Advertisement

Hydrobiologia

, Volume 838, Issue 1, pp 121–137 | Cite as

Strong genetic isolation despite wide distribution in a commercially exploited coastal shark

  • Kelvin L. HullEmail author
  • Tamaryn A. Asbury
  • Charlene da Silva
  • Matthew Dicken
  • Ana Veríssimo
  • Edward D. Farrell
  • Stefano Mariani
  • Carlotta Mazzoldi
  • Ilaria A. M. Marino
  • Lorenzo Zane
  • Simo N. Maduna
  • Aletta E. Bester-van der MerweEmail author
Primary Research Paper

Abstract

The common smoothhound, Mustelus mustelus, is an epibenthic species targeted by fisheries around the world driven by the increasing demand for shark products. Given the wide-spread occurrence of this species and corresponding lack of molecular data in many areas of said distribution, baseline molecular assessments of this commercially important shark may contribute to finer-scale analyses in areas in which this species is targeted. Therefore, population genetic analyses were conducted along the East Atlantic, from the Mediterranean Sea to the south-east coast of Africa, using microsatellite markers and the mitochondrial control region (mtCR). Overall, M. mustelus displayed low to moderate genetic diversity, with the Mediterranean populations appearing to exhibit the lowest mitochondrial diversity, and the west African populations displaying the lowest nuclear diversity. Microsatellite analysis indicated strong genetic differentiation between the three regions, with finer-scale population structure in each region, without correlation between genetic and geographical distance. For the mtCR sequences, a total of 18 haplotypes were identified, with a high degree of divergence discernable between the regions, largely in accordance with the microsatellite data. The study documents a remarkable level of population isolation across a vast area, suggesting little or no present-day connectivity among extant populations. The findings may serve as an essential baseline for global population management and commercial traceability of this threatened shark.

Keywords

Genetic differentiation Microsatellites Mitochondrial DNA Fisheries management Mustelus mustelus 

Notes

Acknowledgements

The authors would like to thank the Central Analytical Facility at Stellenbosch University, South Africa, for sequencing conducted. This project was partly funded by the National Research Foundation of South Africa.

Supplementary material

10750_2019_3982_MOESM1_ESM.pdf (405 kb)
Supplementary material 1 (PDF 405 kb)
10750_2019_3982_MOESM2_ESM.pdf (489 kb)
Supplementary material 2 (PDF 489 kb)

References

  1. Amaral, A. R., L. B. Beheregaray, K. Bilgmann, D. Boutov, L. Freitas, K. M. Robertson, M. Sequeira, K. A. Stockin, M. M. Coelho & L. M. Möller, 2012. Seascape genetics of a globally distributed, highly mobile marine mammal: the short-beaked common dolphin (genus Delphinus). PloS ONE 7: e31482.Google Scholar
  2. Avise, J. C., 2012. Molecular Tools. In Avise, J. C. (ed.), Molecular Markers, Natural History and Evolution. Springer, New York: 44–91.Google Scholar
  3. Avise, J. C., J. E. Neigel & J. Arnold, 1984. Demographic influences on mitochondrial DNA lineage survivorship in animal populations. Journal of Molecular Evolution 20: 99–105.Google Scholar
  4. Bandelt, H. J., F. Peter & A. Röhl, 1999. Median-joining networks for inferring intraspecific phylogenies. Molecular Biology 16: 37–48.Google Scholar
  5. Barker, M. J. & V. Schluessel, 2005. Managing global shark fisheries: suggestions for prioritizing management strategies. Aquatic Conservation: Marine and Freshwater Ecosystems 15: 325–347.Google Scholar
  6. Barker, A. M., A. P. Nosal, E. A. Lewallen & R. S. Burton, 2015. Genetic structure of leopard shark (Triakis semifasciata) populations along the Pacific coast of North America. Journal of Experimental Marine Biology and Ecology 472: 151–157.Google Scholar
  7. Beerli, P. & M. Palczewski, 2010. Unified framework to evaluate panmixia and migration direction among multiple sampling locations. Genetics 185: 313–326.Google Scholar
  8. Bester-van der Merwe, A. E., D. N. Bitalo, J. M. Cuevas, J. Ovenden, S. Hernández, C. da Silva, M. E. McCord & R. Roodt-Wilding, 2017. Population genetics of southern hemisphere tope shark (Galeorhinus galeus): intercontinental divergence and constrained gene flow at different geographical scales. PLoS ONE 12: e0184481.Google Scholar
  9. Bitalo, D. N., S. N. Maduna, C. da Silva, R. Roodt-Wilding & A. E. Bester-van der Merwe, 2015. Differential gene flow patterns for two commercially exploited shark species, tope (Galeorhinus galeus) and common smoothhound (Mustelus mustelus) along the south-west coast of South Africa. Fisheries Research 172: 190–196.Google Scholar
  10. Bonfil, R., 2008. The Biology and Ecology of the Silky Shark, Carcharhinus falciformis. In Camhi, M. D., E. K. Pikitch & E. A. Babcock (eds), Sharks of the Open Ocean: Biology, Fisheries and Conservation. Fish and Aquatic Resources Series 13. Blackwell Publishing Ltd., Hoboken: 114–127.Google Scholar
  11. Boomer, J. J., R. G. Harcourt, M. P. Francis & A. J. Stow, 2012. Genetic divergence, speciation and biogeography of Mustelus (sharks) in the central Indo-Pacific and Australasia. Molecular Phylogenetics and Evolution 64: 697–703.Google Scholar
  12. Cavanagh, R. D. & C. Gibson, 2007. Overview of the Conservation Status of Cartilaginous Fishes (Chondrichthyans) in the Mediterranean Sea. IUCN, Gland, Switzerland and Malaga: 8–27.Google Scholar
  13. Chabot, C. L. & L. G. Allen, 2009. Global population structure of the tope (Galeorhinus galeus) inferred by mitochondrial control region sequence data. Molecular Ecology 18: 545–552.Google Scholar
  14. Chabot, C. L., M. Espinoza, I. Mascareñas-Osorio & A. Rocha-Olivares, 2015. The effect of biogeographic and phylogeographic barriers on gene flow in the brown smoothhound shark, Mustelus henlei, in the northeastern Pacific. Ecology and Evolution 5: 1585–1600.Google Scholar
  15. Charif, D. & J. R. Lobry, 2007. Seqin R 1.0-3: a contributed package to the R project for statistical computing devoted to biological sequences retrieval and analysis. Structural approaches to sequence evolution. Springer, Berlin, Heidelberg: 207–232.Google Scholar
  16. Clarke, S. C., M. K. McAllister, E. J. Milner-Gulland, G. P. Kirkwood, C. G. J. Michielsens, D. J. Agnew, E. K. Pikitch, H. Nakano & M. S. Shivji, 2006. Global estimates of shark catches using trade records from commercial markets. Ecology Letters 9: 1115–1126.Google Scholar
  17. Clarke, C. C., S. A. Karl, R. L. Horn, A. M. Bernard, J. S. Lea, F. H. Hazin, P. A. Prodöhl & M. S. Shivji, 2015. Global mitochondrial DNA phylogeography and population structure of the silky shark, Carcharhinus falciformis. Marine Biology 162: 945–955.Google Scholar
  18. Colloca, F., M. Enea, S. Ragonese & M. Di Lorenzo, 2017. A century of fishery data documenting the collapse of smoothhounds (Mustelus spp.) in the Mediterranean Sea. Aquatic Conservation: Marine and Freshwater Ecosystems 27: 1145–1155.Google Scholar
  19. Cornuet, J. M. & G. Luikart, 1996. Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144: 2001–2014.Google Scholar
  20. da Silva C., 2018. Biology, movement behaviour and spatial dynamics of an exploited population of smoothhound shark Mustelus mustelus around a coastal Marine Protected Area in South Africa. PhD Thesis, University of Cape Town.Google Scholar
  21. da Silva, C., S. E. Kerwath, C. G. Attwood, E. B. Thorstad, P. D. Cowley, F. Økland, C. G. Wilke & T. F. Næsje, 2013. Quantifying the degree of protection afforded by a no-take marine reserve on an exploited shark. African Journal of Marine Science 35: 57–66.Google Scholar
  22. da Silva, C., A. J. Booth, S. F. J. Dudley, S. E. Kerwath, S. J. Lamberth, R. W. Leslie, M. E. McCord, W. H. H. Sauer & T. Zweig, 2015. The current status and management of South Africa’s chondrichthyan fisheries. African Journal of Marine Science 37: 233–248.Google Scholar
  23. Darriba, D., G. L. Taboada, R. Doallo & D. Posada, 2012. JMODELTEST 2: more models, new heuristics and parallel computing. Nature Methods 9: 772.Google Scholar
  24. Dent, F. & S. Clarke, 2015. State of the global market for shark products. Food and Agriculture Organization of the United Nations, Rome.Google Scholar
  25. Diop, M. & J. Dossa, 2011. 30 years of shark fishing in West Africa: development of fisheries, catch trends, and their conservation status in sub-regional fishing commission member countries. Report to FIBA. http://www.iucnssg.org/tl_files/Assets/Regional%20files/West%20Africa/30years_eng.pdf. Accessed 17 Dec 2017.
  26. Djakouré, S., P. Penven, B. Bourlès, V. Koné & J. Veitch, 2017. Respective roles of the Guinea Current and local winds on the coastal upwelling in the northern Gulf of Guinea. Journal of Physical Oceanography 47: 1367–1387.Google Scholar
  27. Dudgeon, C. L., D. Broderick & J. R. Ovenden, 2009. IUCN classification zones concord with, but underestimate, the population genetic structure of the zebra shark Stegostoma fasciatum in the Indo-West Pacific. Molecular Ecology 18: 248–261.Google Scholar
  28. Dulvy, N. K., S. L. Fowler, J. A. Musick, R. D. Cavanagh, P. M. Kyne, L. R. Harrison, J. K. Carlson, L. N. K. Davidson, S. V. Fordham & M. P. Francis, 2014. Extinction risk and conservation of the world’s sharks and rays. eLife 3: e00590.Google Scholar
  29. Duncan, K. M., A. P. Martin, B. W. Bowen & H. G. De Couet, 2006. Global phylogeography of the scalloped hammerhead shark (Sphyrna lewini). Molecular Ecology 15: 2239–2251.Google Scholar
  30. Evanno, G., S. Regnaut & J. Goudet, 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14: 2611–2620.Google Scholar
  31. Excoffier, L. & H. E. L. Lischer, 2010. ARLEQUIN suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10: 564–567.Google Scholar
  32. Farrell, E. D., M. Clarke & S. Mariani, 2009. A simple genetic identification method for north-east Atlantic smoothhound sharks (Mustelus spp.). ICES Journal of Marine Science 66: 561–565.Google Scholar
  33. Ferrer I., S. Bonanomi, F. Colloca, M. Di Lorenzo, I.A.M. Marino, A. Sala, L. Zane & C. Mazzoldi, 2017. Genetic ID and preliminary population genetics of two threatened smoothhound sharks: insights for conservation. In: Euromarine Workshop, 23–25 May 2017, Venice, Italy.Google Scholar
  34. Graves, J. E., 1998. Molecular insight into the population structure of cosmopolitan marine fishes. Journal of Heredity 89: 427–437.Google Scholar
  35. Hoelzel, A. R., M. S. Shivji, J. Magnussen & M. P. Francis, 2006. Low worldwide genetic diversity in the basking shark (Cetorhinus maximus). Biology Letters 2: 639–642.Google Scholar
  36. Jost, L., 2008. GST and its relatives do not measure differentiation. Molecular Ecology 17: 4015–4026.Google Scholar
  37. Kalinowski, S. T., 2005. HP-RARE 1.0: a computer program for performing rarefaction on measures of allelic richness. Molecular Ecology Notes 5: 187–189.Google Scholar
  38. Keeney, D. B., M. R. Heupel, R. E. Hueter & E. J. Heist, 2005. Microsatellite and mitochondrial DNA analyses of the genetic structure of blacktip shark (Carcharhinus limbatus) nurseries in the northwestern Atlantic, Gulf of Mexico, and Caribbean Sea. Molecular Ecology 14: 1911–1923.Google Scholar
  39. Kopelman, N. M., J. Mayzel, M. Jakobsson, N. A. Rosenberg & I. Mayrose, 2015. CLUMPAK: a program for identifying clustering modes and packaging population structure inferences across K. Molecular Ecology Resources 15: 1179–1191.Google Scholar
  40. Kousteni, V., P. Kasapidis, G. Kotoulas & P. Megalofonou, 2015. Strong population genetic structure and contrasting demographic histories for the small-spotted catshark (Scyliorhinus canicula) in the Mediterranean Sea. Heredity 114: 333–343.Google Scholar
  41. Kumar, S., G. Stecher & K. Tamura, 2016. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution 33: 1870–1874.Google Scholar
  42. Li, Y. L. & J. X. Liu, 2018. STRUCTURESELECTOR: a web-based software to select and visualize the optimal number of clusters using multiple methods. Molecular Ecology Resources 18: 176–177.Google Scholar
  43. Librado, P. & J. Rozas, 2009. DNASP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452.Google Scholar
  44. Maduna, S. N., C. da Silva, S. P. Wintner, R. Roodt-Wilding & A. E. Bester-van der Merwe, 2016. When two oceans meet: regional population genetics of an exploited coastal shark, Mustelus mustelus. Marine Ecology Progress Series 544: 183–196.Google Scholar
  45. Maduna, S. N., C. Rossouw, C. da Silva, M. Soekoe & A. E. Bester-van der Merwe, 2017. Species identification and comparative population genetics of four coastal houndsharks based on novel NGS-mined microsatellites. Ecology and Evolution 7: 1462–1486.Google Scholar
  46. Mann, B. Q. & E. M. Bullen, 2009. ORI/WWF-SA Tagging Project: Summary of Tag and Recapture Data for Smoothhoundsharks (Mustelus mustelus) Caught Along the Southern African Coast from 1984 to 2008. Oceanographic Research Institute, Durban.Google Scholar
  47. Mantel, N., 1967. The detection of disease clustering and a generalized regression approach. Cancer Research 27: 1183–1185.Google Scholar
  48. Marino, I. A. M., E. Riginella, A. Cariani, F. Tinti, E. D. Farrell, C. Mazzoldi & L. Zane, 2014. New molecular tools for the identification of 2 endangered smoothhound sharks, Mustelus mustelus and Mustelus punctulatus. Journal of Heredity 106: 123–130.Google Scholar
  49. Marino, I. A. M., L. Finotto, F. Colloca, M. Di Lorenzo, M. Gristina, E. D. Farrell, L. Zane & C. Mazzoldi, 2017. Resolving the ambiguities in the identification of two smooth-hound sharks (Mustelus mustelus and Mustelus punctulatus) using genetics and morphology. Marine Biodiversity 48: 1551–1562.Google Scholar
  50. Mazzoldi, C., A. Sambo & E. Riginella, 2014. The Clodia database: a long time series of fishery data from the Adriatic Sea. Science Data 1: 140018.Google Scholar
  51. Meeuwis, J. & J. Lutjeharms, 1990. Surface thermal characteristics of the Angola-Benguela front. South African Journal of Marine Science 9: 261–279.Google Scholar
  52. Momigliano, P., R. Harcourt, W. D. Robbins, V. Jaiteh, G. N. Mahardika, A. Sembiring & A. Stow, 2017. Genetic structure and signatures of selection in grey reef sharks (Carcharhinus amblyrhynchos). Heredity 119: 142.Google Scholar
  53. Orlic, M., M. Gacic & P. Laviolette, 1992. The currents and circulation of the Adriatic Sea. Oceanologica Acta 15: 109–124.Google Scholar
  54. Ovenden, J. R., 2013. Crinkles in connectivity: combining genetics and other types of biological data to estimate movement and interbreeding between populations. Marine Freshwater Research 64: 201–207.Google Scholar
  55. Paradis, E., J. Claude & K. Strimmer, 2004. Ape: analyses of phylogenetics and evolution in R language. Bioinformatics 20: 289–290.Google Scholar
  56. Park S., 2001. The Excel Microsatellite toolkit (version 3.1.1). Animal Genomics Laboratory: University College, Dublin.Google Scholar
  57. Peakall, R. & P. E. Smouse, 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288–295.Google Scholar
  58. Pennings, P. S., A. Achenbach & S. Foitzik, 2011. Similar evolutionary potentials in an obligate ant parasite and its two host species. Journal of Evolutionary Biology 24: 871–886.Google Scholar
  59. Pereyra, S., G. García, P. Miller, S. Oviedo & A. Domingo, 2010. Low genetic diversity and population structure of the narrownose shark (Mustelus schmitti). Fisheries Research 106: 468–473.Google Scholar
  60. Pritchard, J. K., M. Stephens & P. Donnelly, 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945–959.Google Scholar
  61. Puechmaille, S. J., 2016. The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem. Molecular Ecology Resources 16: 608–627.Google Scholar
  62. Ronquist, F., M. Teslenko, P. Van Der Mark, D. L. Ayres, A. Darling, S. Höhna, B. Larget, L. Liu, M. A. Suchard & J. P. Huelsenbeck, 2012. MRBAYES 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61: 539–542.Google Scholar
  63. Rousset, F., 2008. GENEPOP’007: a complete re-implementation of the genepop software for Windows and Linux. Molecular Biology and Evolution 8: 103–106.Google Scholar
  64. Saidi, B., M. N. Bradaï & A. Bouaïn, 2008. Reproductive biology of the smooth-hound shark Mustelus mustelus (L.) in the Gulf of Gabès (south-central Mediterranean Sea). Journal of Fish Biology 72: 1343–1354.Google Scholar
  65. Sambrook, J. & D. W. Russell, 2001. Molecular cloning: a laboratory manual. Cold Spring Harbour Laboratory Press, New York.Google Scholar
  66. Schmidt, J. V., C. L. Schmidt, F. Ozer, R. E. Ernst, K. A. Feldheim, M. V. Ashley & M. Levine, 2009. Low genetic differentiation across three major ocean populations of the whale shark, Rhincodon typus. PLoS ONE 4: e4988.Google Scholar
  67. Schultz, J. K., K. A. Feldheim, S. H. Gruber, M. V. Ashley, T. M. McGovern & B. W. Bowen, 2008. Global phylogeography and seascape genetics of the lemon sharks (genus Negaprion). Molecular Ecology 17: 5336–5348.Google Scholar
  68. Serena F., C. Mancusi, S. Clò, J. Ellis & S.V. Valenti, 2009. Mustelus mustelus (Common smoothhound). The IUCN Red List of Threatened Species. http://www.iucnredlist.org/details/39358/0. Accessed 6 Feb 2017.
  69. Simpfendorfer, C. & M. Heupel, 2004. Assessing Habitat Use and Movement. In Carrier, J. C., J. A. Musick & M. R. Heithaus (eds), Biology of Sharks and Their Relatives. CRC Press, Boca Raton: 553–572.Google Scholar
  70. Smale, M. J. & L. J. V. Compagno, 1997. Life history and diet of two southern African smoothhound sharks, Mustelus mustelus (Linnaeus, 1758) and Mustelus palumbes Smith, 1957 (Pisces: Triakidae). South African Journal of Marine Science 18: 229–248.Google Scholar
  71. Stevens, J. D., R. Bonfil, N. K. Dulvy & P. A. Walker, 2000. The effects of fishing on sharks, rays, and chimaeras (chondrichthyans), and the implications for marine ecosystems. ICES Journal of Marine Science 57: 476–494.Google Scholar
  72. Teske, P. R., T. R. Golla, J. Sandoval-Castillo, A. Emami-Khoyi, C. D. van der Lingen, S. von der Heyden, B. Chiazzari, B. J. van Vuuren & L. B. Beheregaray, 2018. Mitochondrial DNA is unsuitable to test for isolation by distance. Scientific Reports 8: 8448.Google Scholar
  73. Ukwe, C. N., C. A. Ibe & K. Sherman, 2006. A sixteen-country mobilization for sustainable fisheries in the Guinea current large marine ecosystem. Ocean and Coastal Management 49: 385–412.Google Scholar
  74. Van Oosterhout, C., W. F. Hutchinson, D. P. M. Will & P. Shipley, 2004. MICROCHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4: 535–538.Google Scholar
  75. Veríssimo, A., Í. Sampaio, J. R. McDowell, P. Alexandrino, G. Mucientes, N. Queiroz, C. da Silva, C. S. Jones & L. R. Noble, 2017. World without borders—genetic population structure of a highly migratory marine predator, the blue shark (Prionace glauca). Ecology and Evolution 7: 4768–4781.Google Scholar
  76. Vignaud, T. M., E. Clua, J. Mourier, J. A. Maynard & S. Planes, 2013. Microsatellite analyses of blacktip reef sharks (Carcharhinus melanopterus) in a fragmented environment show structured clusters. PloS ONE 8: e61067.Google Scholar
  77. Vignaud, T. M., J. Mourier, J. A. Maynard, R. Leblois, J. L. Spaet, E. Clua, V. Neglia & S. Planes, 2014. Blacktip reef sharks, Carcharhinus melanopterus, have high genetic structure and varying demographic histories in their Indo-Pacific range. Molecular Ecology 23: 5193–5207.Google Scholar
  78. White, C., K. A. Selkoe, J. Watson, D. A. Siegel, D. C. Zacherl & R. J. Toonen, 2010. Ocean currents help explain population genetic structure. Proceedings of the Royal Society B: Biological Sciences 277: 1685–1694.Google Scholar
  79. Wright, S., 1943. Isolation by distance. Genetics 28: 114–138.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kelvin L. Hull
    • 1
    Email author
  • Tamaryn A. Asbury
    • 1
  • Charlene da Silva
    • 2
  • Matthew Dicken
    • 3
    • 4
  • Ana Veríssimo
    • 5
    • 6
  • Edward D. Farrell
    • 7
  • Stefano Mariani
    • 8
  • Carlotta Mazzoldi
    • 9
  • Ilaria A. M. Marino
    • 9
  • Lorenzo Zane
    • 9
    • 10
  • Simo N. Maduna
    • 1
  • Aletta E. Bester-van der Merwe
    • 1
    Email author
  1. 1.Molecular Breeding and Biodiversity Group, Department of GeneticsStellenbosch UniversityStellenboschSouth Africa
  2. 2.Department of Agriculture, Forestry and Fisheries, Fisheries ResearchRogge BayCape TownSouth Africa
  3. 3.KwaZulu-Natal Sharks BoardUmhlanga RocksSouth Africa
  4. 4.Department of Development Studies, School of Economics, Development and TourismNelson Mandela Metropolitan UniversityPort ElizabethSouth Africa
  5. 5.CIBIO – U.P. – Research Center for Biodiversity and Genetic ResourcesVairãoPortugal
  6. 6.Virginia Institute of Marine ScienceCollege of William and MaryGloucester PointUSA
  7. 7.School of Biology and Environmental Science, Science Centre WestUniversity College DublinDublin 4Ireland
  8. 8.School of Environment and Life SciencesUniversity of SalfordGreater ManchesterEngland, UK
  9. 9.Department of BiologyUniversity of PadovaPaduaItaly
  10. 10.Consorzio Nazionale Interuniversitario per le Scienze delMare (CoNISMa)RomeItaly

Personalised recommendations