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Evaluating the performance of survey-based operational management procedures

Published online by Cambridge University Press:  17 March 2010

Marine Pomarede ,
Richard Hillary ,
Leire Ibaibarriaga ,
Johannes Bogaards  and
Panayiota Apostolaki
Marine Pomarede
Affiliation:
Fisheries Group, Imperial College, Division of Biology, Silwood Park, Ascot SL5 7PY, UK
Richard Hillary
Affiliation:
Fisheries Group, Imperial College, Division of Biology, Silwood Park, Ascot SL5 7PY, UK
Leire Ibaibarriaga
Affiliation:
AZTI, Herrera Kaia, Portualdea z/g, 20110 Pasajes, Spain
Johannes Bogaards
Affiliation:
IMARES, PO Box 68, Haringkade 1, 1970 AB, IJmuiden, The Netherlands
Panayiota Apostolaki
Affiliation:
CEFAS, Pakefield road, NR33 OHT, Lowestoft, UK
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Abstract

The design and evaluation of survey-based management strategies is addressed in this article, using three case-study fisheries: North Sea herring, Bay of Biscay anchovy and North Sea cod, with a brief history and the main management issues with each fishery outlined. A range of operational management procedures for the case study stocks were designed and evaluated using trends that may be derived from survey indices (spawner biomass, year-class strength and total mortality) with an array of simple and more structured observation error regimes simulated. Model-free and model-based indicators of stock status were employed in the management procedures. On the basis of stochastic stock-specific simulations, we identified the following key determinants of successful management procedures: (i) adequate specification of the stock-recruit relationship (model structure, parameter estimates and variability), (ii) knowledge of the magnitude and structure of the variation in the survey indices, and (iii) explication of the particular management objectives, when assessing management performance. More conservative harvesting strategies are required to meet specified targets in the presence of increasing stochasticity, due to both process and observation error. It was seen that survey-based operational management procedures can perform well in the absence of commercial data, and can also inform aspects of survey design with respect to acceptable levels of error or bias in the surveys.

Keywords

FLR fishery simulation systemManagement strategy evaluationFish surveyFishery-independent dataHerringAnchovyCodNorth SeaBiscay
Type
Research Article
Information
Aquatic Living Resources , Volume 23 , Issue 1 , January 2010 , pp. 77 - 94
Copyright
© EDP Sciences, IFREMER, IRD, 2010

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References

Anonymous, 2004, Inquiry into the future of the Scottish fishing industry. The Royal Society of Edinburgh. Edinburgh, pp. 1–108.
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
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
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
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.
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.
Butterworth, D.S., Punt, A.E., 1999, Experiences in the evaluation and implementation of management procedures. ICES J. Mar. Sci. 56, 985–998. CrossRef
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.
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
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
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
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. CrossRef
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
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
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
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.
FISBOAT, 2003, Description of work Sixth framework programme priority [8.1] [Policy-oriented research]. Specific targeted research or innovation project. Annex I.
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.
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
Hammond P.S., Donovan G.P., The RMP: managing whales in an uncertain world. J. Cetacean Res. Manage. Spec. Issue 3, in press.
Hillary, R., 2009, An introduction to FLR fisheries simulation tools. Aquat. Living Resour. 22, 225–232. CrossRef
ICES, 1991, Herring assessment working group for the area south of 62oN. ICES CM 1991/Assess.15.
ICES, 2001, Study group on evaluation of current assessment procedures for North Sea herring. ICES CM 2001/ACFM:22.
ICES 2006a, Herring assessment working group for the area south of 62oN. ICES CM 2006/ACFM:20.
ICES, 2006b, Working group on the assessment of mackerel, horse mackerel, sardine and anchovy. ICES CM 2006/ACFM:08.
ICES, 2006c, Working group on the assessment of demersal stocks in the North Sea and Skagerrak. ICES CM 2006/ACFM:09.
ICES, 2007a, ICES Advisory Committee on Fishery Management, Advisory Committee on the Marine Environment and Advisory Committee on Ecosystems. ICES advice, 6.
ICES, 2007b, Herring assessment working group for the area south of 62°N. ICES CM 2007/ACFM:11.
ICES, 2008, Herring assessment working group for the area south of 62°N. ICES CM 2008/ACOM:02.
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.
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
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
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.
Lewy, P., Nielsen, A., 2003, Modelling stochastic fish stock dynamics using Markov chain Monte Carlo. ICES J. Mar. Sci. 60, 743–752. CrossRef
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. CrossRef
Needle C.L., 2005, SURBA 3.0: Technical Manual (first draft). In: FRS Marine Laboratory Aberdeen (Ed.), pp. 10.
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
O'Dwyer A., 2003, Handbook of PI and PID controller tuning rules. Imperial College Press.
Patterson K., Melvin G.D., 1996, Integrated catch at age analysis. Version 1.2. Scottish Fish. Res. Rep. 58.
Pope J.G., 1991, The ICES multispecies assessment group: evolution, insights and future problems. ICES Mar. Sci. Symp. 23–33.
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
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
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
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
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
Smith A.D.M., 1993, Risk assessment or management strategy evaluation: what do managers need and want? ICES CM 1993/D:18.
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
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.
Woillez, M., Rivoirard, J., Petitgas, P., 2009, Notes on survey-based spatial indicators for monitoring fish populations. Aquat. Living Resour. 22, 155–164. CrossRef