Summary
1 _Why_is_it_important_to_manage_fisheries?
2 Why are scientists useful for managing fisheries?
3 What tools do scientists use to produce advice?
4 How does a bio-economic model work?
5 MEFISTO 3.0.: A bio-economic simulation model
1 Why is it important to manage fisheries?
The development of more effective fishing techniques facilitates the work of fishermen, but it can reduce the abundance of fish and even cause its disappearance in the long term. A poorly managed use of the fishing resources is a factor of ecological but also economic risk.
The management of fisheries should, in theory, allow the greatest possible amount of fish to be obtained in a sustainable way over time: with some controls, collapses in fish numbers can be avoided. Good management should allow fishermen to obtain greater income through time, because it allows them to reduce unnecessary expenses and to limit the investments in order to obtain an optimal yield.
Good management also improves the image of those who exploit fishing resources in front of consumers and society; fishermen are part of the sustainable use of the marine system.
2 Why are scientists useful for managing fisheries?
When as in the case of the Mediterranean fisheries is not possible to control the catch, there are many possible management measures in the limits on the number of licenses, limits on the size of catches, limits on the space or time of fishing, subsidies, limits on allowed fishing gears, etc. Researchers, from the information available, can simulate several scenarios with the help of mathematic models. These could include the impact of distributing fishing rights between fishermen in different ways, changing working days or the establishment of closed seasons, etc. Forecasting the consequences of such management actions before they are applied helps the choice of more convenient management systems. This should save both the administration and fishermen money. As noted, by avoiding overexploitation of resources, more profitable and sustainable fisheries should be obtained.
Scientists can also analyze the efficiency of fisheries investments. This type of analysis, on one hand allows fishermen to evaluate their investments, to know if certain costs in equipment can be profitable. On the other, it allows the evaluation of investments coming from administrations. Facing a future where the European Union wants to reduce subsidies to the fishing sector, there is a need to scientifically examine the positive role of certain subsidies, like those for dismissal of fishing vessels.
3 What tools do scientists use to produce advice?
There are several methods used by scientists. The simplest is examining the historical evolution of catch data. Other tools are resource assessment methods, which include data gathering and the use of mathematical models. One of these tools are the simulation and optimization models, which can be bio-economic models.
The bio–economic simulation models simulate the biological behaviour of the resource and the economic behaviour of fisheries. They incorporate the known trajectory of the resources and the fishing fleets. These simulation models allow users to examine what would happen if some parameters in the model are changed, for example oscillations in reproduction or changes in prices or taxes. The models can then identify the most probable future trajectory when these values change, while other factors remain constant. When anticipating the fisheries’ possible evolution, we can identify measures which avoid or minimise the non-desirable aspects of the future; we can modify our behaviour in order to gain more, work less, and preserve the environment.
Bio-economic models simulate the biological behaviour of the resource and the economic behaviour of the fishery. They incorporate the known trajectory of resources and fishing fleets.
4 How does a bio-economic model work?
A bio-economic model is a system of mathematical functions representing two interacting sub-models:
· A biological sub-model reflecting the fishing resource dynamics and its interactions with the human activity of fishing (mortality by fishing).
· An economic sub-model (including fleet, market and fishermen), that takes into account the fleets and markets’ dynamics, and the fishermen’s likely behaviour.
These interacting models can be used to simulate into the future both fleet and fish stock variables. The use of a whole series of management measures can also be simulated, making it possible to forecast the impact of applying different management measures on the fishery.
5 MEFISTO 3.0.: A bio-economic simulation model
5.1 How MEFISTO works?
The MEFISTO is a model built on three modules or boxes:
Stock module: simulates the fishing resources’ dynamics in the sea, from reproduction to growth and death. The stock module can contain simultaneously several sub-modules (in the case of multispecies fisheries). The model considers two types of species:
1. the main species are those species whose dynamics (behaviour, biomass, reproduction, growth, etc.) are known by the scientists and therefore simulated explicitly, and
2. the secondary species, those economically relevant species whose dynamics are not totally known, but their captures are put in relation of the captures of the main species.
The stock module receives information on fishing effort “E” and catchability “q” (including the capacity to fish that a certain boat or fleet has). This information comes initially from another module of the model or from the data that is initially incorporated. This module generates the amount of catches forecast for the period. This information is sent to the following module: the market.
Market module: From the initial data, the market module converts the fish catches of each species generated by the stock model (main as well as secondary) into money, through price functions. These price functions can consider for each species (depending on information available) the influence of the fish size, the supply of fish in the market, the gear with which the fish have been caught, or the time of the year in which the catch was taken.
Fishermen module: simulates the fishermen’s economic behaviour and decisions. Based on the money generated in the market module, fishermen can invest capital in fishing. The fishermen module therefore obtains the effort (within a system where maximum effort is fixed by law) and the catchability, which the fishermen can affect by investing capital in the boat.
At each time step of the simulation (e.g. year simulated) a complete cycle of the 3 modules is run. The benefits (profits) of the preceding period are therefore reflected in the activity of the boat in the following period. The time step can then be repeated for as many times are required to simulate the desired total time period. Obviously, the further forward a forecast is made into the future, the less trustworthy those results are.
5.2 What results can be obtained?
At a basic level, the MEFISTO simulation model allows the user to project into the future the economic consequences of the current situation, where conditions remain constant. But, the model can simulate much more.
On one hand, changes in those initial conditions can be introduced: changing the fishing times, adding or clearing taxes, increasing or diminishing the fleet size, etc. In all these cases the impact on each boat, stock, price, etc. can be seen.
On the other hand the model can simulate possible future events and evaluate their impact. So, simulations can examine what will happen if the biomass decreases (through natural environmental fluctuations) or if the price of fish falls by half or increases. In each case, the effect on each boat, as well as for the total fleet, could be examined.
At the moment, the MEFISTO model allows the user to simulate the impact of changes in effort and the use of several technical and economical measures. Among these are:
· effort control (in fishing days and hours, number of boats);
· gear characteristics; in particular selectivity
· establishment or changes in minimum sizes for certain species;
· changes in subsidies and taxes.
Furthermore, the model allows the change of some parameters in a certain time period in order to simulate possible future scenarios. For example, changes in:
· fuel price
· dismissal price
· subsidies
· fishing hours and days
· boat activation or deactivation
· degree of gear selectivity
· fish imports volume
· fish price.
The designers of the program, which is in a prototype stage, can incorporate possible additional incidences or management measures that may be considered interesting by the fishing sector, for simulation.
5.3 Data required for the model
In order to run the model in a realistic way, a particular set of data is required. These data should be available from companies and fishing associations.
In the first place, market information is needed. This should be available through sale invoices. This information includes data on the sales in weight and value of the primary species and the secondary ones, at the level of each individualized boat and at the smallest time-scale possible (fishing days).
Secondly, information on general aspects of the vessels that compose the fleet of the analyzed area is needed: number by segment, power and tonnage. These data should be available through the fleet census. In the case of small discrepancies, they can be easily solved.
Thirdly, individual information by fishing vessel is needed. This information is only accessible through individualized surveys where the following information is asked:
· Crew number
· Total Present Value of the investments (approximated value of the ship in its present state with all equipment)
· Subsidies received last year (if any). For example subsidised biological closed seasons.
· Annual fixed costs, such as: mooring, insurance, administrative expenses
· Variable costs by fishing day, excluding fuel (those that depend on the number of days a vessel fishes), such as: oil, ice, bait, light, food, etc. (if paid for by the owner)
· Daily fuel consumption (approximated)
· Commercial costs (if it is a fixed percentage of the income, if not, it should be within annual costs)
· Annual Maintenance costs: This includes painting, electrical maintenance of the motor, nets, electronic equipment, etc. transformed into annual costs (so that if they occur every five years, then it has to be divided by five)
· Percentage of the variable costs that can be postponed if there are economic difficulties.
· Monthly fishing days by boat
· Gear characteristics (meters of net, number of hooks, etc.)
· Maximum distance generally travelled from the main port
· Daily hours of work (including the hours employed before and after on land)
· Percentage of the share for wages
Finally, it may be necessary to obtain additional biological data on key species through biological sampling of catches in port. Catch data can be very useful for this, if available as daily species catches by vessel, or monthly catches with corresponding effort measure is available.
