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Case study 8, Approach A2 : Implication of a reduction in fishing Effort to different fleets (Gulf of Lions: biological scenaria A2.1 & A2.2 with 10% & 20% Effort reduction). .

Introduction

This case study scenario includes a 15-year catch projection of the fishery assumming a 10% and 20% reduction in fishing effort. This scenario was applied to four fleets of both Spain and France hake fishery in the Gulf of Lions.

Description of the fishery, stocks and management system

See general introduction of CS8

Description of the base case and scenario evaluations

See general introduction of CS8

Data and parameters

Stock data

The latest assessment of the current hake population in the Gulf of Lions was obtained by running a pseudo-cohort VPA with the VIT program (Lleonart and Salat, 1992; Cheret et al., 2002). The results of this assessment were used in the current case study. Growth and natural mortality rates were obtained, mostly from the bibliography (Aldebert et al. 1993; Aldebert & Recasens, 1998; Bozzano et al. 1997; Recasens et al. 1998).

Fleet data

Four fleets were assumed: a) Spanish trawlers, b) Spanish long-liners, c) French trawlers and d) French gill-netters. Data on catch by fleet were taken from GFCM SAC working documents.

Modelling

FLR (Operating Model)

The FLR packages used were FLCore ver. 1.3-3 and FLStock. Data were modelled using the FLStock class of FLCore. The projection scenario was simulated 1000 times.

Conditioning of Operating Model

Historical Estimates of Time Series

The operational model was based on the results of the latest assessment of the current hake population in the Gulf of Lions obtained by running a pseudo-cohort VPA with the VIT program (Lleonart and Salat, 1992; Cheret et al., 2002).

Biological Parameters

Natural mortality was assummed constant at M=0.2. The fishing mortality (F) estimates by age by fleet derived from VPA results (Cheret et al., 2002) were used.

Stock Recruitment Relationships

A constant recruitment model was suggested by Aldebert et al., 1993 for the hake stock in the Gulf of Lions. Based on the assessment estimates, annual recruitment rates for the projection period were randomly obtained from a normal distribution with mean and coefficient of variation (CV) equal to those estimated for the assessment period (random variability 10%)

Fisheries & Fleets

The Gulf of Lions hake fishery involved four fleets from two different countries, i.e. Spain and France. The four fleets considered in the current model were Spanish trawlers, Spanish long-liners, French trawlers and French gill-netters. Fleet- and age-specific estimates of F were considered assuming that fishing mortality equals age specific catchability times effort.

Economics

At present, economic data were not considered. However, estimates of variable costs for the Gulf of Lions hake fleet are collated and will be included in the models in the near future.

Reference Points

Reference points for hake in the Gulf of Lions are yet to be advanced and thus were not considered.

Observation Error Model

The observables in the model are the initial vector of abundance index by age group. Observation error model was not assumed here.

Management Procedure

The stock is managed through technical measures and effort control rules, thus there is no specific management procedure (e.g. harvest control rules, TAC, quotas)

Results

Scenario A2.1: 10% reduction of Effort

The results of the current runs of the model suggested a relatively stable production pattern in the medium term. The 10% reduction of effort was applied to 2004 recorded fishing effort of all fleets targeting hake in the Gulf of Lions and was implemented in the next year’s total effort, i.e. 2005. The model revealed a response of the hake fishery to this effort restriction measure. More precisely a 7.5% reduction in the total hake catches of 2005 was evident. In 2006 a 5% increase of catches was observed. Total hake catches further increased throughout the projection period to level up to around a 9% higher catch in 2018 (prob > 50%).

Figure 1. Projected Box-whisker plots by year, for the production estimates obtained from 1000 simulations and a 10% reduction in E in 2005.

Scenario A2.2: 20% reduction of Effort

The results of the current runs of the model suggested a relatively stable production pattern in the medium term. The 20% reduction of effort was applied to 2004 recorded fishing effort of all fleets targeting hake in the Gulf of Lions. The model revealed a respond of the hake fishery to this effort restriction measure. More precisely a 20% reduction in E induces a 15.5% decrease in the following year’s catch (2005). In 2006, production is by 11% higher than that of 2005. Hereafter the catches gradually increase and reach a 17.2 % higher value at the end of the projection period (2018) compared to the 2004 (prob > 50%).

Figure 2. Projected Box-whisker plots by year, for the production estimates obtained from 1000 simulations and a 20% reduction in Effort in 2005.

Dissemination

References

Aldebert, Y. & C. Carries. 1988. Problèmes dans l’exploitation du merlu en Golfe du Lion. Rapport 5ème Consultation Technique du Conseil Général des Pêches de la Méditerranée. FAO Fish. Rep., 395: 87-91.

Aldebert, Y., L. Recasens & J. Lleonart. 1993. Analysis of gear interactions in a hake fishery: The case of the Gulf of Lions (NW Mediterranean). Sci. Mar. 57(2-3): 207-217.

Aldebert, Y. & L. Recasens. 1996. Comparison of methods for stock assessment of European hake, Merluccius merluccius, in the Gulf of Lions (north-western Mediterranean). Aquat. Living Res. 9(1); 13-22.

Cheret, Y., H. Farrugio, A. Jadaud, P. Lespagnol, C. Mellon, M. Gaza, E. Massutí, G. Pomar, P. Pereda & J. Lleonart. 2002. Stock assessment of the French-Spanish shared stock of hake (Merluccius merluccius) in the Gulf of Lions. Working document Nº 6 to the GFCM SAC Working group on the assessment of demer-sal stocks, Rome 20-22 March 2002.

Fiorentino, F., A. Zamboni & G. Relini. 1998. La selettività della rete a strascico in Merluccius merluccius sulla base delle esperienze riportate in letteratura. Biol. Mar. Med. 5(2): 465-474.

Lleonart, J. & J. Salat. 1992. VIT: Software for fishery analysis. FAO, Computerized In-formation Series – Fisheries, Nº 11. Rome.

Lleonart, J., F. Maynou, L. Recasens & R. Franquesa. 2003. A bioeconomic model for Mediterranean Fisheries, the hake off Catalonia (Western Mediterranean) as a case study. Sci. Mar., 67 (suppl. 1): 337-351. In: Fisheries stock assessments and predictions: Integrating relevant knowledge, Ø. Ulltang, G. Blom [eds.].

Oliver, P. & E. Massutí. 1995. Biology and fisheries of western Mediterranean hake (M. merluccius). In Hake: Biology, fisheries and markets. Alheit, J. & T. J. Pitcher (ed.) London: Chapman & Hall, pp. 181-202.

Maravelias, C. D. & C. Papaconstantinou 2006. Geographic, seasonal and bathymetric distribu-tion of demersal fish species in the eastern Mediterranean. Journal of Applied Ichthy-ology 22: 35-42.

Papaconstantinou C. & K.I. Stergiou. 1995. Biology and Fisheries of Eastern Mediter-ranean hake (M. merluccius). In: Hake: Biology, fisheries and markets. Edited by J.Alheit and T. Pitcher. Chapman & Hall, London, 1995.

Acknowledgements

EFIMAS Contribution to the work

This work has been made under the EFIMAS Project.

Participants:

Costas Papaconstantinou (HCMR),

John Haralabous (HCMR),

Christos Maravelias (HCMR),

George Tserpes (HCMR),

Vincenzo Placenti IREPA (Italy)

Ramon Franquesa UB (Spain)

Jordi Guillen UB (Spain)

Ines Herrero UPO (Spain)

Ikerne del Valle UPV (Spain)

Kepa Astorkiza UPV (Spain)

Inma Astorkiza UPV (Spain)

 
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