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Original Articles

Assessing the risk of alternative management strategies in a Mediterranean fishery: protecting the younger vs reducing fishing effort

, &
Pages 183-198 | Received 15 Feb 2013, Accepted 15 Jul 2013, Published online: 09 Aug 2013

REFERENCES

  • E.J. Allen, Modeling with Ito Stochastic Differential Equations, Springer, Dordrecht, 2007.
  • E.J. Allen, Derivation of stochastic partial differential equations for size- and age-structured populations, J. Biol. Dyn. 3 (2009), pp. 73–86. doi: 10.1080/17513750802162754
  • P. Alvarez and M. Chifflet, The fate of eggs and larvae of three pelagic species, mackerel (Scomber scombrus), horse mackerel (Trachurus trachurus) and sardine (Sardina pilchardus) in relation to prevailing currents in the Bay of Biscay: Could they affect larval survival? Sci. Mar. 76(3) (2012), pp. 573–586. doi: 10.3989/scimar.03298.07H
  • K. Antonakakis, M. Giannoulaki, A. Machias, S. Somarakis, S. Sanchez, L. Ibaibarriaga, and A. Uriarte, Assessment of the sardine (Sardina pilchardus Walbaum, 1792) fishery in the eastern Mediterranean basin (North Aegean Sea), Med. Mar. Sci. 12/2 (2011), pp. 333–357.
  • C.J. Arendse, A. Govendera, and G.M. Branch, Are closed fishing seasons an effective means of increasing reproductive output? A per-recruit simulation using the limpet Cymbula granatina as a case history, Fish. Res. 85 (2007), pp. 93–100. doi: 10.1016/j.fishres.2007.01.001
  • S.A. Bell, A beginner's guide to uncertainty in measurement, National Physical Laboratory, Teddington, Middlesex, 2001.
  • A. Charles, Living with uncertainty in fisheries: analytical methods, management priorities and the Canadian groundfishery experience, Fish. Res. 37 (1998), pp. 37–50. doi: 10.1016/S0165-7836(98)00125-8
  • W. Chen, M. Al-Husaini, and M. Al-Foudari, Using age-structured models to develop a stock recovery strategy for Kuwait's shrimp fishery, Fish. Res. 2–3 (2007), pp. 276–284. doi: 10.1016/j.fishres.2006.10.003
  • J.E. Cloern and F.H. Nichols, A von Bertalanffy growth model with a seasonally varying coefficient, J. Fish. Res. Board Can. 35 (1978), pp. 1479–1482. doi: 10.1139/f78-231
  • J.M. Da-Rocha, M.D. Garza-Gil, and M.M. Varela-Lafuente, A model of fishing periods applied to the European sardine fishery, Fish. Res. 109 (2011), pp. 16–24. doi: 10.1016/j.fishres.2011.01.008
  • N. Fouzai, M. Coll, I. Palomera, A. Santojanni, E. Arneri, and V. Christensen, Fishing management scenarios to rebuild exploited resources and ecosystems of the Northern-Central Adriatic (Mediterranean Sea), J. Mar. Sys. (2012), pp. 102–105.
  • J.D. Gibbons and S. Chakraborti, Nonparametric Statistical Inference, 4th ed., Marcel Dekker, New York, 2003.
  • D.J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, Siam Rev., Soc. Ind. App. Math. 43 (2001), pp. 525–546.
  • H. Hoppensteadt, Mathematical theories of populations demographics, genetics, and epidemics series, CBMS-NSF Regional Conference Series in Applied Mathematics, New York, 1975.
  • H. Hoshino, E.J. Milner-Gulland, and R.M. Hillary, Bioeconomic adaptive management procedures for short-lived species: A case study of Pacific saury (Cololabis saira) and Japanese common squid (Todarodes pacificus), Fish. Res. 121–122 (2012), pp. 17–30. doi: 10.1016/j.fishres.2012.01.007
  • S. Guénette and T.J. Pitcher, An age-structured model showing the benefits of marine reserves in controlling overexploitation, Fish. Res. 39 (1999), pp. 295–303. doi: 10.1016/S0165-7836(98)00173-8
  • Y. Jiao, Y. Chen, and J. Wroblewski, An application of the composite risk assessment method in assessing fisheries stock status, Fish. Res. 72 (2005), pp. 173–183. doi: 10.1016/j.fishres.2004.11.003
  • K. Kugarajh, L.K. Sandal, and G. Berge, Implementing a stochastic bioeconomic model for the north-east arctic cod fishery, J. Bioecon. 8 (2006), pp. 35–53. doi: 10.1007/s10818-005-5783-x
  • A. Machias, M. Giannoulaki, S. Somarakis, E. Schismenou, K. Tsagkarakis, A. Siapatis, C. Stamataki, V. Vassilopoulou, A. Kalianiotis, and C. Papaconstantinou, Acoustic biomass estimates of sardine in the Aegean sea (June 2003, 2004, 2005, 2006). Working document presented in the Working group on Small Pelagic Species, Sub-Committee on Stock Assessment, GMCM. Athens, Greece, 2007. Available at http://www.icm.csic.es/rec/projects/scsa/
  • C.D. Maravelias, R. Hillary, J. Haralabous, and E.V. Tsitsika, Stochastic bioeconomic modelling of alternative management measures for anchovy in the Mediterranean Sea, ICES J. Mar. Sci. 67 (2010), pp. 1291–1300. doi: 10.1093/icesjms/fsq018
  • MATLAB and Statistics Toolbox Release 2012b, The MathWorks, Inc., Natick, MA, USA.
  • M.O. Nevárez-Martínez, E.A. Chávez, M.A. Cisneros-Mata, and D. Lluch-Belda, Modeling of the Pacific sardine Sardinops caeruleus fishery of the Gulf of California, Mexico, Fish. Res. 41 (1999), pp. 273–283. doi: 10.1016/S0165-7836(99)00023-5
  • D.V. Politikos, D.E. Tzanetis, C.V. Nikolopoulos, and C.D. Maravelias, The application of an age-structured model to the north Aegean anchovy fishery: An evaluation of different management measures, Math. Biosci. 237 (2012), pp. 17–27. doi: 10.1016/j.mbs.2012.03.002
  • R. Puga, S. Hernandez Vasquez, J.L. Martinez, and M.E. De Leon, Bioeconomic modelling and risk assessment of the Cuban fishery for spiny lobster Panulirus argus, Fish. Res. 75 (2005), pp. 149–163. doi: 10.1016/j.fishres.2005.03.014
  • Report of the sub-Committee on Stock Assessment (SCSA) Working Group on Stock Assessment of small pelagic species, 2009. Fisheries Commission for the Meditarranean (GFCM). Italy, 26–30 October, 70pp. Available at http://151.1.154.86/GfcmWebSite/SAC/SCSA/2009/SCSA_WG_Small_Pelagics_2009_Report_Draft.pdf
  • S. Somarakis, K. Ganias, A. Siapatis, C. Koutsikopoulos, A. Machias, and C. Papaconstantinou, Spawning habitat and daily egg production of sardine (Sardina pilchardus) in the eastern Mediterranean, Fish. Oceanogr. 15 (2006), pp. 281–292. doi: 10.1111/j.1365-2419.2005.00387.x
  • E.V. Tsitsika, C.D. Maravelias, and J. Haralabous, Modelling and forecasting pelagic fish production using univariate and multivariate ARIMA models, Fish. Sci. 73 (2007), pp. 979–988. doi: 10.1111/j.1444-2906.2007.01426.x
  • Z. Zhang and A. Campbell, Application of a stochastic spawning stock biomass per recruit model for the horse clam fishery in British Columbia, Fish. Res. 57 (2002), pp. 9–23. doi: 10.1016/S0165-7836(01)00333-2