Advertisement

Watersheds influence the wood turtle’s (Glyptemys insculpta) genetic structure

  • Cindy BouchardEmail author
  • Nathalie Tessier
  • François-Joseph Lapointe
Research Article

Abstract

The wood turtle (Glyptemys insculpta) is a freshwater species endemic to eastern North America and is currently listed as endangered by the International Union for Conservation of Nature. Wood turtle local populations are considered units for the species recovery, and are defined as discrete interbreeding populations in a distinct watershed; however, there are no studies to date supporting this definition. The main objective of this paper was to genetically characterize wood turtles from a northern portion of their range, and test an isolation-by-watershed hypothesis, the first of its kind at such a large geographical scale. Turtles were sampled in 24 watercourses from 12 different watersheds for a total of 331 individuals, each genotyped for nine microsatellite loci. Within each watershed, genetic diversity was similar between sites, and observed heterozygosity ranged from 0.677 to 0.754. Partial redundancy analyses then confirmed that watershed isolation contributed to 18% of the total observed genetic variation, while spatial autocorrelation and the post-glacial Expansion Model did not significantly explain any variation. Clustering methods revealed substantial spatial genetic structure, with sampled groups falling into ten nested hierarchical clusters. We recommend further consideration of these ten clusters to determine if they meet the evolutionary significance criterion to become designatable units, whose genetic structures were influenced by watershed structure.

Keywords

Clustering Conservation genetics Freshwater turtle Landscape genetics Microsatellite Partial redundancy analysis Watershed 

Notes

Acknowledgements

We would like to thank numerous individuals for providing wood turtle samples: W. Bertacchi, G. Bourget, M. Bruno, C. Daigle, Y. Dubois, A. Dumont, M. Dumont, S. Gagnon, P. Gaudet, S. Giguère, C. Greaves, J. Jutras, P. Labonté, M. Laflèche, M. Toner M. Leclerc, D. Masse, S. Paradis, Y. Robitaille, D. Rodrigue, K. Smith, D. St-Hilaire, and C. Trochue. We are also grateful to several biologists, technicians, and volunteers from the Quebec Government, Parks Canada, Corporation Gestion de la Forêt de l’Aigle, Corporation de l’Aménagement de la Rivière l’Assomption, Ecomuseum, and Université de Montréal for helping with field sampling. We would also like to thank G. Bourget, Y. Dubois, S. Giguère, D. Masse, and S. Pelletier for providing additional details of wood turtle locations, L. Veilleux for producing the map, and A. Rogic for editing earlier drafts of this manuscript. Finally, we are thankful for the thoughtful comments and suggestions provided by two anonymous reviewers.

Funding

This study was supported in part by a Natural Sciences and Engineering Research Council grant (Grant No. 0155251, F.-J. Lapointe), Fondation de la faune du Québec, Parks Canada, Fédération canadienne de la faune, and Faune-Nature Québec program.

Compliance with ethical standards

Conflict of interest

The authors declare no conflicts of interest.

References

  1. Alacs EA, Janzen FJ, Scribner KT (2007) Genetic issues in freshwater turtle and tortoise conservation. Chelonian Res Monogr 4:107–123Google Scholar
  2. Amato ML, Brooks RJ, Fu J (2008) A phylogeographic analysis of populations of the wood turtle (Glyptemys insculpta) throughout its range. Mol Ecol 17(2):570–581PubMedGoogle Scholar
  3. Anderson MJ, Legendre P (1999) An empirical comparison of permutation methods for tests of partial regression coefficients in a linear model. J Stat Comput Simul 62(3):271–303Google Scholar
  4. Anderson CD, Epperson BK, Fortin MJ, Holderegger R, James PMA, Rosenberg MS, Scribner KT. Spear S (2010) Considering spatial and temporal scale in landscape-genetic studies of gene flow. Mol Ecol 19(17):3565–3575PubMedGoogle Scholar
  5. Arvisais M, Bourgeois J-C, Levesque E, Daigle C, Masse D, Jutras J (2002) Home range and movements of a wood turtle (Clemmys insculpta) population at the northern limit of its range. Can J Zool 80:402–408Google Scholar
  6. Arvisais M, Levesque E, Bourgeois J-C, Daigle C, Masse D, Jutras J (2004) Habitat selection by the wood turtle (Clemmys insculpta) at the northern limit of its range. Can J Zool 82:391–398Google Scholar
  7. Avise JC, Bowen BW, Lamb T, Meylan AB, Bermingham E (1992) Mitochondrial DNA evolution at a turtle’s pace: evidence for low genetic variability and reduced microevolutionary rate in the Testudines. Mol Biol Evol 9:457–473PubMedGoogle Scholar
  8. Balloux F, Lugon-Moulin N (2002) The estimation of population differentiation with microsatellite markers. Mol Ecol 11(2):155–165PubMedGoogle Scholar
  9. Beneteau CL, Mandrak NE, Heath DD (2009) The effects of river barriers and range expansion of the population genetic structure and stability in greenside darter (Etheostoma blennioides) populations. Conserv Genet 10:477Google Scholar
  10. Borcard D, Legendre P (2002) All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol Model 153:51–68Google Scholar
  11. Cagle FR (1939) A system of marking turtles for future identification. Copeia 1939(3):170–173Google Scholar
  12. Castellano CM, Behler JL, Amato G (2009) Genetic diversity and population genetic structure of the wood turtle (Glyptemys insculpta) at Delaware Water Gap National Recreation Area, USA. Conserv Genet 10(6):1783–1788Google Scholar
  13. Caye K, Jay F, Michel O, Francois O (2018) Fast inference of individual admixture coefficients using geographic data. Ann Appl Stat 12:586–608Google Scholar
  14. Chen C, Durand E, Forbes F, François O (2007) Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study. Mol Ecol Notes 7:747–756Google Scholar
  15. Chikhi L, Sousa VC, Luisi P, Goossens B, Beaumont MA (2010) The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes. Genetics 186:983–995PubMedPubMedCentralGoogle Scholar
  16. Committee on the Status of Endangered Wildlife in Canada (COSEWIC) (2007) COSEWIC assessment and update status report on the wood turtle (Glyptemys insculpta) in Canada. Committee on status of Endangered Wildlife in Canada, OttawaGoogle Scholar
  17. Committee on the Status of Endangered Wildlife in Canada (COSEWIC) (2015) Guidelines for recognizing designatable units below the species level (approved by COSEWIC November 2015). Available from https://www.canada.ca/en/environment-climate-change/services/committee-status-endangered-wildlife/guidelines-recognizing-designatable-units.html Access 21 November 2017
  18. Compton BW, Rhymer JM, McCollough J (2002) Habitat selection by wood turtles (Clemmys insculpta). Herpetol Rev 33(3):166Google Scholar
  19. Crawford NG (2010) SMOGD: software for the measurement of genetic diversity. Mol Ecol Resour 10:556–557PubMedGoogle Scholar
  20. Cureton JC, Janis M, Lutterschmidt WI, Randle CP, Ruthven DC, Deaton R (2014) Effects of urbanization on genetic diversity, gene flow, and population structure in the ornate box turtle (Terrapene ornata). Amphib-Reptil 35(1):87–97Google Scholar
  21. Daigle C (1997) Size and characteristics of a wood turtle, Clemmys insculpta, population in southern Quebec. Can Field-Nat 111(3):440–444Google Scholar
  22. Daigle C, Jutras J (2005) Quantitative evidence of decline in a southern Québec wood turtle (Glyptemys insculpta) population. J Herpetol 39:130–132Google Scholar
  23. Davy CM, Murphy RW (2014) Conservation genetics of the endangered spotted turtle (Clemmys guttata) illustrate the risks of “bottleneck tests”. Can J Zool 92(2):149–162Google Scholar
  24. DeSalle R, Amato G (2004) The expansion of conservation genetics. Nat Rev Genet 5(9):702PubMedGoogle Scholar
  25. Durand E, Jay F, Gaggiotti OE, François O (2009) Spatial inference of admixture proportions and secondary contact zones. Mol Biol Evol 26:1963–1973PubMedGoogle Scholar
  26. Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359–361Google Scholar
  27. Eaton KR, Loxterman JL, Keeley ER (2018) Connections and containers: using genetic data to understand how watershed evolution and human activities influence cutthroat trout biogeography. PLoS ONE 13(8):e0202043PubMedPubMedCentralGoogle Scholar
  28. Environment Canada (2016) Recovery strategy for the wood turtle (Glyptemys insculpta) in Canada. Species at Risk Act Recovery Strategy Series. Environment Canada, OttawaGoogle Scholar
  29. Ernst CH, Lovich JE (2009) Turtles of the United States and Canada, 2nd edn. Hopkins Fulfilment Service, MarylandGoogle Scholar
  30. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611–2620PubMedGoogle Scholar
  31. Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evolut Bioinform 1:117693430500100003Google Scholar
  32. Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Annu Rev Ecol Evol Syst 34(1):487–515Google Scholar
  33. Fridgen C, Finnegan L, Reaume C, Cebek J, Trottier J, Wilson PJ (2013) Conservation genetics of wood turtle (Glyptemys insculpta) populations in Ontario, Canada. Herpetol Conserv Biol 8(2):351–358Google Scholar
  34. Gibbon JW, Scott DE, Ryan TJ, Buhlmann KA, Tuberville TD, Metts BS, Greene JL, Milla T, Leiden Y, Poppy S, Winne CT (2000) The global decline of reptiles, déjà vu amphibians. Bioscience 50(8):653–666Google Scholar
  35. Gibbs JP, Shriver WG (2002) Estimating the effects of road mortality on turtle populations. Conserv Biol 16(6):1647–1652Google Scholar
  36. Harding JH, Bloomer TJ (1979) The wood turtle, Clemmys insculpta: a natural history. Bull N Y Herpetol Soc 15:9–26Google Scholar
  37. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806PubMedGoogle Scholar
  38. Jensen EL, Govindarajulu P, Russello MA (2014) When the shoe doesn’t fit: applying conservation unit concepts to western painted turtles at their northern periphery. Conserv Genet 15(2):261–274Google Scholar
  39. Jones MT, Sievert PR (2009) Effects of stochastic flood disturbance on adult wood turtles, Glyptemys insculpta, in Massachusetts. Can Field-Nat 123(4):313–322Google Scholar
  40. Jost L (2008) GST and its relatives do not measure differentiation. Mol Ecol 17(18):4015–4026PubMedGoogle Scholar
  41. Kalinowski ST (2004) Counting alleles with rarefaction: private alleles and hierarchical sampling designs. Conserv Genet 5:539–543Google Scholar
  42. Kalinowski ST (2005) HP-Rare: a computer program for performing rarefaction on measures of allelic diversity. Mol Ecol Notes 5:187–189Google Scholar
  43. King TL, Julian SE (2004) Conservation of microsatellite DNA flanking sequence across 13 Emydid genera assayed with novel bog turtle (Glyptemys muhlenbergii) loci. Conserv Genet 5(5):719–725Google Scholar
  44. Koen EL, Bowman J, Garroway CJ, Wilson PJ (2013) The sensitivity of genetic connectivity measures to unsampled and under-sampled sites. PLoS ONE 8(2):e56204PubMedPubMedCentralGoogle Scholar
  45. Koen EL, Bowman J, Wilson PJ (2015) Isolation of peripheral populations of Canada lynx (Lynx canadensis). Can J Zool 93(7):521–530Google Scholar
  46. Kuo CH, Janzen FJ (2004) Genetic effects of a persistent bottleneck on a natural population of ornate box turtles (Terrapene ornata). Conserv Genet 5(4):425–437Google Scholar
  47. Landguth EL, Cushman SA, Schwartz MK, McKelvey KS, Murphy M, Luikart G (2010) Quantifying the lag time to detect barriers in landscape genetics. Mol Ecol 19(19):4179–4191PubMedGoogle Scholar
  48. Legendre P, Anderson MJ (1999) Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecol Monogr 69:1–24Google Scholar
  49. Legendre P, Oksanen J, ter Braak CJF (2011) Testing the significance of canonical axes in redundancy analysis. Methods Ecol Evol 2:269–277Google Scholar
  50. Lovich JE, Ernst CH, McBreen JF (1990) Growth, maturity, and sexual dimorphism in the wood turtle, Clemmys insculpta. Can J Zool 68:672–677Google Scholar
  51. Luque S, Saura S, Fortin M-J (2012) Landscape connectivity analysis for conservation: insights from combining new methods with ecological and genetic data. Landsc Ecol 27:153–157Google Scholar
  52. Lynch M (1991) The genetic interpretation of inbreeding depression and outbreeding depression. Evolution 45(3):622–629PubMedGoogle Scholar
  53. Manel S, Holderegger R (2013) Ten years of landscape genetics. Trends Ecol Evol 28(10):614–621PubMedGoogle Scholar
  54. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evolution 18(4):189–197Google Scholar
  55. Marchand MN, Litvaitis JA (2004) Effects of habitat features and landscape composition on the population structure of a common aquatic turtle in a region undergoing rapid development. Conserv Biol 18(3):758–767Google Scholar
  56. Marsack K, Swanson BJ (2009) A genetic analysis of the impact of generation time and road-based habitat fragmentation on eastern box turtles (Terrapene c. carolina). Copeia 2009(4):647–652Google Scholar
  57. Meffe GK, Carroll CR (1997) Genetics: conservation of diversity within species. In: Meffe GK, Carroll CR (eds) Principles of conservation biology Sinauer Associates. Sunderland, Massachusetts, pp 161–201Google Scholar
  58. Mockford SW, McEachern L, Herman TB, Snyder M, Wright JM (2005) Population genetic structure of a disjunct population of blanding’s turtle (Emydoidea blandingii) in Nova Scotia, Canada. Biol Conserv 123:373–380Google Scholar
  59. Moritz C (1994) Defining ‘evolutionarily significant units for conservation’. Trends Ecol Evol 9:373–375PubMedGoogle Scholar
  60. Oksanen JF, Blanchet G, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2017) Vegan: community ecology package. R package version 2.4-2. Available from https://CRAN.R-project.org/package=vegan
  61. Palsbøll PJ, Berube M, Allendorf FW (2007) Identification of management units using population genetic data. Trends Ecol Evol 22(1):11–16PubMedGoogle Scholar
  62. Paz-Vinas I, Quemere E, Chikhi L, Loot G, Blanchet S (2013) The demographic history of populations experiencing asymmetric gene flow: combining simulated and empirical data. Mol Ecol 22:3279–3291PubMedGoogle Scholar
  63. Peakall ROD, Smouse PE (2006) GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6(1):288–295Google Scholar
  64. Peakall ROD, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539PubMedPubMedCentralGoogle Scholar
  65. Peres-Neto PR, Legendre P, Dray S, Borcard D (2006) Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology 87(10):2614–2625PubMedGoogle Scholar
  66. Pittman SE, King TL, Faurby S, Dorcas ME (2011) Demographic and genetic status of an isolated population of bog turtles (Glyptemys muhlenbergii): implications for managing small populations of long-lived animals. Conserv Genet 12(6):1589–1601Google Scholar
  67. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959PubMedPubMedCentralGoogle Scholar
  68. R Development Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available from https://www.R-project.org/
  69. Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J Hered 86:248–249Google Scholar
  70. Reid BN, Mladenoff DJ, Peery MZ (2017) Genetic effects of landscape, habitat preference and demography on three co-occurring turtle species. Mol Ecol 26(3):781–798PubMedGoogle Scholar
  71. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43(1):223–225PubMedGoogle Scholar
  72. Rousset F (2008) Genepop’007: a complete reimplementation of the Genepop software for Windows and Linux. Mol Ecol Resour 8:103–106PubMedGoogle Scholar
  73. Ryman N, Palm S, André C, Carvalho GR, Dahlgren TG, Jorde PE, Laikre L, Larsson LC, Palmé A, Ruzzante DE (2006) Power for detecting genetic divergence: differences between statistical methods and marker loci. Mol Ecol 15(8):2031–2045PubMedGoogle Scholar
  74. Saumure RA, Bider JR (1998) Impact of agriculture development on a population of wood turtles (Clemmys insculpta) in Southern Québec, Canada. Chelonian Conserv Biol 3:37–45Google Scholar
  75. Saumure RA, Herman TB, Titman RD (2007) Effects of haying and agricultural practices on a declining species: the North American wood turtle, Glyptemys insculpta. Biol Cons 135(4):565–575Google Scholar
  76. Schwartz MK, McKelvey KS (2009) Why sampling scheme matters: the effect of sampling scheme on landscape genetic results. Conserv Genet 10:441–452Google Scholar
  77. Segelbacher G, Höglund J, Storch I (2003) From connectivity to isolation: genetic consequences of population fragmentation in capercaillie across Europe. Mol Ecol 12(7):1773–1780PubMedGoogle Scholar
  78. Segelbacher G, Cushman SA, Epperson BK, Fortin MJ, François O, Hardy OJ, Holderegger R, Taberlet P, Waits LP, Manel S (2010) Applications of landscape genetics in conservation biology: concepts and challenges. Conserv Genet 11:375–385Google Scholar
  79. Shaffer HB, Gidiş M, McCartney-Melstad E, Neal KM, Oyamaguchi HM, Tellez M, Toffelmier EM (2015) Conservation genetics and genomics of amphibians and reptiles. Ann Rev Anim Biosci 3(1):113–138Google Scholar
  80. Smith WH, Wooten JA, Camp CD, Stevenson DJ, Jensen JB, Turner M, Alexander RN (2018) Genetic divergence correlates with the contemporary landscape in populations of slimy salamander (Plethodon glutinosus) species complex across the lower piedmont and coastal plain of the Southeastern United States. Can J Zool 96(11):1244–1254Google Scholar
  81. Souza FL, Cunha AF, Oliveira MA, Pereira GAG, dos Reis SF (2002) Estimating dispersal and gene flow in the neotropical freshwater turtle Hydromedusa maximiliani (Chelidae) by combining ecological and genetic methods. Genet Mol Biol 25(2):151–155Google Scholar
  82. Spradling TA, Tamplin JW, Dow SS, Meyer KJ (2010) Conservation genetics of a peripherally isolated population of the wood turtle (Glyptemys insculpta) in Iowa. Conserv Genet 11(5):1667–1677Google Scholar
  83. Storfer A (1999) Gene flow and endangered species translocations: a topic revisited. Biol Conserv 87(2):173–180Google Scholar
  84. Taberlet P, Luikart G (1999) Non-invasive genetic sampling and individual identification. Biol J Linn Soc 68:41–55Google Scholar
  85. Templeton AR, Shaw K, Routman E, Davis SK (1990) The genetics consequences of habitat fragmentation. Ann Missouri Bot Gard 77(1):12–27Google Scholar
  86. Tessier N, Paquette SR, Lapointe FJ (2005) Conservation genetics of the wood turtle (Glyptemys insculpta) in Quebec, Canada. Can J Zool 83(6):765–772Google Scholar
  87. Turtle Conservation Fund (2002) A global action plan for conservation of tortoises and freshwater turtles. Strategy and funding prospectus 2002–2007. Conservation International and Chelonian Research Foundation, Washington, DCGoogle Scholar
  88. van Dijk PP, Harding J (2011) Glyptemys insculpta. (errata version published in 2016) The IUCN Red List of Threatened Species 2011: e.T4965A97416259. Downloaded on 15 June 2017Google Scholar
  89. Van Oosterhout C, Hutchinson WF, Wills DP, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4(3):535–538Google Scholar
  90. Vargas-Ramirez M, Stuckas H, Castaňo-Mora OV, Fritz U (2012) Extremely low genetic diversity and weak population differentiation in the endangered Colombian river turtle Podocnemis lewyana (Testudines: Podocnemididae). Conserv Genet 13:65–77Google Scholar
  91. Wade MJ, McCauley DE (1988) Extinction and recolonization: their effects on the genetic differentiation of local populations. Evolution 42:995–1005PubMedGoogle Scholar
  92. Waits LP, Luikart G, Taberlet P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Mol Ecol 10:249–256PubMedGoogle Scholar
  93. Walde AD, Bider JR, Daigle C, Masse D, Bourgeois J-C, Jutras J, Titman RD (2003) Ecological aspects of a wood turtle, Glyptemys insculpta, population at the Northern limit of its range in Quebec. Can Field Nat 117(3):377–388Google Scholar
  94. Walde AD, Bider RJ, Masse D, Saumure RA, Titman RD (2007) Nesting ecology and hatching success of the wood turtle, Glyptemys insculpta, in Quebec. Herpetol Conserv Biol 2(1):49–60Google Scholar
  95. Willoughby JR, Sundaram M, Lewis TL, Swanson BJ (2013) Population decline in a long-lived species: the wood turtle in Michigan. Herpetologica 69(2):186–198Google Scholar
  96. Willoughby JR, Sundaram M, Wijayawardena BK, Kimble SJ, Ji Y, Fernandez NB, Antonides JD, Lamb MC, Marra NJ, DeWoody JA (2015) The reduction of genetic diversity in threatened vertebrates and new recommendations regarding IUCN conservation rankings. Biol Conserv 191:495–503Google Scholar
  97. Zellmer AJ, Knowles LL (2009) Disentangling the effects of historic vs. contemporary landscape structure on population genetic divergence. Mol Ecol 18:3593–3602PubMedGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Département de Sciences BiologiquesUniversité de MontréalMontréalCanada
  2. 2.MFFP-FauneLongueuilCanada

Personalised recommendations