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Case study 8, Approach A3: Implication of an effort reduction measure to the fleet operating in Northern Alboran Sea. Bio-economic scenarios assuming 10 and 20% reduction in effort

Introduction

This case study scenario include a 15-year catch projection of the fishery assuming effort reduction (by both 10% and 20%). These scenarios were applied to the trawl fleet in Northern Alboran Sea.

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

As in most Mediterranean fisheries, the main problem when analyzing this fishery is the lack of good biological and economic data. It was not possible to find data by size or by individuals. Moreover, the size of the sample is limited to eight years. However, we had daily catch and effort data over this period, which has allowed us to make some estimations based on a large amount of cross sectional observations over the sample period.Therefore assessment of the current hake population in the Alboran Sea was obtained by using surplus production models as the lack of data on catches by fish size forced us to use surplus production models. Specifically, we used the Pella- Tomlimson model which is more general than the traditional Shaeffer model. Results showed that the estimations of the stock seemed to follow a steady decrease over time as can be appreciated in the figure 1.

Figure 1. Evolution of the hake stock biomass.

Concerning the estimation estrategy, we decided not to use equilibrium estimation procedures, but regression methods and minimum error estimators instead. The reason for this is that rarely fisheries are in the equilibrium state which is the basic assumption when using equilibrium estimation procedures. In figure 2, it can be observed the estimated vs the predicted catches

Figure 2. Estimated vs. predicted catches.

Fleet data

We had daily landing data for six spanish south mediterranean port. We used a non-linear production function with three inputs: stock size, effort and engine power of the vessels. Moreover, we relaxed the assumption that the elasticities of the main inputs are equal to 1 (which is usually included in the basic models). Since this turns out to be a very non-linear model, we first carried out the analysis using a more basic model based in the biological Shaeffer model and a Cobb-Douglas function with elasticities equal to one. This model provided us with initial pre-estimates for the parameters, which we used to estimate the more general model described above.

Modelling

FLR (Operating Model)

The FLR packages used were FLCore for simulations.

Conditioning of Operating Model

Historical Estimates of Time Series The operational model was based on the assessment we made of the hake population in the Alboran Sea using surplus production models.

Biological Parameters

The values of the parameters found were K =112 (hundred tonnes), r=0.501 and m=1.1.

Fisheries & Fleets

We had landing data for the trawl fleet based in six different Spanish Southern Mediterranean Ports. However as many of the vessels landed their captures in different ports over time we could not distinguished ports in our analysis.

Economics

Economic data were considered. Individual engine power for each vessel was available and daily individual amount and value of the catch. Estimates of variable and fixed costs for the trawl fishery in Northern Alboran Sea are currently included in the models. The economic depreciation of the vessels was also estimated. The results also provide estimates of the average monthly fishermen salaries.

Management Procedure

We assumed for this scenario a reduction of 10% and 20% in effort.

Results

Our simulation results predict that, in the benchmark case, for the following 15 years there will be a sharpest decrease in the catches if no policy is implemented and the exploitation pattern keeps at current levels.

If a reduction of effort is made by either 10 or 20%, the model predicts (Figure 1) that there will be a reduction in the catches for the first following years but there will be an increase in the catches from year 2015 and onwards.

Figure 3.Simulated evolution of catches for the effort reduction scenario

Concerning the evolution of the simulated stock for the following 15 years, our simulation results (Figure 4) suggest that even if the decline of the biomass is lower when we consider the reductions in effort, the biomass is still prone to decline.

Figure 4.Simulated evolution of the stock biomass for the effort reduction scenario

In Figure 5, it has been graphed the estimated average values of fishermen’s salaries over the period considered. Monthly salaries are estimated using the accumulated annual salaries and taking into account that fishermen work 10 months per year as the fleet is on subsidised seasonal closures for two months. It can be seen that the salaries have shown a sharp decline and they will keep the decrease in the case of effort reductions. A similar pattern follows the shipowner’s profits, though the decline of their profits is even sharper (Figure 6).

Figure 5. Evolution of fishermen’s monthly salaries for the effort reduction scenario

Figure 6. Evolution of shipowner’s monthly profit for the effort reduction scenario

Dissemination

The following paper has been produced form to be submitted to Fisheries Research:

Herrero, I., Riesgo, L., Andre, F.J.(2008) “Is it time to impose new regulations or simply to enforce current ones?”.

Acknowledgements

EFIMAS Contribution to the work

This work has been performed under the EFIMAS Project.

Participants: Ines Herrero , Laura Riesgo y Francisco Javier André. We want to thank Hans Frost and Ayoe Hoff for valuable comments.

 
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