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Application of a continuous time delay-difference model for the population dynamics of winter-spring cohort of neon flying squid (Ommastrephes bartramii, Lesueur 1821) in the North-west Pacific Ocean

Published online by Cambridge University Press:  23 November 2015

Baochao Liao
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China Faculty of Science, Yantai Nanshan University, Yantai 265713, China
Qun Liu*
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China
Xiaohui Wang
Affiliation:
Faculty of Science, Yantai Nanshan University, Yantai 265713, China
Abdul Baset
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China
Shamsheer Hyder Soomro
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China
Aamir Mahmood Memon
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China Marine Fisheries Department, Fish Harbor West Wharf, Karachi 74000, Pakistan
Khadim Hussain Memon
Affiliation:
Department of Fisheries, Ocean University of China, Qingdao 266003, China Marine Fisheries Department, Fish Harbor West Wharf, Karachi 74000, Pakistan
Muhsan Ali Kalhoro
Affiliation:
Faculty of Marine Sciences, Lasbela University of Agriculture, Balochistan, Pakistan
*
Correspondence should be addressed to:Q. Liu, Department of Fisheries, Ocean University of China, Qingdao 266003, China email: qunliu@ouc.edu.cn

Abstract

A continuous time delay-difference model (CD-DM) was applied to the Chinese neon flying squid (Ommastrephes bartramii) jigging fisheries data (2001–2004) in the north-west Pacific Ocean. The continuous time delay-difference model (CD-DM) was modified from the discrete-time delay-difference model (D-DM), in which recruitment, growth and mortality rates are treated as varying continuously over time. Some commercially important stocks, such as shrimp and O. bartrami with recruitment, growth and mortality rates all varying continuously over time, may be better analysed by a continuous delay-difference model. We estimated the growth and recruitment of O. bartramii on the basis of the CD-DM, and biological reference points (BRPs) and accuracy of estimates are discussed in this study. We obtained population sizes of 183.9–201.8 million squid during early September 2004. The status of the stock was not in a sustainable state at this time with the available data, which suggests that measures should be taken for the sustainable utilization of this stock. The ability to calculate reference points without need of a full age-structured data makes CD-DM an attractive option for data-poor fisheries. We provided an alternative method for assessing O. bartramii stock and bridged the gap between simple surplus production models and complex fully age-structured models.

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 2015 

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References

REFERENCES

Bower, J.R. and Ichii, T. (2005) The red flying squid (Ommastrephes bartramii): a review of recent research and the fishery in Japan. Fisheries Research 76, 3955.Google Scholar
Cao, J., Chen, X.J. and Chen, Y. (2011) Generalized linear Bayesian models for standardizing CPUE of Ommastrephes bartramii for Chinese squid-jigging fishery in northwest Pacific Ocean. Scientia Marina 75, 679689.Google Scholar
Chen, X., Chen, Y. and Tian, S. (2008a) An assessment of the west winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Fisheries Research 92, 221230.Google Scholar
Chen, X., Qian, W. and Liu, B. (2008b) An assessment of the west winter–spring cohort of neon flying squid, Ommastrephes bartramii, in the Northwest Pacific Ocean using the depletion model. Transactions of Oceanology and Limnology 2, 130140.Google Scholar
Deriso, R.B. (1980) Harvesting strategies and parameter estimation for an age-structured model. Canadian Journal of Fisheries Aquatic Sciences 37, 268282.Google Scholar
Dichmont, C.M., Punt, A.E. and Deng, A. (2003) Application of a weekly delay-difference model to commercial catch and effort data for tiger prawns in Australia's Northern Prawn Fishery. Fisheries Research 65, 335350.Google Scholar
Efron, B. and Tibshirani, R.J. (1993) An introduction to the bootstrap. New York, NY: Chapman and Hall.Google Scholar
Fournier, D.A. (1987) A length-based stock assessment method utilizing a generalized delay-difference model. Canadian Journal of Fisheries Aquatic Sciences 44, 422437.Google Scholar
Haddon, M. (2011) Modelling and quantitative methods in fisheries, 2nd edn. New York, NY: Chapman and Hall.Google Scholar
Hall, N.G. (1997) Delay-difference model to estimate the catch of different categories of the western rock lobster (Panuliruscygnus) for the two stages of the annual fishing season. Marine and Freshwater Research 48, 949958.Google Scholar
Hilborn, R. and Walters, C.J. (1992) Quantitative fisheries stock assessment, choices, dynamics and uncertainty. New York, NY: Chapman and Hall.Google Scholar
Hollowed, A.B., Ianelli, J.N. and Livingston, P.A. (2000) Including predation mortality in stock assessments: a case study for Gulf of Alaska walleye pollock. ICES Journal of Marine Science 57, 279293.Google Scholar
Houghton, J.D., Doyle, T.K., Davenport, J. and Hays, G.C. (2006) The ocean sunfish Mola mola: insights into distribution, abundance and behaviour in the Irish and Celtic Seas. Journal of the Marine Biological Association of the United Kingdom 86, 12371243.Google Scholar
Ichii, T., Mahapatra, K. and Okamura, H. (2006) Stock assessment of the autumn cohort of neon flying squid (Ommastrephes bartramii) in the North Pacific based on past large-scale high seas driftnet fishery data. Fisheries Research 78, 286297.Google Scholar
Jackson, G.D. and Choat, J.H. (1992) Growth in tropical cephalopods: an analysis based on statolith microstructure. Canadian Journal of Fisheries Aquatic Sciences 49, 218228.Google Scholar
Jensen, O.P., Gilroy, D.J. and Hogan, Z. (2009) Evaluating recreational fisheries for an endangered species: a case study of taimen, Huchotaimen, in Mongolia . Canadian Journal of Fisheries Aquatic Sciences 66, 17071718.Google Scholar
Jiao, Y., Hayes, C. and Cortés, E. (2009) Hierarchical Bayesian approach for population dynamics modelling of fish complexes without species-specific data. ICES Journal of Marine Science 66, 367377.Google Scholar
Livingston, P.A. and Methot, R.D. (1998) Incorporation of predation into a population assessment model of eastern Bering Sea walleye pollock. Fishery Stock Assessment Models, 663678.Google Scholar
Moustahfid, H., Tyrrell, M.C. and Link, J.S. (2009) Accounting explicitly for predation mortality in surplus production models: an approach to longline inshore squid (Loligo pealeii). North American Journal of Fisheries Management 29, 15551566.Google Scholar
Musick, J.A., Bonfil, R. and Stevens, J.D. (2005) Management techniques for elasmobranch fisheries. Rome: FAO.Google Scholar
Murata, M. (1990) Oceanic resources of squids. Marine Behavior and Physiology 18, 1971.Google Scholar
Pallare, P. and Restrepo, V. (2003) Use of delay-difference models to assess the India bigeye stock. IOCT Proceedings 6, 148150.Google Scholar
Pierce, G.J. and Guerra, A. (1994) Stock assessment methods used for cephalopod fisheries. Fisheries Research 21, 255285.Google Scholar
Quinn, T.J. and Deriso, R.B. (1999) Quantitative fish dynamics. New York, NY: Oxford University Press.Google Scholar
Robert, M., Faraj, A. and McAllister, M.K. (2010) Bayesian state-space modelling of the De Lury depletion model: strengths and limitations of the method, and application to the Moroccan octopus fishery. ICES Journal of Marine Science 67, 12721290.Google Scholar
Roper, C.F., Sweeney, M.J. and Nauen, C.E. (1984) FAO species catalogue. Vol. 3. Cephalopods of the world. An annotated and illustrated catalogue of species of interest to fisheries. Rome: FAO Fisheries Synopsis.Google Scholar
Schnute, J.T. (1985) A general theory for analysis of catch and effort data. Canadian Journal of Fisheries and Aquatic Sciences 42, 414429.Google Scholar
Su, Z.M. and Liu, Q. (1998) A continuous Fox-form of the surplus production observation-error estimator. Fisheries Research 34, 5976.Google Scholar
Su, Z.M. and Randall, M.P. (2012) Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error. Ecological Modelling 224, 7689.Google Scholar
Tyrrell, M.C., Link, J.S. and Moustahfid, H. (2011) The importance of including predation in fish population models: implications for biological reference points. Fisheries Research 108, 18.Google Scholar
Walters, C.J. (2011) Continuous time Schnute–Deriso delay-difference model for age-structured population dynamics, http://www.fisheries.ubc.ca/biblio/author/2.Google Scholar
Walters, C.J. and Martell, S.J.D. (2004) Fisheries ecology and management. Princeton, NJ: Princeton University Press.Google Scholar
Wang, Y.G. and Chen, X.J. (2005) The resource and biology of economic oceanic squid in the world. Beijing: Ocean Press.Google Scholar
Wang, Y., Zheng, J. and Yu, C. (2014) Stock assessment of chub mackerel (Scomber japonicus) in the central East China Sea based on length data. Journal of the Marine Biological Association of the United Kingdom 94, 211217.Google Scholar
Welch, W.D. and Morris, J.F.T. (1993) Age and growth of flying squid (Ommustrephes burtrumii). Bulletin of the International North Pacific Fisheries Commission 53, 183190.Google Scholar
Yatsu, A., Midorikawa, S. and Shimada, T. (1997) Age and growth of the neon flying squid, Ommastrephes bartramii, in the North Pacific Ocean. Fisheries Research 29, 257270.Google Scholar
Young, I.A., Pierce, G.J. and Daly, H.I. (2004) Application of depletion methods to estimate stock size in the squid (Loligo forbesi) in Scottish waters (UK). Fisheries Research 69, 211227.Google Scholar