Advertisement

Conservation Genetics

, Volume 18, Issue 5, pp 1151–1163 | Cite as

Genome-wide SNPs reveal low effective population size within confined management units of the highly vagile Galapagos shark (Carcharhinus galapagensis)

  • Diana A. PazmiñoEmail author
  • Gregory E. Maes
  • Colin A. Simpfendorfer
  • Pelayo Salinas-de-León
  • Lynne van Herwerden
Research Article

Abstract

The Galapagos shark (Carcharhinus galapagensis) is one of over thirty shark species inhabiting the Galápagos Marine Reserve (GMR), where it is a priority species for conservation. Identifying stock structure and effective population size for species-specific management and effective conservation of this top predator is important. We examined stock structure, connectivity and effective population size of Galapagos sharks among GMR locations using genome-wide neutral Single Nucleotide Polymorphism (8103 SNP) and mtDNA markers. Potential historical gene flow and/or sex-biased dispersal were also examined using the mitochondrial control region (997 bp). Cluster analyses of neutral SNPs revealed two differentiated stocks in the GMR—a western (Isabela Island) and eastern (San Cristóbal and Santa Cruz Islands) stock. Effective population size (Ne) estimates of approximately 200 suggest these populations are susceptible to ongoing natural and anthropogenic stressors and are of concern for long term resilience of populations. Mitochondrial DNA failed to identify distinct stocks, with AMOVA analyses indicating most genetic variation occurs within, rather than among locations. This pattern of genome-wide nuclear (but not mtDNA) discrimination among neighbouring islands either points to possible sex-biased dispersal by females or identifies limitations of the single organelle mtDNA marker at such small spatial scales. Regional differences across the archipelago or in behaviour may be implicated in the observed population structure. Further research focusing on a larger, Pacific wide analysis of population connectivity and effective population size at a broader spatial scale is required, to estimate the extent of discreteness and potential local adaptation. Potential adaptive units (AUs) in Galapagos sharks should ultimately be identified to leverage adaptive management and fisheries forensics applications.

Keywords

DArTSeq SNPs Management units Connectivity Ne Fisheries Galapagos Marine Protected Area 

Notes

Acknowledgements

We are extremely grateful to M Pazmiño, E Espinosa, F Córdova, LR Nieto, E Noboa, B Noboa, W Buenaño, C Tomalá, M Córdova, and other fishermen and field assistants who generously cooperated with us during sample collection. Special thanks to the Galápagos National Park for their support with samples and permits to collect and export samples from the Galápagos Islands (permit number 065-2013PNG). For laboratory, analytical, and logistic support we thank M Green, R Basita, DA Ortiz, D Alarcón, NA Andrade and M Hirschfeld. We thank the Ecuadorian Government, who funded this research through the National Secretary of Higher Education, Science and Technology (SENESCYT) scholarship; and to EcoCiencia foundation, which funded part of the project by an EcoFondo grant.

Supplementary material

10592_2017_967_MOESM1_ESM.docx (1.6 mb)
Supplementary material 1 (DOCX 1667 KB)
10592_2017_967_MOESM2_ESM.pdf (309 kb)
Supplementary material 2 (PDF 309 KB)

References

  1. Allendorf FW, Hohenlohe PA, Luikart G (2010) Genomics and the future of conservation genetics. Nat Rev Genet 11:697–709. doi: 10.1038/nrg2844 CrossRefPubMedGoogle Scholar
  2. Antao T, Lopes A, Lopes RJ, et al (2008) LOSITAN: A workbench to detect molecular adaptation based on a Fst-outlier method. BMC Bioinform 9:323. doi: 10.1186/1471-2105-9-323 CrossRefGoogle Scholar
  3. Antao T, Pérez-Figueroa A, Luikart G (2011) Early detection of population declines: high power of genetic monitoring using effective population size estimators. Evol Appl 4:144–154. doi: 10.1111/j.1752-4571.2010.00150.x CrossRefPubMedGoogle Scholar
  4. Barbieri M, Maltagliati F, Roldán MI, Castelli A (2014) Molecular contribution to stock identification in the small-spotted catshark, Scyliorhinus canicula (Chondrichthyes, Scyliorhinidae). Fish Res 154:11–16. doi: 10.1016/j.fishres.2014.01.021 CrossRefGoogle Scholar
  5. Baum JK, Myers RA, Kehler DG et al (2003) Collapse and conservation of shark populations in the northwest Atlantic. Science 299:389–392. doi: 10.1126/science.1079777 CrossRefPubMedGoogle Scholar
  6. Belkhir K, Borsa P, Chikhi L, et al (2004) GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations.Google Scholar
  7. Bennett M, Gordon I, Kyne PM (2003) SSG Australia & Oceania regional rorkshop, March 2003. Carcharhinus galapagensis. The IUCN Red List of Threatened Species. Version 2014.1. http://www.iucnredlist.org
  8. Bensted-Smith R (2002) A biodiversity vision for the Galapagos Islands. In: Danulat E, Edgar GJ (eds) Reserva Marina de Galápagos. Línea base de la biodiversidad. Fundación Charles Darwin, Galápagos, Ecuador, pp 60–69Google Scholar
  9. Blower DC, Riginos CR, Ovenden JR (in preparation) NeOGen: a tool to predict genetic effective population size (Ne) for low-fecundity, slowly-maturing, iteroparous species, and to assist empirical Ne study designGoogle Scholar
  10. Camhi M, Fowler S, Musick JA, et al (1998) Sharks and their relatives: ecology and conservation. IUCNSSC Shark Spec Group IUCN Gland Switz Camb UK iv-39.Google Scholar
  11. Carreras-Carbonell J, Macpherson E, Pascual M (2006) Population structure within and between subspecies of the Mediterranean triplefin fish Tripterygion delaisi revealed by highly polymorphic microsatellite loci. Mol Ecol 15:3527–3539. doi: 10.1111/j.1365-294X.2006.03003.x CrossRefPubMedGoogle Scholar
  12. Compagno LJ (1984) FAO species catalogue, Sharks of the world: an annotated and illustrated catalogue of shark species known to date. Part 2. Carcharhiniformes. FAO Fish Synop 125:251–655Google Scholar
  13. Cortés E (2000) Life history patterns and correlations in sharks. Rev Fish Sci 8:299–344. doi: 10.1080/10408340308951115 CrossRefGoogle Scholar
  14. Do C, Waples RS, Peel D, et al (2014) NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol Ecol Resour 14:209–214. doi: 10.1111/1755-0998.12157 CrossRefPubMedGoogle Scholar
  15. Dulvy NK, Baum JK, Clarke S et al (2008) You can swim but you can’t hide: the global status and conservation of oceanic pelagic sharks and rays. Aquat Conserv Mar Freshw Ecosyst 18:459–482. doi: 10.1002/aqc.975 CrossRefGoogle Scholar
  16. Dulvy NK, Fowler SL, Musick JA et al (2014) Extinction risk and conservation of the world’s sharks and rays. eLife 3:e00590. doi: 10.7554/eLife.00590 CrossRefPubMedPubMedCentralGoogle Scholar
  17. Duncan KM, Martin AP, Bowen BW, De Couet HG (2006) Global phylogeography of the scalloped hammerhead shark (Sphyrna lewini). Mol Ecol 15:2239–2251. doi: 10.1111/j.1365-294X.2006.02933.x CrossRefPubMedGoogle Scholar
  18. Earl DA, vonHoldt BM (2011) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361. doi: 10.1007/s12686-011-9548-7 CrossRefGoogle Scholar
  19. Edgar GJ, Banks S, Fariña JM et al (2004) Regional biogeography of shallow reef fish and macro-invertebrate communities in the Galapagos archipelago. J Biogeogr 31:1107–1124. doi: 10.1111/j.1365-2699.2004.01055.x CrossRefGoogle Scholar
  20. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620. doi: 10.1111/j.1365-294X.2005.02553.x CrossRefPubMedGoogle Scholar
  21. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491PubMedPubMedCentralGoogle Scholar
  22. Excoffier L, Laval G, Schneider SS (2005) Arlequin (version 3.0): An integrated software package for population genetics data analysisGoogle Scholar
  23. Franklin IR, Frankham R (1998) How large must populations be to retain evolutionary potential? Anim Conserv 1:69–70. doi: 10.1111/j.1469-1795.1998.tb00228.x CrossRefGoogle Scholar
  24. Garber AF, Tringali MD, Franks JS (2005) Population genetic and phylogeographic structure of wahoo, Acanthocybium solandri, from the western central Atlantic and central Pacific Oceans. Mar Biol 147:205–214. doi: 10.1007/s00227-004-1533-1 CrossRefGoogle Scholar
  25. Garvin MR, Saitoh K, Gharrett AJ (2010) Application of single nucleotide polymorphisms to non-model species: a technical review. Mol Ecol Resour 10:915–934. doi: 10.1111/j.1755-0998.2010.02891.x CrossRefPubMedGoogle Scholar
  26. Gilbert KJ, Whitlock MC (2015) Evaluating methods for estimating local effective population size with and without migration. Evolution Int J org Evolution 69:2154–2166. doi: 10.1111/evo.12713 CrossRefGoogle Scholar
  27. Grant WAS, Bowen BW (1998) Shallow population histories in deep evolutionary lineages of marine fishes: insights from sardines and anchovies and lessons for conservation. J Hered 89:415–426. doi: 10.1093/jhered/89.5.415 CrossRefGoogle Scholar
  28. Grewe PM, Feutry P, Hill PL et al (2015) Evidence of discrete yellowfin tuna (Thunnus albacares) populations demands rethink of management for this globally important resource. Sci Rep 5:16916. doi: 10.1038/srep16916 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Hare MP, Nunney L, Schwartz MK et al (2011) Understanding and estimating effective population size for practical application in marine species management. Conserv Biol 25:438–449. doi: 10.1111/j.1523-1739.2010.01637.x CrossRefPubMedGoogle Scholar
  30. Hearn AR, Acuña D, Ketchum D et al (2014) Elasmobranchs of the Galapagos Marine Reserve. In: Denkinger J, Vinueza L (eds) The Galapagos Marine Reserve: a dynamic socio-ecological system. Springer, New York, pp 23–59CrossRefGoogle Scholar
  31. Heist EJ, Musick JA, Graves JE (1996) Genetic population structure of the shortfin mako (Isurus oxyrinchus) inferred from restriction fragment length polymorphism analysis of mitochondrial DNA. Can J Fish Aquat Sci 53:583–588. doi: 10.1139/f95-245 CrossRefGoogle Scholar
  32. Helyar SJ, Hemmer-Hansen J, Bekkevold D et al (2011) Application of SNPs for population genetics of nonmodel organisms: new opportunities and challenges. Mol Ecol Resour 11:123–136. doi: 10.1111/j.1755-0998.2010.02943.x CrossRefPubMedGoogle Scholar
  33. Heupel MR, Knip DM, Simpfendorfer CA, Dulvy NK (2014) Sizing up the ecological role of sharks as predators. Mar Ecol Prog Ser 495:291–298. doi: 10.3354/meps10597 CrossRefGoogle Scholar
  34. Heylings P, Bensted-Smith R, Altamirano M (2002) Zonificación e historia de la Reserva Marina de Galápagos. In: Danulat E, Edgar GK (eds) Reserva Marina de Galápagos Línea base de la biodiversidad. Fundación Charles Darwin/Parque Nacional Galápagos. Galápagos, Santa Cruz, pp 4–7Google Scholar
  35. Hill WG (1981) Estimation of effective population size from data on linkage disequilibrium. Genet Res 38:209–216. doi: 10.1017/S0016672300020553 CrossRefGoogle Scholar
  36. Houvenaghel GT (1978) Oceanographic conditions in the Galápagos Archipelago and their relationships with life on the islands. In: Boje R, Tomczak M (eds) Upwelling Ecosystems. Springer, Berlin, pp 181–200CrossRefGoogle Scholar
  37. Huelsenbeck JP, Ronquist F, Nielsen R, Bollback JP (2001) Bayesian inference of phylogeny and Its impact on evolutionary biology. Science 294:2310–2314CrossRefPubMedGoogle Scholar
  38. Jacquet J, Alava JJ, Pramod G et al (2008) In hot soup: sharks captured in Ecuador’s waters. Environ Sci 5:269–283. doi: 10.1080/15693430802466325 CrossRefGoogle Scholar
  39. Jennings S (2000) Patterns and prediction of population recovery in marine reserves. Rev Fish Biol Fish 10:209–231. doi: 10.1023/A:1016619102955 CrossRefGoogle Scholar
  40. Jombart T, Ahmed I (2011) adegenet 1.3–1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27:3070–3071. doi: 10.1093/bioinformatics/btr521 CrossRefPubMedPubMedCentralGoogle Scholar
  41. Kearse M, Moir R, Wilson A et al (2012) Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28:1647–1649. doi: 10.1093/bioinformatics/bts199 CrossRefPubMedPubMedCentralGoogle Scholar
  42. Keeney DB, Heupel M, Hueter RE, Heist EJ (2003) Genetic heterogeneity among blacktip shark, Carcharhinus limbatus, continental nurseries along the U.S. Atlantic and Gulf of Mexico. Mar Biol 143:1039–1046. doi: 10.1007/s00227-003-1166-9 CrossRefGoogle Scholar
  43. Keeney DB, Heupel MR, Hueter RE, Heist EJ (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. Mol Ecol 14:1911–1923. doi: 10.1111/j.1365-294X.2005.02549.x CrossRefPubMedGoogle Scholar
  44. Ketchum JT, Hearn A, Klimley AP et al (2014a) Seasonal changes in movements and habitat preferences of the scalloped hammerhead shark (Sphyrna lewini) while refuging near an oceanic island. Mar Biol 161:755–767. doi: 10.1007/s00227-013-2375-5 CrossRefGoogle Scholar
  45. Ketchum JT, Hearn A, Klimley AP et al (2014b) Inter-island movements of scalloped hammerhead sharks (Sphyrna lewini) and seasonal connectivity in a marine protected area of the eastern tropical Pacific. Mar Biol 161:939–951. doi: 10.1007/s00227-014-2393-y CrossRefGoogle Scholar
  46. Kohler NE, Casey JG, Turner PA (1998) NMFS cooperative shark tagging program, 1962–1993: an atlas of shark tag and recapture data. Mar Fish Rev 60:1–87Google Scholar
  47. Lamichhaney S, Barrio AM, Rafati N et al (2012) Population-scale sequencing reveals genetic differentiation due to local adaptation in Atlantic herring. Proc Natl Acad Sci U S A 109:19345–19350CrossRefPubMedPubMedCentralGoogle Scholar
  48. Lanfear R, Calcott B, Ho SYW, Guindon S (2012) PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses. Mol Biol Evol 29:1695–1701. doi: 10.1093/molbev/mss020 CrossRefPubMedGoogle Scholar
  49. Larson WA, Seeb LW, Everett MV et al (2014) Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha). Evol Appl 7:355–369. doi: 10.1111/eva.12128 CrossRefPubMedPubMedCentralGoogle Scholar
  50. Lischer HEL, Excoffier L (2012) PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28:298–299. doi: 10.1093/bioinformatics/btr642 CrossRefPubMedGoogle Scholar
  51. Luikart G, Ryman N, Tallmon DA et al (2010) Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches. Conserv Genet 11:355–373. doi:  10.1007/s10592-010-0050-7 CrossRefGoogle Scholar
  52. Lynch M, Lande R (1998) The critical effective size for a genetically secure population. Anim Conserv 1:70–72. doi: 10.1111/j.1469-1795.1998.tb00229.x CrossRefGoogle Scholar
  53. Martin AP, Naylor GJP, Palumbi SR (1992) Rates of mitochondrial DNA evolution in sharks are slow compared with mammals. Nature 357:153–155CrossRefPubMedGoogle Scholar
  54. Mcmillan WO, Palumbi SR (1995) Concordant evolutionary patterns among Indo-West Pacific butterflyfishes. Proc Biol Sci 260:229–236CrossRefPubMedGoogle Scholar
  55. Moura AE, Kenny JG, Chaudhuri R et al (2014) Population genomics of the killer whale indicates ecotype evolution in sympatry involving both selection and drift. Mol Ecol 23:5179–5192. doi: 10.1111/mec.12929 CrossRefPubMedPubMedCentralGoogle Scholar
  56. Murillo JC, Reyes H, Zárate P et al (2004) Evaluación de la captura incidental durante el plan piloto de pesca de altura con palangre en la Reserva Marina de Galápagos. Dirección del Parque Nacional GalápagosGoogle Scholar
  57. Nei M (1987) Genetic distance and molecular phylogeny. Popul Genet Fish Manag Seattle, USA, pp.193–223Google Scholar
  58. Nei M, Li WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Natl Acad Sci USA 76:5269–5273CrossRefPubMedPubMedCentralGoogle Scholar
  59. Newman D, Pilson D (1997) Increased probability of extinction due to decreased genetic effective population size: experimental populations of Clarkia pulchella. Evol Int J Org Evol 51:354–362. doi: 10.2307/2411107 CrossRefGoogle Scholar
  60. Nielsen EE, Hemmer-Hansen J, Poulsen NA et al (2009) Genomic signatures of local directional selection in a high gene flow marine organism; the Atlantic cod (Gadus morhua). BMC Evol Biol 9:276. doi: 10.1186/1471-2148-9-276 CrossRefPubMedPubMedCentralGoogle Scholar
  61. Ouborg NJ, Pertoldi C, Loeschcke V et al (2010) Conservation genetics in transition to conservation genomics. Trends Genet 26:177–187. doi: 10.1016/j.tig.2010.01.001 CrossRefPubMedGoogle Scholar
  62. Ovenden JR, Kashiwagi T, Broderick D et al (2009) The extent of population genetic subdivision differs among four co-distributed shark species in the Indo-Australian archipelago. BMC Evol Biol 9:40. doi: 10.1186/1471-2148-9-40 CrossRefPubMedPubMedCentralGoogle Scholar
  63. Palstra FP, Ruzzante DE (2008) Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence? Mol Ecol 17:3428–3447. doi: 10.1111/j.1365-294X.2008.03842.x CrossRefPubMedGoogle Scholar
  64. Palstra FP, O’connell MF, Ruzzante DE (2007) Population structure and gene flow reversals in Atlantic salmon (Salmo salar) over contemporary and long-term temporal scales: effects of population size and life history. Mol Ecol 16:4504–4522. doi: 10.1111/j.1365-294X.2007.03541.x CrossRefPubMedGoogle Scholar
  65. Pardini AT, Jones CS, Noble LR et al (2001) Sex-biased dispersal of great white sharks. Nature 412:139–140. doi:  10.1038/35084125 CrossRefPubMedGoogle Scholar
  66. Pilot M, Dahlheim ME, Hoelzel AR (2010) Social cohesion among kin, gene flow without dispersal and the evolution of population genetic structure in the killer whale (Orcinus orca). J Evol Biol 23:20–31. doi: 10.1111/j.1420-9101.2009.01887.x CrossRefPubMedGoogle Scholar
  67. Planes S, Fauvelot C (2002) Isolation by distance and vicariance drive genetic structure of a coral reef fish in the Pacific Ocean. Evol Int J org Evol 56:378–399CrossRefGoogle Scholar
  68. Portnoy DS, Mcdowell JR, Heist EJ et al (2010) World phylogeography and male-mediated gene flow in the sandbar shark, Carcharhinus plumbeus. Mol Ecol 19:1994–2010. doi: 10.1111/j.1365-294X.2010.04626.x CrossRefPubMedGoogle Scholar
  69. Portnoy DS, Puritz JB, Hollenbeck CM et al (2015) Selection and sex-biased dispersal in a coastal shark: the influence of philopatry on adaptive variation. Mol Ecol 24:5877–5885. doi: 10.1111/mec.13441 CrossRefPubMedGoogle Scholar
  70. Pritchard JK, Wen W (2003) Documentation for structure software: Version 2. http://pritch.bsd.uchicago.edu.elibrary.jcu.edu.au.
  71. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  72. Purcell S, Neale B, Todd-Brown K et al (2007) PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575CrossRefPubMedPubMedCentralGoogle Scholar
  73. R Development Core Team (2008) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna. http://www.R-project.org
  74. Rambaut A, Suchard MA, Xie D, Drummond A (2014) Tracer v1.6, http://beast.bio.ed.ac.uk/Tracer.
  75. Reyes H, Salinas-de-León P, Banda G et al (2014) Plan Piloto de Pesca de Altura con arte de pesca “Empate Oceanico Modificado” en la Reserva Marina de Galápagos. Dirección del Parque Nacional Galápagos, Puerto Ayora, GalapagosGoogle Scholar
  76. Rodríguez-Ramilo ST, Wang J (2012) The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis. Mol Ecol Resour 12:873–884. doi: 10.1111/j.1755-0998.2012.03156.x CrossRefPubMedGoogle Scholar
  77. Rus Hoelzel A, Shivji MS, Magnussen J, Francis MP (2006) Low worldwide genetic diversity in the basking shark (Cetorhinus maximus). Biol Lett 2:639–642. doi: 10.1098/rsbl.2006.0513 CrossRefPubMedPubMedCentralGoogle Scholar
  78. Salinas-de-León P, Acuña-Marrero D, Rastoin E et al (2016) Largest global shark biomass found in the northern Galápagos Islands of Darwin and Wolf. Peer J. doi: 10.7717/peerj.1911 PubMedPubMedCentralGoogle Scholar
  79. Sansaloni CP, Petroli CD, Carling J et al (2010) A high-density Diversity Arrays Technology (DArT) microarray for genome-wide genotyping in Eucalyptus. Plant Methods 6:16. doi: 10.1186/1746-4811-6-16 CrossRefPubMedPubMedCentralGoogle Scholar
  80. Sansaloni C, Petroli C, Jaccoud D et al (2011) Diversity Arrays Technology (DArT) and next-generation sequencing combined: genome-wide, high throughput, highly informative genotyping for molecular breeding of Eucalyptus. BMC Proc 5:54. doi: 10.1186/1753-6561-5-S7-P54 CrossRefGoogle Scholar
  81. Simpfendorfer CA (2000) Predicting population recovery rates for endangered western Atlantic sawfishes using demographic analysis. Environ Biol Fishes 58:371–377. doi: 10.1023/A:1007675111597 CrossRefGoogle Scholar
  82. Smoot ME, Ono K, Ruscheinski J et al (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27:431–432. doi: 10.1093/bioinformatics/btq675 CrossRefPubMedGoogle Scholar
  83. Steinig EJ, Neuditschko M, Khatkar MS et al (2016) Netview p: a network visualization tool to unravel complex population structure using genome-wide SNPs. Mol Ecol Resour 16:216–227. doi: 10.1111/1755-0998.12442 CrossRefPubMedGoogle Scholar
  84. Stevens JD, Bonfil R, Dulvy NK, Walker PA (2000) The effects of fishing on sharks, rays, and chimaeras (chondrichthyans), and the implications for marine ecosystems. ICES J Mar Sci J Cons 57:476–494. doi: 10.1006/jmsc.2000.0724 CrossRefGoogle Scholar
  85. Stow AJ, Zenger KR, Briscoe D et al (2006) Isolation and genetic diversity of endangered grey nurse shark (Carcharias taurus) populations. Biol Lett 2:308–311. doi: 10.1098/rsbl.2006.0441 CrossRefPubMedPubMedCentralGoogle Scholar
  86. Sundqvist L, Keenan K, Zackrisson M et al (2016) Directional genetic differentiation and asymmetric migration. Ecol Evol 6:3461–3475. doi: 10.1002/ece3.2096 CrossRefPubMedPubMedCentralGoogle Scholar
  87. Sunnucks P, Hales DF (1996) Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). Mol Biol Evol 13:510–524CrossRefPubMedGoogle Scholar
  88. Taguchi M, King JR, Wetklo M, et al (2015) Population genetic structure and demographic history of Pacific blue sharks (Prionace glauca) inferred from mitochondrial DNA analysis. Mar Freshw Res 66:267–275. doi: 10.1071/MF14075 CrossRefGoogle Scholar
  89. Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24:1596–1599. doi: 10.1093/molbev/msm092 CrossRefPubMedGoogle Scholar
  90. van Herwerden L, Almojil D, Choat H (2008) Population genetic structure of Australian Galápagos reef sharks Carcharhinus galapagensis at Elizabeth and Middleton Reefs Marine National Nature Reserve and Lord Howe Island Marine Park. Final report to the Department of the Environment, water, heritage and the arts. Queensland, AustraliaGoogle Scholar
  91. Walsh MR, Munch SB, Chiba S, Conover DO (2006) Maladaptive changes in multiple traits caused by fishing: impediments to population recovery. Ecol Lett 9:142–148. doi: 10.1111/j.1461-0248.2005.00858.x CrossRefPubMedGoogle Scholar
  92. Waples RS, Anderson EC (2017) Purging putative siblings from population genetic data sets: a cautionary view. Mol Ecol 26:1211–1224. doi: 10.1111/mec.14022 CrossRefPubMedGoogle Scholar
  93. Ward RD (2000) Genetics in fisheries management. Hydrobiologia 420:191–201. doi: 10.1023/A:1003928327503 CrossRefGoogle Scholar
  94. Wetherbee BM, Crow GL, Lowe CG (1996) Biology of the Galapagos shark, Carcharhinus galapagensis, in Hawaii. Environ Biol Fishes 45:299–310. doi: 10.1007/BF00003099 CrossRefGoogle Scholar
  95. White WM, McBirney AR, Duncan RA (1993) Petrology and geochemistry of the Galápagos Islands: portrait of a pathological mantle plume. J Geophys Res Solid Earth 98:19533–19563. doi: 10.1029/93JB02018 CrossRefGoogle Scholar
  96. Wolf JB, Harrod C, Brunner S et al (2008) Tracing early stages of species differentiation: ecological, morphological and genetic divergence of Galápagos sea lion populations. BMC Evol Biol 8:150. doi: 10.1186/1471-2148-8-150 CrossRefPubMedPubMedCentralGoogle Scholar
  97. Wolff M, Ruiz DJ, Taylor M (2012) El Niño induced changes to the bolivar channel ecosystem (Galapagos): comparing model simulations with historical biomass time series. Mar Ecol Prog Ser 448:7–22. doi: 10.3354/meps09542 CrossRefGoogle Scholar
  98. Zimmerhackel JS, Schuhbauer AC, Usseglio P et al (2015) Catch, bycatch and discards of the Galapagos Marine Reserve small-scale handline fishery. Peer J. doi: 10.7717/peerj.995 PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Diana A. Pazmiño
    • 1
    • 2
    Email author
  • Gregory E. Maes
    • 1
    • 2
    • 3
    • 4
  • Colin A. Simpfendorfer
    • 1
  • Pelayo Salinas-de-León
    • 5
    • 6
  • Lynne van Herwerden
    • 1
    • 2
  1. 1.Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and EngineeringJames Cook UniversityTownsvilleAustralia
  2. 2.Comparative Genomics Centre, College of Science and EngineeringJames Cook UniversityTownsvilleAustralia
  3. 3.Laboratory of Biodiversity and Evolutionary GenomicsUniversity of Leuven (KU Leuven)LeuvenBelgium
  4. 4.Laboratory for Cytogenetics and Genome Research, Center for Human GeneticsGenomics CoreLeuvenBelgium
  5. 5.Department of Marine SciencesCharles Darwin Research StationPuerto AyoraEcuador
  6. 6.Pristine Seas, National Geographic SocietyWashington, D.C.USA

Personalised recommendations