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Spatial–temporal variations in primary productivity and population dynamics of skipjack tuna Katsuwonus pelamis in the western and central Pacific Ocean

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Abstract

The western and central Pacific Ocean (WCPO) is the largest skipjack tuna Katsuwonus pelamis fishing ground in the world. Understanding the spatial–temporal variation of primary productivity in the WCPO is critical, as such variation might be associated with the distribution of skipjack tuna stocks. This study adopts three types of remote sensing data, i.e., sea surface temperature (SST), chlorophyll-a concentration and photosynthetically active radiation, and applies a vertically generalized production model to simulate the euphotic depth-integrated primary productivity (IPP) of the WCPO to elucidate the relationships between the distribution and variation in IPP and the estimated population dynamics of skipjack tuna. In addition, catch data from a Taiwanese purse seine fishing company (2003–2010) were analyzed to improve the accuracy of the model. The results suggest that (a) in the WCPO, the most of the high-IPP locations are in the eastern Pacific areas; (b) the areas in which IPP is significantly correlated with the El Niño Southern Oscillation are mainly located along the equatorial zone; and (c) there were high recruitments of skipjack in 26 and 49 months following an IPP bloom, respectively. The findings from this study reveal the correlation between primary productivity and fish resources and highlight the influence of climate variability on tuna resources.

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References

  1. Gitay H, Brown S, Easterling W, Jallow B, Antle J, Apps M, Beamish R, Chapin T, Cramer W, Frangi J (2001) Ecosystems and their goods and services. Cambridge University Press, Cambridge

    Google Scholar 

  2. FAO (2012) The state of the world fisheries and aquaculture 2012. FAO Fisheries and Aquaculture Department, Rome

    Google Scholar 

  3. Li XJ, Chao Y, McWilliams JC, Fu LL (2001) A comparison of two vertical-mixing schemes in a Pacific Ocean general circulation model. J Clim 14:1377–1398

    Article  Google Scholar 

  4. Chai F, Dugdale RC, Peng TH, Wilkerson FP, Barber RT (2002) One-dimensional ecosystem model of the equatorial Pacific upwelling system. Part I: Model development and silicon and nitrogen cycle. Deep Sea Res Part II 49:2713–2745

    Article  CAS  Google Scholar 

  5. Jiang M-S, Chai F, Dugdale R, Wilkerson F, Peng T-H, Barber R (2003) A nitrate and silicate budget in the equatorial Pacific Ocean: a coupled physical–biological model study. Deep Sea Res Part II 50:2971–2996

    Article  CAS  Google Scholar 

  6. Lehodey P, Bertignac M, Hampton J, Lewis A, Picaut J (1997) El Niño Southern Oscillation and tuna in the western Pacific. Nature 389:715–718

    Article  CAS  Google Scholar 

  7. Lehodey P (2001) The pelagic ecosystem of the tropical Pacific Ocean: dynamic spatial modelling and biological consequences of ENSO. Prog Oceanogr 49:439–468

    Article  Google Scholar 

  8. Lima M, Naya DE (2011) Large-scale climatic variability affects the dynamics of tropical skipjack tuna in the western Pacific Ocean. Ecography 34:597–605

    Article  Google Scholar 

  9. Brill RW, Dewar H, Graham JB (1994) Basic concepts relevant to heat transfer in fishes, and their use in measuring the physiological thermoregulatory abilities of tunas. Environ Biol Fishes 40:109–124

    Article  Google Scholar 

  10. Lehodey P, Senina I, Calmettes B, Hampton J, Nicol S (2013) Modelling the impact of climate change on Pacific skipjack tuna population and fisheries. Clim Change 119:95–109

    Article  Google Scholar 

  11. Senina I, Sibert J, Lehodey P (2008) Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: application to skipjack tuna. Prog Oceanogr 78:319–335

    Article  Google Scholar 

  12. Solomon S (2007) Climate change 2007—the physical science basis: Working Group I contribution to the fourth assessment report of the IPCC. Cambridge University Press, Cambridge

  13. Bainbridge V and McKay BJ (1968) The feeding of cod and redfish larvae. International Commission for the Northwest Atlantic Fisheries special publication No. 7:187–217

  14. Runge J (1988) Should we expect a relationship between primary production and fisheries? The role of copepod dynamics as a filter of trophic variability. Hydrobiologia 167:61–71

    Article  Google Scholar 

  15. Smith RC and Baker KS (1978) The bio-optical state of ocean waters and remote sensing. Limnol Oceanogr 23:247–259

  16. Behrenfeld MJ, Randerson JT, McClain CR, Feldman GC, Los SO, Tucker CJ, Falkowski PG, Field CB, Frouin R, Esaias WE, Kolber DD, Pollack NH (2001) Biospheric primary production during an ENSO transition. Science 291:2594–2597

    Article  CAS  PubMed  Google Scholar 

  17. Campbell J, Antoine D, Armstrong R, Arrigo K, Balch W, Barber R, Behrenfeld M, Bidigare R, Bishop J, Carr M-E, Esaias W, Falkowski P, Hoepffner N, Iverson R, Kiefer D, Lohrenz S, Marra J, Morel A, Ryan J, Vedernikov V, Waters K, Yentsch C, Yoder J (2002) Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance. Global Biogeochem Cycles 16:74–75

    Article  Google Scholar 

  18. Behrenfeld MJ, Falkowski PG (1997) Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol Oceanogr 42:1–20

    Article  CAS  Google Scholar 

  19. Milutinovic S, Bertino L (2011) Assessment and propagation of uncertainties in input terms through an ocean-color-based model of primary productivity. Remote Sens Environ 115:1906–1917

    Article  Google Scholar 

  20. Wolter K, Timlin MS (1998) Measuring the strength of ENSO events: how does 1997/98 rank? Weather 53:315–324

    Article  Google Scholar 

  21. Morel A, Berthon JF (1989) Surface pigments, algal biomass profiles, and potential production of the euphotic layer: relationships reinvestigated in view of remote-sensing applications. Limnol Oceanogr 34:1545–1562

    Article  CAS  Google Scholar 

  22. Benestad RE (2004) Empirical-statistical downscaling in climate modeling. Eos, Trans. Am Geophys Union 85:417–422

    Article  Google Scholar 

  23. Chavez FP, Messie M, Pennington JT (2011) Marine primary production in relation to climate variability and change. In: Carlson CA and Giovannoni SJ (eds) Annual review of marine science, Vol 3, p 227–260

  24. Couto AB, Holbrook NJ, Maharaj AM (2013) Unravelling eastern Pacific and central Pacific ENSO contributions in south Pacific chlorophyll-a variability through remote sensing. Remote Sens 5:4067–4087

    Article  Google Scholar 

  25. Nishikawa Y (1985) Average distribution of larvae of oceanic species of scombroid fishes,1956–1982. Far Seas Fish Res Lab 12:1–99

    Google Scholar 

  26. Hoyle S, Davies N, Langley A Hampton J (2011) Stock assessment of skipjack tuna in the western and central Pacific Ocean. Seventh Regular Session of the Scientific Committee, Pohnpei, Federated States of Micronesia, p 134

  27. Matsumoto WM (1958) Description and distribution of larvae of four species of tuna in central Pacific waters. US Government Printing Office, Washington

  28. Basilone G, Bonanno A, Patti B, Mazzola S, Barra M, Cuttitta A, McBride R (2013) Spawning site selection by European anchovy (Engraulis encrasicolus) in relation to oceanographic conditions in the Strait of Sicily. Fish Oceanogr 22:309–323

    Article  Google Scholar 

  29. Condie SA, Mansbridge JV, Cahill ML (2011) Contrasting local retention and cross-shore transports of the East Australian Current and the Leeuwin Current and their relative influences on the life histories of small pelagic fishes. Deep Sea Res Part II 58:606–615

    Article  Google Scholar 

  30. Ichii T, Mahapatra K, Sakai M, Wakabayashi T, Okamura H, Igarashi H, Inagake D, Okada Y (2011) Changes in abundance of the neon flying squid Ommastrephes bartramii in relation to climate change in the central north Pacific Ocean. Mar Ecol-Prog Ser 441:151–164

    Article  Google Scholar 

  31. Muhling BA, Beckley LE, Gaughan DJ, Jones CM, Miskiewicz AG, Hesp SA (2008) Spawning, larval abundance and growth rate of Sardinops sagax off southwestern Australia: influence of an anomalous eastern boundary current. Mar Ecol-Prog Ser 364:157–167

    Article  Google Scholar 

  32. Jonsson N, Jonsson B, Hansen LP (1998) The relative role of density-dependent and density-independent survival in the life cycle of Atlantic salmon Salmo salar. J Anim Ecol 67:751–762

    Article  Google Scholar 

  33. Earl JE, Semlitsch RD (2013) Spatial subsidies, trophic state, and community structure: examining the effects of leaf litter input on ponds. Ecosystems 16:639–651

    Article  Google Scholar 

  34. Chavez FP, Messie M, Pennington JT (2011) Marine primary production in relation to climate variability and change. Annu Rev Mar Sci 3:227–260

    Article  Google Scholar 

  35. Gushing D, Dickson R (1977) The biological response in the sea to climatic changes. Adv Mar Biol 14:1–122

    Article  Google Scholar 

  36. Hjermann DO, Bogstad B, Eikeset AM, Ottersen G, Gjosaeter H, Stenseth NC (2007) Food web dynamics affect northeast Arctic cod recruitment. Proc Biol Sci 274:661–669

    Article  PubMed  Google Scholar 

  37. Hjermann DO, Stenseth NC, Ottersen G (2004) Indirect climatic forcing of the Barents Sea capelin: a cohort effect. Mar Ecol Prog Ser 273:229–238

    Article  Google Scholar 

  38. MacKenzie BR, Koster FW (2004) Fish production and climate: sprat in the Baltic Sea. Ecology 85:784–794

    Article  Google Scholar 

  39. Stige LC, Ottersen G, Brander K, Chan KS, Stenseth NC (2006) Cod and climate: effect of the North Atlantic Oscillation on recruitment in the North Atlantic. Mar Ecol Prog Ser 325:227–241

    Article  Google Scholar 

  40. Chavez FP, Strutton PG, Friederich CE, Feely RA, Feldman GC, Foley DC, McPhaden MJ (1999) Biological and chemical response of the equatorial Pacific Ocean to the 1997-98 El Nino. Science 286:2126–2131

    Article  CAS  PubMed  Google Scholar 

  41. Yen KW, Lu HJ, Chang Y, Lee MA (2012) Using remote-sensing data to detect habitat suitability for yellowfin tuna in the western and central Pacific Ocean. Int J Remote Sens 33:7507–7522

    Article  Google Scholar 

  42. Lehodey P, Senina I, Murtugudde R (2008) A spatial ecosystem and populations dynamics model (SEAPODYM)—modeling of tuna and tuna-like populations. Prog Oceanogr 78:304–318

    Article  Google Scholar 

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Acknowledgments

The authors wish to thank Dr. M.-A. Lee, Dr. C.-L. Sun, Dr. M.-K. Hsu, Dr C.-R. Wu, Dr. D.-C. Liu, Dr. S.-P. Wang, Dr. C.-H. Liao and Dr. H.-W Huang for their comments on previous versions. The suggestions and useful comments of two anonymous referees are also gratefully acknowledged. We also thank the Council of Agriculture (100AS-10.1.2-FA-F1, 101AS-11.1.2-FA-F1) and National Science Council (NSC100-2621-M-002-037) of the Republic of China for their financial support.

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Correspondence to Kuo-Wei Yen.

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Yen, KW., Lu, HJ. Spatial–temporal variations in primary productivity and population dynamics of skipjack tuna Katsuwonus pelamis in the western and central Pacific Ocean. Fish Sci 82, 563–571 (2016). https://doi.org/10.1007/s12562-016-0992-x

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  • DOI: https://doi.org/10.1007/s12562-016-0992-x

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