Free Access
Issue
Aquat. Living Resour.
Volume 23, Number 1, January-March 2010
Page(s) 77 - 94
Section Regular articles
DOI https://doi.org/10.1051/alr/2010005
Published online 17 March 2010
  • Anonymous, 2004, Inquiry into the future of the Scottish fishing industry. The Royal Society of Edinburgh. Edinburgh, pp. 1–108. [Google Scholar]
  • Apostolaki P., Hillary R., 2009, Harvest control rules in the context of fishery-independent management of fish stocks. Aquat. Living Resour. 22, 217–224. [CrossRef] [EDP Sciences] [Google Scholar]
  • 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] [Google Scholar]
  • Bogaards J.A., Kraak S.B.M., Rijnsdorp A.D., 2009, Bayesian survey-based assessment of North Sea plaice (Pleuronectes platessa): extracting integrated signals from multiple surveys. ICES J. Mar. Sci. 66, 665–679. [CrossRef] [Google Scholar]
  • Butterworth D.S., Bergh M.O., 1993, The development of a management procedure for the South African anchovy resource. In: Smith S.J., Hunt J.J., Rivard D. (Eds.), Risk evaluation and biological reference points for fisheries management, Can. Spec. Publ. Fish. Aquat. Sci., pp. 83–99. [Google Scholar]
  • Butterworth D.S., Cochrane K.L., De Oliveira J.A.A., 1997, Management procedures: a better way to manage fisheries? The South African experience. In: Pikitch E.K., Huppert D.D., Sissenwine M.P. (Eds.), Global trends: fisheries management. Bethesda, Maryland, Am. Fish. Soc. Symp. 20, 83–90. [Google Scholar]
  • Butterworth D.S., Punt A.E., 1999, Experiences in the evaluation and implementation of management procedures. ICES J. Mar. Sci. 56, 985–998. [CrossRef] [Google Scholar]
  • Campbell R.A., Dowling N.A., 2005, Evaluating harvest strategies for a rapidly expanding fishery: the Australian broadbill swordfish fishery. In: Kruse G.H., Gallucci V.F., Hay D.E., Perry R.I., Peterman R.M., Shirley T.C., Spencer P.D. (Eds.), Fisheries assessment and management in data-limited situations. University of Alaska, Fairbanks, Alaska Sea Grant College Program Report 05–02, pp. 509–532. [Google Scholar]
  • Chen J.H., Thompson M.E., Wu C.B., 2004, Estimation of fish abundance indices based on scientific research trawl surveys. Biometrics 60, 116–123. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  • Cochrane K.L., Butterworth D.S., de Oliveira J.A.A., Roel B.A., 1998, Management procedures in a fishery based on highly variable stocks and with conflicting objectives: experiences in the South African pelagic fishery. Rev. Fish Biol. Fish. 8, 177–214. [CrossRef] [Google Scholar]
  • Cook R.M., 1997, Stock trends in six North Sea stocks as revealed by an analysis of research vessel surveys. ICES J. Mar. Sci. 54, 924–933. [CrossRef] [Google Scholar]
  • Cotter A.J.R., Burt L., Paxton C.G.M., Fernandez C., Buckland S.T., Pax J.X., 2004, Are stock assessment methods too complicated? Fish Fish. 5, 235–255. [Google Scholar]
  • Cotter A.J.R., Mesnil B., Piet G.J., 2007, Estimating stock parameters from trawl cpue-at-age series using year-class curves. ICES J. Mar. Sci. 64, 234–247. [CrossRef] [Google Scholar]
  • Cotter A., Mesnil B., Witthames P., Parker-Humphreys M., 2009, Notes on nine biological indicators estimable from trawl surveys with an illustrative assessment for North Sea cod. Aquat. Living Resour. 22, 135–153. [CrossRef] [EDP Sciences] [Google Scholar]
  • De Oliveira J.A.A., Butterworth D.S., 2004, Developing and refining a joint management procedure for the multispecies South African pelagic fishery. ICES J. Mar. Sci. 61, 1432–1442. [CrossRef] [Google Scholar]
  • Dichmont C.M., Deng A.R., Venables W.N., Punt A.E., Haddon M., Tattersall. K., 2005, A new approach to assessment in the NPF: spatial models in a management strategy environment that includes uncertainty. CSIRO Div. Marine Research, Hobart. [Google Scholar]
  • FISBOAT, 2003, Description of work Sixth framework programme priority [8.1] [Policy-oriented research]. Specific targeted research or innovation project. Annex I. [Google Scholar]
  • FAO, Food and Agriculture Organisation of the United Nations, 1996, Precautionary approach to fisheries. Part 2: Guidelines on the precautionary approach to capture fisheries and species introductions. In: FAO (Ed.) FAO Fish. Tech. Pap. 350, pp. 1–62. [Google Scholar]
  • Geromont H.F., De Oliveira J.A.A., Johnston S.J., Cunningham C.L., 1999, Development and application of management procedures for fisheries in southern Africa. ICES J. Mar. Sci. 56, 952–966. [CrossRef] [Google Scholar]
  • Hammond P.S., Donovan G.P., The RMP: managing whales in an uncertain world. J. Cetacean Res. Manage. Spec. Issue 3, in press. [Google Scholar]
  • Hillary R., 2009, An introduction to FLR fisheries simulation tools. Aquat. Living Resour. 22, 225–232. [CrossRef] [EDP Sciences] [Google Scholar]
  • ICES, 1991, Herring assessment working group for the area south of 62oN. ICES CM 1991/Assess.15. [Google Scholar]
  • ICES, 2001, Study group on evaluation of current assessment procedures for North Sea herring. ICES CM 2001/ACFM:22. [Google Scholar]
  • ICES 2006a, Herring assessment working group for the area south of 62oN. ICES CM 2006/ACFM:20. [Google Scholar]
  • ICES, 2006b, Working group on the assessment of mackerel, horse mackerel, sardine and anchovy. ICES CM 2006/ACFM:08. [Google Scholar]
  • ICES, 2006c, Working group on the assessment of demersal stocks in the North Sea and Skagerrak. ICES CM 2006/ACFM:09. [Google Scholar]
  • ICES, 2007a, ICES Advisory Committee on Fishery Management, Advisory Committee on the Marine Environment and Advisory Committee on Ecosystems. ICES advice, 6. [Google Scholar]
  • ICES, 2007b, Herring assessment working group for the area south of 62°N. ICES CM 2007/ACFM:11. [Google Scholar]
  • ICES, 2008, Herring assessment working group for the area south of 62°N. ICES CM 2008/ACOM:02. [Google Scholar]
  • IWC, International Whaling Commission, 1999, The revised management procedure (RMP) for baleen whales. Annex N to the Report of Scientific Committee. J. Cetacean Res. Manage. 1 (Suppl.), 251–258. [Google Scholar]
  • Johnston S.J., Butterworth D.S., 2005, The evolution of operational management procedures for the South African west coast rock lobster fishery. N.Z. J. Mar. Freshw. Res. 39, 687–702. [CrossRef] [Google Scholar]
  • 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] [Google Scholar]
  • Kirkwood G.P., 1997, The revised management procedure of the International Whaling Commission. In: Pikitch E.K., Huppert D.D., Sissenwine M.P. (Eds.), Global trends: fisheries management. Bethesda, Maryland, Am. Fish. Soc. Symp. 20, 91–99. [Google Scholar]
  • Lewy P., Nielsen A., 2003, Modelling stochastic fish stock dynamics using Markov chain Monte Carlo. ICES J. Mar. Sci. 60, 743–752. [CrossRef] [Google Scholar]
  • McAllister M.K., Kirchner C.H., 2001, Development of Bayesian stock assessment methods for Namibian orange roughy Hoplostethus atlanticus. S. Afr. J. Mar. Sci.- Suid-Afr. Tydsk. Seewetens. 23, 241–264. [Google Scholar]
  • Needle C.L., 2005, SURBA 3.0: Technical Manual (first draft). In: FRS Marine Laboratory Aberdeen (Ed.), pp. 10. [Google Scholar]
  • Nielsen A., Lewy P., 2002, Comparison of the frequentist properties of Bayes and the maximum likelihood estimators in an age-structured fish stock assessment model. Can. J. Fish. Aquat. Sci. 59, 136–143. [CrossRef] [Google Scholar]
  • O'Dwyer A., 2003, Handbook of PI and PID controller tuning rules. Imperial College Press. [Google Scholar]
  • Patterson K., Melvin G.D., 1996, Integrated catch at age analysis. Version 1.2. Scottish Fish. Res. Rep. 58. [Google Scholar]
  • Pope J.G., 1991, The ICES multispecies assessment group: evolution, insights and future problems. ICES Mar. Sci. Symp. 23–33. [Google Scholar]
  • Punt A.E., Donavan G.P., 2007, Developing management procedures that are robust to uncertainty: lessons from the International Whaling Commission. ICES J. Mar. Sci. 64, 603–612. [CrossRef] [Google Scholar]
  • Punt A.E., Pribac F., Taylor, Bruce L., Walker, Terence I., 2005, Harvest strategy evaluation for school and gummy shark. J. Northw. Atl. Fish. Sci. 35, 387–406. [CrossRef] [Google Scholar]
  • Punt A.E., Smith A.D.M., 1999, Harvest strategy evaluation for the eastern stock of gemfish (Rexea solandri). ICES J. Mar. Sci. 56, 860–875. [CrossRef] [Google Scholar]
  • Punt A.E., Smith A.D.M., Cui G.R., 2001, Review of progress in the introduction of management strategy evaluation (MSE) approaches in Australia's South East fishery. Mar. Freshw. Res. 52, 719–726. [CrossRef] [Google Scholar]
  • Rademeyer R.A., Plagányi E.E., Butterworth, D.S., 2007, Tips and tricks in designing management procedures. ICES J. Mar. Sci. 64, 618–625. [CrossRef] [Google Scholar]
  • Smith A.D.M., 1993, Risk assessment or management strategy evaluation: what do managers need and want? ICES CM 1993/D:18. [Google Scholar]
  • Trenkel V.M., 2008, A two-stage biomass random effects model for stock assessment without catches: what can be estimated using only biomass survey indices? Can. J. Fish. Aquat. Sci. 65, 1024–1035. [CrossRef] [Google Scholar]
  • Tuck G.N., Sainsbury K.J., Williams R., 2003, Abundance estimation and TAC setting for Patagonian toothfish (Dissostichus eleginoides) at Macquarie Island: a synopsis. Sub-Antarctic fisheries assessment group, SAFAG17, Agenda 5. [Google Scholar]
  • Woillez M., Rivoirard J., Petitgas P., 2009, Notes on survey-based spatial indicators for monitoring fish populations. Aquat. Living Resour. 22, 155–164. [CrossRef] [EDP Sciences] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.