2 Discussions 

The use of surplus production approach permits to calculate the maximum sustainable yield MSY and the optimal fishing effort (F_opt) without catchability, requires only catches and effort data and do not needs age structure.
 

The application of the surplus production models constitutes a privileged way of the cephalopod stock assessment (FAO, 1985). Analytical assessment is currently impractical (ICES WGCEPH, 2010). 
 

Our results showed an under-fishing state. It is recommended to increase the effort until 30 000 trips which corresponds to a maximum sustainable yield of 206 Ton. But these value still dependant on fisheries conditions, economic situation and particularly environmental factors. In fact, catches are decreasing; stock may be in depleted state without necessarily being over fished. This situation, however, may be explained by the effect of climatic parameter as demonstrated by Jabeur et al (2010) on this stock. Besides, the effect of the quality of data may not be avoided.
 

Surplus production approach does not tell us much about the mechanism affecting the population dynamics and assumes that the stock has stabilized at current rate of fishing. 
 

Trophic linkages and interaction between several species, which are captured simultaneously and may be differently affected by gears, are excluded from mono-specific models. For this reason, these models are insufficient to explain different exploitation scenarios (Guerra et al., 2010).
 

Furthermore, some studies prove that integration of environmental parameters in models should be developed. As it is demonstrated by authors, fluctuation of cephalopod population is explained by the influence of various environmental factors (Boyle and Rodhouse, 2005; Caddy, 1983; Pierce et al., 2008) and confirmed by Jabeur et al (2010) on stock of the east coast of Tunisia. In fact, according to this last study, the decrease of yield is related to the effect of temperature and rainfall. Monastir, for instance, some years were particularly influenced by climatic parameters from 1999 to 2006; these years were characterized by weak yield. For these last seven years, temperature was increased during larval period corresponding to the hot season from August to October (for example mean temperature was 21.13℃ in 1995 and 23.14℃ in 2006, INM, National Institute of Meteorology), which play a role in increasing the mortality of this species and so influence negatively the recruitment. But no diminution of temperature for cold season (January~May) was detected. Although, rainfall was found to be weakly correlated with the abundance of common octopus, but the diminution of the quantities of precipitations during some years (1998~2002), had a negative repercussion on yield, which explain the decrease of production of common octopus in Monastir from 1999 to 2006.    
 

The incorporation of environmental factors in surplus production model is a necessity to explain the mechanism affecting the population dynamics of Octopus vulgaris. Hence, multidisciplinary and multispecies approaches are fundamental in management of common octopus stock (Guerra et al., 2010). According to Marine Strategy Framework (COM, 2008), recent directions incite researchers to integrate ecosystem approaches. Furthermore, the ignorance of historic characteristics of life cycle may be the cause of biased estimation which has repercussion on cephalopod fishing management.
 

Among these characteristics, the definition of stock unity is fundamental for management purpose. In addition to biological and genetic aspect, the paucity data and sometimes the absence of these data are crucial problems related to theories and models for mono-specific population especially the yield data. In fact, the coefficient of variation (CV) catch data had the greater bias on the assessment than the CV of fishing effort. According to recent literature for assessment and management of such resource, we recommend the integration of environmental factors in model as a primordial step for further studies for the importance of fisheries management and the conservation of species. 
 

Several studies consider environmental conditions as endogenous to fishery models, but in most assessment these conditions are taken to be exogenous to the problem and consider that economic indicators are dominant and containing more information to traditional single-stock indicators (Simonit and Perring, 2005). 
 

But in cephalopod the relationship between population and environmental factors were more studied. For common octopus, no study is dealing with economic approach even in Tunisia. 
 

As perspective, for analysis of the actual situation, it is crucial to combine the environmental and economic data and integrate them in global model as a tool which allows corrective action to take decision for the management of stock.
 

3 Materials and methods

3.1 Data

The data used, were production and fishing effort collected for the region of Monastir in the eastern coast of Tunisia (Figure 2) from the official fishing statistics of the national general direction of fishing and aquaculture (DGPA).  

Fishing data (production and effort) have been recorded for the period of the fishing season of common octopus (mid October/November to mid May) since 1995 to 2006. The effort used is the number of trips and landing is expressed in Ton.
 

Because of the lack of some data about effort, estimations were done as shown and explained in Jabeur et al (2010). In fact, official octopus effort was corrected from a monthly coefficient which is computed using available data and precise data collected for some years of fishing effort in Monastir recorded by official services of fishery. This coefficient is a ratio calculated as follow:
 

(Octopus effort)/(Overall effort)
 

The use of the coefficient of correction is only practiced for inshore activities because some of them are known to be selective for other species than octopus. For the trawling fishing, the effort is used without corrections because they are not selective and able to catch octopus if it is accessible.
 

3.2 Models

Data are available on the yield and the effort expended over a sufficient number of years (12 years). According to Laloe (1995) we cannot give definitive answer about the number of years may be appropriate, but Hilborn (2003) outlines that generally, stock assessments are new developments within the last 10~20 years. 
 

The fishing effort has undergone substantial changes over the period covered and standardized. 
 

The application of surplus production models permits to determine the optimum level of effort, which corresponds to the effort that produces the maximum yield that can be sustained without affecting long-term productivity of the stock, the so-called maximum sustainable yield (MSY), which is estimated from these input data:
 

f(i)=effort in year i, i=1,2,...,n 

Y/f=yield (catch in weight) per unit of effort in year i

Y/f may be derived from the yield, Y(i), of year i for the entire fishery and the corresponding effort, f(i), by Y/f=Y(i)/f(i), i=1,2,...,n

The most common production models are Schaefer model (linear model, 1954) and Fox model (exponential model, 1970). 
 

The expressing of yield per unit of effort, Y/f, as a function of the effort, f, using exponential model is written as: Y(i)/f(i)=exp[c + d*f(i)] and linear one as Y(i)/f(i)=a+b*f(i) if f(i)≤a/b
 

The comparison between coefficient of correlation (R²) for Scheaffer and Fox models allows the choice of the model with the greatest value to be used in stock assessment. 
 

Authors’ contributions

KW collected data drafted the manuscript, JC participated in the collection of data and revised the design of the manuscript and BA participated by coordination funding of the study. All authors read and approved the final manuscript.
 

Acknowledgements

We express our thanks to the Laboratory of Analysis, Treatment and Valorization of Products and Pollutants of the Environment for supporting of our work. As we are grateful to agent of DGPA (Direction Générale de la Pêche et l’Aquaculture) and CRDA (Commissariat Régionale développement Agricole ) in Monastir to made fishery data available. We acknowledge also the manuscript improvement by anonymous reviewers and English improvement by Afifa (ISBM Monastir, Tunisia)
 

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