Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-17T23:18:41.838Z Has data issue: false hasContentIssue false
  • English
  • Français

Using the ALADYM simulation model for exploring the effects of management scenarios on fish population metrics

Published online by Cambridge University Press:  19 July 2010

Maria Teresa Spedicato ,
Jean-Charles Poulard ,
Chrissi-Yianna Politou ,
Krzysztof Radtke ,
Giuseppe Lembo  and
Pierre Petitgas
Maria Teresa Spedicato*
Affiliation:
COISPA Tecnologia & Ricerca, Via dei trulli 18-20, 70126 Bari, Italy
Jean-Charles Poulard
Affiliation:
IFREMER, Dept. Ecologie & Modèles Halieutiques, EMH, BP 21105, 44311 Nantes, France
Chrissi-Yianna Politou
Affiliation:
Hellenic Centre for Marine Research, Agios Kosmas, 16777 Helliniko, Greece
Krzysztof Radtke
Affiliation:
Sea Fisheries Institute, Kołłtaja 1, 81-332 Gdynia, Poland
Giuseppe Lembo
Affiliation:
COISPA Tecnologia & Ricerca, Via dei trulli 18-20, 70126 Bari, Italy
Pierre Petitgas
Affiliation:
IFREMER, Dept. Ecologie & Modèles Halieutiques, EMH, BP 21105, 44311 Nantes, France
*
a Corresponding author: spedicato@coispa.it
Get access

Abstract

Simulation of fisheries systems is a widely used approach that integrates monitoring and assessment tools. We applied the ALADYM (age-length based dynamic model) simulation model to three different studies aimed at investigating correlations between pressure and population metrics, exploring the viability of different mortality levels in long-term scenarios and predicting the effects of combined management measures. Uncertainty was incorporated into the simulations following the Monte Carlo paradigm. Three stocks were used for these exercises: red mullet in the central-southern Tyrrhenian Sea and European hake in both the Bay of Biscay and the Aegean Sea. The analysis of the relationships between total mortality and indicators highlighted significant pairwise negative correlations for red mullet. These signals of decline were supported by the spawning potential ratio indicator (mean exploited to mean unexploited spawning-stock biomass ESSB/USSB), which was low compared to target levels. It only remained within safe bounds (>0.2; probability: 0.90–0.95) at total mortality levels lower than 1.6. The simulation results for European hake in the Bay of Biscay showed that a sustainable exploitation rate might range from 0.87 to 1.04. The benefits of combined management measures were demonstrated for European hake in the Aegean Sea, and with a further dataset on the Eastern cod stock in the Baltic Sea.

Keywords

Simulation modelModel-based indicatorsFishery managementReference pointsMullus barbatusMerluccius merlucciusMediterranean SeaAtlantic Ocean
Type
Research Article
Information
Aquatic Living Resources , Volume 23 , Issue 2 , April 2010 , pp. 153 - 165
Copyright
© EDP Sciences, IFREMER, IRD 2010

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.J., Serena, F., 1998, Selettività e vulnerabilità del nasello nella pesca a strascico. Biol. Mar. Medit. 5, 496–504.Google Scholar
Anonymous, 2002, Stock Assessment in the Mediterranean - SAMED. Final Report EU Project n° 99/047.
Anonymous, 2006, National Program for Fisheries Data Collection 2002-2006 (ER 1543/2000). Techn. Rep. HCMR.
Bartolino, V., Ottavi, A., Colloca, F., Ardizzone, G.D., Stefansson, G., 2008, Bathymetric preferences of juvenile European hake (Merluccius merluccius). ICES J. Mar. Sci. 65, 963–969.CrossRefGoogle Scholar
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. Stud. Rev. GFCM-FAO, No. 83.
Chen, S., Watanabe, S., 1989, Age dependence of natural mortality coefficient in fish population dynamics. Nippon Suisan Gakkaishi 55, 205–208.CrossRefGoogle Scholar
Cooke, J.G., 1999, Improvement of fishery-management advice through simulation testing of harvest algorithms. ICES J. Mar. Sci. 56, 797–810.CrossRefGoogle Scholar
Cotter, J., Petitgas, P., Abella, A., Apostolaki, P., Mesnil, B., Politou, C.-Y., Rivoirard, J., Rochet, M.-J., Spedicato, M.T., 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.CrossRefGoogle Scholar
Cotter, J., 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.CrossRefGoogle Scholar
de Pontual, H., Groison, A.L, Piñeiro, C., Bertignac, M., 2006, Evidence of underestimation of European hake growth in the Bay of Biscay, and its relationship with bias in the agreed method of age estimation. ICES J. Mar. Sci. 63, 1674–1681.CrossRefGoogle Scholar
Fiorentino, F., Zamboni, A., Relini, G., 1998, La selettività della rete a strascico in Merluccius merluccius sulla base delle esperienze riportate in letteratura. Biol. Mar. Medit. 5, 465–474.Google Scholar
Haddon, M., 2001, Modelling and quantitative methods in fisheries. Chapman & Hall CRC.
Hilborn R., Mangel M., 1997, The ecological detective: confronting models with data. Princeton University Press.
ICES, 1991, Report of the working group on fisheries units in sub-areas VII and VIII. Int. Council Explor. Sea C.M. 1991/Assess. 24.
ICES, 2006, Report of the working group on the assessment of southern shelf stocks of hake, monk and megrim (WGHMM), 9-18 May 2006, Bilbao. ICES CM 2006/ACFM:29.
Jensen, A.L., 1996, Beverton and Holt life history invariants result from optimal trade-off of reproduction and survival. Can. J. Fish. Aquat. Sci. 53, 820–822.CrossRefGoogle Scholar
Lembo, G., Abella, A., Fiorentino, F., Martino, S., Spedicato, M.-T., 2009, ALADYM: an age and length-based single species simulator for exploring alternative management strategies. Aquat. Living Resour. 22, 233–241.CrossRefGoogle Scholar
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. Sci. Mar. 67, 259–268.CrossRefGoogle Scholar
Lleonart, J., Maynou, F., 2003, Fish stock assessments in the Mediterranean: state of the art. Sci. Mar. 67, 37–49.CrossRefGoogle Scholar
Mace, P.M., 1994, Relationships between common biological reference points used as threshold and targets of fisheries management strategies. Can. J. Fish. Aquat. Sc. 51, 110–122.CrossRefGoogle Scholar
Mace P.M., Sissenwine M.P., 1993, How much spawning per recruit is enough? In: Smith S.J., Hunt J.J., Revered D. (eds.) Risk evaluation and biological reference points for fisheries management. Can. Spec. Publ. Fish. Aquat. Sci. 120, 101–118.
Martin I., 1991, A preliminary analysis of some biological aspects of hake (Merluccius merluccius L. 1758) in the Bay of Biscay. ICES CM 1991/G:54.
Maunder, M.N., Harley, S., Hampton, J., 2006, Including parameter uncertainty in forward projections of computationally intensive statistical population dynamic models. ICES J. Mar. Sci. 63, 969–979.Google Scholar
Merino, G., Karlou-Riga, C., Anastopoulou, I., Maynou, F., Lleonart, J., 2007, Bioeconomic simulation analysis of hake and red mullet fisheries in the Gulf of Saronikos (Greece). Sci. Mar. 71, 525–535.CrossRefGoogle Scholar
Murua, H., Motos, L., 2006, Reproductive strategy and spawning activity of the European hake Merluccius merluccius (L.) in the Bay of Biscay. J. Fish Biol. 69, 1288–1303.CrossRefGoogle Scholar
Murua, H., Lucio, P., Santurtún, M., Motos, L., 2006, Seasonal variation in egg production and batch fecundity of European hake Merluccius merluccius (L.) in the Bay of Biscay. J. Fish Biol. 69, 1304–1316.CrossRefGoogle Scholar
NRC, 1998, Improving fish stock assessments. Washington DC, National Academy Press.
Papaconstantinou C., Stergiou K., 1995, Biology and fisheries of eastern Mediterranean hake (M. merluccius). In: Alheit J., Pitcher T.J. (eds.) Hake: Biology, fisheries and markets. Chapman & Hall, London, pp. 149–180.
Papaconstantinou C., Petrakis G., Caragitsou E., Labropoulou M., Karkani M., Vassilopoulou V., Mytilineou Ch., Lefkaditou E., Siapatis A., Kavadas S., Chatzinikolaou P., Anastassopoulou A., Kapiris K., Terrats A., Dogrammatzi A., Bekas P., Christidis G., Fourtouni A., 1998, Development of the Greek fisheries. Assessment of the demersal fisheries resources of commercial interest in the S. Aegean Sea. Techn. Rep. NCMR.
Petitgas P., Poulard J.-C., Radtke K., Spedicato M.-T., Ibaibarriaga L., Politou C.-Y., Korsbrekke K., Deernberg C., Fernandes P., 2007, Comprehensive indicator-based diagnostics of fish stocks using fishery-independent survey data: the FISBOAT Rep. ICES CM 2007/O.
Punt, A.E., 2003, Managing West Coast groundfish resources through simulations. Fish. Bull. 101, 860–873.Google Scholar
Rochet, M.-J., Rice, J.C., 2009, Simulation-based management strategy evaluation: ignorance disguised as mathematics? ICES J. Mar. Sci. 66, 754–762.CrossRefGoogle Scholar
Rochet M.-J., Trenkel V.M., 2009, Why and how could indicators be used in an Ecosystem Approach to Fisheries Management? In: Beamish R.J., Rothschild B.J. (eds.), The future of fisheries science in North America, Fish & Fisheries Series, Springer, pp. 209–226.
Sparre P., Venema S.C., 1998, Introduction to tropical fish stock assessment. Part 1, manual. FAO Fish. Techn. Pap. 306 Rev. 2.
Spedicato, M.T., Carbonara, P., Rinelli, P., Silecchia, T., Lembo, G., 2006, Biological reference points based on spawning stock biomass levels: the case of red mullet (Mullus barbatus L., 1758). Biol. Mar. Medit. 13, 112–123.Google Scholar
Tserpes G., Fiorentino F., Levi D., Cau A., Murenu M., Zamboni A., Papaconstantinou C., 2002, Distribution of Mullus barbatus and M. surmuletus (Osteichthyes: Perciformes) in the Mediterranean continental shelf: implications for management. In: Abelló P., Bertrand J.A., Gil de Sola L., Papaconstantinou C., Relini G., Souplet A. (eds.) Mediterranean marine demersal resources: the MEDITS International Trawl Survey (1994-1999). Sci. Mar. 66 (Suppl. 2) 39–54.
Tserpes G., Haralabous J., Maravelias C., 2007, A non-equilibrium surplus production model approach using Medits data. GFCM-SAC-Sub-Committee Stock Assessment. Workshop on trawl survey based monitoring fishery system in the Mediterranean, Rome 26-28 March 2007.
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. 8.
Wang, S.P., Maunder, M.N., Aires-da-Silva, A., 2009, Implications of model and data assumptions: An illustration including data for the Taiwanese long-line fishery into the eastern Pacific Ocean bigeye tuna (Thunnus obesus) stock assessment. Fish. Res. 97, 118–126.CrossRefGoogle Scholar