Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T03:59:00.459Z Has data issue: false hasContentIssue false
  • English
  • Français

ALADYM: an age and length-based single species simulator for exploring alternative management strategies

Published online by Cambridge University Press:  17 June 2009

Giuseppe Lembo ,
Alvaro Abella ,
Fabio Fiorentino ,
Sergio Martino  and
Maria-Teresa Spedicato
Giuseppe Lembo
Affiliation:
COISPA Tecnologia & Ricerca, Via dei trulli 18-20, 70126 Bari, Italy
Alvaro Abella
Affiliation:
ARPAT-AREA MARE, Via Marradi 114, Livorno, Italy
Fabio Fiorentino
Affiliation:
IAMC-CNR, Via L. Vaccara 61, Mazara del Vallo (TP), Italy
Sergio Martino
Affiliation:
COISPA Tecnologia & Ricerca, Via dei trulli 18-20, 70126 Bari, Italy
Maria-Teresa Spedicato
Affiliation:
COISPA Tecnologia & Ricerca, Via dei trulli 18-20, 70126 Bari, Italy
Get access

Abstract

ALADYM (age-length based dynamic model) is an age-length based simulation model designed to predict the consequences of management scenarios on a single population, in terms of different metrics and indicators. Removals are simulated as total mortality modulated using a selectivity pattern and a fishing activity coefficient. ALADYM uses the classical equations of population dynamics to create a tool that uses fishery-independent information (e.g. from trawl surveys) as the primary source. The formulation of population dynamics at a small time scale (month) allows to model the effects of harvest controls that evolve through the year, which is particularly useful for fast growing species. The possibility of specifying a vector of natural mortality by age/length makes the model more suitable for situations where stocks are exploited at an early life stage, as in many Mediterranean fisheries, while introducing variations along the time of the harvesting pattern accounts for non-equilibrium situations. Stochastic effects can be added to some key life-history traits to incorporate uncertainty in input parameters and in their relationships. ALADYM can be used for a range of applications such as comparing management strategies, evaluating indicator changes or searching for reference points.

Keywords

Fish population dynamicsSimulation modelFishery-independent approachFishery management
Type
Research Article
Information
Aquatic Living Resources , Volume 22 , Issue 2: Fish Stock Assessments Using Surveys and Indicators , April 2009 , pp. 233 - 241
Copyright
© EDP Sciences, IFREMER, IRD, 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

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
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
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. CrossRef
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. CrossRef
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. CrossRef
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. CrossRef
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. CrossRef
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. CrossRef
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. CrossRef
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. CrossRef
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