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Issue Aquat. Living Resour.
Volume 22, Number 2, April-June 2009
Fish Stock Assessments Using Surveys and Indicators
Page(s) 233 - 241
DOI 10.1051/alr/2009024
Published online 17 June 2009

References of  Aquat. Living Resour. 22, 233–241 (2009)
  • Abella A., Caddy J.F., Serena F., 1997, Do natural mortality and availability decline with age? An alternative yield paradigm for juvenile fisheries, illustrated by hake fishery in the Mediterranean. Aquat. Living Resour. 10, 257–269 [CrossRef] [EDP Sciences].
  • Abella A., Belluscio A., Bertrand J., Carbonara P., Giordano D., Sbrana M., Zamboni A., 1999, Use of MEDITS data and commercial fleet information for the assessment of some Mediterranean demersal resources. Aquat. Living Resour. 12, 155–166 [CrossRef] [EDP Sciences].
  • Alegrìa-Hernandez V., Jukic S., 1988, Stock-recruitment relationship for the hake (Merluccius merluccius L.) from the open middle Adriatic-Jabuka Pit. FAO Fish. Rep. 394, 137–141.
  • Anonymous, 2002, Stock assessment in the Mediterranean. Final Report EU Project No. 99/047.
  • Anonymous, 2007, Programma Operativo FEP per il settore pesca, Italia, CCI: 2007IT14FPO001, 178 pp. http://www.fondieuropei2007-2013.it/upload%5CFEP%5C20071115_PA_programma_operativo_FEP.pdf
  • Bull B., Francis R.I.C.C., Dunn A., McKenzie A., Gilbert D.J., Smith M.H., 2005, CASAL (C++ algorithmic stock assessment laboratory): CASAL User Manual v2.07- 2005/08/21. NIWA Tech. Rep. 127.
  • Butterworth D.S., 2007, Why a management procedure approach? Some positives and negatives. ICES J. Mar. Sci. 64, 613–617 [CrossRef].
  • Butterworth D.S., A.E. Punt, 1999, Experiences in the evaluation and implementation of management procedures. ICES J. Mar. Sci. 56, 985–998 [CrossRef].
  • Beare D.J., Needle C.L., Burns F. Reid D.G., 2005, Using survey data independently from commercial data in stock assessment: an example using haddock in ICES Division VIa. ICES J. Mar. Sci. 62, 996–1005 [CrossRef].
  • Beverton R.J.H., Holt S.J., 1957, On the dynamics of exploited fish populations. UK Min. Agric. Fish., Fish. Invest. (Ser. 2) No. 19.
  • Barrowman N.J., Myers R.A., 2000, Still more spawner-recruitment curves: the hockey stick and its generalizations. Can. J. Fish. Aquat. Sci. 57, 665–676 [CrossRef].
  • Caddy J.F., 1991, Death rates and time intervals: is there an alternative to the constant natural mortality rate axiom? Rev. Fish Biol. Fish. 1, 109–138.
  • Caddy J.F., 2006, The potential use of indicators, reference points and the traffic light convention for managing Black Sea fisheries. In: Lembo G. (Ed.) Selected papers presented at the Workshop on biological reference points. Rome, 20-21 April 2004. General Fisheries Commission for the Mediterranean. Studies and Reviews No. 83. Rome, FAO.
  • Chen S., Watanabe S., 1989, Age dependence of natural mortality coefficient in fish population dynamics. Nippon Suisan Gakkaishi 55, 205–208.
  • Cotter J., Petitgas P., Abella A., Apostolaki P., Mesnil B., Politou C.Y, Rivoirard J., Rochet M.J., Spedicato M,. Trenkel V.M, Woillez M., 2009, Towards an ecosystem approach to fisheries management (EAFM) when trawl surveys provide the main source of information. Aquat. Living Resour. 22, 243–254.
  • Darby C.D., Flatman S. 1994, Lowestoft VPA Suite Version 3.1 User Guide. MAFF: Lowestoft.
  • De Lara M., Doyen L., Guilbaud T., Rochet M.J., 2007, Is a management framework based on spawning-stock biomass indicators sustainable? A viability approach. ICES J. Mar. Sci. 64, 1–7.
  • De Oliveira J.A.A, Kell L.T., Punt A.E., Roel B.A., Butterworth D.S., 2008, Managing without best predictions: the management strategy evaluation framework. In: Payne A., Cotter J., Potter T. (Eds.) Advances in Fisheries Science. 50 years on from Beverton and Holt. Blackwell Publishing, Oxford, pp. 104–134.
  • FAO, 1996, Technical Guidelines for Responsible Fisheries. No. 2. Rome, FAO: 54p.
  • FAO, 2003, The ecosystem approach to fisheries. FAO Technical Guidelines for Responsible Fisheries. No. 4, Suppl. 2. Rome.
  • Gallucci V.F., Saila S.B., Gustafson J., Rothschild B.J. (Eds.). 1996, Stock assessment: quantitative methods and applications for small-scale fisheries. CRC Press, Lewis Publishers.
  • Gulland J.A., 1969, Manuel des méthodes d'évaluation des stocks d'animaux aquatiques. Première partie-Analyse des populations. Manuels FAO de science halieutique, N° 4.
  • Haddon M., 2001, Modelling and quantitative methods in fisheries. Chapman & Hall CRC Press.
  • Haltuch M.A., Punt, A.E., Dorn M.W., 2008, Evaluating alternative estimators of fishery management reference points. Fish. Res. 94, 210–303 [CrossRef].
  • Hilborn R., Walters C.J., 1992, Quantitative Fisheries Stock Assessment. Choice, Dynamics & Uncertainty. Chapman & Hall.
  • Hoggarth D.D., Abeyasekera S., Arthur R.I., Beddington J.R., Burn, R.W., Halls A.S., Kirkwood G.P., McAllister M., Medley P., Mees C.C., Parkes G.B., Pilling G.M., Wakeford R.C., Welcomme R.L., 2006, Stock assessment for fishery management – A framework guide to the stock assessment tools of the fisheries management science programme (FMSP). FAO Fish. Tech. Pap. No. 487, Rome, FAO.
  • Kell L.T., O'Brien C.M., Smith M.T., Stokes T.K., Rackham B.D., 1999, An evaluation of management procedures for implementing a precautionary approach in the ICES context for North Sea plaice (Pleuronectes platessa L.). ICES J. Mar. Sci. 56, 834–845 [CrossRef].
  • Kell L.T., Mosqueira I., Grosjean P., Fromentin J.M., Garcia D., Hillary R., Jardim E., Mardle S., Pastoors M.A., Poos J.J., Scott F., Scott R.D., 2007, FLR: an open-source framework for the evaluation and development of management strategies. ICES J. Mar. Sci. 64, 640–646 [CrossRef].
  • ICES, 1995, Report of the Working Group on Long-term Management Measures. ICES CM 1995/Assess.15.
  • Levi D., Andreoli M.G., Bonanno A., Fiorentino F., Garofalo G., Mazzola S., Norrito G., Patti B., Pernice G., Ragonese S., Giusto G.B., Rizzo P., 2003, Embedding sea surface temperature anomalies into the stock recruitment relationship of red mullet (Mullus barbatus L. 1758) in the Strait of Sicily. Scient. Mar. 67, 259–268.
  • Lembo G., Spedicato M.T,. 2006, Red mullet assessment in the GSA 10 using ALADYM simulation model. Sub-Committee Stock Assessment SAC-GFCM, FAO Headquarters, 11-14 Sept. 2006.
  • Lembo G., Martino S., Abella A.J., Fiorentino F., Spedicato M.T., 2007, ALADYM (Age-Length Based Dynamic Model): a stochastic simulation tool to predict population dynamics and management scenarios using fishery-independent information. Workshop on trawl survey based monitoring fishery system in the Mediterranean, GFCM, FAO, 26–28 March 2007.
  • Lleonart J., Salat J., 1997, VIT: Software for fishery analysis,. User's manual. FAO Computerised Information, Ser. Fish. 11.
  • McGarvey R., Feenstra J., Ye Q., 2007, Modeling fish number dynamically by age and length: partitioning cohort into “slices”. Can. J. Fish. Aquatic. Sci. 64, 1157-1173 [CrossRef].
  • Mesnil B., 2003, The catch-survey analysis (CSA) method of fish stock assessment: an evaluation using simulated data. Fish. Res. 63, 193-212 [CrossRef]
  • Mesnil B., Cotter J., Fryer R.J., Coby L. Needle C.L., Trenkel V.M., 2009, A review of fishery-independent assessment models, and initial evaluation based on simulated data. Aquat. Living Resour. 22, 207–216.
  • Methot R.D., 2000, Technical description of the stock synthesis assessment program. NOAA Technical Memorandum NMFS{NWFSC{43. http://www.nwfsc.noaa.gov/ publications/techmemos/tm43/tm43.pdf
  • Needle C.L. 2003, Survey-based assessments with surba. Working Document to the ICES Working Group on Methods of Fish Stock Assessment, Copenhagen, 29 Jan.–5 Febr. 2003.
  • Quinn T.J.II,. Deriso R.B., 1999, Quantitative fish dynamics. Oxford University Press, Oxford.
  • Pastoors M.A., Poos J.J., Kraak S.B.M., Machiels M.A.M., 2007, Validating management simulation models and implications for communicating results to stakeholders. ICES J. Mar. Sci. 64, 818–824 [CrossRef].
  • Pilling G.M., Apostolaki P., Failler P., Floros C., Large P.A., Morales-Nin B., Reglero P., Stergiou K.I., Tsikliras A.C., 2008, Assessment and management of data-poor fisheries. In: Payne A., Cotter J., Potter T. (Eds.) Advances in Fisheries Science. 50 years on from Beverton and Holt. Blackwell Publishing, Oxford, pp. 280–305.
  • Pope J.G., 1972, An investigation on the accuracy of virtual population analysis using cohort analysis. Int. Comm. Northw. Atl. Fish. Res. Bull. 9, 65–74.
  • Porch C.E., Eklund A.M., Scott G.P., 2006, A catch-free stock assessment model with application to goliath grouper (Epinephelus itajara) off southern Florida. Fish. Bull. 104, 89–101.
  • Prager M., 2005, Users Manual for ASPIC: A Stock-Production Model Incorporating Covariates (vers.5), NMFS, Beaufort Lab. Doc. BL-2004-01.
  • Punt A.E., Hilborn R., 1996, Biomass dynamic models. User's manual. FAO Computerized Information Series (Fisheries) No. 10. Rome, FAO.
  • Punt A.E., 2003, Evaluating the efficacy of managing West Coast groundfish resources through simulations. Fish. Bull. 101, 860–873.
  • Ricker W.E., 1954, Stock and recruitment. J. Fish. Res. Board Can. 11, 559–623.
  • Shepherd J.G., 1982, A versatile new stock-recruitment relationship for fisheries, and the construction of sustainable yield curves. J. Cons. Explor. Mer 40, 67–75.
  • Sinclair A.F., 2001, Natural mortality of cod (Gadus morhua) in the Southern Gulf of St Lawrence. ICES J. Mar. Sci. 58, 1–10 [CrossRef].
  • Sparre P., Venema S.C., 1998, Introduction to tropical fish stock assessment. Part 1, manual. FAO Fish. Techn. Pap. 306 Rev. 2.
  • Skagen D.W., Dankel D. 2007, Management with sparse data. ICES CM 2007/O:22.
  • Thompson W.F., Bell F.H., 1934, Biological statistics of the Pacific halibut fishery. 2. Effect of changes in intensity upon total yield and yield per unit of gear. Rep. Int. Fish. (Pacific Halibut) Comm. N°8.
  • Trenkel V.M., 2008, A two-stage biomass random effects model for stock assessment without catches: What can be estimated using only survey biomass indices? Can. J. Fish. Aquat. Sci. 65, 1024–1035 [CrossRef].
  • Trenkel V.M., Rochet M.J., Mesnil B., 2007, From model-based prescriptive advice to indicator-based interactive advice. ICES J. Mar. Sci. 64, 768–774 [CrossRef].
  • Ulrich C., Andersen B.S., Sparre P.J., Nielsen J.R., 2007, TEMAS: fleet-based bio-economic simulation software to evaluate management strategies accounting for fleet behaviour. ICES J. Mar. Sci. 64, 647–651 [CrossRef].



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