analysis of mitochondrial DNA (mtDNA): east (the peninsula of Florida), west (the panhandle of Florida), and along the Brooksville Ridge. This study
Tonia S. SchwartzOverview 4 has limited resolving power, however, because Testudinea mtDNA generally has low genetic variability (Avise et al. 1992), as was the case here. Without reliable information on genetic subdivision, it is difficult for refuge managers and relocation organizations to make informed decisions that take into account genetic consequences. The goal of this thesis project was to develop a microsatellite library from which a suite of markers would be characterized that would be applicable to gopher tortoise studies ranging from the interpopulation level to parentage analysis. These markers would then be used to identify genetically distinct assemblages for management purposes and for a historical perspective on how and when the gopher tortoise colonized Florida. Organization of Thesis The first chapter describes the development of the microsatellite sub-genomic library from Gopherus polyphemus and the identification and characteristics of nine microsatellite loci. Also addressed is the applicability of these loci in other chelonian species. In the second chapter, the microsatellite data are used to estimate population parameters important for conservation management of the tortoise populations. These parameters include population subdivision and genetic diversity. This information is used to identify genetic assemblages that call for a revitalization of current policy and its enforcement. In the third chapter, the microsatellite data is used along with fossil and climate records and geologic history to estimate historical biogeography of gopher tortoise populations.
Tonia S. SchwartzOverview 5REFERENCESAuffenberg, W., and R. Franz, 1982 The status and distribution of the gopher tortoise ( Gopherus polyphemus ), pp 95-126 in North American tortoises: conservation and ecology U. S. Fish and Wildlife Service, Washington D. C. Avise, J. C., B. W. Bowen, T. Lamb, A. B. Meylan, and E. Bermingham, 1992 Mitochondrial-DNA Evolution at a Turtles Pace Evidence for Low GeneticVariability and Reduced Microevolutionary Rate in the Testudines. Molecular Biology and Evolution 9 : 457-473. Brown, M. B., G. S. McLaughlin, P. A. Klein et al., 1999 Upper respiratory tract disease in the gopher tortoise is caused by Mycoplasma agassizii Journal of Clinical Microbiology 37 : 2262-2269. Bury, B. R., D. J. Germano, 1994 Biology of North American Tortoises, pp. 1-5 in Fish and Wildlife Research No. 13 United States Department of the Interior National Biological Survey, Washington D. C. Diemer Berish, J. E., 1989 An overview of gopher tortoise relocation, pp. 1-6, edited by G. T. R. S. Proceedings. State of Florida Game and Fresh Fish Commission. Diemer Berish, J. E., L. D. Wendland, C. A. Gates, 2000 Distribution and prevalence of upper respiratory tract disease in gopher tortoise in Florida. Journal of Herpetology 34 : 5-12. Diemer, J. E., 1986 The Ecology and Management of the Gopher Tortoise in the Southeastern United-States. Herpetologica 42 : 125-133.
Tonia S. SchwartzOverview 6 Gilpin, M. E., M. E. Soul, 1986 Minimum viable populations processes of species extinction, pp. 19-34, in: Conservation Biology, edited by M. E. Soul. Sinauer Associates, Inc., Sunderland, Massachusetts. Jacobson, E. R., J. M. Gaskin, M. B. Brown et al., 1991 Chronic upper respiratory tract disease of free-ranging desert tortoises ( Xerobates agassizii ). Journal of Wildlife Diseases 27 : 296-316. Kent, D. M., M. A. Langston, D. W. Hanf 1997 Observations of vertebrates associated with gopher tortoise burrows in Orange County, Florida. Florida Scientist 60 : 193-196. Lande, R., G. F. Barrowchough, 1987 Effective population size, genetic variation, and their use in population management, pp. 87-123 in Viable populations for conservation, edited by M. E. Soul. Cambridge University Press, Cambridge. Levell, J. P., 1995 A field guide to reptiles and the law. SerpentÂ’s Tale, Excelsior, Minnesota. Lips, K. R., 1991 Vertebrates associated with tortoise ( Gopherus polyphemus ) burrows in four habitats in south-central Florida. Journal of Herpetology 25 : 477-481. McCoy, E. D., and H. R. Mushinsky, 1992 Studying a Species in Decline Gopher Tortoises and the Dilemma of Correction Factors. Herpetologica 48 : 402-407. Mueller, H. J., 1964 The relation of recombination to mutational advances. Mutation Research 1 : 2-9.
Tonia S. SchwartzOverview 7 Osentoski, M. F. and T. Lamb, 1995 Intraspecific phylogeography of the gopher tortoise, Gopherus polyphemus: RFLP analysis of amplified mtDNA segments. Molecular Ecology 4 : 709-718. Selander, R. K., A. G. Clark, T. S. Wittman, 1991 Evolution at a molecular level. Sinauer Associates, Inc., Sunderland, Massachusetts. Templeton, A. R., 1986 Coadaptation and outbreeding depression, pp. 105-116 in Conservation Biology edited by M. E. Soul. Sinauer Associates, Inc., Sunderland, Massachusetts. Vida, G., 1994 Global issues of genetic diversity, in: Conservation Genetics edited by S. K. Jain. Birkhuser, Boston. Witz, B. W., D. S. Wilson, M. D. Palmer, 1991 Distribution of Gopherus polyphemus and its vertebrate symbionts in three burrow categories. American Midland Naturalist 126 : 152-158.
Tonia S. Schwartz Chapter 1 8CHAPTER 1: THE DEVELOPMENT OF MICROSATELLITE LOCI FOR THEGENUS GOPHERUS (TESTUDINES: TESTUDINIDAE) AND THEIRAPPLICABILITY TO OTHER CHELONIAN SPECIESINTRODUCTIONThe four tortoise species endemic to North America are each threatened or endangered throughout their geographic ranges (Bury and Germano 1994). The demand for management of tortoise populations intensifies as their respective habitats continue to be fragmented or destroyed by development. Understanding life history traits such as mating strategies and genetic population parameters is necessary to fully realize and, thereby, evaluate the effectiveness of management plans or the lack thereof. On a longlived species such as the gopher tortoise it is difficult to address many of these questions using ecological studies. A genetic approach may provide historical information on how populations have evolved and the trends they are currently following. While an extensive amount of research on gopher tortoises has been done at the ecological level, very little has been done at the genetic level. This is likely due to the lack of appropriate markers to address many of the questions of interest. Herein, I describe the development of nine microsatellite markers from Gopherus polyphemus that are appropriate for addressing questions at the population and individual level. Microsatellites are rapidly evolving nuclear loci characterized by tandomly repeated sequences that are two to five nucleotides in length; for example 5-CAACAACAACAA(n)-3. These genetic markers are extremely variable because of their mechanisms of mutation: polymerase slippage during replication (Caskey et al. 1992; Levinson and Gutman 1987; Schltterer and Tautz 1992; Shriver et al. 1993;
Tonia S. Schwartz Chapter 1 9 Strand et al. 1993) and unequal meiotic exchanges during recombination (Jefferys et al. 1988; Jefferys et al. 1985; Stephan 1986; Stephan 1989; Tautz and Renz 1984). The highlevel of variation at microsatellite loci increases the probability of detecting genetic differences among individuals and populations (Coltman et al. 1998; Funk et al. 1999). Thus, these markers are applicable for parentage analysis along with population studies to determine inbreeding coefficients and population subdivision and gene flow.MATERIALS AND METHODSDeveloping the Microsatellite Library I have developed a microsatelliteenriched DNA library from the G. polyphemus genome using microsatellite-enrichment protocol by Fischer and Bachmann (1998) that was modified by Severance (2002). Total cell DNA was isolated from a single G. polyphemus individual following a salt extraction protocol (Mullenbach et al. 1989). Three micrograms of genomic DNA from a single tortoise was restriction digested with 100 U of Sau 3A (Boehringer Manheim, Germany) for two hours at 37Â…C. Sau 3A was used because it has a four base pair (bp) recognition site causing it to cut relatively often in the genome leaving a GATC overhang that is included in the six bp recognition site of Bgl II Bgl II linkers that served as PCR primer sites (25mer and 21mer: Annovis, Inc., PA) were ligated to the digested genomic DNA at 12 C overnight. Three concentrations of the ligation (undiluted, 1:10, and 1:100) were amplified via PCR with final concentrations of 1X buffer (Promega, WI), 2.5 mM MgCl2(Promega, WI), 0.2 mM of each dNTP (Roche Diagnostics Corp., IN), 0.05 M of each Bgl II primer, 2.5 U Taq polymerase (Promega, WI), and l of ligation dilution as template, with the cycling parameters 95 C for 3 min, 30 cycles of 95 C for 1 min; 60 C for 1 min; 70 C for 2 min, and a final extension at 72 C for 10 min on a Omn-e Hybaid thermal cycler. The PCR reaction using the undiluted ligation resulted in the most concentrated PCR product when run on an agarose gel, thus 20 l of this PCR product were denatured and the fragments containing AC, TC, or CAA repeat regions were hybridized overnight at 48 C to the following biotin labeled microsatellite oligos 5(AC)15TATAAGATA-3, 5-(TC)15TATAAGATA-3, and 5-(CAA)15TATAAGATA-3
Tonia S. Schwartz Chapter 1 10 (Annovis, Inc., PA). The hybridization mixture was resuspended with Streptavdin Magnespheres Paramagnetic Particles (SA-PMP: Promega, WI). SA-PMP have a magnetic core with a streptavidin coating that has an extremely strong and stable affinity to biotin (Kd = 10-15). The SA-PMP were used to capture PCR fragments containing repeat regions that were hybridized to the biotin labeled oligos. When the tube was inserted into a magnetic stand, the SA-PMP held the fragments containing the repeat regions while the unhybridized fragments of DNA (i.e. fragments not containing sequence repeats) were washed away. This hybridization procedure was repeated twice. Three concentrations of the resulting enriched microsatellite fraction of DNA (undiluted, 1:10, and 1:100) were again PCR amplified using the Bgl II oligo primers and the same cycling parameters. These PCR products were combined and cleaned by ethanol precipitation. The clean PCR products were then digested with 100 U Sau3A and recleaned by ethanol precipitation for cloning. Individual microsatellites were identified through cloning and sequencing. Twenty-five microliters of the enriched PCR product were digested with 100 U of Bgl II restriction enzyme (Boehringer Manheim, Germany). pBSK+ vector containing the ampicillin resistance gene and the Lac-Z gene (Stratagene, CA) was digested with 100 U Bam HI (Boehringer Manheim, Germany) that cut within the Lac-Z gene resulting in the same sticky overhang as digestions of the PCR products by Bgl II. The digested vector was dephosphorylated with Shrimp Alkaline Phosphatase to prevent self-ligation. The digests were cleaned using a phenol chloroform extraction and then ethanol precipitated. The PCR product was ligated overnight at 12 C into the pBSK+ vector and subsequently transformed into NovaBlue Singles Competent Cells (Novagen, WI) according to the manufactures protocol. Ten microliters of cells were plated on ampicillin and X-gal treated agar culture plates. This allows for selection of clones that have taken in a ligated plasmid that provides resistance to the ampicillin. In addition, the X-Gal treatment allows for blue/white screening for the detection of plasmids that have taken up an insert and interrupted the function of the -galactisidase gene thereby not allowing the bacteria to break down the X-Gal to produce a blue by-product that is indicative of a self-ligated plasmid. The plasmids from the white clones were screened via PCR amplification with
Tonia S. Schwartz Chapter 1 11 a final concentrations of 1X buffer, 2.5 mM MgCl2, 0.213 mM of each dNTP, 10 pmols each M13 forward and reverse primer, 2.5 U Taq polymerase with the cycling conditions 94 C for 2 min, 35 cycles of 94 C for 30 sec; 55 C for 30 sec; 72 C for 30 sec, and a final extension at 72 C for 7 min with a Omn-e Hybaid thermal cycler. The PCR products were electrophoresed on agarose gels to confirm recombinant status and assess insert size. One thousand recombinant clones were transferred to microtiter plates containing a solution of Luria Broth (LB) and glycerol (30% glycerol, 5% NaCL, 1% Triptone, 0.5% yeast extract, 0.1% 1N NaOH) for permanent storage at -80 C. To identify recombinant clones containing microsatellites, plasmids from 102 clones were PCR amplified with the previously described conditions. PCR products were cleaned and concentrated with 30,000 MW Amicon Ultrafree-MC centrifugal filter devices (Millipore, MA). The inserts were cycle sequenced in the forward direction using DYEnamic E-T Terminator Cycle Sequencing Premix Kit (Amersham Pharmacia Biotech Inc., NJ) in 10 l reactions using 70-100 ng of PCR product and 5-15 pmol of M13 primer with the manufactures cycling parameters, and electrophoresed on an ABI 310 sequencer (PE Applied Biosystems, CA). Sequences containing a repeat region were sequenced in the reverse direction and the sequences were visually analyzed to check for miscalled base nucleotides and aligned using Sequencher (Gene Codes Corporation, MI). Sequences containing potentially useful microsatellite loci were analyzed in Primer3 Input program (htt://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi) and/or Oligo 4.06 Primer Analysis Software (National Biosciences Inc.) to identify suitable primer locations in the regions flanking the microsatellite loci. Considerations for choosing primers that would increase the potential of multiplexing the PCR reactions and Genescan analysis were an annealing temperature between 59 C and 60 C and the resulting product size. Once a locus was optimized, 2.5 l of PCR product from 17 geographically separated individuals were electrophoresed on a 5% polyacrylamide gel (5% 19:1 acrylamide/bis-acrylamide, 0.5X TBE [1.12 M Tris, 0.89 M Boric Acid, 4% 0.5 M EDTA at pH 8.0], 0.375% ammonium persulfate, 0.188% tetramethylethlenadiamine), and visualized with EtBr (0.05 g/ml ethidium bromide in 0.5X TBE) to determine if the locus was variable. From the 84 clones screened, I developed nine variable loci for
Tonia S. Schwartz Chapter 1 12 which fluorescently labeled primers were made from Virtual Filter Set C containing the dyes 6-FAM (blue), TET (green), 6-HEX (yellow) (TAMRA, red was reserved for the size standard) (Integrated DNA Technologies, IA). Fluorescent labels were assigned to the loci based on the size of the PCR product to allow for all of the loci to be multiplexed in two PCR reactions, and thereby two Genescan reactions (Table 1.1). PCR Protocol for G. polyphemus Samples Â— The 20 l PCR reaction for multiplexing mix 1 contains 1.5 U Taq polymerase in storage buffer B (20 mM Tris-HCL (pH 8.0), 100 mM KCL, 0.1 mM EDTA, 1 mM DTT, 50% glycerol, 0.5% Nonidet-P40 and 0.5% Tween 20; Promega, WI), 4 g Bovine Serum Albumin, 2.25 Â— 3.0 mM MgCl2, 1 X reaction buffer (50 mM KCl, 10mM Tris-HCl pH 9.0 at 25 C, and 0.1% Triton X100; Promega, WI), 0.213 mM of each dNTP, 15 pmols of the primers GP15F and GP15R-6-FAM, 10 pmols of the primers GP30F-TET, GP30R, GP55F-TET, GP55, GP26F, GP26R-TET, and from 0.3 to 1.0 l of genomic DNA. Multiplexing mix 2 contained the same components except 10 pmols of the primers GP96F-6-FAM, GP96R, GP61F-6-HEX GP61R, GP19F-FAM, GP19R and 15 pmols of primers GP102F-TET, GP102R, GP81F, GP81R-6-FAM were used. When not multiplexed, single locus reactions contained 1 U of Taq polymerase and 0.2 mM of each dNTP, while keeping the concentration of the other components constant. The cycling parameters on a Omn-e Hybaid thermal cycler for all reactions were: 94 C for 2 min, 35 cycles of 94 C for 30 sec; 60 C for 30 sec; 72 C for 30 sec, and a final extension at 72 C for 30 min to ensure the addition of the final adenine base pair. Note that most loci can be interchangeable among multiplexed reactions with further optimization of MgCl2 and relative primer concentrations. Genescan Protocol for G. polyphemus Samples (Table 1.1) For each individual, the two multiplexed PCR reactions were runas separate Genescan reactions. Depending on amplification success, 0.3 Â— 2.5 l of PCR product were denatured for 4 min at 95 C with 12.5 l of formamide containing 0.5 l of 500 bp TAMARA size standard (1/2 of
Tonia S. Schwartz Chapter 1 13 the recommended concentration; PE Applied Biosystems, CA). Subsequently, the samples were electrophoresed on an ABI prism 310 sequencer (25 min for PCR Mix 1, 27 min for PCR Mix 2) using the Genescan software to genotype each individual. Observed and expected heterozygosities were calculated in Arlequin (Schneider et al. 2002) using nine populations with more than 18 samples. I performed a regression analysis in JMP IN version 4.0 (SAS Institute) to determine if there was a relationship between the mean number of repeats at a locus and the number of alleles found at that locus. Applicability to Other Chelonian Species Â— To determine the applicability of these loci in studies on related chelonian species, I tested each locus on 1-2 samples of the three other North American tortoise species ( G. agassizii, G. berlandieri and G. flavomarginatus), four striped mud turtle ( Kinosternon baurii ) samples and one green sea turtle ( Chelonia mydas ) sample. Optimization for each locus was attempted by varying the annealing temperature and the final concentration of MgCl2, while maintaining the other PCR conditions as described previously for G. polyphemus The samples were analyzed on Genescan to determine their variability. If samples were homozygous at any of the loci, those loci were sequenced in the forward direction to determine if a microsatellite was present, and thereby the potential for the locus to display variability when screened in more individuals. Sequencing conditions were as described above using non-fluorescently labeled PCR product and the forward primer for the respective locus.RESULTSIn search of microsatellite loci suitable for population level analysis, I sequenced inserts from 91 clones from the G. polyphemus sub-genomic microsatellite-enriched library. Many of the inserts (32: 37.6%) did not contain a microsatellite (Figure 1.1). Of
Tonia S. Schwartz Chapter 1 14 the 53 inserts that did contain a microsatellite, many (35.8%) were too close to the plasmid vector to allow for the development of a functional primer, or had too few repeats (< 8 repeats) and were unlikely be variable (20.8%; Figure 1.1). Of the types of repeat regions recovered, 43.4% were perfect repeats (most of which were small), 15.1% were imperfect repeats, 28.3% were compound perfect repeats, and 13.2% were compound imperfect repeats according to Webers (1990) classifications (Figure 1.2). The library was designed to capture three types of repeat motifs (AC, CT, and CAA; some sequences contained multiple repeat regions) but the majority or the repeat regions, 57.1% (49 out of 84) were AC repeat motifs, 36.9% (31) were CT repeat motifs, and only 1 (1.2%) had a CAA repeat motif (Figure 1.3). I designed primers for 25 loci (47.2% of the sequences that contained a repeat region), of which 9 (36%) were variable and could be optimized (Figures 1.1). See Appendix A for details on five loci, for which primers were developed but were not variable in the 17 gopher tortoises screened, or were not functional for my purposes but may be useful in other studies or other species. Of the nine optimized loci 4 had perfect microsatellites, 2 had imperfect microsatellites, 2 had compound perfect microsatellites, and 1 had a compound imperfect microsatellite. Of the nine loci, 6 had AC repeat motifs, and 3 had CT repeat motifs (Table 1.2). In the nine variable microsatellite loci developed, the number of G. polyphemus alleles per locus ranged from 2-19, making these loci suitable for population level analysis with the potential for use in parentage studies. The characteristics of these nine loci and the primer sequences are described in Table 1.2. The observed heterozygosities for the loci ranged from 0.18 Â— 0.61 with all but one locus (GP26) being lower than expected when calculated in Arlequin (Table 1.2). The mean number of repeat units was positively related to the number of alleles per locus (r2 = 0.614, df = 8; P = 0.0125). Applicability of Microsatellite Loci to Other Chelonian Species (Table 1.3) Â— Of the nine-microsatellite loci developed from the G. polyphemus genome, all of them amplified in the two G. agassizi samples, and eight of the loci were variable. The monomorphic locus (GP96) was sequenced to verify the presence of a microsatellite. All
Tonia S. Schwartz Chapter 1 15 of the loci amplified in both the G. berlandieri sample and the G. flavomarginatus sample. In both species, all of the loci were either variable on Genescan or displayed a microsatellite when sequenced. Across families, only six of the nine loci amplified in K. baurii Of these six, only two (GP96 and GP30) were variable on Genescan when four individuals were screened. Three of the loci not variable on Genescan were sequenced to verify that two of theses loci contained microsatellites (GP19 and GP81). I was unable to sequence locus GP102. Only three loci amplified in C. mydas For one individual tested, one locus was variable (GP96) and the other two were monomorphic but contained microsatellites when sequenced (GP19 and GP61).DISCUSSIONLibrary Characteristics Â— Although magnetic separation was used in the development of this library to select for PCR fragments containing AC, CT, or CAA microsatellites, 33% of the clones sequenced did not contain a microsatellite. This may have been a result of low stringency during hybridization; thereby allowing PCR fragments not containing repeat regions to bind to the oligos or to other PCR products that were bound to the oligo. For the development of future libraries, it may be beneficial to increase the number of hybridization / wash steps or to increase the stringency of the hybridization, in order to reduce the number of clones not containing a microsatellite. Despite the fact that three types of repeat regions were selected, the percentages of the repeat motifs in the microsatellites recovered were greatly skewed (Figure 1.3). The difference in the numbers of the two types of dinucleotide repeats recovered (58.3% AC and 35.7% CT) may be representative of the actual proportions of those repeat regions in the G. polyphemus genome, the differences in the ability of AC and CT oligos to hybridize to the PCR fragments (Breslauer et al. 1986), or the relative closeness of these repeats to the Sau 3 restriction site. The capture of only one PCR fragment with a CAA repeat maybe an artifact of the hybridization process but it is likely that this
Tonia S. Schwartz Chapter 1 16 difference represents a deficiency of this type of repeat in the gopher tortoise genome. The reasoning is that two other microsatellite-enriched libraries were constructed using the same protocol on the marine snail ( Melongenia corona ; K. Hayes in prep.) and stony coral (Montastria spp.; Severance 2002), both of which had a majority of trinucleotide repeats thereby indicating the hybridization protocol followed works well for trinucleotide repeats along with the dinucleotide repeats. Many (32%) of the microsatellites were too close to the end of the PCR product such that there was insufficient room in the flanking region to develop a functional primer. Furthermore, of the type of repeats recovered, there was a high percentage of compound microsatellites as described by Weber (1990). Although this may be representative of the genome, it also may have been a result of two or more of the oligos binding to the compound fragments causing them to be more efficiently captured than fragments with simple repeats. Supporting this idea, all but two of the compound microsatellites contained both an AC and a CT repeat motif. While comparisons across Testudines microsatellite libraries are difficult because of the different protocols, selective methods, and the types of repeat regions that are selected for. It is interesting that many microsatellites developed for turtles have complex repeats and in situations where researchers have attempted to select for only perfect repeats they have often reported having recovered a large number of complex repeats (FitzSimmons et al. 1995; Pearse et al. 2001; Sites et al. 1999). The observed heterozygosities in the loci described here were generally lower when compared to the heterozygosities found in other turtle microsatellites (FitzSimmons et al. 1995; Kichler et al. 1999; Osentoski et al. 2002; Pearse et al. 2001; Sites et al. 1999). Whether this represents a characteristic of the gopher tortoise or the loci themselves is debatable. A positive relationship was found between the size of the repeat region and the number of alleles at those loci, thereby indicating longer repeats are more variable. This relationship was also found in sea turtles (FitzSimmons et al. 1995) and humans (Jefferys et al. 1988).
Tonia S. Schwartz Chapter 1 17 Genescan Characteristics The use of Genescan for microsatellite analysis has proven to be more efficient, more accurate, and safer than the conventional use of radioisotopes (Schwengel et al. 1994). Nevertheless, as with any technique it can always be further optimized and it has its share of quirks that need to be understood and reckoned with. Genescan determines the size (length in base pairs) of the allele by the relative time it takes for the fluorescently labeled PCR product to migrate past the laser. Various factors such as polymer temperature and consistency can affect the ability of the DNA fragments to migrate. In addition, peak intensity will vary between samples as a result of varied PCR amplification success and the salt concentration in the Genescan sample. As a result, the same allele may appear at a slightly different size (up to one base pair) potentially making scoring difficult. Likewise multiplexing PCR reactions, such that more than one set of primers is used in a single reaction, often can result in extra PCR products when primers from different loci work together to amplify a non-targeted locus. Both of the multiplexing reactions described in this chapter have extra bands that can easily be identified because they are consistent in that they do not change in size or they coincide with specific alleles, thereby they can simply be discounted from the analysis. Thus it is important to know the sizes and characteristic patterns of the possible alleles and extra peaks at each locus. Appendix B describes each of the nine loci pointing out their unique characteristics and patterns that may be helpful when scoring the loci. The non-template addition of a base pair (usually an adenine) to the PCR fragment can cause problems in the scoring of alleles if the addition is not complete. Incomplete addition of the extra adenine is likely a result when the reverse primer has a thymine on the 5 end such that the growing PCR product ends in an adenine that would inhibit the addition of an extra adenine. When analyzing the data in Genescan, incomplete addition results in split peaks that are one base pair different in size and makes scoring of alleles difficult. One locus (GP19: Appendix B) in particular was greatly affected by this problem. One way to remedy this is to make a primer with an additional tail to the 5 end that will promote (or inhibit) the 3 addition (Brownstein et
Tonia S. Schwartz Chapter 1 18 al. 1996). Magnuson et al. (1996) found that replacing the last nucleotide on the reverse PCR primers with an adenine on the 5 end such that the growing PCR product ends in a thymine, would facilitate the addition of an extra adenine to the 3 end to the majority of the PCR fragments. Stutter peaks usually occur immediately before the allele as a result of the Taq polymerase slipping during PCR (Caskey et al. 1992; Liepelt et al. 2001; Schltterer and Tautz 1992; Strand et al. 1993; Tautz and Renz 1984). At any particular locus, the longer alleles usually have fluorescent peaks that are shorter in height, and have more stutter peaks. For most of the loci described here, except for GP15, alleles can be differentiated from stutter peaks based on the 2/3 rule, such that if the individual is heterozygous at a locus, the area beneath the peak of the longer allele is at least 2/3 the area of the shorter allele. For loci like GP15 that has many alleles that span 60 base pairs, the 2/3 rule is not true because the longer alleles produce peaks that are considerably shorter in height. Applicability of Microsatellite Loci to Other Chelonian Species In testing these microsatellite loci in other chelonian species, I have determined they will be most applicable to population studies involving North American tortoises (Genus Gopherus ). The more variable loci (GP96, GP30, GP15, GP102, GP26, and GP81) are useful for parentage analysis in G. polyphemus and potentially in other tortoise species The loci presented here also maybe useful in combination with microsatellites discovered in other turtle species for population level studies (FitzSimmons et al. 1995; Kichler et al. 1999; Moore and Ball 2002; Osentoski et al. 2002; Pearse et al. 2001; Sites et al. 1999; Valenzuela 2000; Zaroya and Meyer 1998). Six of the loci show varying degrees of conservation across families in the Order Testudines since they are present in either K. baurii or C. mydas In three of these loci, not only have the primer sites of the flanking regions been conserved, but the microsatellite region themselves have been conserved. In addition, the four C. mydas primers described by Fitzsimmons (1995) were tested on the gopher tortoise, and only
Tonia S. Schwartz Chapter 1 19 CM72 amplified but was monomophic across populations, thereby providing additional evidence for turtle DNA evolving relatively slowly (Avise et al. 1992).
Tonia S. Schwartz Chapter 1 20REFERENCESAvise, J. C., B. W. Bowen, T. Lamb, A. B. Meylan and E. Bermingham, 1992 Mitochondrial DNA evolution at a turtleÂ’s pace: evidence for low genetic variability and reduced microevolutionary rate in Testudines. Molecular Biology and Evolution 9: 457-473. Breslauer, K. J., R. Frank, H. Blocker and L. A. Marky, 1986 Predicting DNA duplex stability from the base sequence. Proceedings of the National Academy of Sciences of the United States of America 83: 3746-3750. Brownstein, M. J., J. D. Carpten and J. R. Smith, 1996 Modulation of non-templated nucleotide addition by Taq DNA polymerase: primer modifications that facilitate genotyping. Biotechniques 20: 1004-1010. Bury, B. R., and D. J. Germano, 1994 Biology of North American Tortoises, pp. 1-5 in Fish and Wildlife Research No. 13 United States Department of the Interior National Biological Survey, Washington D. C. Caskey, C. T., A. Pizzuti, Y.-H. Fu, R. G. J. Fenwick and D. L. Nelson, 1992 Triplet repeat mutations in human disease. Science 256: 784-789. Coltman, D. W., W. D. Bowen and J. M. Wright, 1998 Birth weight and neonatal survival of harbour seal pups are positively correlated with genetic variation measured by microsatellites. Proceedings of the Royal Society of London, B 265: 803-809
Tonia S. Schwartz Chapter 1 21 Fischer, D., and K. Bachmann, 1998 Microsatellite enrichment in organisms with large genomes ( Allium cepa L.). Biotechniques 24: 796-802. FitzSimmons, N. N., C. Moritz and S. S. Moore, 1995 Conservation and dynamics of microsatellite loci over 300 million years of marine turtle evolution. Molecular Biology and Evolution 12: 432-440. Funk, W. C., D. A. Tallmon and F. W. Allendorf, 1999 Small effective population size in the long-toed salamander. Molecular Ecology 8: 1633-1640. Jefferys, A. J., N. J. Royle, V. Wilson and Z. Wong, 1988 Spontaneous mutation rates to new length alleles at tandem-repetitive hypervariable loci in human DNA. Nature 332: 278-281. Jefferys, A. J., V. Wilson and S. L. Thein, 1985 Hypervariable Â’minisatelliteÂ’ regions in human DNA. Nature 314: 67-73. Kichler, K., M. T. Holder, S. K. Davis, R. Marquez and D. W. Owens, 1999 Detection of multiple paternity in the KempÂ’s ridley sea turtle with limited sampling. Molecular Ecology 8: 819-830. Levinson, G., and G. A. Gutman, 1987 Slipped-strand mispairing: A major mechanism for DNA sequence evolution. Molecular Biology and Evolution 4: 203-221. Liepelt, S., V. Kuhlenkamp, M. Anzidei, G. G. Vendramin and B. Ziegenhagen, 2001 Pitfalls in determining size homoplasy of microsatellite loci. Molecular Ecology Notes 1: 332-335.
Tonia S. Schwartz Chapter 1 22 Magnuson, V. L., D. S. Ally, S. J. Nylund, Z. E. Karanjawala, J. B. Rayman et al. 1996 Substrate nucleotide-determined non-templated addition of adenine by Taq DNA polymerase: implications for PCR-based genotyping and cloning. Biotechniques 21: 700-709. Moore, M. K., and R. M. Ball, 2002 Multiple paternity in loggerhead turtle ( Caretta caretta ) nests on Melbourne Beach, Florida: a microsatellite analysis. Molecular Ecology 11: 281-288. Mullenbach, R., P. J. L. Lagoda and C. Welter, 1989 An efficient salt-chloroform extraction of DNA from blood and tissues. Trends in Genetics 5: 391. Osentoski, M. F., S. Mockford, J. M. Wright, M. Snyder, B. Herman et al. 2002 Isolation and characterization of microsatellite loci from the BlandingÂ’s turtle, Emydoidea blandingii. Molecular Ecology Notes 2: 147-149. Pearse, D. E., F. J. Janzen and J. C. Avise, 2001 Genetic markers substantiate ong-term storage and utilization of sperm by female painted turtles. Heredity 86: 378-384. Schltterer, C., and D. Tautz, 1992 Slippage synthesis of simple sequence DNA. Nucleic Acids Research 20: 211-215. Schneider, S., D. Roessli and L. Excoffier, 2002 Arlequin ver. 2.000: A software for population genetics data analysis., pp., Genetics and Biometry Laboratory, University of Geneva, Switzerland. Schwengel, D. A., A. E. Jedlicka, E. J. Nanthakumar, J. L. Weber and R. C. Levitt, 1994 Comparison of fluorescence-based semi-automated genotyping of multiple microsatellite loci with autoradiographic techniques. Genomics 22: 46-54.
Tonia S. Schwartz Chapter 1 23 Severance, E. G., 2002 Connectivity, genetic diversity, and complex evolution of reefbuildingScleractinia in the Western Atlantic/Caribbean province: Consequences for todayÂ’s coral reefs, pp. in Department of Biology University of South Florida, Tampa. Shriver, M. D., L. Jin, R. Chakraborty and E. Boerwinkle, 1993 VNTR allele frequency distributions under the stepwise mutation model: A computer simulation approach. Genetics 134: 983-993. Sites, J. W. J., N. N. FitzSimmons, N. J. Da Silvia and V. H. Cantarelli, 1999 Population genetic structure in the giant Amazon River turtle ( Podocenemis expansa ): inferences from two classes of molecular markers. Chelonia Conservation and Biology 4: 454-463. Stephan, W., 1986 Recombination and the evolution of satellite DNA. Genetical Research 47: 167-174. Stephan, W., 1989 Tandem-repetitive noncoding DNA: forms and forces. Molecular Biology and Evolution 6: 198-212. Strand, M., T. A. Prolia, R. M. Liskay and T. D. Petes, 1993 Destabilization of tracts of simple repetitive DNA in yeast by mutations affecting DNA mismatch repair. Nature 365: 274-276. Tautz, D., and M. Renz, 1984 Simple sequences are ubiquitous repetitive components of eukaryotic genomes. Nucleic Acids Research 12: 4127-4138. Valenzuela, N., 2000 Multiple paternity in side-neck turtles Podocnemis expansa: evidence from microsatellite DNA data. Molecular Ecology 9: 99-106.
Tonia S. Schwartz Chapter 1 24 Weber, J. L., 1990 Informativeness of human (dC-dA)n polymorphisms. Genomics 7: 524-530. Zaroya, R., and A. Meyer, 1998 Cloning and characterization of a microsatellite in the mitochondrial control region of the African side-necked turtle, Pelomedusa subruf. Gene 216: 149-153.
Tonia S. Schwartz Chapter 1 25 TABLE 1.1: Multiplexing microsatellite PCR and Genescan reactions protocol that was used in this study. LocusSize Range (BP)Fluorescing MoleculeMix 1Mix 2 GP15 207-269 6-FAM X GP19 252-256 6-FAM X GP26 358-370 TET X GP30 194-232 TET X GP55 265-271 TET X GP61 197-245HEXX GP81 397-415 6-FAM X GP96 141-157 6-FAM X GP102 299-339 TET X
TABLE 1.2: Primer sequences and locus characteristics for Gopherus polyphemus microsatellites. Total number of individuals screened ranged from 264 to 279. Average (and SD) of observed heterozygosities (HO) and expected heterozygosities (HE) are reported for nine populations of 18 individuals or greater. An asterisk indicates that locus was out of Hardy-Weinberg equilibr ium (P 0.01) in at least one population. / = an interruption in the repeat motif, A = number of alleles, N= number of samples.Locus Repeat Sequence in ClonePrimer Sequence and Fluorescent Label GenBank Accession # Size in Base Pairs A N Ho SD He GP15GA(15)GT(8)F:5-CCTATTTTTCCCCCTCACAGT-3AF546895207-269190.610.66 R: 6FAM -5-GAAAATAAAAACAGTCCCAACCA-3275 0.1 0.10 GP19GT(9)/GT(3)GA(6)F: 6FAM -5-GCAGGACAGTGCCACACTA-3AF546891252-25630.180.22 R:5-CAGCCATATTAATGACAATCTG-3272 0.17 0.18 GP26GT(12)F:5-GACAACCATCTTTACCCACA-3AF546892358-37060.41*0.40 R: TET-5TCCCAAGACATAAGTCAGTAGC-3274 0.16 0.13 GP30GT(13)F: TET -5-GAATGCAGCACTGCTTGGTA-3AF546889194-232100.37*0.55 R:5-CGAAGAGGGAGCACGTTTAG-3264 0.16 0.03 GP55GT(9)F: TET -5-TTAGGGATTTTCTGTCTACTTCAG-3AF546893265-27120.350.40 R:5-CGCAATGTGACACGCTATT-3272 0.19 0.16 GP61GT(12)F: 6HEX -5-GCATTAAACCATTGTGCCTCA-3AF546896197-24570.410.46 R:5-AGTGGTGGTCGAAGTGGAAC-3279 0.18 0.18 GP81GT(11) GA(10)F:5-TCACACAAACCCCATCCATA-3AF546894397-41570.590.66 R: 6FAM -5-TCCATTGAATTGCCATCTGA-3269 0.08 0.07 GP96GA(11)F: 6FAM -5TCAGTTACCGGATAATGTTCAGTG-3AF546888141-15780.24*0.35 R:5-TGCTGTTACCTCGTGCATGT-3279 0.20 0.21 GP102GT(5)CT(13)CA(5)F: TET -5-AGCTGCCTGACTGCTATGCT-3AF546890299-339150.43*0.60 R:5-GCATAATCAGCATCAACAACAAA-3273 0.20 0.11
Tonia S. Schwartz Chapter 1 27 TABLE 1.3: Cross-species PCR amplification, Genescan, and sequencing results. For each locus-species combination, the first line contains the PCR annealing temperature and final MgCl2 concentration for single locus reactions; the second is the number of alleles (number of individuals) ; and the third is the repeat motif (when sequenced). X indicates no amplification at conditions ranging from 55-60 C with 2.5-3mM MgCl2. NO MS indicates no microsatellite detected after sequencing the locus and ND indicates not determined.GopherusGopherusGopherusGopherusKinosternonChelonia Locus polyphemusagassiziiberlandieriflavomarginatusbauriimydas GP15 60 C/2.5mM55 C/2.5mM55 C/2.5mM55 C/2.5mM XX 19(275)2(1)2(1)2(1) GA(15)GT(8)NDNDND GP19 60 C/2.5mM60 C/2.5mM60 C/2.5mM60 C/2.5mM60 C/2.5mM60 C/2.5mM 3(272)2(1)1(1)1(1)1(4)1(1) GT(9)GT(3)GA(6)NDGT(7)GA(5)GT(16)GA(8)GT(8)GA(7)GT(11)GA(4)GP26 60 C/2.5mM57 C/3mM57 C/3.0mM60 C/3.0mM XX 6(274)2(1)1(1)1(1) GT(12)NDGT(11)GT(11)GP30 60 C/2.5mM57 C/2.5mM57 C/2.25mM57 C/2.5mM55 C/3.0mM X 10(264)3(2)1(1)1(1)2(4) GT(13)NDGT(7)GT(4)ND GP55 60 C/2.5mM55 C/3.0mM60 C/2.5mM60 /2.5mM XX 2(272)2(1)2(1)2(1) GT(9)NDNDND GP61 60 C/2.5mMM60 C/2.5mM60 C/2.5mM60 C/2.25mM60 C/2.5mM60 C/2.5mM 7(279)4(2)1(1)2(1)1(4)1(1) GT(13)NDGT(28)NDNO MSGT(2)GP81 60 C/2.5mM57 C/2.5mM57 C/2.5mM60 C/2.5mM57 C/2.5mM X 7(269)2(1)1(1)1(1)ND GT(11)GA(10)NDGT(9)GA(11)GT(8)GA(9)GA(23)GP96 60 C/2.5mM57 C/2.5mM57 C/2.5mM57 C/2.5mM57 C/2.5mM60 C/2.5mM 8(279)1(2)1(1)1(1)2(4)2(1) GA(11)GA(17)GA(11)GA(9)NDND GP102 60 C/2.5mM55 C/3.0mM60 C/2.5mM57 C/2.5mM55 C/3.0mM X 15(273)2(1)1(1)1(1)1(4) GT(5)CT(13)CA(5)NDGT(4)CT(7)CT(8)ND
FIGURE 1.1 : The percentages of types of microsatellite sequences found in the 91 clones from the G. polyphemus sub-genomic microsatellite library. The right hand chart represents the 25 sequences from which primers were designed. Nine of these loci were optimized and variable for genotyping individuals. MS = microsatellite. No MS 38% M S too sma ll 9% MS too big 1% MS too close to plasmid 22% could not be optimized for unknown reasons 8% optimized and variable 11% could not be optimized because repeat too close to plasmid 5% invariable, hypervariable, o r unreliable 6%
Tonia S. Schwartz Chapter 1 29 FIGURE 1.2: The percentages of the types of microsatellites found in the 61 clones that contained microsatellite regions. Compound Perfect Imperfect 0 5 10 15 20 25 30 35 40 45 % Compound imperfect Compound perfect
Tonia S. Schwartz Chapter 1 30 FIGURE 1.3: The percentages of microsatellites recovered that contained the repeat motifs targeted during the construction of the microsatellite library. Other refers to repeat motifs that were not targeted. 0 10 20 30 40 50 60 % CACAACTOther Repeat Motifs
Tonia S. Schwartz Chapter 2 31 CHAPTER 2: POPULATION GENETICS OF THE GOPHER TORTOISE: IMPLICATIONS FOR CONSERVATIONINTRODUCTIONTHE SPECIES OF CONCERNThe gopher tortoise ( Gopherus polyphemus ) is considered an essential component of the sand hill and scrub habitat throughout the southeastern coastal plains of the United States. Researchers have deemed this tortoise a keystone species largely because its burrows provide habitat and refuge for approximately 60 vertebrate and 300 invertebrate commensal species, many of which are legally protected. Presently, the gopher tortoise is federally listed in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), as Threatened according to the Florida Committee for Rare and Endangered Plants and Animals (FCREPA) (Bury and Germano 1994; Diemer 1986), and as a Species of Special Concern by Florida Fish and Wildlife Conservation Commission (FWC). Auffenberg and Franz (1982) reported that gopher tortoise population sizes were estimated to have declined 80% since the 1880s. The severe decline in tortoise population numbers and sizes, especially in Florida, is primarily due to past human predation, and habitat degradation and destruction as a result of increased urbanization (Auffenberg and Franz 1982). This trend has likely continued over the past 20 years as development in Florida has intensified. Furthermore, a growing number of populations are being found to be infected with the contagious and potentially lethal upper respiratory tract disease (URTD) caused by Mycoplasma spp. (Brown et al. 1999b; Diemer Berish et al. 2000; Diemer 1986; Jacobson et al. 1991).
Tonia S. Schwartz Chapter 2 32 Habitat destruction continues to displace tortoises from suitable habitat, decrease population sizes, and disrupt migratory corridors. The consequential reduction in gene flow, thereby results in isolated populations that are mostly found in protected areas such as state and national parks or private lands. As predicted by population genetics theory, small isolated populations have higher levels of inbreeding, and the effects of genetic drift are more pronounced (Hartl and Clark 1997). Both of these processes can potentially decrease the fitness of the population due to loss of genetic variability and accumulation of deleterious, recessive alleles (Gilpin and Soul 1986; Lande and Barrowclough 1987; Mueller 1964). Genetically depauperate populations may have a reduced ability to adapt to a changing environment and to new diseases, an important consideration in light of the recent findings of URTD in many gopher tortoise populations throughout Florida (Diemer Berish et al. 2000; Selander et al. 1991; Vida 1994). Accompanying the habitat destruction are mitigation efforts to relocate individual tortoises or entire populations that interfere with human development. Current FWC policy requires developers to test tortoises for antibodies against Mycoplasma spp. causing URTD and if negative, to relocate the tortoises and/or populations within 50 miles north or south and any distance east or west of the original location. The policy allows tortoises to be placed into preexisting populations within the holding capacity of the site (the number of tortoise that can survive on the resources of a given site). This policy specifically states that tortoises should not be moved into or adjacent to genetically distinct populations (U.S. Fish and Wildlife 2000). At present no genetic testing is done before moving the tortoises. The mixing of genetically divergent populations may have different effects on the future of the integrated population. First, the mixing could benefit the population by introducing new genetic variability for natural selection to act upon. Conversely, if
Tonia S. Schwartz Chapter 2 33 tortoise populations become locally adapted to elements in their particular habitats, such as thermal clines or soil type and hydrology that may influence nesting behavior and egg physiology (Tucker and Warner 1999), relocation events may be quite detrimental not only to the relocated tortoises, but also to the host population. In this way, the arbitrary mixing of potentially distinct genetic stocks of tortoises may lead to outbreeding depression such that hybridization of host tortoises and relocated tortoises would disrupt the locally adapted gene complexes, thereby decreasing the overall reproductive fitness of the individuals and consequently the population (Diemer Berish 1989; Templeton 1986). Thus we have two conflicting extremes that may result from development and mitigation: inbreeding as a result of isolating populations into state and national park islands, and outbreeding as a result of mixing genetic stocks through relocation procedures. These extremes would need to be minimized for successful conservation of tortoise populations as well as of the species. Management plans addressing both the genetic and the disease issues are essential for the preservation of gopher tortoise populations. In addressing the genetic issues, effective management decisions at the population level require information on life history traits and genetic population parameters. A large number of ecological studies on the tortoise exist but very little genetic research has been conducted on Florida gopher tortoise populations. In one of the few studies published, Osentoski and Lamb (1995) detected three major genetic assemblages in Florida using restriction fragment length polymorphism (RFLP) analysis of mitochondrial DNA (mtDNA): eastern Florida (most of the peninsula), western Florida (the panhandle), and along the Brooksville Ridge on the west central coast (Figure 2.1). This study may have had limited resolving power, however, because Testudinea mtDNA generally evolves relatively slowly (Avise et al. 1992). With a more quickly evolving marker, further resolution of the previously described genetic assemblages is likely. This is especially true for the eastern assemblage that extended over 450 miles north and south and included diverse habitats. Without reliable information on genetic subdivision, it is difficult for refuge managers and relocation organizations to make informed decisions that take into account genetic
Tonia S. Schwartz Chapter 2 34 consequences. In addition, as development in Florida continues, areas and populations essential for the persistence of genetic diversity within this species need to be identified and protected. The goal of this research is to estimate the genetic diversity within the gopher tortoise ( Gopherus polyphemus ) as well as to determine the genetic structure of the populations across Florida using microsatellite markers. Microsatellites are considered neutral markers containing simple sequence repeats that are bi-parentally inherited. They evolve relatively quickly because of the way they mutate, either slip-strand mispairing (Levinson and Gutman 1987a; Shriver et al. 1993) or unequal crossing-over (Jefferys et al. 1985; Tautz and Renz 1984). Because they evolve quickly, these markers can provide high-resolution population structure that can be used not only to provide detailed information about the natural history of a population but also about how populations are related. These markers also allow for the definition of management units of the gopher tortoise based on allele frequency differences. I also discuss the evolutionary and anthropogenic processes that may affect the biodiversity within this species. Finally this paper provides options of integrating genetics and management policy for the preservation of the gopher tortoise.MATERIALS AND METHODSSAMPLE COLLECTIONBlood samples were collected from a total of 18 Florida, and 2 Georgia locations (Table 2.1 and Figure 2.1). Sample sizes for each population ranged from 1 to 26. Samples from nine of the Florida populations and the two Georgia populations were graciously shared by other researchers (Appendix C). The tortoises from the other nine Florida populations that were sampled solely for this study were caught by hand or by pit trapping. For each tortoise, I recorded the sex based on the curvature of the plastron in males, carapace length, plastron length, and weight (Appendix C). The tortoises were temporarily marked (numbered and dated) on the plastron with felt tip marker, which is known to remain for a period of two weeks to over a year. The location of each tortoise
Tonia S. Schwartz Chapter 2 35 was recorded on an aerial map. Blood was drawn from the brachial vein with a heparinized 26-gauge needle and a 10 cc syringe (Turmo). Some blood samples were received from other researchers as concentrated red blood cells. One to two drops of blood or approximately 10 l of concentrated red blood cells were placed into a vial containing PVP/BME blood storage buffer (0.01 M Tris, 100 _l NaCl, 50 mM EDTA, 1% polyvinylpyrrolidone, 0.2% 2-mercaptoethanol, 0.75% SDS). Samples were kept at 4 C and stored permanently at -80 C when genetic laboratory work was completed. DNA ISOLATIONTotal cell DNA was isolated from ~100 l of the blood/buffer samples by a modified phenol/chloroform protocol (Herrmann and Frischauf 1987; Karl et al. 1992). Purified DNA was resuspended in 0.5X TE (Tris, EDTA), maintained at 4 C while in use and stored permanently at Â—80 C when genetic work was completed. DATA COLLECTION The samples were PCR amplified at nine microsatellite loci (see Chapter 1). The nine loci were divided into two multiplexing reactions that were used for both PCR amplification and Genescan analysis as described in Chapter 1. STATISTICAL ANALYSESEach of the 18 populations (WA and EV were removed from many of the analyses since they consisted of only one and two samples, respectively) were tested for deviations from Hardy-Weinberg equilibrium (HWE) through Fishers Exact Tests in Arlequin, using 10,000 dememorization steps and 100,000 Markov Chain Steps (Guo and Thompson 1992; Schneider et al. 2002). Independent segregation of loci (i.e. genotypic linkage equilibrium) was tested in Genepop using a likelihood ratio test (Raymond and Rousset 1985; Slatkin and Excoffier 1996) with 1000 dememorization steps, 100 batches, and 1000 iterations per batch. P-values for HWE and linkage disequilibrium were adjusted using the sequential Bonferroni correction for multiple tests (Rice 1989).
Tonia S. Schwartz Chapter 2 36 Allele frequencies were determined using the Microsatellite Tools for Excel (Park 2001). Gene diversity per locus and averaged across populations was calculated in Fstat (Goudet 1995; Goudet 2001) using an unbiased estimator nk 1pi 2 k Â— HokHsk = ___ nk -1 2 (nk) Where nk is the sample size of sample k, pik is the frequency of allele Ai in sample k, and Hok is the observed proportion of heterozygotes in sample k (Goudet 2001; Nei 1987). Each sample with greater than 10 individuals was tested for the occurrence of a genetic bottleneck in the past 1-6 generations using the program Bottleneck (Corneut and Luikart 1996). During a bottleneck, effective population size is decreased and many of the lower frequency alleles are lost in the population. Subsequently within a number of generations after the bottleneck, the heterozygosity at selectively neutral loci also drops until the population once again reaches mutation-drift equilibrium (Corneut and Luikart 1996). It is during these generations immediately after the bottleneck, when the heterozygosity is still higher than expected based on the number of alleles in the population, that a bottleneck can be detected. The program Bottleneck tests for heterozygosity excess in comparison to the number of alleles found in a population using a sign test (Corneut and Luikart 1996), a Wilcoxon sign-rank test to determine if the proportion of loci with heterozygosity excess is significantly larger than expected at equilibrium (Luikart et al. 1998b), and a mode-shift indicator that detects a characteristic shift in the allele frequency distributions when a population has gone through a bottleneck (Luikart et al. 1998a). Population genetic distances were estimated using pairwise FST (Wright 1921; Wright 1969) and the microsatellite specific RST (Slatkin 1995) in Arlequin (Schneider et al. 2002) and the P-values were adjusted using the sequential Bonferroni correction (Rice
Tonia S. Schwartz Chapter 2 37 1989). Analysis of Molecular Variance (AMOVA: Excoffier et al. 1992) based on both FST and RST values was used to partition the allelic variance among groupings of populations and thereby to define genetic assemblages using the program Arlequin (Schneider et al. 2002). Twenty-two different grouping structures of samples divided into 5-10 groups were tested to determine the structure with the least within group variance and the most among group variance. Once the structure of the populations was identified, pairwise FST and RST estimates were calculated between the genetic assemblages. Specific migrants (or tortoises that have been moved) that were genetically distinct from the other tortoises in the population where they were sampled, were identified based on allelic frequencies at each locus using a probabilistic assignment test in the program Structure (Pritchard et al. 2000). This program determines a genetic picture characteristic of each population and subsequently tests each individual as to how well they fit into the genetic picture of each population. Thus each individual is given specific probability of originating from each population.RESULTSIn testing all of the populations for deviation from HWE, 2 of the 168 locus-bypopulation comparisons (GP96 in JD and GP102 in MB) were significantly out of HWE (Bonferroni corrected P 0.05): Table 2.1). Both of these loci showed heterozygote deficiencies indicating those loci may have null alleles in those populations. Null alleles are non-amplifiable as a result of mutations in the primer region, thus the individuals carrying that allele appear to be homozygous when they are actually heterozygous (Callen et al. 1993; Koorey et al. 1993). The locus-by-locus test for linkage in the 19 populations indicated that 32 of the 567 comparisons (some loci were monomorphic in some populations so comparisons were not possible) were significantly linked at the P 0.05 level. The populations with the
Tonia S. Schwartz Chapter 2 38 most loci in linkage disequilibrium were BH, EA, WS, and JC with 7, 6, 4, and 4 locipairs linked respectively (before Bonferroni correction). Only one comparison (in BH) was significant at the Bonferroni corrected P 0.1 level (Table 2.2). None of the locipairs were linked across all populations. Over all populations, average genetic diversity over all loci ranged from 0.389 in EV Â— 0.65 in IS; both of these populations have very low sample sizes (2 and 5 respectively: Table 2.1). In comparing populations with more than 10 samples, CC had the lowest genetic diversity estimate at 0.390 and BS had the highest at 0.570 (Table 2.1). This study identified twenty-three private alleles (alleles that were unique to a single population; Table 2.1 and Appendix D). Depending on the frequency of the private alleles, they can be rough indicators of gene flow into and out of a population. The populations with the most private alleles were JD with 7, BS and MB with 3 each, and CK and JC with 2 each. It is interesting to note that a private allele was found in both EV and WA despite the small sample sizes from both locations (2 and 1 respectively). One of the private alleles (208 at locus GP15: Appendices D and E) in the JD population was the result of an indel causing it to be one bp different in size when compared to all other alleles that have a two bp difference at this dinucleotide repeat locus. This allele was found in individuals that were heterozygous and individuals that were homozygous at this locus. In addition, it was found at a relatively high frequency in JD (27%: Appendices D and E). In the chance that the 208 allele was actually a result of technical problems and not a real allele, the data were reanalyzed with the 208 allele converted to allele 207 (the most common allele in all the populations), and with locus GP15 completely eliminated. While the pairwise distances change somewhat, the resulting structure of the populations and the genetic assemblages were the same for all the analyses. Using the program Bottleneck, of the thirteen populations tested, four (JC, BC, HH, CC) indicated the occurrence of a genetic bottleneck in the past six generations at
Tonia S. Schwartz Chapter 2 39 both the sign test and the Wilcoxon sign-rank test (P 0.087). MB indicated the occurrence of a bottleneck at all three of the tests (P<0.059). Both population genetic distance estimates (FST and RST) showed the same overall pattern. FST values for all pairwise populations comparisons ranged from 0.000 to 0.470 and pairwise RST values ranged from 0.000 to 0.489 (Table 2.3). The AMOVAs based on FST and RST estimates had the same overall patterns but differed slightly in the groupings of the northwestern populations (Figure 2.2). Of the 22 structures tested that were based on hierarchically and geographically grouped populations, both FST and the RST values each produced two patterns that maximize the among group variation and minimized the within group variation. The RST based AMOVA with the least within group variation (1.07%) and the most among group variation (24.69%) had six assemblages: northwestern (abbreviated NW; contained the population JC); northern (abbreviated NT; contained the population MB); north-central (abbreviated NC; contained the population BS); northeastern (abbreviated NE; contained populations CF, RA, and GB); mid-Florida (abbreviated MF; contained populations EA, OM, LL, WS, HH, CC, BC, BH, and FC); southeastern (abbreviated SE; contained the population JD); IS was equally likely to group with MB or BS; and CK was equally likely to group with JC or alone (overall RSTof 0.26; P 0.000; Figure 2.2). The FST based AMOVA with the least within group variation (7.88%) and the most among group variation (14.81%) was similar except IS grouped with BS, and CK was equally likely to be grouped alone or with BS and IS in the north-central assemblage (overall FST of 0.23, P 0.000; Figure 2.2). Pairwise FSTestimates between genetic assemblages ranged from 0.044 between NC assemblage and CK, to 0.346 between NW and MF assemblage. Pairwise RST estimates ranged from 0.000 between NW assemblage and CK, and 0.484 between NW assemblage and SE assemblage (Table 2.4) Four individual migrants were identified using the program Structure (Table 2.5). One individual found in CK (GPO-199) had a 9% probability of originating there, 23% probability of originating from LL, and 19% probability of coming from EA. One individual sampled in WS (GPO-68) had only 13% chance of originating in WS and 71%
Tonia S. Schwartz Chapter 2 40 chance of coming from BC. One individual from RA (GPO-193) only had 38% chance of originating in RA and 52% chance of coming from BH. One individual from JD (GPO-146) only had 0.6% chance of originating from JD and 48% chance of coming from BH, and 20% chance coming from HH.DISCUSSIONMOLECULAR EVOLUTION OF MICROSATELLITESBefore discussing the population data, it is important to understand the mutation models operating on microsatellites. Inappropriate use of analyses programs based on different mutation models can affect the results and their interpretation. Presently three models of microsatellite evolution have been described: the infinite allele model (IAM: Jefferys et al. 1988; Jefferys et al. 1985; Stephan 1986; Stephan 1989; Tautz and Renz 1984), the stepwise mutation model (SMM: Caskey et al. 1992; Levinson and Gutman 1987a; Ohta and Kimura 1973; Schltterer and Tautz 1992; Shriver et al. 1993), and the two-phase mutation model (TPM: Di Rienzo et al. 1994). According to the IAM, mutations (likely caused by unequal-crossing over during recombination) result in new alleles in the population (Kimura and Crow 1964). In the SMM, mutations are caused by slip-strand mispairing that results in alleles with small changes in repeat number (Levinson and Gutman 1987b; Schltterer and Tautz 1992). The TPM incorporates in varying degrees the mutational methods of the two previously described. Although variations of the TPM are the most probable model for most loci, most current algorithms and statistical programs are based on either the IAM or the SMM (Di Rienzo et al. 1994). RST estimates are thought to be more accurate for microsatellite loci because they use the variance in repeat number thus modeling the SMM, whereas FST estimates use the variance in allele frequency and thereby is based on the IAM (Gaggiotti et al. 1999; Slatkin 1995). Gaggioti et al. (1999) recommends the use of FST estimates as a conservative estimate for small sample sizes (N 10 ) and low number of loci ( 10) when population sizes are low ( 500). Although most of the locations used in this study had more than 10 samples, fewer than 10 loci were scored. Consequently, to provide the
Tonia S. Schwartz Chapter 2 41 most comprehensive depiction of the possible population genetic structure, both FST and RST estimates were displayed for most of the analyses. Policy and its ramifications on genetic diversity The Florida Fish and Wildlife Conservation Commission (FWC) is responsible for regulating developers and managing gopher tortoise populations, although much of the necessary data to do so are absent. This study provides information to understand the current genetic structure of populations and likewise to understand the consequences policies will have at the genetic level. A fair amount of genetic subdivision across Florida and southern Georgia was found in this study. Based on FST and RST estimates, the genetic variance seen across Florida was partitioned into five or potentially six genetic assemblages (Figure 2.2). Jonathan Dickenson State Park on the southeastern coast of Florida formed its own genetic assemblage with substantial difference from most other populations in both FSTand RST estimates (Table 2.4). This assemblage was further supported by the seven private alleles found in JD, many of which were in relatively high frequencies (Appendicies D and E). Thus indicating there has not been much gene flow out of this population. The middle assemblage covered the largest area and only three of its populations (LL, OM, and EV) possessed one private allele each. The island of Cayo Costa State Park fell within the middle assemblage possibly due to historical reasons on how and when the island was colonized (see Chapter 3). Within the two samples I was able to collect from the Cape Sable population in the Everglades (EV) there was a private allele. This indicates the allele was likely in relatively high frequency in that population and that with more sampling this population may have shown more genetic distinctness. Further sampling in this area is unlikely because Hurricane Gabrielle in September of 2001 likely had a drastic detrimental affect on that island population. Sampling shortly after the hurricane, we saw a large number of burrows but we were only able to trap two gopher tortoises, and we saw a couple of ones dead outside of their burrows possibly as a result of drowning.
Tonia S. Schwartz Chapter 2 42 In northern Florida and southern Georgia, this study identified three to four distinct genetic assemblages. Both the RST and FST estimates supported a northeastern assemblage (GB, RA, and CF: Figure 2.2 and Table 2.4). The AMOVAs also supported a north-central assemblage characterized by BS, a northern assemblage characterized by MB, and a northwestern assemblage characterized by JC. The RST and FST values and the number of private alleles found in the characterizing populations in each of these assemblages indicate they were quite divergent from each other and from the northeastern assemblage (Table 2.4). The relative positions of CK and IS within the assemblages were debatable. This inconsistent grouping may be a result of low samples sizes in both these populations. When working with genetic markers that have a relatively larger number of alleles, larger sample sizes are important to accurately reflect the relative frequencies of the alleles in each population. Thus more complete sampling in these areas may better define their relationships to other populations. The northwestern assemblage containing Jones Research Center (JC) in southwestern Georgia was also supported by the 2 unique alleles that were found in that population (Table 2.1). In addition the single sample from Wakulla Springs State Park in the panhandle of Florida (WA: Figure 2.1 and Table 2.1) had a private allele. Whether this area would be included in the northwestern assemblage, or become its own assemblage as suggested by the mtDNA data (Osentoski and Lamb 1995) requires further sampling. The current policy on relocation of gopher tortoises that interfere with development requires that individuals should be relocated no further than 50 miles north or south of the original population, but there are no restriction the distance east or west. The policy also states the tortoises should not be moved into or adjacent to genetically distinct populations, although genetic testing does not precede relocation. The relatively close proximity of the genetically distinct assemblages identified in this study (especially in northern Florida) calls for a more conservative approach than the current FWC policy if the goal is to maintain the genetic distinctness of the areas. The genetic data presented here indicate that in many cases moving tortoises within the distances described would allow tortoises to be introduced into at least two other genetically distinct assemblages (Figure 2.2).
Tonia S. Schwartz Chapter 2 43 The genetic implications from this study provide both consequential evidence from past mitigation events, and a warning for future efforts based on this current policy. The mid-Florida assemblage contains the largest number of populations and covers the largest area, an area of Florida that has been heavily influenced by development and habitat destruction (Figure 2.2). Thus mitigation efforts (whether official and planned or dumping by well-intentioned citizens) have been extensive throughout this area making it a melting pot of genetic diversity and consequently reducing any genetic distinctness within the region that may have been present at one time. This admixture is apparent when testing for pairwise linkage disequilibrium among loci. Within the mid-Florida assemblage Boyd Hill State Park (BH) and EcoArea (EA) exhibited linkage disequilibrium at 7 and 6 loci pairs respectively before sequential Bonferroni correction for multiple comparisons (Table 2.2). Both BH and EA have been sites of tortoise relocation and dumping as the surrounding cities have developed. Wekiva Springs State Park (WS) and Lake Louisa State Park (LL), which also are in areas of high development (near Orlando, Florida), have linkage disequilibrium at 4 and 2 comparisons respectively before the sequential Bonferroni correction (Table 2.2). Although only one of these (in BH) is significant after the sequential Bonferroni correction (P 0.1), I believe this trend represents genetic homogenization in areas of development. This is an important consideration if the goal of management is to maintain genetically distinct areas or assemblages. Florida has a variety of unique and distinct habitats that transgress over relatively small geographic ranges. While the gopher tortoise is reproductively restricted to xeric habitat, the specific components (such as temperature extremes and averages, and soil hydrology) of these environments undoubted change somewhat when comparing costal to inland scrub, and along the 400 miles extending north to south that make up the peninsula of Florida. These environmental variations provide a likely scenario for the evolution of local adapted gene complexes. These local adaptations would result in increased fecundity of individuals and consequently the populations while they remain in that specific habitat. For example, local adapted gene complexes may play a role in nest
Tonia S. Schwartz Chapter 2 44 site selection and egg physiology during incubation, which would be affected by the soil hydrology of the habitat. Locally adapted traits that are under directional selection would evolve faster than the neutral loci where divergence is dependent on drift and restricted gene flow (McKay and Latta 2002). In this case, the neutral loci used in this study (microsatellites) would underestimate the amount of genetic divergence among the populations that have evolved locally adaptive gene complexes. Many of the populations (and genetic assemblages) in this study have diverged at their neutral loci as a result genetic drift that can occur when gene flow is limited. In addition, three of the populations in the mid-Florida assemblage (BH, EA, and LL) show distinct signs of admixture indicating there was genetic structure in this area at one time. Admixture is only evident when sampling the individuals that have been translocated. Thus while these populations may seem to be healthy because the adults are present, unless the individuals are successfully reproducing viable and relatively fit offspring, the population will not be sustained. Predicting the health of gopher tortoise populations may by especially deceptive because the tortoises long lifespan of at least 60 years (Diemer 1986). Continual monitoring of these populations will be telling because it is this next couple of generations where the first effects of outbreeding depression would be evident. Relocation has been a primary option in scenarios where development and species habitat conflict. Although a relocation effort may appear to be relatively successful because the animals survival and persistence on the site, the evolutionary success of the new population is dependent on many complicated factors. In relocation experiments, researchers have had mixed results of tortoises surviving and remaining for a number of years on the relocation site (Burke 1989; reviewed in Diemer Berish 1989; Diemer 1987). From these studies, survival and persistence of individuals immediately after relocation depends on a variety of factors including social behavior in terms of sex ratios and social hierarchy, habitat preferences, and introduction procedures such as starter holes and penning the animals prior to release. Because of the tortoises long generation time, none of these studies have been able to address the evolutionary success of the relocations in terms of loss of alleles and decreased heterozygosity from inbreeding.
Tonia S. Schwartz Chapter 2 45 In a literature review conducted by Stockwell et al. (1996) covering 29 studies that included fish, reptile, bird, and mammal species, 50% of the translocated populations had decreased heterozygosity when compared to the parental population, and 75% had decreased allelic diversity. Loss of heterozygosity and genetic diversity can evolutionarily handicap a population by eliminating its potential to evolve with its environment thus causing a reduction in the fitness of the population (Allendorf 1986; Allendorf and Leary 1988; Mitton and Grant 1994). A reduction in fitness adversely affects population growth (Leberg 1990) and inherently increase the probability the population will go extinct. The loss of genetic variation after relocation is most likely caused by an unsuspected bottleneck during the translocation that results in a drastically decreased effective population size (Ne) regardless of the size of the translocated population. Sex ratio, mating behaviors, and the variability in reproductive success of individuals in the population all contribute the Ne (Crow and Kimura 1970; Meffe and Vrijenhoek 1988). Thus natural populations of the gopher tortoise are already expected to have a relatively small Ne because of poor clutch success and the potential for a polygamous mating system (Douglas and Winegarner 1977; Landers 1980). The added loss of genetic variation from relocation into a site where gene flow is limited may severely hinder the evolutionary success of the population. A decline in a population (or just the number of breeders in a population) as a result of a bottleneck results in a relatively large loss in the number of alleles, but it takes a number of generations for the heterozygosity to decrease relative to the number of alleles left in the population. It is this excess in heterozygosity right after a bottleneck as compared to the expected heterozygosity based on the number of alleles left in the bottlenecked population that allows the bottleneck to be detected (Cornuet and Luikart 1996). In this way the program Bottleneck can detect bottlenecks that have occurred in the past six generations in studies that have sample sizes of 20-30 individuals and use 520 loci (Luikart and Cornuet 1998). Despite relatively low statistical power from having small sample sizes, the effects of isolation and potential bottlenecks have been detected in some of the sample locations. In three gopher tortoise populations there were strong indications of a bottleneck having occurred within the past 6 generations (72 120 years
Tonia S. Schwartz Chapter 2 46 assuming a generation time of 15 Â— 20 years): Moody Air Force Base, Jones Research Center, Highland Hammocks, Brooker Creek County Park, and Cayo Costa State Park. The likelihood of a false indication of genetic bottlenecks in this study is quite low because of the low statistical power with only nine microsatellite loci each of which are likely to be following a slightly different mutation model, and to limited sample size (Cornuet and Luikart 1996). Historical records concerning the development around these protected areas and their management will be useful in verifying these genetic bottlenecks and their potential causes. The amount of genetic diversity in a population also is affected by the degree of gene flow among populations (Crow and Kimura 1970; Meffe and Vrijenhoek 1988). This study has shown that the populations within the assemblages have relatively high levels of gene flow among them. If gopher tortoise populations are isolated into small protected park islands surrounded by development with no influx of new alleles, these populations may have a decreased ability to adapt to the changing environment (Selander et al. 1991). Genetics and Policy The ultimate goal of species management and conservation is not only to preserve a single population, but to preserve adaptive diversity and evolutionary potential across a geographic range that will sustain the larger Evolutionary Significant Unit (ESU: Crandall et al. 2000; Ryder 1986; Waples 1991). One method of doing so is to identify management units (MU) as defined by Moritz (1994; 2002). Individual populations are important for the evolution of a species as a whole because they allow for varied selection in different habitats that will sustain genetic variation in the species. Thus genetically distinct individuals and populations (or species) should not be moved across wide geographic distances that would effectively homogenize populations (Moritz 1999; Moritz 2002; Rhymer and Simberloff 1996). Overall management and relocation strategies should be based on estimates of current and historical gene flow patterns that indicate which populations can and possibly
Tonia S. Schwartz Chapter 2 47 should continue to exchange genetic material (Slatkin 1987). Migration has the potential to introduce genetic variability into populations if the migrants breed with the residents (Slatkin 1987). The migratory ability of a species is most easily preserved by saving natural networks of genetic connections while also focusing on distinct populations. By saving these connections of mosaic habitats for migration and selection to act, ecologically important genetic variation may be maintained through the preservation of a heterogeneous environment (Endler 1973; McKay et al. 2001; Moritz 2002; Stortz 1998). Estimates of gene flow among populations can be useful for identifying migration routes for preservation. Alas there will always be conflicts between humans and gopher tortoises over the coveted land, and mitigation is the likely outcome. Thus according to FWC policy of not mixing tortoises from genetically distinct assemblages, genetic testing before mitigation is a necessity if is to be an effective strategy for gopher tortoise management. This dataset demonstrates the potential usefulness of a genetic database in management. Such a database would contain population level information on genetic data (mtDNA and microsatellites), health status (URTD), and habitat characteristics, all of which could be used to define management units (Moritz 1994). An assignment test based on these parameters could be used to determine the best area to relocate tortoises that interfere with development, therefore decreasing the possibility of losing local adaptations along with potential exposure of sterile populations to the mycoplasm that causes URTD. Under the current policy up to 25% of the tortoises in population have to be tested for URTDs (has antibodies against mycoplasma causing URTDs) before that population can be relocated. If a single individual from the 25% tests sero-positive, incidental take permits (permission to kill) are issued for all the tortoises within the population that are conflicting with development (Williams 2001). The benefit of killing tortoises from populations with individuals that test sero-positive for the disease is debatable. The presence of these antibodies indicates that the tortoise had been exposed to the diseasecausing organism in the recent past and has produced an immune response. Thus a
Tonia S. Schwartz Chapter 2 48 tortoise testing sero-positive may have a number of different statuses: the tortoise may be infected with the disease and may soon die, it may have survived the disease with immunity and may potentially be a carrier of the disease, or it may have survived with immunity and has cleared the disease from its system. In addition, it has been shown that offspring of infected mothers can carry antibodies against the mycoplasma for at least a year even if the offspring have not been infected. Furthermore, other mycoplasma species are known to elicit the same immune response but not necessarily cause the disease, resulting in false positives. While it has been proven that URTDs has the potential to be lethal (Brown et al. 1999a; Brown et al. 1999b) the severity of the disease and its variability in natural populations has yet to be fully characterized. A number of researchers have monitored both gopher and desert tortoises for a number of years and witnessed individual tortoises cycling through being sero-positive and seronegative (Brown et al. 1999a), while reproducing successfully (R. Ashton and D. Rostal pers. comm). In addition, current research on populations around the state of Florida has indicated that most, if not all, of the populations being tested contain tortoises that test sero-positive (C. Legler and H. Mushinsky pers. comm.). The goal of not wanting to infect potentially healthy populations through the introduction of these diseased tortoises is valid; but it seems unlikely that a Species of Special Concern would benefit as a whole, when thousands of individuals are being destroyed. In addition, the selective killing of tortoises that show a particular immune response (potentially beneficial) can have drastic affects on the overall genetic diversity of a species. To be sero-positive, the tortoise has to produce an immune response to the pathogen. If that immune response is sufficient to fight the disease the tortoise would be resistant to the URTD. Selecting seropositive tortoises out of the population or species not only eliminates sick, contagious individuals, but also individuals with genes conveying resistance against the pathogen. This human induced selection (verse natural selection) could negatively affect the potential for this species to evolve with current and future pathogens. Lastly, if it is currently the case that all populations possess sero-positive individuals such that developers can get take permits to build over any gopher tortoise population that
Tonia S. Schwartz Chapter 2 49 interferes with their plans, then the purpose of the Species of Special Concern status is pointless and this species is in fact not protected at all. Continual destruction of the tortoises and their populations will cause a continual decline in the species until it qualifies as endangered and is potentially past the point of having enough genetic diversity for the species to be maintained. In conclusion, this microsatellite study complements the mtDNA study supporting the fact that the gopher tortoise currently has a fair amount of genetic diversity. Because of their increased resolution relative to mtDNA, these genetic markers were able to identify at least five genetic assemblages in the peninsula of Florida and southern Georgia. Base on mtDNA results there is at least one more assemblage in the panhandle of Florida (Osentoski and Lamb 1995). FWC policy needs to be updated and enforced to protect these genetic assemblages. A way of doing this is to set up the proposed database that can be used to assign mitigated tortoises to an area where they will be most effective to management.
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TABLE 2.1: Population estimates for each locus and for all loci combined. Abbreviations and sample sizes are below the population name. HE and HO are expected and observed heterozygosities, indicates loci that were out of Hardy-Weinberg equilibrium at the P 0.05 level, after sequential Bonferroni correction. HWD is the number of populations that were in Hardy-Weinberg Disequilibrium at that locus. Mean SE is mean and the standard error across loci or across populations. M indicates monomorphic loci, NA indicates values that could not be determined. A is the number of alleles: the number in parenthesis indicates the number of alleles that are unique to that population, GD is genetic diversity. Population and sample size (N) GP15GP19GP26GP30GP55GP61GP81GP96GP102Mean SE Total Alleles Wakulla Springs State Park WA (N=1) HEHOGD A NA NA NA 2(1) M NA 1 M NA 1 NA NA NA 2 M NA 1 NA NA NA 2 NA NA NA 2 NA NA NA 2 M NA 1 NA NA NA 14(1) Jones Research Center JC (N=19) HEHOGD A 0.74 0.563 0.746 5(1) 0.152 0.105 0.102 5 0.615 0.684 0.583 4 0.554 0.706 0.550 3 M 0.000 1 0.691 0.632 0.654 3 0.674 0.740 0.646 4 0.768 0.474 0.740 5 0.585 0.316 0.569 3(1) 0.597 0.194 0.528 0.220 0.510 0.270 30(2) Cedar Key Scrub State Preserve CK (N=8) HEHOGD A 0.675 1.000 0.652 3 0.592 1.000 0.563 3 0.659 0.750 0.652 3 0.775 0.500 0.777 4(1) M 0.000 1 0.425 0.375 0.321 2 0.495 0.429 0.381 3 0.683 0.375 0.625 5 0.450 0.125 0.357 3(1) 0.594 0.126 0.569 0.316 0.481 0.239 27(2) Continued on the next page.
Population and sample size (N) GP15GP19GP26GP30GP55GP61GP81GP96GP102Mean SE Total Alleles Big Shoals State Park BS (N=11) HEHOGD A 0.879 0.818 0.859 10(3) 0.606 0.727 0.600 3 0.684 0.818 0677 5 0.684 0.364 0.623 3 0.091 0.091 0.091 2 0.515 0.455 0.455 2 0.766 0.727 0.732 4 0.736 0.727 0.691 6 0.468 0.273 0.400 3 0.603 0.230 0.555 0.267 0.570 0.227 38(3) Moody Air Force Base MB (N=15) HEHOGD A 0.639 0.533 0.612 4 0.262 0.071 0.203 2 0.653 0.533 0.619 4 0.800 0.667 0.781 5(1) M 0.000 1 0.468 0.429 0.415 3 0.624 0.714 0.621 4 0.710 0.571 0.701 5 0.886 0.286* 0.852 7(2) 0.630 0.194 0.476 0.211 0.534 0.278 35(3) Itchnuckney Springs State Park IS (N=4) HEHOGD A 0.844 0.800 0.750 5 0.467 0.200 0.500 2 0.778 0.800 0.775 4 0.778 0.800 0.775 4 0.533 0.000 0.400 2 0.600 0.400 0.550 2 0.889 0.600 0.850 4 0.644 0.800 0.500 2 0.844 0.400 0.750 4 0.709 0.152 0.533 0.300 0.650 0.162 29 Cecil Field Air force Base CF (N=4) HEHOGD A 0.607 0.750 0.583 3 0.750 0.500 0.708 3 0.786 0.250 0.667 3 0.857 0.250 0.750 3 M 0.000 1 0.464 0.250 0.250 5 0.929 0.500 0.875 4 0.643 0.500 0.458 3 0.643 0.250 0.667 3 0.710 0.150 0.322 0.159 0.551 0.274 25 Gold Head Branch State Park GB (N=9) HEHOGD A 0.909 0.000 0.903 9(1) 0.294 0.333 0.292 2 0.634 0.556 0.639 4 0.617 0.250 0.518 2 0.294 0.333 0.292 2 0.575 0.333 0.556 3 0.641 0.222 0.632 4 0.294 0.333 0.292 2 0.569 0.333 0.583 3 0.536 0.208 0.299 0.146 0.523 0.204 31(1) Continued on the next page. Table 2.1 continued.
Population and sample size (N) GP15GP19GP26GP30GP55GP61GP81GP96GP102Mean SE Total Alleles Ray Ashtons Tortoise Preserve RA (N=21) HEHOGD A 0.871 0.850 0.862 8(1) 0.351 0.200 0.307 3 0.568 0.600 0.567 4 0.590 0.278 0.546 3 0.169 0.118 0.114 2 0.603 0.550 0.572 4 0.687 0.579 0.675 4 0.351 0.350 0.309 4 0.620 0.474 0.624 4 0.534 0.210 0.444 0.230 0.508 0.227 36(1) Oldenburg Mitigation Park OM (N=15) HEHOGD A 0.677 0.500 0.629 4 0.563 0.714 0.530 3 0.378 0.357 0.319 3 0.585 0.500 0.544 5 0.262 0.214 0.198 2 0.262 0.071 0.203 2 0.664 0.857 0.657 4 0.474 0.286 0.426 3 0.717 0.385 0.696 5(1) 0.507 0.173 0.432 0.244 0.467 0.191 29(1) Brooker Creek County Park BC (N=15) HEHOGD A 0.609 0.625 0.573 3 0.314 0.250 0.317 2 0.566 0.625 0.565 4 0.508 0.429 0.540 2 0.516 0.500 0.517 2 0.266 0.235 0.213 2 0.679 0.563 0.683 4 0.116 0.059 0.059 2 0.699 0.647 0.700 4 0.471 0.196 0.437 0.210 0.460 0.218 25 Fort Cooper State Park FC (N=4) HEHOGD A 0.607 0.750 0.583 3 0.428 0.500 0.417 2 0.536 0.750 0.500 2 0.780 0.500 0.625 3 0.464 0.250 0.250 2 0.464 0.250 0.250 2 0.571 1.000 0.500 2 M 0.000 1 0.857 0.500 0.708 3 0.588 0.155 0.563 0.259 0.426 0.223 20 USF Research Ecology Area EA (N=26) HEHOGD A 0.617 0.577 0.617 5 0.322 0.217 0.324 2 0.313 0.308 0.313 5 0.535 0.462 0.515 3 0.147 0.115 0.111 2 0.318 0.240 0.281 3 0.729 0.565 0.727 4 0.154 0.120 0.117 3 0.640 0.560 0.668 3 0.419 0.216 0.352 0.192 0.401 0.224 30 Continued on the next page. Table 2.1 continued.
Population and sample size (N) GP15GP19GP26GP30GP55GP61GP81GP96GP102Mean SE Total Alleles Boyd Hill State Park BH (N=24) HEHOGD A 0.621 0.625 0.61 4 0.231 0.208 0.194 3 0.425 0.333 0.435 4 0.602 0.292 0.547 3 0.337 0.417 0.325 2 0.280 0.292 0.254 2 0.645 0.542 0.625 4 0.269 0.083 0.231 3 0.598 0.667 0.597 4 0.445 0.171 0.384 0.195 0.424 0.176 29 Cayo Costa State Park CC (N=21) HEHOGD A 0.528 0.579 0.526 4 0.354 0.286 0.317 2 0.383 0.316 0.342 2 0.565 0.176 0.518 2 0.562 0.444 0.510 2 0.408 0.429 0.395 2 0.481 0.550 0.479 2 0.138 0.095 0.093 5 0.377 0.158 0.333 4 0.422 0.134 0.337 0.174 0.390 0.140 22 Highlands Hammock State Park HH (N=19) HEHOGD A 0.611 0.600 0.579 4 0.522 0.412 0.489 2 0.191 0.133 0.129 2 0.529 0.200 0.476 3 0.536 0.333 0.514 2 0.371 0.474 0.368 2 0.668 0.667 0.641 3 0.563 0.632 0.509 2 0.563 0.263 0.570 3 0.506 0.143 0.413 0.195 0.475 0.151 23 Everglades National Park EV (N=2) HEHOGD A 0.533 0.500 0.500 2(1) 1.00 0.00 1.00 2 0.833 0.500 0.500 2 0.833 0.500 0.500 2 0.833 0.500 0.500 2 0.833 0.500 0.500 2 M 0.000 1 M 0.000 1 M 0.000 1 0.810 0.152 0.417 0.204 0.389 0.333 15(1) Lake Louisa State Park HEHOGD A 0.640 0.611 0.641 5 0.522 0.529 0.485 2 0.321 0.294 0.27 4 0.510 0.444 0.490 2 0.219 0.059 0.169 2 0.400 0.222 0.359 2 0.724 0.588 0.689 3 0.354 0.167 0.300 5(1) 0.583 0.353 0.590 3 0.475 0.163 0.363 0.194 0.445 0.178 28(1) Continued on the next page. Table 2.1 continued.
Population and sample size (N) GP15GP19GP26GP30GP55GP61GP81GP96GP102Mean SE Total Alleles Wekiwa Springs State Park WS (N=22) HEHOGD A 0.601 0.636 0.573 4 0.633 0.619 0.590 3 0.336 0.286 0.337 4 0.498 0.400 0.501 3 0.174 0.045 0.132 2 0.285 0.182 0.242 2 0.661 0.476 0.665 4 0.174 0.136 0.132 3 0.630 0.333 0.635 4 0.444 0.202 0.346 0.207 0.423 0.215 29 Jonathan Dickinson State Park JD (N=21) HEHOGD A 0.628 0.500 0.603 5(2) 0.541 0.600 0.489 2 0.422 0.350 0.384 4 0.541 0.389 0.539 5(2) 0.152 0.105 0.102 2 0.777 0.670 0.752 5(1) 0.715 0.619 0.718 4(1) 0.383 0.095* 0.349 5 0.808 0.762 0.794 8(1) 0.552 0.210 0.454 0.239 0.526 0.223 40(7) Mean Total (n=279) HESE HOSE GD SE A A 0.676 0.116 0.586 0.236 0.653 0.116 4.6 19 0.453 0.197 0.393 0.262 0.444 0.208 2.45 3 0.531 0.183 0.486 0.211 0.488 0.172 3.4 6 0.639 0.124 0.427 0.170 0.583 0.106 4.2 10 0.377 0.227 0.235 0.174 0.222 0.189 1.75 2 0.474 0.170 0.368 0.158 0.399 0.161 2.6 7 0.679 0.112 0.608 0.169 0.621 0.189 3.4 7 0.438 0.30 0.341 0.241 0.344 0.242 3.35 8 0.639 0.141 0.394 0.176 0.581 0.195 3.65 15 0.556 0.107 0.433 0.086 0.482 0.068 77(23) Table 2.1 continued.
TABLE 2.2: Linkage disquilibrium P-values below 0.05 for locus-by-locus comparisons for each population in Genepop with 1000 dememorization steps, 100 batches with 1000 iterations per batch. Of the 548 comparisons only one (*) was significant at the P 0.1 level after sequential Bonferroni correction. All the populations in red are located in the Mid-Florida Assemblage. Populat ion abbreviations are as in Table 2.1.GP15GP19GP26GP30GP55GP61GP81GP96GP102 GP15 GP19 0.016 LL GP26 0.000 BH* 0.043 BC0.047 LL GP30 0.009 JC GP55 0.001 HH 0.033 WS0.047 LL GP61 0.025 BH 0.027 CC 0.001 JD 0.002 JCGP81 0.013 BH 0.048 RA 0.014 WS 0.012 BH 0.002 MB 0.015 OM 0.029 CC 0.036 EA 0.025 WS 0.022 WS GP96 0.022 BH 0.004 BH0.009 EA0.029 BH0.015 EA GP102 0.023 EA 0.031 BS0.046 JC 0.037 EA0.016 EA 0.001 JC-
TABLE 2.3: Genetic distances among populations calculated in Arlequin. RST values by averaging variance are below diagonal; FSTvalues are above the diagonal. Sequential Bonferroni corrected P-values 0.05 are in boldJCCKBSMBISCFGBRAOMBCFCEABHCCHHEVLLWSJD JC0.2840.245 0.184 0.1930.3080.2650.2500.3410.3590.3440.3620.3450.4700.393 0.409 0.3420.3520.274 CK0.000-0.044 0.172 0.0770.211 0.1640.1030.1660.245 0.205 0.1930.2310.3600.225 0.360 0.1640.1420.232 BS0.1210.0320.170 0.0010.124 0.100 0.0420.069 0.157 0.134 0.1120.1530.229 0.1060.2000.062 0.0870.163 MB0.1630.1480.064-0.107 0.2130.1960.1800.2020.2190.1820.2320.2070.3630.278 0.330 0.2180.2280.231 IS0.1630.1290.0000.000-0.1300.0820.0510.0810.1200.0970.1220.1180.2220.1400.156 0.086 0.099 0.115 CF0.1700.0210.0000.0990.059-0.0970.160 0.1610.206 0.182 0.1950.2060.3330.240 0.3080.1720.183 0.212 GB 0.255 0.2210.1430.2180.1110.073-0.019 0.151 0.1400.171 0.1610.1000.3400.244 0.210 0.1490.1670.202 RA 0.161 0.1000.039 0.158 0.0780.0000.0150.0920.1070.1360.1070.1030.2720.168 0.256 0.0870.1110.160 OM 0.3430.293 0.0880.1230.0200.1660.255 0.172 -0.0520.0410.0170.029 0.143 0.0630.1270.0000.029 0.139 BC 0.3490.271 0.0650.1640.0290.159 0.2590.155 0.000-0.063 0.087 0.023 0.1420.136 0.160 0.0680.1150.183 FC0.2830.1810.0320.0810.0000.0480.1640.1120.0000.000-0.0900.069 0.2450.195 0.1240.0850.119 0.180 EA 0.4140.396 0.150 0.180 0.0590.243 0.2890.214 0.0030.0240.013-0.052 0.2280.128 0.2350.0020.024 0.170 BH 03670.311 0.085 0.191 0.0500.0000.233 0.144 0.0160.0000.0370.0260.1840.140 0.1680.044 0.0840.157 CC 0.3730.349 0.119 0.166 0.0000.1590.278 0.193 0.0140.0130.0450.0340.0100.113 0.184 0.1470.1900.223 HH 0.290 0.1920.0000.0640.0000.2300.281 0.150 0.0000.0240.0040.0300.0060.037-0.2100.067 0.1220.204 EV0.3090.2740.1440.0980.0000.2430.1280.1660.1520.2380.0980.2800.2530.2190.236-0.1580.2580.166 LL 0.3730.349 0.117 0.155 0.0220.2190.258 0.185 0.0000.0060.0000.0180.0060.0070.0010.222-0.009 0.135 WS 0.4340.415 0.197 0.247 0.1380.2640.302 0.230 0.0560.0470.0650.0160.0430.0610.1190.3670.0270.139 JD 0.4890.4740.3000.333 0.2410.304 0.2550.2540.1710.175 0.283 0.1720.2070.1600.290 0.262 0.1660.116
Tonia S. Schwartz Chapter 2 67 TABLE 2.4: Genetic distances among assemblages calculated in Arlequin. Assemblage abbreviations are as in Figure 2.2 unless indicated otherwise. NW = northwest assemblage (JC), CK = Cedar Key Scrub Preserve, NT = northern assemblage (MB), NC = north-central assemblage (BS), NE = northeast assemblage, MF = mid-Florida assemblage, SE = southeastern assemblage (JD). RST values estimated by averaging variance are below diagonal; FST values are above the diagonal. Sequential Bonferroni corrected P-values less than 0.05 are in bold NW CKNTNCNEMFSE NW 0.2790.1770.2450.2390.3440.269 CK 0.0000.1630.0440.1100.1870.227 NT 0.112 0.119 0.1700.1700.2270.230 NC 0.0850.0620.0480.0560.1040.161 NE0.1760.1290.166 0.0520.1100.165 MF0.4780.4430.2410.1560.252 0.142 SE0.4640.4840.3450.31102130.183
Tonia S. Schwartz Chapter 2 68 TABLE 2.5: Individual tortoises identified as migrants using Structure. Original population is where the sample was collected with the probability that the tortoise originated in that population is in parenthesis. Assigned population are the populations that the tortoise was assigned to with relatively high probabilities.TortoiseOriginal population (probability) Assigned population (probability) GPO-146 JD (0.6%)BH (48%)HH (20%) GPO-199 CK (9%)JD (23%)EA (19%) GPO-068 WS (13%)BC (71%) GPO-193 RA (38%)BH (52%)
Tonia S. SchwartzChapter 2 69 FIGURE 2.1 : Locations sampled in this study overlaying the three genetic assemblages found by Osentoski and Lamb (1995) using RFLPs on mtDNA. The gray shape represents the western assemblage, the striped shape represents the Brooksville Ridge assemblage, and the rest of the area in white represents the eastern assemblage. JC BS GB RA CK MB OM B WS LL E B CC HH JD FC EVwestern assemblage Brooksville Ridge assemblage eastern assemblage BC BH WA EA IS CF
Tonia S. SchwartzChapter 2 70 FIGURE 2.2: Groupings according to AMOVA based on RST and FST values. Each colored circle represents a genetic assemblage. The locations in the black squares were equally likely of belonging to a number of different groupings. JC BS GB CF RA CKMB OM BC FC WS LL EA BH CC HH JD EV IS Assemblages Northwestern Northern Northcentral Northeastern Mid-Florida Southeastern
Tonia S. SchwartzChapter 3 71CHAPTER 3: USING MICROSATELLITE DATA ALONG WITH GEOLOGICAL, CLIMATIC, AND FOSSIL RECORDS TO INFER MOVEMENTS OF THE GOPHERTORTOISE IN PLEISTOCENE FLORIDAINTRODUCTIONFrom the first emergence of the Florida peninsula in the mid-late Miocene (Khudoley and Meyerhoff 1971) until the last glacial event in the late Pleistocene (Muhs et al. 2002) the landscape, connectivity, and the climate of the southeastern United States has varied drastically because of fluctuating sea levels, uplifts, erosion, and weather patterns (Graham 1964; Haq et al. 1987; Lambert and Holling 1998; Murray 1961; Riggs 1983; Vail and Hardenbol 1979). Thus the historical geology and climate of this region has had a defining influence on the biogeography of its flora and fauna. Through the Miocene, Pliocene and Pleistocene the rising sea levels (up to 120 m) during interglacial periods caused the sandy ridges of the Florida peninsula to become a series of islands. This geographic isolation led to population isolation and the evolution of species that are endemic to particular ridges (Christman and Judd 1990; Clark et al. 1999; Deyrup 1996; Huck et al. 1989). Subsequent drops in sea level during glacial events would expose the Florida platform allowing previously disjunct populations to intermingle if the climate and habitat were suitable. A number of studies on species ranging from marine invertebrates to large terrestrial mammals have investigated the effects of these changes on extinction, speciation, hybridization, and population subdivision (Anderson and Peck 1994; Avise and Walker 1998; Avise et al. 1998; Daley 2002; Ellsworth et al. 1994; Lambert and Holling 1998; Murray 2001; Peck and Howden 1985; Swift et al. 1986).
Tonia S. SchwartzChapter 3 72 The gopher tortoise ( Gopherus polyphemus ) has been extant since the Oligocene (Auffenberg 1974). Although the gopher tortoise historically had a much larger range as indicated by fossils found in southern Canada down through northern Mexico (Auffenberg 1962; Auffenberg 1974; Blair 1958; Brattstrom 1953; Oelrich 1957), they currently occupy a relatively small region in the southeastern United States. The fossil record indicates the tortoise was present in parts of Florida during the Pliocene and Pleistocene (Hay 1930; Holman 1958; Holman 1959). Thus the gopher tortoise and its distribution have undoubtedly been subjected to and influenced by past geological and climactic changes. A previous study on gopher tortoise population subdivision using RFLP analysis of four mitochondrial DNA (mtDNA) regions (12S/16S, ND2/COI, ND5/ND6, CYTb/DL), identified three major phylogeographic assemblages (eastern, western, and Brooksville ridge area: Osentoski and Lamb 1995) (Figure 2.1). Testudines are thought to have relatively slowly evolving mtDNA that may not completely reveal the historical subdivision experienced within and among genetic assemblages (Avise et al. 1992). Nuclear microsatellite loci are relatively fast evolving and are biparentally inherited. These markers would be useful to further elucidate the historical colonization and dispersal patterns of the gopher tortoise. The purpose of this chapter is to evaluate similarities and differences in the patterns of dispersal and historical biogeography inferred from microsatellites and from RFLPS on mtDNA (Osentoski and Lamb 1995). In addition, I attempt to use these genetic data along with the historical geological, climactic, and fossil records to identify gopher tortoise refugia and dispersal patterns across Florida.MATERIALS AND METHODSCollection of the genetic data used in this chapter is described in the Materials and Methods in Chapter 2. Only the 15 populations with more than eight individuals were used for the analyses in this chapter (Table 3.1). RST estimates of population subdivision,
Tonia S. SchwartzChapter 3 73 and estimates of genetic distance ( )2 (Goldstein et al. 1995; Nei 1995; Slatkin 1995) were calculate in Rst Calc using 1000 permutations and 1000 bootstraps. The relationship among the populations were determined by using the pairwise RST and ( )2 estimates to create Neighbor-Joining dendrograms in Phylip (Felsenstein 1993). These resulting dendrograms were used to define genetic assemblages. Isolation-by-distance was tested by correlating pairwise geographic verse genetic distances using the program Mantel (Leidloff 1999). Fossil, geological, and climatic data were summarized from the literature to identify historical ridges that had the potential to serve as tortoise refugia. The pattern of biogeographic subdivisions based on the microsatellite and mtDNA were then overlaid on the maps of potential refugia.RESULTSOsentoski and Lamb (1995) found three genetic assemblages of gopher tortoises using mtDNA. The microsatellite data present here complements the mtDNA study by further resolving two of their defined genetic assemblages (Brooksville Ridge and eastern assemblages). Because of sampling restrictions I am unable to evaluate their third assemblage (western assemblage: Figure 2.1 and 3.1). Although some pairwise population estimates indicated panmixia (i.e. RST = 0 (between WS and EA, and between LL and OM), many of the populations showed substantial subdivision (i.e. RST = 0.374 between JC and CC: Table 3.2). The NeighborJoining dendrograms based on RST and ( )2 values identified four major assemblages. These assemblages will be referred to as the microsatellite-based west coast, central, southeastern, and northern assemblages (Figure 3.1). The microsatellite-based west coast assemblage contains two groupings. One of these is spatially similar to the southern Brooksville Ridge identified with the mtDNA (thus for simplicity it will also be referred to as the Brooksville Ridge group). The second group in the western assemblage was the southern group that the mtDNA data had placed in the eastern assemblage. The three other microsatellite-based assemblages fall within the mtDNA defined eastern assemblage. The northern assemblage has three groups: Georgia, a loosely grouped
Tonia S. SchwartzChapter 3 74 northwest, and a north-central group (Figure 3.1). The mantel test indicated that the populations are isolated-by-distance (P<0.01, r=0.545).DISCUSSIONSimilar to many other southeastern endemic species with western sister species, the gopher tortoise likely colonized the east via the Gulf Coast Corridor that provided an arid migration route from Texas to the east coast during glacial periods Osentoski and Lamb (1995) estimated the split between their mtDNA western and eastern assemblages in the Florida panhandle, east of the Apalachicola river boundary, to date back to the early Pleistocene (1.3 mya). A similar subdivision has been reported in a number of species including pocket gophers (Avise et al. 1979) and the white-tailed deer (Ellsworth et al. 1994). The genetic break occurring ~1.3 mya roughly corresponds with one of the interglacial periods that would have resulted in the peninsula of Florida being largely underwater except for a few ridges. This study focuses on further resolving two of these larger assemblages defined by the mtDNA (eastern and Brooksville Ridge assemblages), thus the timing of events for this study is the later half of the Pleistocene. Gopher tortoise adults are hardy but require specific habitat conditions for reproduction and health. In addition, the gopher tortoises are not capable of especially long distance travel. Therefore, the colonization and dispersal of the gopher tortoise during the Pleistocene would have been guided by the sea levels and further limited by availability of suitable habitat. The repeated rise and fall in sea level during the Pleistocene resulted in remnant coastal dunes that were inhabited by many geographically restricted species. These ridges include Lake Wales Ridge (interchangeable with Haines City Ridge for the purpose of this chapter), the Southern Atlantic Coast Ridge, Mt. Dora Ridge, and Southern Brooksville Ridge (Figure 3.1: Jackson 1973; Webb 1990; Winker and Howard 1977). As the tortoises colonized the peninsula during the Pleistocene, these ridges likely provided the only scrub-like habitat
Tonia S. SchwartzChapter 3 75 suitable for their survival during the interglacial periods occurring in the later part of the Pleistocene (Alt 1974; Hoyt 1969; Pirkle and Yoho 1970; White 1970) The microsatellites data indicate that the Lake Wales Ridge, the Brooksville Ridge, the Southern Atlantic Coast Ridge, and the Mt. Dora Ridge likely were gopher tortoise refugia caused by the high sea-levels during interglacial periods, which resulted in the four genetic assemblages seen in the dendrogram in Figures 3.2. The last interglacial period (Wisconsinean) was estimated to have occurred from 136,000 years ago (ya) to 115,000 ya (Muhs et al. 2002). While the temperatures were warmer than present during that time, the water table was elevated (Muhs et al. 2002) causing much of the available land to be wetlands and marsh habitat unsuitable for gopher tortoises. Based on pollen records, the northern edge of Florida was covered with boreal forests that extended through Georgia and confined sand pine to the mid-Florida region (Deevey 1949; Potzger and Tharp 1954). The sand pine is a tree endemic to scrub habitat that also is suitable for gopher tortoises. Thus the climate conditions during the last interglacial period may have forced the tortoise populations into the southern ends of ridges, which likely provided the only suitable gopher tortoise climate and habitat. Jonathan Dickenson showed high levels of divergence from other populations and was located on one of the more recent ridges that would have been exposed during the Pleistocene, the Southern Atlantic Coast Ridge (Figure 3.2). Furthermore, the Jonathan Dickenson tortoise population contained a number of private alleles, (see Chapter 2) which indicate that Jonathan Dickenson has been isolated for a considerable amount of time. Jonathan Dickenson also was the most genetically diverse population sampled (see Chapter 2). Interestingly, these same patterns of high levels of genetic divergence and high genetic diversity was also seen in scrub lizard ( Sceloperus woodi ) populations on the Southern Atlantic Coast Ridge (Clark et al. 1999).
Tonia S. SchwartzChapter 3 76 The sea level and water table dropped between 115,000 ya and the glacial maximum17,000 ya thereby causing the environment to became more arid and temperatures colder than present (Muhs et al. 2002). Fossil records suggest this was a time of mass extinction of mammals and large tortoises (Lambert and Holling 1998). However, the gopher tortoises survival during this cold period is attributed to its ability to build burrows that would have protected it from extreme cold (Auffenberg 1974). As a result of the cold climate at this time, the tortoises probably didnt move any farther north as the land became available, but instead moved laterally to share genes with other ridges and southward to colonize newly available habitat. The dendrogram in Figure 3.2 indicates that tortoise populations in the southeastern part of Florida were most closely related to tortoises from the Southern Brooksville Ridge. These areas were likely colonized after the last drop in sea level when the land became more arid. The now island of Cayo Costa would have been continuous with the rest of south Florida at that time and only within the past 17,000 yrs became isolated as the sea level began to rise again to its present level. As a result of the warming temperatures, dry climate, and low sea level the tortoises also were able to colonize northern Florida and southern Georgia. The tortoise populations is this area are most closely related to tortoises populations found on Mt. Dora Ridge. The highly significant isolation-by-distance determined by the mantel test, which is indicative of a stepping-stone model, indicates the tortoises steadily migrated north up to the northwest portion of north Florida and finally into southern Georgia. A 8,000 yr old gopher tortoise fossil found in Levy County, Florida indicates tortoises were present in the Cedar Key area during this time (Holtman 1978). In conclusion, the microsatellite data were able to provide more resolution to the framework biogeographic patterns that were determined by the mtDNA. In two of the mtDNA-defined assemblages, the microsatellites were able to define four major assemblages (corresponding to four ridges). These areas likely had varying levels of gene flow over time, resulting from changes in sea level and the water table that may have fragmented and reconnected suitable gopher tortoise habitat. The overall dispersal
Tonia S. SchwartzChapter 3 77 pattern was isolation-by-distance. From the combined data is evident that the historical distribution of the gopher tortoise was restricted not only due to sea levels and the water table, but also the climate and the temperature.
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Tonia S. SchwartzChapter 3 79 Avise, J. C., and D. Walker, 1998 Pleistocene phylogeographic effects on avian populations and the speciation process. Proceedings of the Royal Society of London Series B-Biological Sciences 265: 457-463. Avise, J. C., D. Walker and G. C. Johns, 1998 Speciation durations and Pleistocene effects on vertebrate phylogeography. Proceedings of the Royal Society of London Series B-Biological Sciences 265: 1707-1712. Blair, F. W., 1958 Distributional patterns of vertebrates in the Southern United States in relation to past and present environments American Association for the Advancement of Science. Brattstrom, B., 1953 The amphibians and reptiles from Rancho La Brea. Transactions of the San Diego Society of Natural History 11: 365-392, figs. 361-364. Christman, S. P., and W. S. Judd, 1990 Notes on plants endemic to Florida scrub. Florida Scientist 47: 52-73. Clark, A. M., B. W. Bowen and L. C. Branch, 1999 Effects of natural habitat fragmentation on an endemic scrub lizard ( Sceloporus woodi ): an historical perspective based on a mitochondrial DNA gene genealogy. Molecular Ecology 8: 1093-1104. Cooke, C. W., 1939 Scenery of Florida, interpreted by a geologist, pp. 118 in Florida Geological Survey Bulletin No. 17 Daley, G. M., 2002 Creating a paleoecological framework for evolutionary and paleoecological studies: An example from the Fort Thompson Formation (Pleistocene) of Florida. Palaios 17: 419-434.
Tonia S. SchwartzChapter 3 80 Deevey, E. S., 1949 Biogeography of the Pleistocene. Bulletin of the Geological Society of America 60: 1315-1416. Deyrup, M., 1996 Two new grasshoppers from relict uplands of Florida (Orthopter: acrididae). Transactions of the American Entomology Society 122: 199-211. Ellsworth, D. L., R. L. Honeycutt, N. J. Silvy, J. W. Bickham and W. D. Klimstra, 1994 Historical Biogeography and Contemporary Patterns of Mitochondrial-DNA Variation in White-Tailed Deer from the Southeastern United-States. Evolution 48: 122-136. Felsenstein, J., 1993 PHYLIP (Phylogeny Inference Package) version 3.5C. Distributed by author. Department of Genetics, University of Washington, Seattle. Goldstein, E. B., A. R. Linares, L. L. Cavalli-Sforza and M. W. Feldman, 1995 Genetic absolute dating based on microsatellites and the origin of modern humans. Proceedings of the National Academy of Sciences of the United States of America 92: 6723-6727. Graham, A., 1964 Origin and evolution of the biota of southeastern North America: Evidence from the fossil plant record. Evolution 18: 571-585. Haq, B. U., J. Hardenbol and P. R. Vail, 1987 Chronology of fluctuation sea levels since the Triassic. Science 235: 1156-1167. Hay, O. P., 1930 Second bibliography and catalog of fossil Vertebrata of North America Carnegie Institute, Washington. Holman, J. A., 1958 The Pleistocene herpetofauna of the Saber-Tooth Cave, Citrus County, Florida. Copeia 1959: 96-102.
Tonia S. SchwartzChapter 3 81 Holman, J. A., 1959 Amphibians and reptiles from the Pleistocene (Illinoisan) of Williston, Florida. Copeia 1959: 96-102. Holtman, J. A., 1978 The late Pleistocene herpetofauna of DevilÂ’s Den sinkhole, Levy County, Florida. Herpetologica 34: 228-237. Hoyt, J. H., 1969 Late Cenozoic structural movements, northern Florida. Gulf Coast Association of Geological Societies Transactions? 19: 1-9. Huck, R. B., W. S. Judd and W. W. M., 1989 A new Dicerandra (Labiatae) from the Lake Wales Ridge of Florida, with a cladistic analysis and discussion of endemism. Systematic Botany 14: 197-213. Jackson, J. F., 1973 Distribution and population phenetics of the Florida scrub lizard, Sceloporus woodi Copeia 4: 746-761. Khudoley, K. M., and A. A. Meyerhoff, 1971 Paleogeography and geological history of Greater Antilles. Geological Society of America Mem. 125: XV + 199. Lambert, W. D., and C. S. Holling, 1998 Causes of ecosystem transformation at the end of the Pleistocene: Evidence from mammal body-mass distributions. Ecosystems 1: 157-175. Leidloff, A., 1999 Mantel nonparametric test calculator, pp., Brisbane, Australia. Muhs, D. R., K. R. Simmons and B. Steinke, 2002 Timing and warmth of the Last Interglacial period: new U-series evidence from Hawaii and Bermuda and a new fossil compilation for North America. Quaternary Science Reviews 21: 13551383. Murray, A. M., 2001 The fossil record and biogeography of the Cichlidae (Actinopterygii : Labroidei). Biological Journal of the Linnean Society 74: 517-532.
Tonia S. SchwartzChapter 3 82 Murray, G. E., 1961 Geology of the Atlantic and Gulf coastal province of North America HarperÂ’s Geoscience Series, Harper and Brothers, New York. Nei, M., 1995 Genetic support for the out-of-Africa theory of human evolution. Proceedings of the National Academy of Sciences of the United States of America 92: 6720-6722. Oelrich, T. M., 1957 The status of the Upper Pliocene turtle, Testudo turgida Cope. Journal of Paleontology 31: 228-241, figs221-226. Osentoski, M. F., and T. Lamb, 1995 Intraspecific phylogeography of the gopher tortoise, Gopherus polyphemus : RFLP analysis of amplified mtDNA segments. Molecular Ecology 4: 709-718. Peck, S. B., and H. F. Howden, 1985 Biogeography of Scavenging Scarab Beetles in the Florida Keys Post-Pleisotocene Land-Bridge Islands. Canadian Journal of Zoology-Revue Canadienne De Zoologie 63: 2730-2737. Pirkle, E. C., and W. H. Yoho, 1970 The heavy mineral ore body of Trail Ridge, Florida. Econ. Geology 65: 17-30. Potzger, J. E., and B. C. Tharp, 1954 Pollen study of two bogs in Texas. Ecology 35: 462-467. Riggs, S. R., 1983 Paleoceanographic model of Neogene phosphorite deposition. Science 223: 123-131. Schmidt, W., 1997 Geomorphology and Physiography of Florida, pp. 1-12 in The Geology of Florida edited by A. F. Randazzo and D. S. Jones. University Press of Florida, Gainesville.
Tonia S. SchwartzChapter 3 83 Slatkin, M., 1995 A measure of population subdivision based on microsatellite allele frequencies. Genetics 139: 457-462. Swift, C. C., C. R. Gilbert, S. A. Bortone, G. H. Burgess and R. W. Yerger, 1986 Zoogeography of the freshwater fishes of the southeastern Unites States: Savannah River to Lake Pontchartrain, pp. 213-266 in The zoogeography of North American freshwater fishes edited by C. H. Hocutt and E. O. Wiley. John Wiley & Sons, New York. Vail, P. R., and J. Hardenbol, 1979 Sea level changes during the Tertiary. Oceanus 22: 71-79. Webb, S. D., 1990 Historical biogeography, pp. 70-102 in Ecosystems of Florida edited by R. L. Myers and J. J. Ewel. University of Central Florida Press, Orlando, Florida. White, W. A., 1970 The geomorphology of the Florida peninsula, pp. 164. Florida Department of Natural Resources Geological Bulletin. Winker, C. D., and J. D. Howard, 1977 Correlation of tectonically deformed shorelines on the southern Atlantic Coastal Plain. Geology 5: 123-127.
Tonia S. SchwartzChapter 3 84 TABLE 3.1 : Sampling locations and their two letter abbreviations that are used throughout the chapter. LocationAbbreviation N Jones Research Center, GeorgiaJC20 Cedar Key Scrub State Preserve, FloridaCK8 Big Shoals Wildlife Park, FloridaBS11 Moody Airforce Base, GeorgiaMB14 Gold Head Branch State Park, FloridaGB9 Ray Aston Tortoise Preserve, FloridaRA19 Oldenburg Mitigation Park, FloridaOM14 Brooker Creek County Park, FloridaBC17 USF Ecology Area, FloridaEA25 Boyd Hill State Park, FloridaBH24 Cayo Costa State Park, FloridaCC21 Highlands Hammock State Park, FloridaHH16 Lake Louisa State Park, FloridaLL17 Wekiva Springs State Park, FloridaWS21 Jonathan Dickenson State Park, FloridaJD20 Total256
TABLE 3.2: Population distances ( )2 estimated in Rst Calc are above the diagonal, and RST estimates calculated in Rst Calc below the diagonal. Bold type indicates RST values that were significant at sequential Bonferroni corrected P 0.05.JCCKBSMBISCFGBRAOMBCFCEABHCCHHEVLLWSJD JC -0.2140.3820.2760.5030.6520.7910.5940.7010.9400.8220.5620.7321.2930.8781.2030.6670.7021.009 CK 0.045-0.1140.3750.4270.5030.8030.3740.3400.5680.4150.3190.4510.8460.5840.8800.3460.3650.582 BS 0.1180.004-0.4180.2440.4770.5350.1800.0860.2660.1740.1010.1670.5130.3620.4270.0850.1360.260 MB 0.0770.1160.147-0.2100.5470.9640.7940.4940.7980.8460.3810.5170.9080.63110.280.4750.5140.821 IS 0.1120.0910.0310.018-0.5600.6690.5200.2320.3580.5980.1930.1910.3190.3560.4880.1820.2710.498 CF 0.1340.0940.0970.1160.083-0.5250.4830.5940.6540.6850.4100.4341.1441.1411.1660.5510.4610.594 GB 0.1800.1940.1350.2360.1310.075-0.1650.6330.6280.7000.5380.5031.0520.9040.8140.5900.5760.498 RA0.172 0.1120.049 0.246 0.1260.0940.014-0.2840.3930.3170.3040.2900.7960.5760.5400.2990.3240.299 OM0.239 0.1280.012 0.200 0.0370.1640.1810.110-0.1660.1510.0680.0810.3720.2280.3020.0320.0950.174 BC0.3020.220 0.113 0.300 0.0940.1750.180 0.155 0.081-0.2350.2100.1090.2790.3120.3980.1800.2170.309 FC 0.2490.1280.0240.2860.1560.1590.1770.0920.0230.079-0.1930.2810.7160.5250.3980.1860.2150.196 EA0.217 0.1380.033 0.177 0.0280.1010.168 0.135 0.028 0.132 0.069-0.0810.4660.3950.4860.0260.0230.148 BH0.254 0.1830.067 0.216 0.0240.1020.147 0.119 0.0320.0530.1130.047-0.3760.3500.4320.0790.1130.263 CC0.3740.3050.2170.326 0.0790.304 0.2840.2830.1900.146 0.294 0.2650.202 -0.4260.4870.3760.4260.535 HH0.271 0.2100.144 0.232 0.0850.2900.240 0.205 0.105 0.149 0.206 0.2120.1740.144 -0.5080.3500.4210.529 EV 0.3460.2740.1400.3430.1030.2940.2060.1730.0970.1560.1100.2370.1790.1940.194-0.4320.5700.490 LL0.249 0.1490.020 0.215 0.0200.1540.183 0.131 0.0000.1090.0610.0020.042 0.1970.171 0.152-0.0360.136 WS0.252 0.1510.051 0.221 0.0630.1160.173 0.137 0.043 0.126 0.0760.0000.066 0.2330.213 0.2640.007-0.099 JD0.2960.2050.0970.281 0.1350.1420.130 0.1060.0740.143 0.0470.076 0.1280.2340.217 0.1800.0660.040-
Tonia S. SchwartzChapter 3 86 FIGURE 3.1 : The genetic assemblages identified by the Neighbor-Joining dendrogram based on pairwise RST, and the corresponding sand ridges that were present during the Pleistocene. The black shapes are historical ridges (modified from Cooke 1939; Schmidt 1997). The gray shapes are two of the genetic assemblages identified with the mtDNA (Osentoski and Lamb 1995). The colored shapes are genetic assemblages identified through microsatellites that could have existed on the ridges during interglacial periods. The colors correspond to the colored bars on the dendrogram. LL EA GB RA OM BH BC HH CC WS JD BS CK JC MB northern assemblage on Mt. Dora Ridge east coast assemblage on Brooksville Ridge central assemblage Lake Wales Ridge Jonathan Dickenson on Atlantic Coast Ridge JC BS GB RA CK MB OM BC WS LL EA BH CC HH JD
Tonia S. SchwartzChapter 3 87 JC BS GB RA CK MB OM BC WS LL EA BH CC HH JD FIGURE 3.2 : The colored shapes on the map represent highest ridges in Florida during the Pleistocene (modified from Cooke 1939; Schmidt 1997). Red represents Lake Wales Ridge, Orange represents Brooksville Ridge, Purple represents Mt. Dora Ridge, and Pink represents Atlantic Costal Ridge. The arrows represent the dispersal patterns from the ridges and the colors correspond to the unrooted NJ dendrogram, which is based on pairwise RST estimates. LL EA GB RA OM BH BC HH CC WS JD BS CK JC MB east coast A assemblage on Brooksville Ridge central assemblage Lake Wales Ridge Jonathan Dickenson on Atlantic Coast Ridge
APPENDIX A PRIMERS FOR MICROSATELLITE LOCI NON-VARIABLE OR UNRELIABLE IN G. POLYPHEMUSTABLE 1: Loci that were not useful for population level analysis in G. polyphemus but may be useful in other tortoise species. Amplification conditions listed are the annealing temperature and final MgCl2 concentrations. All other PCR conditions are as described in Chapter 1 for other loci. // indicates more than 5 bp interruption.LocusRepeat Region Primer SequencesSize (bp) CharacteristicsAmplification Conditions GenBank Accession # GP2>GT40F:CATTCTTCGTGAGGAGGATGA R:CCAGTCAAATACTTTGGAGGA 315Extremely variable, stutters on Genescan (n=75) 60 C / 2.5mM AF546901 GP32CA9//CA7F:ACAACAATGTGGGAATATGTGC R:ATTTGGCATGACTGGCATTT 271Not Variable (n=17) 61 C / 2.5 mm AF546897 GP63CA7CT5-TCA -CT3-CG-CT7F:GGCCTTTGCAGAGTACAGAA R:ACTGCTGGCACTTTCTTGTG 219Not Variable (n=17) 60 C / 2.5mM AF546898 GP69>GT30F:AGAGCCAGAGGTTTGCACAT R:AAACCCAAAGGGACCACTGT 226Variable but unreliable (n=75) 65 C / 2.75mM AF546900 GP77CT10CA14F:TGGCTTCTCATGCTAGACACC R:TCCAGGGCTTTACCACAAAC 432Not Variable (n=17) 51 C / 2.5mM AF546899
APPENDIX B CHARACTERISTICS OF ALLELES AND NOTES ON SCORINGThis appendix is designed to assist researchers in the scoring of the loci developed in this project. Herein, I will depict go od, typical, and problematic Genescan results and how they may be scored. Included are examples of Genescan runs on the ABI 310 automated sequencer (capillary based). The peak morphologies are usually similar when compared to an ABI 370 (gel), but the al lele sizes are usually 2-4 bp shorter DEFINITIONS AND TIPS Allele Â— what has been determined to be the true allelic peak. Area Â— the area under the peak on the Genescan run. The area is dependent on the intensity of the fluorescence due to the concentration of that PCR product in the Genescan mix. Too much PCR product results in over fluorescence that may cause the all ele to appear up to 1.5 bp larger, and possibly multiple colors to appear under the peaks due to over-excitation of the laser. The area can be useful in deciphering stutter peaks from the true allelic peaks. bp Â— base pairs (i.e. the unit of length of the DNA fragment). Extra Peak Â— A peak resulting from the primers being unfaithful to the microsatellite locus and multiplexing PCR reactions. Th ese peaks are consistent in that they do not change in size or they change in the exact increments as the allele they coincide with Height Â— (taller, smaller) refers to the peak height on the Genescan run. Length Â— (longer, shorter) refers to the determined number of base pairs of the DNA fragment from the Genescan run, thereby defining that allele. Stutter Peak Â— the peaks immediately before the allele that has resulted from the Taq polymerase slipping during PCR. Stutter peaks are usually more intense in the larger alleles at any particular locus.
APPENDIX B (CONTINUED)GOOD RESULTSMix 1 : Extra peaks often occur at 124 bp blue, 134 bp green, and 203 bp green. Mix 2 Loci: GP15 GP30 GP55 GP26 Extra peaks Loci GP96 GP61 GP19 GP102 GP81
APPENDIX B (CONTINUED)TYPICAL AND PROBLEMATIC RESULTS: Numbers on the pictures are the allele sizes for the locus in question. LOCUSCHARACTERISTICSEXAMPLES Mix 1 GP30 A. Extra peaks due to this locus include; 169 bp, 183 bp, and 203 bp. B. Allele 210 has a large Â—2 stutter peak. C. Allele 220 is usually considerably shorter with more stutter peaks. A B C 194 210 194 220 194 220
GP15 A. The larger the alleles, the shorter and more stutter peaks they have. GP55 A. Every allele usually has a 2 bp stutter peak. B. Alleles often have extra peaks at approximately 34 bp and 66 bp. GP26 A. Alleles often have an extra peak at approximately 47 bp. A A B A 206 226 265 271 364 APPENDIX B (CONTINUED)
Mix 2 GP96 A. Every allele usually has a 2 bp stutter peak B. Alleles often have an extra peak at approximately 20 bp. A A B 364 366 147 151 APPENDIX B (CONTINUED)
GP61 A. Alleles often have an extra peak at approximately 26 bp. B. Allele 245 is often shorter, with more stutter peaks than other smaller alleles. GP19 A. This locus often has a problem with split peaks that are 1 bp different. This is likely the result of the incomplete addition of the extra A to the PCR product. A B 197 207 197 245 APPENDIX B (CONTINUED)
GP102 A. Every allele usually has a 2 bp stutter peak. B. Alleles often have an extra peak at approximately 70 bp. C. Allele 333 and 339 are usually shorter and have 2 or 3 stutter peaks. A B C 319 313 333 APPENDIX B (CONTINUED)
GP81 A. Every allele usually has a 2 bp stutter peak. A 397 409 APPENDIX B (CONTINUED)
APPENDIX C CHARACTERISTICS OF INDIVIDUAL TORTOISES SAMPLEDDNA types are coded as RBC = sample received as concentrated red blood cells, WH = sample received as whole blood. Field numbers that were given with a permanent marker while sampling are indicated by #. All other numbers are either holes in scute s (EA numbering unless otherwise noted) or number assigned by researchers providing the samples. Upper Respiratory Tract Disease (URTD), indicates a negative result, + indicates a positive result, S indicates a suspect result. For appearance, g indicate s good health. KG = weight in kg, CL=carapace length in cm, PL=plastron length in cm.Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Big Shoals Wildlife Management Area, Florida Gpo-216Summer 2001WendlandRBC1 Gpo-217Summer 2001WendlandRBC4 Gpo-218Summer 2001WendlandRBC5 Gpo-219Summer 2001WendlandRBC7 Gpo-220Summer 2001WendlandRBC8 Gpo-221Summer 2001WendlandRBC9 Gpo-226Summer 2001WendlandRBC27 Gpo-222Summer 2001WendlandRBC10 Gpo-223Summer 2001WendlandRBC11 Gpo-224Summer 2001WendlandRBC12 Gpo-225Summer 2001WendlandRBC15 Boyd Hill State Park, Florida Gpo-0096/5/00Schwartz/LeglerWB11428.627.3g Gpo-0106/5/00Schwartz/LeglerWB#132.531.1g
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-0116/5/00Schwartz/LeglerWB#227.626.7g Gpo-0126/5/00Schwartz/LeglerWB#326.324.4g-mottled shell-fungus? Gpo-0187/7/00Schwartz/LeglerWB#1529.826.9-few bubbles around eyes, bottom eyelids puffy? Gpo-0197/7/00Schwartz/LeglerWB1223.626.824.4+g Gpo-0207/7/00Schwartz/LeglerWBBH hole-96 427.225.1+Lots of ticks, puffy eyes? Gpo-0217/7/00Schwartz/LeglerWB#22.824.623.5-g Gpo-0227/12/00Schwartz/LeglerWB#35.331.228.1Sg Gpo-0237/12/00Schwartz/LeglerWB#44.227.926+g Gpo-0247/14/00Schwartz/LeglerWB#54.930.727Sg Gpo-0257/14/00Schwartz/LeglerWB#64.827.325.3Sg front right plastron piece broken off Gpo-0267/16/00Schwartz/LeglerWB#74.32629+g Gpo-0277/16/00Schwartz/LeglerWB#8427.725.2+g Gpo-0287/16/00Schwartz/LeglerWB#94.227.826+g Gpo-0297/16/00Schwartz/LeglerWB98 #10 5.430.5+g Gpo-0307/16/00Schwartz/LeglerWB#116.73331.1g Gpo-0317/16/00Schwartz/LeglerWB#123.826.825.2+g Gpo-0327/16/00Schwartz/LeglerWB#135.428.326.8+g Gpo-0367/19/00Schwartz/LeglerWB#188.8.131.52+g Gpo-0377/19/00Schwartz/LeglerWB#155.83127.7+runny nose Gpo-0387/19/00Schwartz/LeglerWB#164.328.326+runny nose Gpo-0407/28/00Schwartz/LeglerWBBH hole-99 5.328.827.5+g Gpo-0417/28/00Schwartz/LeglerWB#173.326.525.2+ Gpo-0427/28/00Schwartz/LeglerWB#185.5530.928.9+g APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-0437/28/00Schwartz/LeglerWB#19 ?4.828.226.6g Brooker Creek County Park, Florida Gpo-241Fall 2001Stiles/RiedelRBC2 Gpo-242Fall 2001Stiles/RiedelRBC3 Gpo-243Fall 2001Stiles/RiedelRBC11 Gpo-244Fall 2001Stiles/RiedelRBC13 Gpo-245Fall 2001Stiles/RiedelRBC16 Gpo-246Fall 2001Stiles/RiedelRBC17 Gpo-247Fall 2001Stiles/RiedelRBC20 Gpo-248Fall 2001Stiles/RiedelRBC22 Gpo-249Fall 2001Stiles/RiedelRBC25 Gpo-250Fall 2001Stiles/RiedelRBC28 Gpo-251Fall 2001Stiles/RiedelRBC29 Gpo-252Fall 2001Stiles/RiedelRBC30 Gpo-253Fall 2001Stiles/RiedelRBC101 Gpo-254Fall 2001Stiles/RiedelRBC105 Gpo-255Fall 2001Stiles/RiedelRBC106 Gpo-256Fall 2001Stiles/RiedelRBC107 Gpo-257Fall 2001Stiles/RiedelRBC108 Gpo-258Fall 2001Stiles/RiedelRBC116 Gpo-259Fall 2001Stiles/RiedelRBC118 Cayo Costa State Park, Florida Gpo-0984/13/01Schwartz/SmithWB#11.61918goodForgot to put SDS in buffer APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-0994/14/01and 5/11/01 Schwartz/SmithWB#24.82927.75goodcaught twice, bled for URTDs the second capture Gpo-1004/15/01 and 5/11/01 Schwartz/SmithWB#36.532.629.7goodbled for URTDs the second time caught Gpo-1014/15/01Schwartz/SmithWB#44.629.226Ok, wheezing?Forgot to put SDS in buffer Gpo-1024/15/01Schwartz/SmithWB#55.931.829.4okForgot to put SDS in buffer Gpo-1034/15/01Schwartz/SmithWB#64.328.327.2ok 5 toes on left front, nails are bent, 4th toenail on rear right is bent Forgot to put SDS in buffer Gpo-1044/15/01Schwartz/Smithpetrified skin #7petrified skin off of a skeleton Gpo-1055/14/01Schwartz/SmithWB#84.5~30.5~27.3good bottom, nuchal scute long DoesnÂ’t seem to belong to that burrow. 6% SDS in buffer Gpo-1065/15/01Schwartz/SmithWB#94.2~27.9~26.7good, shyCouldnÂ’t find vein, tried for 1/2 hour, got a few drops of blood. 6% SDS in buffer Gpo-1075/15/01Schwartz/SmithWB#104.5~33~28.6good, very active dents on carapace: 2nd row, 3rd scut back on right side, cdntal 2 & 3 scutes 6% SDS in buffer Gpo-1085/15/01Schwartz/SmithWB#115~29.2~25.4Good very large cental plastron 6% SDS in buffer APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-1095/15/01Schwartz/SmithWB#125~30.5~27.9Good6% SDS in buffer Gpo-1105/15/01Schwartz/SmithWB#135.5~30.5~27.9Good6% SDS in buffer Gpo-1115/15/01Schwartz/SmithWB#145.2~31.7 5 ~28.6Good6% SDS in buffer Gpo-1125/15/01Schwartz/SmithWB#154.8~30.5~27.3Good6% SDS in buffer Gpo-1135/15/01Schwartz/SmithWB#165.2~33~29.2left eye clouded (blind?). Eyelid swollen. Looks very old. Nose on skin rubbed off. 6% SDS in buffer Gpo-1145/16/01Schwartz/SmithWB#175.1~31.1~27.9wheezing, not energetic. Eyes goobery. Due to early morning cold temp? 6% SDS in buffer Gpo-1155/16/01Schwartz/SmithWB#185~30.5~26.3Good Beautiful green eyes! 6% SDS in buffer Gpo-1165/16/01Schwartz/SmithWB#195.4~31.1~28.6rt. Eye goobery, otherwise good Marks on back 6% SDS in buffer Gpo-1175/16/01Schwartz/SmithWB#205.6~31.1~27.9good6% SDS in buffer Gpo-1185/16/01Schwartz/SmithWB#214.9~29.2~26.7Good6% SDS in buffer Cecil Field/Branan Field Mitigation Park, Florida Gpo-234Summer 2001WendlandRBC23 Gpo-235Summer 2001WendlandRBC34 Gpo-236Summer 2001WendlandRBC38 Gpo-237Summer 2001WendlandRBC66 Cedar Key State Scrub Preserve, Florida Gpo-16807/25/01Schwartz/BrockmanWB#1NA24.924Healthy Gpo-16907/25/01Schwartz/BrockmanWB#2NA25.923.5Healthy APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-17007/25/01Schwartz/BrockmanWB#3NA26.823.3Healthy Gular scute broken/ground down, plastron chipped up Gpo-17107/26/01Schwartz/BrockmanWB#4NA28.225.1HealthyPictures taken. Gpo-17207/26/01Schwartz/BrockmanWB#5NA2925Healthy Cut Eye lid; possilby from thorn. Seems to be healing Gpo-1998/11/01Schwartz/WarnerWB#6NA26.324.2Good Health chipped up shell; flaking off. Gpo-2008/11/01Schwartz/WarnerWB#7NA24.221.9Wheezing Gpo-2018/12/01Schwartz/WarnerWB#8NA28.825.5 Dr. McCoyDr. McCoy Gpo-00110/17/99RBCSick tortoise in Dr. McCoyÂ’s LabMade library from USF Ecology Area, Florida Gpo-1195/18/01Schwartz/LeglerRBC#12 Gpo-00210/27/99Schwartz/LeglerRBC136by fence Gpo-00311/3/99Schwartz/LeglerRBC77, SCAR ON BACK Gpo-00411/11/99Schwartz/LeglerRBC403403,SCAR ON BACK Gpo-0055/3/00Schwartz/LeglerRBCUN, SCAR ON BACK Gpo-0066/2/00Schwartz/LeglerRBC#1 100? 23g Gpo-0076/2/00Schwartz/LeglerRBC#227.5g Gpo-0086/2/00Schwartz/LeglerRBC#3? Un?27.5g Gpo-0136/12/00Schwartz/LeglerRBC Gpo-0146/11/00Schwartz/LeglerRBC#32.82220.7-g APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-0156/13/00Schwartz/LeglerRBC37184.108.40.206-g Gpo-0166/14/00Schwartz/LeglerRBC3433.9, 3.6 on 727-00 26.825.3+g Gpo-0177/5/00Schwartz/LeglerRBC308528.826.9+g Gpo-0337/17/00Schwartz/LeglerRBC#4 10(BH) 26.124.8+g Gpo-0347/17/00Schwartz/LeglerRBC3524.127.426+g Gpo-0357/19/00Schwartz/LeglerRBC#53.927.724.4+g Gpo-0397/20/00Schwartz/LeglerRBC4412.82522.3-g Gpo-0447/31/00Schwartz/LeglerRBC#6+ Gpo-0457/31/00Schwartz/LeglerRBC43323.521.5gJuvinile, No ELISA, NoHormones Gpo-0468/1/00Schwartz/LeglerRBC4622.924.922.8-g Gpo-0478/5/00Schwartz/LeglerRBC1366.532.530.1Sg Gpo-09211/5/00Schwartz/LeglerRBC#7325.724-gBled twice for hormone stuff Gpo-09311/5/00Schwartz/LeglerRBC#82.421.924-gBled twice for hormone stuff Gpo-09411/5/00Schwartz/LeglerRBC#9427.124.9+gBled twice for hormone stuff Gpo-09511/5/00Schwartz/LeglerRBC#10 346 3.726.725.4SBled twice for hormone stuff Gpo-09611/5/00Schwartz/LeglerRBC Gpo-09711/5/00Schwartz/LeglerRBC Cape Sable, Everglades National Park, Florida Gpo-26011/30/01Schwartz/Smith/HayesWB11 paper towel Clear eyes Healthypit trapped APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-26112/01/01Schwartz/Smith/HayesWB22.324.222.4goodPit Trapped Fort Cooper State Park, Florida Gpo-08110/20/00RBC#12.52321.6g Gpo-1225/25/01?Schwartz/LeglerRBC#2 Gpo-16507/02/01Schwartz/LeglerRBC#3 Gpo-16607/2001Schwartz/LeglerRBC#4 Gold Head Branch State Park, Florida Gpo-1205/21/01Schwartz/LeglerRBC14g Gpo-1215/21/01Schwartz/LeglerRBC#2 Gpo-227Summer 2001WendlandRBC2 Gpo-228Summer 2001WendlandRBC9 Gpo-229Summer 2001WendlandRBC21 Gpo-230Summer 2001WendlandRBC22 Gpo-231Summer 2001WendlandRBC42 Gpo-232Summer 2001WendlandRBC51 Gpo-233Summer 2001WendlandvRBC52 Highland Hammocks State Park, Florida Gpo-12306/02/01Schwartz/WarnerWB#1NA27.525.9Health Very Dark color muddy? Dents ontop of shell, ridges Gpo-12406/02/01Schwartz/WarnerWB#2NA25.422.2Good friskyFound with female: #3 / Gpo125 APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-12506/02/01Schwartz/WarnerWB#3NA27.123.8HealthyFound with Male: #2 / Gpo124 Gpo-12606/03/01Schwartz/WarnerWB#4NA29.327.4Healthy Gpo-12706/03/01Schwartz/WarnerWB#5NA28.326.3Healthy Gpo-12906/03/01Schwartz/WarnerWB#7NA18.216.2Juvenile, flat plastron Gpo-13006/03/01Schwartz/WarnerWB#8NA30.727.2Healthy Gpo-13106/03/01Schwartz/WarnerWB#9NA27.224.3Healthy Gpo-13206/03/01Schwartz/WarnerWB#10NA16.715.3Very muddy, healthyContinued to bleed had a hard time stopping. Gpo-13306/03/01Schwartz/WarnerWB#11NA24.928HealthyHad a hard time bleeding. Right before a storm. Gpo-13406/03/01Schwartz/WarnerWB#12 Not number ed NA15.914.8HealthyBIT ME! Very small blood sample. NOT Gpo-13506/03/01Schwartz/WarnerWBNot number ed NA15.613.9Healthy, very shy.NO BLOOD TAKEN. Not Gpo-13606/16/01Schwartz/WarnerWB13NA~28.4~24.1gtube#13A has too many drops of blood. Tube #13B has 3 drops of blood. Gpo-13706/16/01Schwartz/WarnerWB#15NA~23.7~22.2wheezy breething when we bled her, made farting noises with mouth. Gpo-13806/16/01Schwartz/WarnerWB#14NA~28.6~24.4g APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-13906/16/01Schwartz/WarnerWB#16NA~22.2~20.1g Gpo-14006/17/01Schwartz/WarnerWB17NA~24.9~22.0g Gpo-14106/17/01Schwartz/WarnerWB#18NA~22.1~20.0g Gpo-14206/17/01Schwartz/WarnerWB#19NA~27.5~25.6g Gpo-14306/17/01Schwartz/WarnerWB#20NA~29.4~27.0g chipped up plastron Gpo-12806/03/01Schwartz/WarnerWB#6NA28.024.8Healthy Itchnuckney Springs State Park, Florida Gpo-23910-01LeglerRBC188 Gpo-19507/28/01LeglerRBC161 Gpo-19608/06/01LeglerRBC#1 Gpo-19708/06/01LeglerRBC#2 Gpo-24010-01LeglerRBC189 Jonathan Dickenson State Park, Florida Gpo-14406/19/01Schwartz/CurtisWB#1NA23.722.4g Gpo-14506/19/01Schwartz/CurtisWB#2NA27.223.7good / old old green paint? In shape of Â’UÂ’ on carapace, plastron nuchal left chipped off, very worn down claws. Gpo-14606/19/01Schwartz/CurtisWB#3NA27.524.9Ok Snotty nose Gpo-14706/19/01Schwartz/CurtisWB#4NA27.224.9healthyOne sample of blood and one of lymph fluid. Gpo-14806/19/01Schwartz/CurtisWB#5NA31.827.6g very heavy pregnant? Shit a lot. Blood coagulate like lava lamp. Took pictures with Caitlin. APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-14906/19/01Schwartz/CurtisWB#6NA28.625.3g light colored carapace, very worn and chipped. Gpo-15006/19/01Schwartz/CurtisWB#7NA29.726.3g platron nuchal notch very long. Deep plastron grooves. Back right notch chipped Gpo-15106/19/01Schwartz/CurtisWB#8NA25.823.3snotty nose: puffy-mucusy eye membranes, raspy breathing blood clotty like lava lamp. Gpo-15206/19/01Schwartz/CurtisWB#9NA29.827.7Ok, slightly wheezy Holes in scutes: back carapace: one hole in each of last two scutes on left side and on last scute on right side. Gpo-15306/19/01Schwartz/CurtisWB#10NA30.5NAHealthy Dent towards end of carapace Gpo-15406/19/01Schwartz/CurtisWB#11NA28.325.2g Very strong and shy. Took me forever to get her arm out. Gpo-15506/20/01Schwartz/CurtisWB#12NA27.425.3g Gpo-15606/20/01Schwartz/CurtisWB#13NA35.131g extremely large tortoise, shell very rounded. Huge tortoise!!! Gpo-15706/20/01Schwartz/CurtisWB#14NA28.224.8g Gpo-15806/20/01Schwartz/CurtisWB#15NA23.821.4gHad a hard time stopping the bleeding. Gpo-15906/20/01Schwartz/CurtisWB#16NA32.226.1good Â— wheezy pox in carapace and plastron, plastron nuchal scute is broken. APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-16006/20/01Schwartz/CurtisWB#17NA26.923.8gCaitlin Bled. Clotty lava lamp Gpo-16107/01/01Schwartz/BassWB#18NA31.629.2Healthy small spine in base of left eye. Crack on leftmarginal scute. Gpo-16207/01/01Schwartz/BassWB#19NA29.226.1Healthy lots of ticks Gpo-16307/01/01Schwartz/BassWB#20NA30.128.3Healthy Gpo-16407/01/01Schwartz/BassWB#21NA26.023.8Good slight wheeze Jones Research Center, Georgia Gpo-277BirkhartRBC2 Gpo-278BirkhartRBC6 Gpo-279BirkhartRBC20 Gpo-280BirkhartRBC25 Gpo-281BirkhartRBC46 Gpo-283BirkhartRBC75 Gpo-284BirkhartRBC76 Gpo-285BirkhartRBC101 Gpo-286BirkhartRBC115 Gpo-287BirkhartRBC240 Gpo-289BirkhartRBC256 Gpo-290BirkhartRBC261 Gpo-291BirkhartRBC277 Gpo-292BirkhartRBC292 Gpo-282BirkhartRBC48 Gpo-288BirkhartRBC243 APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-293BirkhartRBC320 Gpo-294BirkhartRBC340 Gpo-295BirkhartRBC343 Gpo-296BirkhartRBC355 Gpo-297BirkhartRBC364 Lake Lousia State Park, Florida Gpo-0488/7/00Schwartz/LeglerRBC#1631.128.1-g Gpo-0498/7/00Schwartz/LeglerRBC#25.529.529-g Gpo-0508/7/00Schwartz/LeglerRBC#34.428.225.7+g Gpo-0518/8/00Schwartz/LeglerRBC#44.42826.1-g Gpo-0528/8/00Schwartz/LeglerRBC#55.531.629.2-g Gpo-0538/8/00Schwartz/LeglerRBC#64.829.527.2-g Gpo-0548/8/00Schwartz/LeglerRBC#75.830.529.3-G-bubbles in one eye Gpo-0648/16/00Schwartz/LeglerRBC#86.832.931.4-G-ONE EYE A BIT WATERY Gpo-08210/6/00Legler/LindzeyRBC#94.729.227.7-pit trap Gpo-08310/6/00Legler/LindzeyRBC#102.624.823.9-pit trap Gpo-08410/6/00Legler/LindzeyRBC#112.824.223.1-pit trap Gpo-08510/6/00Legler/LindzeyRBC#122.52321-pit trap Gpo-08610/7/00Legler/LindzeyRBC#220.127.116.11LYSED BLOOD Gpo-08710/7/00Legler/LindzeyRBC#156.133.530.2Gpo-08810/7/00Legler/LindzeyRBC#164.12826.2Gpo-08910/7/00Legler/LindzeyRBC#173.52624.5-PIT TRAP Gpo-09010/7/00Legler/LindzeyRBC#184.828.526Gpo-09110/7/00Legler/LindzeyRBC#193.52725.3-PIT TRAP APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Moody Air Force Base, Georgia Gpo-262LockhartRBC5 Gpo-263LockhartRBC9 Gpo-264LockhartRBC12 Gpo-265LockhartRBC15 Gpo-266LockhartRBC17 Gpo-267LockhartRBC19 Gpo-268LockhartRBC41 Gpo-269LockhartRBC46 Gpo-270LockhartRBC48 Gpo-271LockhartRBC52 Gpo-272LockhartRBC55 Gpo-273LockhartRBC56 Gpo-274LockhartRBC58 Gpo-275LockhartRBC59 Gpo-276LockhartRBC72 Oldenburg Mitigation Park, Florida Gpo-198Summer 2001WendlandRBC#34 Gpo-202Summer 2001WendlandRBC6 Gpo-203Summer 2001WendlandRBC18 Gpo-204Summer 2001WendlandRBC19 Gpo-205Summer 2001WendlandRBC20 Gpo-206Summer 2001WendlandRBC22 Gpo-207Summer 2001WendlandRBC23 Gpo-208Summer 2001WendlandRBC24 APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-209Summer 2001WendlandRBC25 Gpo-210Summer 2001WendlandRBC30 Gpo-211Summer 2001WendlandRBC32 Gpo-212Summer 2001WendlandRBC65 Gpo-214Summer 2001WendlandRBC67 Gpo-215Summer 2001WendlandRBC68 Gpo-213Summer 2001WendlandRBC66 OÂ’leno? Or Gold Head Branch, Florida Gpo-16707/2001LeglerRBC22 Ray Ashtons Tortoise Preserve, Florida Gpo-17306/02/01AshtonRBC2 Gpo-17407/25/01AshtonRBC34 Gpo-17506/05/01AshtonRBC48 Gpo-176AshtonRBC51 Gpo-17705/14/01AshtonRBC52 Gpo-17806/05/01AshtonRBC53 Gpo-17906/17/01AshtonRBC54 Gpo-180AshtonRBC55 Gpo-181AshtonRBC58 Gpo-182AshtonRBC59 Gpo-183AshtonRBC60 Gpo-18407/21/01AshtonRBC63 Gpo-18507/22/01AshtonRBC64 Gpo-18607/19/01AshtonRBC71 APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-18706/19/01AshtonRBC77 Gpo-18806/30/01AshtonRBC81 Gpo-18906/16/01AshtonRBC104 Gpo-19006/02/01AshtonRBC112 Gpo-19105/30/01AshtonRBC316 Gpo-19206/02/01AshtonRBC317 Gpo-19306/20/01AshtonRBC318 San Felesco State Park, Florida Gpo-19408/02/01LeglerRBC#1 Wakulla Springs State Park, Florida Gpo-2388/01Schwartz/BrockmanRBC#1NA2724.5Eyes slightly swollen, large tick on real left leg. Wekiwa Springs State Park, Florida Gpo-0558/15/00Schwartz/LeglerRBC#13.22623-g Gpo-0568/15/00Schwartz/LeglerRBC#22.923.922+g Gpo-0578/15/00Schwartz/LeglerRBC#32.9242.1+g Gpo-0588/15/00Schwartz/LeglerRBC#4324.723+g Gpo-0598/15/00Schwartz/LeglerRBC#52.322.720.8+G-BIG TICKS Gpo-0608/15/00Schwartz/LeglerRBC#6 9(BH) 3.926.9524.3+g Gpo-0618/16/00Schwartz/LeglerRBC#73.8526.624.9+G-EYES LOOKED A LITTLE WEIRD-KIND OF PUFFY BUT HAD A DRY NOSE Gpo-0628/16/00Schwartz/LeglerRBC#84.628.526.1+g APPENDIX C (CONTINUED)
Individual #Collection dateSource of sampleDNAField #KGCLPLURTDAppearanceField Notes Gpo-0638/16/00Schwartz/LeglerRBC#92.925.121.8Sg Gpo-0658/24/00Schwartz/LeglerRBC#103.425.423.3+g Gpo-0668/24/00Schwartz/LeglerRBC#112.623.721.7-g Gpo-0678/24/00Schwartz/LeglerRBC#123.325.424SLOTS OF TICKS-BAD SHELL -OTHERWISE GOOD Gpo-0688/24/00Schwartz/LeglerRBC#132.724.321.5-G-VERY DARK, SOFTER SKINGETTING WET? Gpo-0698/24/00Schwartz/LeglerRBC#10A11716g Gpo-0708/27/00Schwartz/LeglerRBC#142.824.423.5-G-LOTS OF TICKS Gpo-0719/24/00Schwartz/LeglerRBC#1542825.9-Stressed quickly, shell looked worn, otherwise healthy Gpo-0729/24/00Schwartz/LeglerRBC#163.426.224.2-gFighting with #17 Gpo-0739/24/00Schwartz/LeglerRBC#175.129.626.6+gFighting with #16 Gpo-0749/24/00Schwartz/LeglerRBC#18326.324.15Swet/snot, gurgles and rattles when breathing Gpo-0759/24/00Schwartz/LeglerRBC#18A2.123.320.9g Gpo-0769/24/00Schwartz/LeglerRBC#18B1.921.519.5g Gpo-0779/24/00Schwartz/LeglerRBC#193.626.822.8-g Gpo-0789/30/00Schwartz/LeglerRBC#202.824.422.6SgCaught while raining Gpo-07910/1/00Schwartz/LeglerRBC#20A4.327.424.9NDgtough, shy Gpo-08010/1/00Schwartz/LeglerRBC#213.725.923.2+G, rough looking shell APPENDIX C (CONTINUED)
APPENDIX D GRAPHS OF ALLELIC FREQUENCIES FOR EACH LOCUS Locus GP150.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00207 208 209 211 213 215 217 219 221 223 225 227 229 231 233 235 237 239 241 243 245 247 249 251 253 255 257 259 261 263 265 267 269AllelesPercent
APPENDIX D (CONTINUED) Locus GP190.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 252254256 AllelesPercent
APPENDIX D (CONTINUED) Locus GP260.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 358360362364366368370 AllelesPercent
APPENDIX D (CONTINUED) Locus GP300.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00194 196 198 200 202 204 206 208 210 212 214 216 218 220 222 224 226 228 230 232AllelesPercent
APPENDIX D (CONTINUED) Locus GP550.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 265267269271 AllelesPercent
APPENDIX D (CONTINUED) Locus GP610.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00197 199 201 203 205 207 209 211 213 215 217 219 221 223 225 227 229 231 233 235 237 239 241 243 245AllelesPercent
APPENDIX D (CONTINUED) Locus GP810.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 397401403405407409411413415 AllelesPercent
APPENDIX D (CONTINUED) Locus GP960.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 141143145147149151153155 AllelesPercent
APPENDIX D (CONTINUED) Locus GP1020.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00299 301 303 305 307 309 311 313 315 317 319 321 323 325 327 329 331 333 335 337 339AllelesPercent
APPENDIX E TABLE OF ALLELIC FREQUENCIES BY LOCUS FOR EACH POPULATIONLoci WA N=1 JC N=19 CK N=8 BS N=11 MB N=15 IS N=4 CF N=4 GB N=9 RA N=21 OM N=15 BC N=15 FC N=4 EA N=26 BH N=24 CC N=21 HH N=19 EV N=2 LL N=18 JD N=21 WS N=22 GP15 20750.006.2518.7531.8246.6750.0016.6715.0057.1456.2562.5055.7750.0065.7943.3375.0055.5657.5061.36 208 27.50 209 7.50 21125.0016.67 2152.50 21937.5022.7320.005.5620.004.00 2219.0910.0022.2222.5014.299.3826.928.007.8950.0022.222.5020.45 223 25.00 2253.13 22734.389.096.6710.0011.1112.507.143.855.268.335.0013.64 22925.004.5562.505.5625.003.853.332.78 23143.3311.1115.0021.4334.3812.509.6238.0021.0511.114.55 2334.5512.505.56 2395.56 2574.55 25950.00 26143.757.503.33 2634.55 26531.254.553.3310.005.00 2694.55 GP19WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 2526.259.0950.0016.672.503.572.089.52 254100.0094.7450.0045.4589.2970.0037.5083.3382.5057.1481.2575.0080.4389.5819.0538.2450.0061.7660.0050.00 2565.2643.7545.4510.7130.0012.5015.0039.2918.7525.0019.578.3380.9561.7650.0038.2440.0040.48
Loci WA N=1 JC N=19 CK N=8 BS N=11 MB N=15 IS N=4 CF N=4 GB N=9 RA N=21 OM N=15 BC N=15 FC N=4 EA N=26 BH N=24 CC N=21 HH N=19 EV N=2 LL N=18 JD N=21 WS N=22 GP26WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 3584.5516.6740.0025.0011.113.854.0021.052.38 36234.2118.754.5556.676.2514.002.942.50 3647.8931.2540.913.3330.0062.5027.7837.5082.1462.5037.5082.6974.0078.9593.3375.0085.2977.5080.95 366100.0055.2650.0040.9123.3320.0012.5055.5655.007.1421.883.858.825.0011.90 3682.639.0910.005.565.0010.719.3862.507.698.0025.004.76 3702.501.926.672.9415.00 GP30WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 19450.0038.2437.5031.8216.6740.0037.5062.5052.7832.1442.8625.0040.3854.0044.1223.3338.8966.6762.50 2003.33 208 6.6713.89 2105.8818.7554.5530.0020.0050.0037.5044.4460.7157.1462.5057.6942.0055.8870.0075.0061.1111.1135.00 212 1.922.50 22050.0031.2513.6430.0030.0012.502.787.1412.504.00 22212.50 22455.8820.0010.0025.00 226 2.78 232 5.56 GP55WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 2654.5520.0016.675.8810.7150.0012.505.7720.0055.5643.3325.008.825.266.82 271100.00100.00100.0095.45100.0080.00100.0083.3394.1289.2950.0087.5094.2380.0044.4456.6775.0091.1894.7493.18 GP61WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 19750.0023.6881.2568.1875.0060.0087.5061.1162.5089.2988.2487.5084.0085.4273.8176.3225.0077.7816.6786.36 199 16.67 20328.957.14 4.76 205 2.0021.43 20750.0047.3718.7531.8217.8640.0017.5010.7111.7612.5014.0014.5826.1923.6875.0022.2240.4813.64 APPENDIX E (CONTINUED)
Loci WA N=1 JC N=19 CK N=8 BS N=11 MB N=15 IS N=4 CF N=4 GB N=9 RA N=21 OM N=15 BC N=15 FC N=4 EA N=26 BH N=24 CC N=21 HH N=19 EV N=2 LL N=18 JD N=21 WS N=22 2435.567.50 24512.5033.3312.50 GP81WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 39750.002.637.1427.2730.0025.0055.5647.3750.0050.0050.0023.9154.1737.5027.78100.0035.2940.4821.43 40314.2940.9114.2930.00 25.00 5.5628.9521.4321.8813.0420.8362.5050.0032.3530.9528.57 4053.579.3821.742.08 40750.0028.9578.5722.7357.1420.0012.505.5618.4225.0018.7550.0041.3022.9222.2232.3516.6747.62 40950.009.097.1420.005.26 41118.4221.4337.5033.33 2.38 415 11.90 GP96 14150.005.266.254.5512.50 4.76 145 5.269.093.572.502.784.76 14726.3262.5050.0050.0060.0075.0083.3382.5075.0097.06100.0094.0087.5095.2452.63100.0083.3380.9593.18 14950.0039.4712.5027.2714.2940.0010.712.082.38 15123.686.254.5510.7112.5016.672.505.562.27 15312.504.5521.4312.5014.294.0010.424.7647.372.787.144.55 1552.942.00 157 5.56 GP102WAJRCKBSMBISCFGHRAOMBCFCEABHCCHHEVLLJDWS 29914.295.262.38 30144.7414.2925.003.8526.1911.90 3036.2515.7911.5411.7637.504.177.14 30512.50 311100.0013.6410.7110.0062.5038.8915.7923.5314.0010.425.268.827.14 313 2.6335.71 315 9.52 31781.2577.2750.0012.5055.5657.8942.3117.6512.5052.0029.1710.5344.7452.942.3854.76 APPENDIX E (CONTINUED)
Loci WA N=1 JC N=19 CK N=8 BS N=11 MB N=15 IS N=4 CF N=4 GB N=9 RA N=21 OM N=15 BC N=15 FC N=4 EA N=26 BH N=24 CC N=21 HH N=19 EV N=2 LL N=18 JD N=21 WS N=22 3199.0910.0010.5338.4647.0650.0034.0056.2581.5850.00100.0038.249.52 26.19 3213.85 32928.57 3313.57 3335.2625.0030.005.56 3353.57 7.14 33950.00 APPENDIX E (CONTINUED)