Connectivity in grey reef sharks (Carcharhinus amblyrhynchos) determined using empirical and simulated genetic data

Scientific Reports

Volumn 5, Issue , 2015, Pages

  Momigliano, Paolo ^a,b   Harcourt, Robert ^a   Robbins, William D ^c,d   Stow, Adam ^a  

^a MACQUARIE UNIVERSITY   (Australia)

^b SYDNEY INSTITUTE OF MARINE SCIENCE   (Australia)

^c JAMES COOK UNIVERSITY   (Australia)

^d Wildlife Marine ^*  (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; COMPUTER SIMULATION; CONFIDENCE INTERVAL; CORAL REEF; DISCRIMINANT ANALYSIS; GENETIC VARIATION; GENETICS; POPULATION MIGRATION; PRINCIPAL COMPONENT ANALYSIS; SAMPLE SIZE; SHARK;

ANIMAL MIGRATION; ANIMALS; COMPUTER SIMULATION; CONFIDENCE INTERVALS; CORAL REEFS; DISCRIMINANT ANALYSIS; GENETIC VARIATION; PRINCIPAL COMPONENT ANALYSIS; SAMPLE SIZE; SHARKS;

EID: 84940525816     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep13229     Document Type: Article

References (75)

1. Heithaus, M. R., Frid, A., Wirsing, A. J. & Worm, B. Predicting ecological consequences of marine top predator declines. Trends Ecol. Evol. 23, 202-210 (2008).
2. Myers, R. A., Baum, J. K., Shepherd, T. D., Powers, S. P. & Peterson, C. H. Cascading effects of the loss of apex predatory sharks from a coastal ocean. Science 315, 1846-1850 (2007).
3. Bascompte, J., Melian, C. J. & Sala, E. Interaction strength combinations and the overfishing of a marine food web. Proc. Natl. Acad. Sci. USA 102, 5443-5447, doi: 10.1073/pnas.0501562102 (2005).
4. Wirsing, A. J., Heithaus, M. R., Frid, A. & Dill, L. M. Seascapes of fear: evaluating sublethal predator effects experienced and generated by marine mammals. Mar. Mamm. Sci. 24, 1-15 (2008).
5. Ruppert, J. L., Travers, M. J., Smith, L. L., Fortin, M.-J. & Meekan, M. G. Caught in the middle: combined impacts of shark removal and coral loss on the fish communities of coral reefs. PloS one 8, e74648 (2013).
6. Estes, J. A. & Duggins, D. O. Sea otters and kelp forests in Alaska: generality and variation in a community ecological paradigm. Ecol. Monogr. 65, 75-100, doi: 10.2307/2937159 (1995).
7. Mourier, J., Planes, S. & Buray, N. Trophic interactions at the top of the coral reef food chain. Coral Reefs 32, 285-285 (2013).
8. Heupel, M. R., Knip, D. M., Simpfendorfer, C. A. & Dulvy, N. K. O. Mar. Ecol. Prog. Ser. 495, 291-298 (2014).
9. Friedlander, A. M. et al. The real bounty: marine biodiversity in the Pitcairn Islands. PloS one 9, e100142 (2014).
10. Sandin, S. A. et al. Baselines and degradation of coral reefs in the northern Line Islands. PloS one 3, e1548 (2008).
11. Stevenson, C. et al. High apex predator biomass on remote Pacific islands. Coral Reefs 26, 47-51, doi: 10.1007/s00338-006-0158-x (2007).
12. Robbins, W. D. Abundance, demography and population structure of the grey reef shark (Carcharhinus amblyrhynchos) and the whitetip reef shark (Triaenodon obesus)(Fam. Charcharhinidae) Doctoral dissertation thesis. James Cook University, (2006).
13. Chin, A., Simpfendorfer, C., Tobin, A. & Heupel, M. Validated age, growth and reproductive biology of Carcharhinus melanopterus, a widely distributed and exploited reef shark. Mar. Freshw. Res. 64, 965-975 (2013).
14. Hisano, M., Connolly, S. R. & Robbins, W. D. Population growth rates of reef sharks with and without fishing on the Great Barrier Reef: robust estimation with multiple models. PloS one 6, e25028 (2011).
15. Chin, A., Tobin, A., Simpfendorfer, C. & Heupel, M. Reef sharks and inshore habitats: patterns of occurrence and implications for vulnerability. Mar. Ecol. Prog. Ser. 460, 115-125 (2012).
16. Rizzari, J. R., Frisch, A. J. & Magnenat, K. A. Diversity, abundance, and distribution of reef sharks on outer-shelf reefs of the Great Barrier Reef, Australia. Mar. Biol. 161, 2847-2855 (2014).
17. Chin, A., Kyne, P. M., Walker, T. I. & McAuley, R. An integrated risk assessment for climate change: analysing the vulnerability of sharks and rays on Australia's Great Barrier Reef. Global Change Biology 16, 1936-1953 (2010).
18. Hughes, T. P. Catastrophes, phase shifts, and large-scale degradation of a Caribbean coral reef. Science 265, 1547-1547 (1994).
19. Fabricius, K. E. Effects of terrestrial runoff on the ecology of corals and coral reefs: review and synthesis. Mar. Pollut. Bull. 50, 125-146 (2005).
20. Fabricius, K. E. et al. Losers and winners in coral reefs acclimatized to elevated carbon dioxide concentrations. Nature Climate Change 1, 165-169 (2011).
21. Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737-1742 (2007).
22. Graham, N. A., Spalding, M. D. & Sheppard, C. R. Reef shark declines in remote atolls highlight the need for multi-faceted conservation action. Aquat. Conserv. 20, 543-548 (2010).
23. Rizzari, J. R., Frisch, A. J. & Connolly, S. R. How robust are estimates of coral reef shark depletion? Biol. Conserv. 176, 39-47 (2014).
24. Robbins, W. D., Hisano, M., Connolly, S. R. & Choat, J. H. Ongoing collapse of coral-reef shark populations. Curr. Biol. 16, 2314-2319 (2006).
25. Espinoza, M., Cappo, M., Heupel, M. R., Tobin, A. J. & Simpfendorfer, C. A. Quantifying shark distribution patterns and specieshabitat associations: implications of Marine Park Zoning. PloS one 9, e106885 (2014).
26. Heupel, M. R., Simpfendorfer, C. A. & Fitzpatrick, R. Large-scale movement and reef fidelity of grey reef sharks. PloS one 5, e9650 (2010).
27. Espinoza, M., Heupel, M. R., Tobin, A. & Simpfendorfer, C. Residency patterns and movements of grey reef sharks (Carcharhinus amblyrhynchos) in semi-isolated coral reef habitats. Mar. Biol. 162, 343-358, doi: 10.1007/s00227-014-2572-x (2015).
28. Almany, G. et al. Connectivity, biodiversity conservation and the design of marine reserve networks for coral reefs. Coral Reefs 28, 339-351 (2009).
29. Momigliano, P., Harcourt, R. & Stow, A. Conserving coral reef organisms that lack larval dispersal:are networks of Marine Protected Areas good enough? Frontiers in Marine Science 2:16, doi: 10.3389/fmars.2015.00016 (2015).
30. Horne, J. B., Momigliano, P., van Herwerden, L. & Newman, S. J. Murky waters: Searching for structure in genetically depauperate blue threadfin populations of Western Australia. Fisheries Research 146, 1-6 (2013).
31. Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).
32. Smouse, P. E., Peakall, R. & Gonzales, E. A heterogeneity test for fine-scale genetic structure. Mol. Ecol. 17, 3389-3400 (2008).
33. Ovenden, J. R. Crinkles in connectivity: combining genetics and other types of biological data to estimate movement and interbreeding between populations. Mar. Freshw. Res. 64, 201-207 (2013).
34. Stow, A., Sunnucks, P., Briscoe, D. & Gardner, M. The impact of habitat fragmentation on dispersal of Cunningham's skink (Egernia cunninghami): evidence from allelic and genotypic analyses of microsatellites. Mol. Ecol. 10, 867-878 (2001).
35. Epperson, B. Estimating dispersal from short distance spatial autocorrelation. Heredity 95, 7-15 (2005).
36. Vignaud, T., Clua, E., Mourier, J., Maynard, J. & Planes, S. Microsatellite analyses of blacktip reef sharks (Carcharhinus melanopterus) in a fragmented environment show structured clusters. PloS one 8, e61067 (2013).
37. Vignaud, T. M. et al. Blacktip reef sharks, Carcharhinus melanopterus, have high genetic structure and varying demographic histories in their Indo-Pacific range. Mol. Ecol. 23, 5193-5207 (2014).
38. Whitney, N. M., Robbins, W. D., Schultz, J. K., Bowen, B. W. & Holland, K. N. Oceanic dispersal in a sedentary reef shark (Triaenodon obesus): genetic evidence for extensive connectivity without a pelagic larval stage. J. Biogeogr. 39, 1144-1156 (2012).
39. Mourier, J. & Planes, S. Direct genetic evidence for reproductive philopatry and associated fine-scale migrations in female blacktip reef sharks (Carcharhinus melanopterus) in French Polynesia. Mol. Ecol. 22, 201-214 (2013).
40. Barnett, A., Abrantes, K. G., Seymour, J. & Fitzpatrick, R. Residency and spatial use by reef sharks of an isolated seamount and its implications for conservation. PloS one 7, e36574 (2012).
41. Field, I., Meekan, M., Speed, C., White, W. & Bradshaw, C. Quantifying movement patterns for shark conservation at remote coral atolls in the Indian Ocean. Coral Reefs 30, 61-71 (2011).
42. Edgar, G. J. et al. Global conservation outcomes depend on marine protected areas with five key features. Nature (2014).
43. Gratwicke, B. & Speight, M. R. Effects of habitat complexity on Caribbean marine fish assemblages. Mar. Ecol. Prog. Ser. 292, 301-310 (2005).
44. Selig, E. R. & Bruno, J. F. A global analysis of the effectiveness of marine protected areas in preventing coral loss. PLoS ONE 5, e9278, doi: 10.1371/journal.pone.0009278 (2010).
45. McCook, L. J. et al. Adaptive management of the Great Barrier Reef: A globally significant demonstration of the benefits of networks of marine reserves. Proc. Natl. Acad. Sci. 107, 18278-18285 (2010).
46. Sweatman, H. No-take reserves protect coral reefs from predatory starfish. Curr. Biol. 18, R598-R599 (2008).
47. De'ath, G., Fabricius, K. E., Sweatman, H. & Puotinen, M. The 27-year decline of coral cover on the Great Barrier Reef and its causes. Proc. Natl. Acad. Sci. 109, 17995-17999, doi: 10.1073/pnas.1208909109 (2012).
48. Espinoza, M., Ledee, E. J., Simpfendorfer, C. A., Tobin, A. J. & Heupel, M. R. Contrasting movements and connectivity of reefassociated sharks using acoustic telemetry: implications for management. Ecol. Appl. (2015).
49. Parsons, G. Metabolism and swimming efficiency of the bonnethead shark Sphyrna tiburo. Mar. Biol. 104, 363-367 (1990).
50. Chin, A., Heupel, M. R., Simpfendorfer, C. A. & Tobin, A. J. Ontogenetic movements of juvenile blacktip reef sharks: evidence of dispersal and connectivity between coastal habitats and coral reefs. Aquat. Conserv. 23, 468-474, doi: 10.1002/aqc.2349 (2013).
51. Walsh, P. S., Metzger, D. A. & Higuchi, R. Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. BioTechniques 10, 506-513 (1991).
52. Arevalo, E., Davis, S. K. & Sites, J. W. Mitochondrial DNA sequence divergence and phylogenetic relationships among eight chromosome races of the Sceloporus grammicus complex (Phrynosomatidae) in central Mexico. Syst. Biol. 43, 387-418 (1994).
53. Inoue, J. G., Miya, M., Tsukamoto, K. & Nishida, M. Evolution of the Deep-Sea Gulper Eel Mitochondrial Genomes: Large-Scale Gene Rearrangements Originated Within the Eels. Mol. Biol. Evol. 20, 1917-1924, doi: 10.1093/molbev/msg206 (2003).
54. Momigliano, P., Robbins, W. D., Gardner, M. & Stow, A. Characterisation of 15 novel microsatellite loci for the grey reef shark (Carcharhinus amblyrhynchos). Conservation Genetics Resources, 6, 661-663, doi: 10.1007/s12686-014-0174-z (2014).
55. Portnoy, D., Mcdowell, J., Thompson, K., Musick, J. & Graves, J. Isolation and characterization of five dinucleotide microsatellite loci in the sandbar shark, Carcharhinus plumbeus. Mol. Ecol. Notes 6, 431-433 (2006).
56. Hall, T. A. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series 41, 95-98 (1999).
57. Librado, P. & Rozas, J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451-1452 (2009).
58. Excoffier, L. & Lischer, H. E. 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 (2010).
59. Matschiner, M. & Salzburger, W. TANDEM: integrating automated allele binning into genetics and genomics workflows. Bioinformatics 25, 1982-1983 (2009).
60. Raymond, M. & Rousset, F. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Hered. 86, 248-249 (1995).
61. Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. & Shipley, P. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535-538 (2004).
62. FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9. 3) ( Available from www.unil.ch/izea/ softwares/fstat.html, 2001).
63. Keenan, K., McGinnity, P., Cross, T. F., Crozier, W. W. & Prodohl, P. A. diveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors. Methods in Ecology and Evolution 4, 782-788 (2013).
64. Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution, 1358-1370 (1984).
65. Hedrick, P. W. A standardized genetic differentiation measure. Evolution 59, 1633-1638 (2005).
66. Jost, L. GST and its relatives do not measure differentiation. Mol. Ecol. 17, 4015-4026 (2008).
67. Meirmans, P. G. Using the AMOVA framework to estimate a standardized genetic differentiation measure. Evolution 60, 2399-2402 (2006).
68. Peakall, R. & Smouse, P. E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28, 2537-2539 (2012).
69. Jombart, T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403-1405 (2008).
70. Horne, J. B., Momigliano, P., Welch, D. J., Newman, S. J. & van Herwerden, L. Limited ecological population connectivity suggests low demands on self-recruitment in a tropical inshore marine fish (Eleutheronema tetradactylum: Polynemidae). Mol. Ecol. 20, 2291-2306 (2011).
71. Smouse, P. E. & Peakall, R. Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82, 561-573 (1999).
72. Peakall, R., Ruibal, M. & Lindenmayer, D. B. Spatial autocorrelation analysis offers new insights into gene flow in the Australian bush rat, Rattus fuscipes. Evolution 57, 1182-1195 (2003).
73. Balloux, F. EASYPOP (version 1.7): a computer program for population genetics simulations. J. Hered. 92, 301-302 (2001).
74. Frankham, R. Effective population size/adult population size ratios in wildlife: a review. Genet. Res. 66, 95-107 (1995).
75. R Core Team. R: A language and environment for statistical computing. http://www.R-project.org (2014).