in

Connectivity and population structure of albacore tuna across southeast Atlantic and southwest Indian Oceans inferred from multidisciplinary methodology

  • 1.

    Collette, B. & Nauen, C. Scombrids of the world—An annotated and illustrated catalogue of tunas, mackerels, bonitos and related species known to date. FAO Sp. Cat 2, 137 (1983).

    Google Scholar 

  • 2.

    ISSF. ISSF Tuna Stock Status Update, 2015: Status of the world fisheries for tuna. ISSF Technical Report 2015-03A. (International Seafood Sustainability Foundation, Washington, D.C., 2015).

  • 3.

    FAO. The State of World Fisheries and Aquaculture 2012. (2012).

  • 4.

    ISSF. Status of the world fisheries for tuna. ISSF Technical Report. 2019-07. International Seafood Sustainability Foundation, Washington, D.C., USA. https://iss-foundation.org/knowledge-tools/technical-and-meeting-reports/ (2019).

  • 5.

    ICCAT. ICCAT Report of the 2016 ICCAT North and South Atlantic Albacore stock assessment meeting. N & S Atlantic ALB stock assessment meeting–Madeira 2016. (2016).

  • 6.

    IOTC. Albacore executive summary. Status summary for species of tuna and tuna-like species under the IOTC mandate, as well as other species impacted by IOTC fisheries. (2016).

  • 7.

    IOTC. Albacore executive summary. Status summary species tuna and tuna species under iotc mandate well other species impacted by iotc fisheries. (2018).

  • 8.

    Nikolic, N. et al. Review of albacore tuna, Thunnus alalunga, biology, fisheries and management. Rev. Fish. Biol. Fisheries. 27, 775–810 (2016).

    Article  Google Scholar 

  • 9.

    Arrizabalaga, H., Lopez-Rodas, V., Costas, E. & González-Garcás, A. Use of genetic data to assess the uncertainty in stock assessments due to the assumed stock structure: The case of albacore (Thunnus alalunga) from the Atlantic Ocean. Fish. Bull. 105(1), 140–146 (2007).

    Google Scholar 

  • 10.

    Chow, S. & Kishino, H. Phylogenetic relationships between tuna species of the genus Thunnus (Scombridae: Teleostei): Inconsistent implications from morphology, nuclear and mitochondrial genomes. J. Mol. Evol. 41, 741–748 (1995).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 11.

    Takagi, M., Okamura, T., Chow, S. & Taniguchi, N. Preliminary study of albacore (Thunnus alalunga) stock differentiation inferred from microsatellite DNA analysis. Fish. Bull. 99, 697–701 (2001).

    Google Scholar 

  • 12.

    Viñas, J., Bremer, J. A. & Pla, C. Inter-oceanic genetic differentiation among albacore (Thunnus alalunga) populations. Mar. Biol. 145, 225–232 (2004).

    Article  CAS  Google Scholar 

  • 13.

    Arrizabalaga, H. et al. Population structure of albacore, Thunnus alalunga, inferred from blood groups and tag recapture analyses. Mar. Ecol. Prog. Ser. 282, 245–252 (2004).

    ADS  Article  Google Scholar 

  • 14.

    Wu, G. C. C., Chiang, H. C., Chen, K. S., Hsu, C. C. & Yang, H. Y. Population structure of albacore (Thunnus alalunga) in the Northwestern Pacific Ocean inferred from mitochondrial DNA. Fish. Res. 95, 125–131 (2009).

    Article  Google Scholar 

  • 15.

    Davies, C. A., Gosling, E. M., Was, A., Brophy, D. & Tysklind, N. Microsatellite analysis of albacore tuna (Thunnus alalunga): Population genetic structure. Mar. Biol. 158, 2727–2740 (2011).

    Article  Google Scholar 

  • 16.

    Nikolic, N. & Bourjea, J. Differentiation of albacore stock: Review by oceanic regions. Collect. Vol. Sci. Pap. ICCAT 70(3), 1340–1354 (2014).

    Google Scholar 

  • 17.

    Pawson, M. G. & Jennings, S. A critique of methods for stock identification in marine capture fisheries. Fish. Res. 25, 203–217 (1996).

    Article  Google Scholar 

  • 18.

    Waldman, J. R. The importance of comparative studies in stock analysis. Fish. Res. 43, 237–246 (1999).

    Article  Google Scholar 

  • 19.

    Nielsen, E. E., Hemmer-Hansen, J., Larsen, P. F. & Bekkevold, D. Population genomics of marine fishes: Identifying adaptive variation in space and time. Mol. Ecol. 18, 3128–3150 (2009).

    PubMed  Article  Google Scholar 

  • 20.

    Waples, R. S. & Naish, K. A. Genetic and evolutionary considerations in fishery management: Research needs for the future. Future Fish. Sci. N. Am. 31, 427–451 (2009).

    Google Scholar 

  • 21.

    Montes, I. et al. Transcriptome analysis deciphers evolutionary mechanisms underlying genetic differentiation between coastal and offshore anchovy populations in the Bay of Biscay. Mar. Biol. 163, 205 (2016).

    Article  CAS  Google Scholar 

  • 22.

    Morita, S. On the relationship between the albacore stocks of the South Atlantic and Indian Oceans. Collect Vol. Sci. Pap. ICCAT 7, 232–237 (1977).

    Google Scholar 

  • 23.

    Gonzalez, E. G., Beerli, P. & Zardoya, R. Genetic structuring and migration patterns of Atlantic bigeye tuna, Thunnus obesus (Lowe, 1839). BMC Evol. Biol. 8, 252 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 24.

    Chow, S. & Ushiama, H. Global population structure of albacore (Thunnus alalunga) inferred by RFLP analysis of the mitochondrial ATPase gene. Mar. Biol. 123, 39–45 (1995).

    CAS  Article  Google Scholar 

  • 25.

    Graves, J. E. & Dizon, A. E. Mitochondrial DNA sequence similarity of Atlantic and Pacific albacore tuna (Thunnus alalunga). Can. J. Fish. Aquat. Sci. 46, 870–873 (1989).

    Article  Google Scholar 

  • 26.

    Viñas, J., Santiago, J. & Pla, C. Genetic characterization and Atlantic-Mediterranean stock structure of Albacore, Thunnus alalunga. Collect Vol. Sci. Pap. ICCAT. 49, 188–190 (1999).

    Google Scholar 

  • 27.

    Pujolar, J. M., Roldán, M. I. & Pla, C. Genetic analysis of tuna populations, Thunnus thynnus thynnus and T. alalunga. Mar. Biol. 3, 613–621 (2003).

    Article  Google Scholar 

  • 28.

    Nakadate, M. et al. Genetic isolation between Atlantic and Mediterranean albacore populations inferred from mitochondrial and nuclear DNA markers. J. Fish Biol. 66, 1545–1557 (2005).

    CAS  Article  Google Scholar 

  • 29.

    Abdul-Muneer, P. M. Application of microsatellite markers in conservation genetics and fisheries management: Recent advances in population structure analysis and conservation strategies. Genet. Res. Int. 2014, 691759 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  • 30.

    Albaina, A. et al. Single nucleotide polymorphism discovery in albacore and Atlantic bluefin tuna provides insights into worldwide population structure. Anim. Genet. 44, 678–692 (2013).

    CAS  PubMed  Article  Google Scholar 

  • 31.

    Laconcha, U. & Iriondo, M. New nuclear SNP markers unravel the genetic structure and effective population size of Albacore tuna (Thunnus alalunga). PLoS ONE 10, e0128247 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 32.

    Heincke, D. F. Naturgeschichte des herring. Abhandlungen Doutsch Seefisch Verein 2, 128–233 (1898).

    Google Scholar 

  • 33.

    Foote, C. J., Wood, C. C. & Withler, R. E. Biochemical genetic comparison of sockeye salmon and kokane, the anadromus and nonanadromus forms of Oncorhynchus nerka. Can. J. Fish. Aquat. Sci. 46, 149–158 (1989).

    Article  Google Scholar 

  • 34.

    Robinson, B. W. & Wilson, D. S. Genetic variation and phenotypic plasticity in a tropically polymorphic population of pumpkinseed sunfish (Lepomis gibbosus). Evol. Ecol. 10, 631–652 (1996).

    Article  Google Scholar 

  • 35.

    Cabral, H. N. et al. Genetic and morphologica variation of Synaptura lusitanica Capello, 1868, along the Portuguese coast. J. Sea Res. 50, 167–175 (2003).

    ADS  Article  Google Scholar 

  • 36.

    Dhurmeea, Z. et al. Reproductive biology of Albacore tuna (Thunnus alalunga) in the Western Indian Ocean. PLoS ONE 11, 0168605–0168610 (2016).

    Article  CAS  Google Scholar 

  • 37.

    Gonzalez, E. G. & Zardoya, R. Relative role of life-history traits and historical factors in shaping genetic population structure of sardines (Sardina pilchardus). BMC Evol. Biol. 7, 197 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 38.

    Young, E. F. et al. Oceanography and life history predict contrasting genetic population structure in two Antarctic fish species. Evol. Appl. 8, 486–509 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  • 39.

    Santos, A. M. P. et al. Sardine (Sardina pilchardus) larval dispersal in the Iberian Upwelling System, using coupled biophysical techniques. Prog. Oceanogr. 162, 83–97 (2018).

    ADS  Article  Google Scholar 

  • 40.

    Kaplan, D. M., Cuif, M. & Fauvelot, C. Uncertainty in empirical estimates of marine larval connectivity. ICES J. Mar. Sci 74(6), 1723–1734 (2016).

    Article  Google Scholar 

  • 41.

    Cowen, R. K., Paris, C. B. & Srinivasan, A. Scaling of connectivity in marine populations. Science 311, 522–527 (2006).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 42.

    Nickols, K. J., White, J. W., Largier, J. L. & Gaylord, B. Marine population connectivity: Reconciling large-scale dispersal and high self-retention. Am. Nat. 185, 196–211 (2015).

    PubMed  Article  Google Scholar 

  • 43.

    Nikolic, N. et al. GERMON project final report (GEnetic stRucture and Migration Of albacore tuna). IFREMER Re. 2015, 219 (2015).

    Google Scholar 

  • 44.

    Dhurmeea, Z. et al. Reproductive biology of albacore tuna (Thunnus. in alalunga) in the Western Indian Ocean. PLoS ONE 11(12), e0168605 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 45.

    Ueyanagi, S. Observations on the distribution of tuna larva in the Indo-Pacific Ocean with emphasis on the delineation of spawning areas of albacore, Thunnus alalunga. Bull. Far. Seas Fish. Res. Lab. 2, 177–219 (1969).

    Google Scholar 

  • 46.

    Bard, F. X. Le Thon Germon (Thunnus alalunga, Bonnaterre 1788) de l’Océan Atlantique. De la dynamique des populations à la stratégie démographique. Thèse de Doctorat d’Etat. Université Pierre et Marie Curie. (XI, 1981).

  • 47.

    Wu, C. L. & Kuo, C. L. Maturity and fecundity of albacore, Thunnus alalunga (Bonnaterre), from the Indian Ocean. J. Fish Soc. Taiwan 20(2), 135–151 (1993).

    Google Scholar 

  • 48.

    Lilliefors, H. W. On the Kolmogorov–Smirnov test for normality with mean and variance unknown. J. Am. Stat. Assoc. 62, 399–402 (1967).

    Article  Google Scholar 

  • 49.

    Levene, H. Robust tests for equality of variances. In Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling (eds Olkin, I. et al.) 278–292 (Stanford University Press, Stanford, 1960).

    Google Scholar 

  • 50.

    Manly, B. Randomization bootstrap and Monte Carlo methods in biology (Chapman & Hall/CRC, Boca Raton, 2007).

    Google Scholar 

  • 51.

    Fay, M. P. & Shaw, P. A. Exact and Asymptotic Weighted Logrank Tests for Interval Censored Data: The Interval R Package. J. Stat. Softw. 36, 1–34 (2010).

    Article  Google Scholar 

  • 52.

    Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage, London, 2011).

    Google Scholar 

  • 53.

    Ogle, D. H. Introductory Fisheries Analyses with R (Chapman & Hall/CRC, Boca raton, 2016).

    Google Scholar 

  • 54.

    Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn. (Springer, Berlin, 2002).

    Google Scholar 

  • 55.

    Ricker, W. E. Linear regression in fisheries research. J. Fish. Res. Board Can. 30, 409–434 (1973).

    Article  Google Scholar 

  • 56.

    Ricker, W. E. Methods for assessment of fish production in fresh waters. IBP Handbook N°3 (Blackwell Scientific Publications, Oxford and Edinburgh, 1968).

    Google Scholar 

  • 57.

    Rossiter, D. G. Technical note: Curve fitting with the R Environment for Statistical Computing. In Enschede (NL): 17, International Institute for Geo-information Science & Earth Observations (2009).

  • 58.

    Nikolic, N. et al. Discovery of genome-wide microsatellite markers in Scombridae: A pilot study on albacore tuna. PLoS ONE 10, e0141830 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 59.

    Rousset, F. Genepop’007: A complete reimplementation of the Genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).

    PubMed  Article  Google Scholar 

  • 60.

    Rousset, F. & Raymond, M. Testing heterozygote excess and deficiency. Genetics 140, 1413–1419 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  • 61.

    Storey, J. D. A Direct Approach to False Discovery Rates. J. R. Stat. Soc. Ser. B Stat. Methodol. 64, 479–498 (2002).

    MathSciNet  MATH  Article  Google Scholar 

  • 62.

    Storey, J. D. The positive false discovery rate: A Bayesian interpretation and the q-value. Ann. Stat. 31, 2013–2035 (2003).

    MathSciNet  MATH  Article  Google Scholar 

  • 63.

    Storey, J. D. & Tibshirani, R. Statistical significance for genome wide studies. Proc. Natl. Acad. Sci. USA. 100, 9440–9445 (2003).

    ADS  MathSciNet  CAS  PubMed  MATH  Article  Google Scholar 

  • 64.

    Storey, J. D., Taylor, J. E. & Siegmund, D. Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: A unified approach. J. R. Stat. Soc. Ser. B Stat. Methodol. 66, 187–205 (2004).

    MathSciNet  MATH  Article  Google Scholar 

  • 65.

    Storey, J., Bass, A., Dabney, A. & Robinson, D. qvalue: Q-value Estimation for False Discovery Rate Control. https://github.com/jdstorey/qvalue (2019).

  • 66.

    Engels, W. R. Exact tests for Hardy-Weinberg proportions. Genetics 183, 1431–1441 (2009).

    PubMed  PubMed Central  Article  Google Scholar 

  • 67.

    Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).

    CAS  PubMed  Google Scholar 

  • 68.

    Excoffier, L., Laval, G. & Schneider, S. Arlequin ver. 3.1: An integrated software package for population genetics data analysis. Evol. Bioinform. Online 1, 47–50 (2005).

    CAS  Article  Google Scholar 

  • 69.

    Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N. & Bonhomme, F. GENETIX, logiciel sous WindowsTM pour la génétique des populations. Laboratoire Génome, Populations, Interactions CNRS UMR 5000. (Université de, 1996).

  • 70.

    Jombart, T. adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).

    CAS  PubMed  Article  Google Scholar 

  • 71.

    Jombart, T. & Ahmed, I. adegenet 1.3-1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27(21), 3070–3071 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 72.

    Thioulouse, J., Chessel, D., Dolédec, S. & Olivier, J. M. ADE-4: A multivariate analysis and graphical display software. Stat. Comput. 7, 75–83 (1997).

    Article  Google Scholar 

  • 73.

    Pritchard, J. K., Stephens, P. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  • 74.

    Li, Y.-L. & Liu, J.-X. StructureSelector: A web-based software to select and visualize the optimal number of clusters using multiple methods. Mol. Ecol. Resour. 18, 176–177 (2018).

    PubMed  Article  Google Scholar 

  • 75.

    Evanno, G. & Regnaut Sand Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).

    CAS  PubMed  Article  Google Scholar 

  • 76.

    Puechmaille, S. J. The program structure does not reliably recover the correct population structure when sampling is uneven: Subsampling and new estimators alleviate the problem. Mol. Ecol. Resour. 16, 608–627 (2016).

    PubMed  Article  Google Scholar 

  • 77.

    Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. CLUMPAK: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 5, 1179–1191 (2015).

    Article  CAS  Google Scholar 

  • 78.

    Takezaki, N., Nei, M. & Tamura, K. POPTREEW: Web version of POPTREE for constructing population trees from allele frequency data and computing some other quantities. Mol. Biol. Evol. 6, 1622–1624 (2014).

    Article  CAS  Google Scholar 

  • 79.

    Parks, D. H. et al. GenGIS 2: Geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework. PLoS ONE 8, 69885 (2013).

    ADS  Article  CAS  Google Scholar 

  • 80.

    Takezaki, N., Nei, M. & Tamura, K. PopTree2: Software for constructing population trees from allele frequency data and computing other population statistics with Windows interface. Mol. Biol. Evol. 27, 747–752 (2010).

    CAS  PubMed  Article  Google Scholar 

  • 81.

    Peakall, R. & Smouse, P. GenAlEx 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295 (2006).

    Article  Google Scholar 

  • 82.

    Mossman, C. A. & Waser, P. M. Genetic detection of sex-biased dispersal. Mol. Ecol. 8, 1063–1067 (1999).

    CAS  PubMed  Article  Google Scholar 

  • 83.

    R development Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, Vienna, 2013). https://www.R-project.org.

  • 84.

    Gastwirth, J. L. et al. lawstat: Tools for Biostatistics. (Public Policy, and Law, 2017).

  • 85.

    Dray, S. & Dufour, A. B. The ade4 package: Implementing the duality diagram for ecologists. J. Stat. Softw. 22(4), 1–20 (2007).

    Article  Google Scholar 

  • 86.

    Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, Boca Raton, 2006).

    Google Scholar 

  • 87.

    Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73(1), 3–36 (2011).

    MathSciNet  MATH  Article  Google Scholar 

  • 88.

    Fournier, D. A. et al. AD Model Builder: Using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim. Methods Softw. 27, 233–249 (2012).

    MathSciNet  MATH  Article  Google Scholar 

  • 89.

    Skaug, H., Fournier, D., Nielsen, A., Magnusson, A. & Bolker, B. Generalized Linear Mixed Models using AD Model Builder. (2013).

  • 90.

    Chen, K.-Y. et al. assignPOP: An r package for population assignment using genetic, non-genetic, or integrated data in a machine-learning framework. Methods Ecol. Evol. 9, 439–446 (2018).

    Article  Google Scholar 

  • 91.

    Gibbs, R. & Colette, B. Comparative anatomy and systemics of the tunas, genus Thunnus. USA. Fish Wildl. Serv. Fish. Bull. 66, 65–130 (1967).

    Google Scholar 

  • 92.

    Cosgrove, R., Arregui, I., Arrizabalaga, H., Goni, N. & Sheridan, M. New insights to behaviour of North Atlantic albacore tuna (Thunnus alalunga) observed with pop-up satellite archival tags. Fish. Res. 150, 89–99 (2014).

    Article  Google Scholar 

  • 93.

    Schaefer, K. M. Reproductive biology of tunas. Fish Physiol. 19, 225–270 (2001).

    Article  Google Scholar 

  • 94.

    Ramon, D. & Bailey, K. Spawning seasonality of albacore, Thunnus alalunga, in the South Pacific Ocean. Fish. Bull. Natl. Oceanic Atmos. Admin. 94(4), 725–733 (1996).

    Google Scholar 

  • 95.

    Description and results. Ferry. Mercator global eddy permitting ocean reanalysis glorys1v1. Tech. Rep. Mercator Ocean Q. Newsl. 36, 15–28 (2010).

    Google Scholar 

  • 96.

    Gaspar, P. et al. Oceanic dispersal of juvenile leatherback turtles: Going beyond passive drift modeling. Mar. Ecol. Prog. Ser. 457, 265–284 (2012).

    ADS  Article  Google Scholar 

  • 97.

    Lalire, M. & Gaspar, P. Modeling the active dispersal of juvenile leatherback turtles in the North Atlantic Ocean. Mov. Ecol. 7, 7 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  • 98.

    Lehodey, P., Senina, L., Dragon, A. C. & Arrizabalaga, H. Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga). Earth Syst. Sci. Data 6, 317–329 (2014).

    ADS  Article  Google Scholar 

  • 99.

    Ryman, N. & Palm, S. POWSIM: A computer program for assessing statistical power when testing for genetic differentiation. Mol. Ecol. Notes 6, 600–602 (2006).

    Article  Google Scholar 

  • 100.

    Saji, N. H., Goswami, B. N., Vinayachandran, P. N. & Yamagata, T. A dipole mode in the tropical Indian Ocean. Nature 401, 360 (1999).

    ADS  CAS  PubMed  Google Scholar 

  • 101.

    Li, J. et al. Impacts of the IOD-associated temperature and salinity anomalies on the intermittent equatorial undercurrent anomalies. Clim. Dyn. 51, 1391–1409 (2018).

    Article  Google Scholar 

  • 102.

    Schouten, M. W., de Ruijter, W. P., van Leeuwen, P. J. & Ridderinkhof, H. Eddies and variability in the Mozambique Channel. Deep Sea Res. Part II Top. Stud. Oceanogr. 50, 1987–2003 (2003).

    ADS  Article  Google Scholar 

  • 103.

    de Ruijter, W. P. M. et al. Eddies and dipoles around South Madagascar: Formation, pathways and large-scale impact. Deep Sea Res. Part I 51, 383–400 (2004).

    Article  Google Scholar 

  • 104.

    de Ruijter, W. P. M., Ridderinkhof, H., Lutjeharms, J. R. E., Schouten, M. W. & Veth, C. Observations of the flow in the Mozambique Channel: Observations in the Mozambique channel. Geophys. Res. Lett. 29, 140-1-140–3 (2002).

    Article  Google Scholar 

  • 105.

    Longhurst, A. R. Ecological Geography of the Sea (Academic Press, London, 2007).

    Google Scholar 

  • 106.

    New, A. et al. Physical and biochemical aspects of the flow across the Mascarene Plateau in the Indian Ocean. Philos. Trans. R Soc. Math. Phys. Eng. Sci. 363, 151–168 (2005).

    ADS  CAS  Google Scholar 

  • 107.

    Penney, A. J., Yeh, S. Y., Kuo, C. L. & Leslie, R. W. Relationships between albacore (Thunnus alalunga) stocks in the southern Atlantic and Indian Oceans. In Int Com Conserv AH Tuna Tuna Symp, Ponta Delgada, Azores (ed. Beckett, J. S.) 10–18 (1998).

  • 108.

    Postel, E. Sur deux lots de germon (Germo alalunga) capturés dans le Golfe de Guinée par les palangriers japonais. Cahiers ORSTOM Série Océanographique 2, 55–60 (1964).

    Google Scholar 

  • 109.

    Liorzou, B. Les nouveaux engins de pêche pour la capture du germon: Description, statistiques, impact sur le stock nord-Atlantique. Collect. Vol. Sci. Pap. 30(1), 203–217 (1989).

    Google Scholar 

  • 110.

    Koto, T. Studies on the albacore-XIV. Distribution and movement of the albacore in the Indian and the Atlantic Oceans based on the catch statistics of Japanese tuna long-line fishery. Bull. Far. Seas Fish. Res. Lab. 1, 115–129 (1969).

    Google Scholar 

  • 111.

    Conand, F. & Richards, W. J. Distribution of tuna larvae between Madagascar and the Equator, Indian Ocean. Biol. Oceanogr. 4, 321–336 (1982).

    Google Scholar 

  • 112.

    Shiohama, T. Overall fishing intensity and length composition of albacore caught by long line fishery. In The Indian Ocean, 1952–1982. IPTP, Vol. 22, 91–109 (1985).

  • 113.

    Fonteneau, A. A summarized presentation of the report of the 2nd. In IOTC WP of the Albacore Meeting held in Bangkok (2008).

  • 114.

    IOTC. Proposition: Résumé exécutive: GERMON. in IOTC, IOTC-2013-SC16-ES01 (2013).

  • 115.

    Nishikawa, Y., Honma, M., Ueyanagi, S. & Kikawa, S. Average distribution of larvae of oceanic species of scombroid fishes, 1956–1981. Far. Seas Fish. Res. Lab. 12, 1–99 (1985).

    Google Scholar 

  • 116.

    Nishida, T. & Tanaka, M. General reviews of Indian Ocean Albacore (Thunnus alalunga). IOTC-2004- WPTMT-03. (2004).

  • 117.

    Stéquert, B. & Marsac, F. La pêche de surface des thonidés tropicaux dans l’océan Indien. (1986).

  • 118.

    Fonteneau, A. & Marcille, J. Ressources, pêche et biologie des thonidés tropicaux de l’Atlantique centre-est. FAO Dot. Tech. Pêches 292. (1988).

  • 119.

    Hoyle, S., Sharma, R. & Herrera, M. Stock assessment of albacore tuna in the Indian Ocean for 2014 using stock synthesis. Indian Ocean Tuna Commission working party on temperate Tunas, Busan, Rep. of Korea, 28–31 July 2014, IOTC–2014–WPTmT05–24_Rev1. (2014).

  • 120.

    Montes, I. et al. Worldwide genetic structure of albacore (Thunnus alalunga) revealed by microsatellite DNA markers. Mar. Ecol. Prog. Ser. 471, 183–191 (2012).

    ADS  CAS  Article  Google Scholar 

  • 121.

    Carlsson, J. et al. Microsatellite and mitochondrial DNA analyses of Atlantic bluefin tuna (Thunnus thynnus thynnus) population structure in the Mediterranean Sea. Mol. Ecol. 13, 3345–3356 (2004).

    CAS  PubMed  Article  Google Scholar 

  • 122.

    Carlsson, J., McDowell, J. R., Carlsson, J. E. & Graves, J. E. Genetic identity of YOY bluefin tuna from the eastern and western Atlantic spawning areas. J. Hered. 98, 23–28 (2007).

    CAS  PubMed  Article  Google Scholar 

  • 123.

    Riccioni, G., Landi, M., Ferrara, G. & Milano, I. Spatio-temporal population structuring and genetic diversity retention in depleted Atlantic bluefin tuna of the Mediterranean Sea. Proc. Natl. Acad. Sci. USA 107, 2102–2107 (2010).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 124.

    Yeh, S. Y., Treng, T. D., Hui, C. F. & Penney, A. J. Mitochondrial DNA sequence analysis on Albacore, Thunnus alalunga, meat samples collected from the waters off western South Africa and the Eastern Indian Ocean. ICCAT Col. Vol. Sci. Pap. 46, 152–159 (1997).

    Google Scholar 

  • 125.

    Durand, J. D., Collet, A., Chow, S., Guinand, B. & Borsa, P. Nuclear and mitochondrial DNA markers indicated unidirectional gene flow of Indo-Pacific to Atlantic bigeye tuna (Thunnus obesus) populations, and their admixture off southern Africa. Mar. Biol. 147, 313–322 (2005).

    CAS  Article  Google Scholar 

  • 126.

    Poulsen, N. A., Nielsen, E. E., Schierup, M. H., Loeschcke, V. & Gronkjaer, P. Long-term stability and effective population size in North Sea and Baltic Sea cod (Gadus morhua). Mol. Ecol. 15, 321–331 (2006).

    CAS  PubMed  Article  Google Scholar 

  • 127.

    Chow, S., Okamoto, H., Miyabe, N., Hiramatsu, K. & Barut, N. Genetic divergence between Atlantic and Indo-Pacific stocks of bigeye tuna (Thunnus obesus) and admixture around South Africa. Mol. Ecol. 9, 221–227 (2000).

    CAS  PubMed  Article  Google Scholar 

  • 128.

    Graham, M. H., Dayton, P. K. & Erlandson, J. M. Ice ages and ecological transitions on temperate coasts. Trends Ecol. Evol. 18, 33–40 (2003).

    Article  Google Scholar 

  • 129.

    Siddall, M. et al. Sea-level fluctuations during the last glacial cycle. Nature 423, 853–858 (2003).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 130.

    Rohfritsch, A. & Borsa, P. Genetic structure of Indian scad mackerel Decapterus russelli: Pleistocene vicariance and secondary contact in the Central Indo-West Pacific Seas. Heredity 95, 315–326 (2005).

    CAS  PubMed  Article  Google Scholar 

  • 131.

    Janko, K. et al. Did glacial advances during the Pleistocene influence differently the demographic histories of benthic and pelagic Antarctic shelf fishes?—Inferences from intraspecific mitochondrial and nuclear DNA sequence diversity. BMC Evol. Biol. 7, 220 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 132.

    Ravago-Gotanco, R. G. & Juinio-Meñez, M. A. Phylogeography of the mottled spinefoot Siganus fuscescens: Pleistocene divergence and limited genetic connectivity across the Philippine archipelago. Mol. Ecol. 19, 4520–4534 (2010).

    CAS  PubMed  Article  Google Scholar 

  • 133.

    Pedrosa-Gerasmio, I. R., Agmata, A. B. & Santos, M. D. Genetic diversity, population genetic structure, and demographic history of Auxis thazard (Perciformes), Selar crumenophthalmus (Perciformes), Rastrelliger kanagurta (Perciformes) and Sardinella lemuru (Clupeiformes) in Sulu-Celebes Sea inferred by mitochondrial DNA sequences. Fish. Res. 162, 64–74 (2015).

    Article  Google Scholar 

  • 134.

    Barth, J. M. I., Damerau, M., Matschiner, M., Jentoft, S. & Hanel, R. Genomic differentiation and demographic histories of Atlantic and Indo-Pacific yellowfin tuna (Thunnus albacares) populations. Genome Biol. Evol. 9(4), 1084–1098 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 135.

    West, W. MSc thesis. Genetic stock structure and estimation of abundance of swordfish (Xiphias gladius) in South Africa. https://open.uct.ac.za/handle/11427/20432. (2016).

  • 136.

    Silva, D. M. et al. Evaluation of IMTA-produced seaweeds (Gracilaria, Porphyra, and Ulva) as dietary ingredients in Nile tilapia, Oreochromis niloticus L., juveniles. Effects on growth performance and gut histology. J. Appl. Phycol. 27, 1671–1680 (2015).

    CAS  Article  Google Scholar 

  • 137.

    Bourjea, J. et al. Phylogeography of the green turtle, Chelonia mydas, in the Southwest Indian Ocean. Mol. Ecol. 16, 175–186 (2007).

    CAS  PubMed  Article  Google Scholar 

  • 138.

    Rudomiotkina, G. P. Distribution of larval tunas (Thunnidae, Perciformes) in the Central-Atlantic Ocean. Int. Council Explor. Sea (ICES), Pelagic Fish (S.) Committee, J. 15 (1973).

  • 139.

    Piccinetti, C. & Piccinetti-Manfrin, G. Relation entre œufs et larves de thonidés et hydrologie en Méditerranée. CNEXO 8, 9–12 (1979).

    Google Scholar 

  • 140.

    Mullins, R. B., McKeown, N. J., Sauer, W. H. H. & Shaw, P. W. Genomic analysis reveals multiple mismatches between biological and management units in yellowfin tuna (Thunnus albacares). ICES J. Mar. Sci. 75, 2145–2152 (2018).

    Article  Google Scholar 

  • 141.

    Fonteneau, A. An overview of Indian Ocean albacore: Fisheries, stocks and research. IOTC-2004-WPTMT-02. (2004).

  • 142.

    Clemens, H. B. The migration, age and growth of Pacific albacore (Thunnus germo), 1951–1958. (1961).

  • 143.

    Talbot, F. H. & Penrith, M. J. Tunnies and Marlins of South Africa. Nature 193, 558–559 (1962).

    ADS  Article  Google Scholar 

  • 144.

    Flittner, G. A. Review of the 1962 seasonal movement of albacore tuna off the Pacific coast of the United States. Commer. Fish. Rev. 25(4), 7–13 (1963).

    Google Scholar 

  • 145.

    Laurs, R. M. & Lynn, R. J. Seasonal migration of North Pacific albacore, Thunnus alalunga, into North America coastal waters: Distribution, relative abundance and association with transition zone waters. US Fish. Bull. 75, 795–822 (1977).

    Google Scholar 

  • 146.

    Johnsson, J. H. Sea temperatures and the availability of albacore (Thunnus germo) off the coasts of Oregon and Washington. Paper presented to the Pacific Tuna biology conference (1961).

  • 147.

    Santiago, J. Dinamica de la poblacion de atun blanco (Thunnus alalunga, Bonaterre 1788) del Atlantico Norte. Thèse de Doctorat, Euskal Erico (2004).

  • 148.

    Boyce, D., Tittensor, D. P. & Worm, B. Effects of temperature on global patterns of tuna and billfish richness. Mar. Ecol. Prog. Ser. 355, 267–276 (2008).

    ADS  Article  Google Scholar 

  • 149.

    Childers, J., Snyder, S. & Kohin, S. Migration and behavior of juvenile North Pacific albacore (Thunnus alalunga). Fish. Oceanogr. 20, 157–173 (2011).

    Article  Google Scholar 

  • 150.

    Hauser, L. & Carvalho, G. R. Paradigm shifts in marine fisheries genetics: Ugly hypotheses slain by beautiful facts. Fish Fish. 9, 333–362 (2008).

    Article  Google Scholar 

  • 151.

    Logan, C. A., Alter, S. E., Haupt, A. J., Tomalty, K. & Palumbi, S. R. An impediment to consumer choice: Overfished species are sold as Pacific red snapper. Biol. Conserv. 141, 1591–1599 (2008).

    Article  Google Scholar 

  • 152.

    Primmer, C. R., Koskinen, M. T. & Piironen, J. The one that did not get away: Individual assignment using microsatellite data detects a case of fishing competition fraud. Proc. Biol. Sci. 267, 1699–1704 (2000).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 153.

    Carvalho, G. R. & Hauser, L. Molecular genetics and the stock concept in fisheries. in Molecular Genetics in Fisheries (eds. Carvalho, G. R. & Pitcher, T. J.) 55–79 (1995).

  • 154.

    Waples, R. S., Punt, A. E. & Cope, J. M. Integrating genetic data into management of marine resources: How can we do it better?. Fish Fish. 9, 423–449 (2008).

    Article  Google Scholar 

  • 155.

    Chouvelon, T. et al. Chemical contaminants (trace metals, persistent organic pollutants) in albacore tuna from western Indian and south-eastern Atlantic Oceans: Trophic influence and potential as tracers of populations. Sci. Total Environ. 597, 481–495 (2017).

    ADS  Article  CAS  Google Scholar 

  • 156.

    Penrith, M. J. G. The systematics and biology of the South African Tunas. (Masters Dissertation, University of Cape Town, 1963).

  • 157.

    IOTC. Report of the Fifteenth Session of the IOTC Scientific Committee. (2012).

  • 158.

    Stequert, B. & Marsac, F. Tropical tuna—surface fisheries in the Indian Ocean. Fisheries Technical Paper FAO, 282 (1989).

  • 159.

    Pecoraro, C. et al. The population genomics of yellowfin tuna (Thunnus albacares) at global geographic scale challenges current stock delineation. Sci. Rep. 8, 13890 (2018).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 


  • Source: Ecology - nature.com

    A symbiotic nutrient exchange within the cyanosphere microbiome of the biocrust cyanobacterium, Microcoleus vaginatus

    Protein metabolism and physical fitness are physiological determinants of body condition in Southern European carnivores