APPENDIX E: ESTIMATION OF TARGET AND LONG-RUN OVERCAPACITY: AN EXAMPLE FROM THE ENGLISH CHANNEL FISHERIES

Estimating overcapacity in fisheries requires an estimate of the potential sustainable level of output that might be possible in the long run, given that stocks have adjusted to changes in the fishing fleet. With multispecies fisheries, the long-run desired output level of each species may differ from the maximum sustainable yield, or maximum economic yield if considered in isolation, as this will also depend on the “optimal” fleet structure that harvests the resource. To assess these optimal fleets and yields, a bio-economic model of the fishery is required that takes into account stock dynamics as well as costs and revenues associated with undertaking different fishing activities.

The definition of “optimal” also depends upon management objectives. An optimal fleet size under an objective of profit maximization will be substantially smaller than one in which employment is considered the key objective. Similarly, the optimal sustainable yields under both scenarios would differ. More often is the case; however, that management must balance several, often conflicting, objectives. Multi-objective bio-economic models therefore play a significant role in assessing the level of overcapacity in species when several management objectives exist. A multi-objective bio-economic model was used to determine the “optimal” fleet configuration and size for key fleet segments operating in the fisheries of the English Channel.

Multispecies, multigear fishery

The English Channel hosts a broad variety of fishing activities aimed at targeting a number of species. Approximately 4,000 boats operate within the English Channel [WHEN?], comprised roughly of 50 percent United Kingdom boats, 45 percent French boats and five percent from other countries (most of these from Belgium). The fleet uses one (or more) of seven gear types: beam trawl, otter trawl, pelagic/mid-water trawl, dredge, line, nets and pots. In total, 92 species are landed by boats operating in the English Channel. However, approximately 30 species make up the majority of landed weight and value.

The English Channel fleet is comprised primarily of small vessels. Over two-thirds of the fleet are less than ten metres in length, and about half of these are less than seven metres. A large proportion of the under seven metres vessels operates essentially on a part-time basis, generally fishing for less than half of the number of expected full-time days.

The boats are, for the most part multi-purpose; they operate with different gears over the year, and in some cases, use different gears in the same month. Fishing activity has been classified into a number of métiers based on gear used and area fished, which can vary within the same month.^[54]

The bio-economic model

The model, described in Pascoe and Mardle (2001), includes both French and United Kingdom fleets operating in the Channel and takes into account the fishing activity of other EU Member States (which, combined, contribute around five percent of the fishing activity). All commercial species caught in the Channel are included in the model, and for some species (e.g. crustaceans) several identified stocks have been included. The model includes a combination of age-structured biological models, as well as surplus production models for some species. That is, all outcomes are sustainable in the long run (both biologically and economically). The model also was specified as an “optimization” model, because it produces the best outcomes given the objectives provided. The output of the model is: the sustainable catch of each species, the fleet size and structure that produces that catch and relevant socio-economic measures of performance, given the fleet structure and catch (e.g. profits, employment).

While estimating the optimal sustainable yield of each species, the model solution is primarily input-based rather than output-based. Fishing activity in the model was modified such that each vessel in the model solution was operating at full capacity utilization (expressed in terms of days fished). The resulting fleet size and structure thereby represented that which was required to harvest the “optimal” yield operating at full capacity. Because the benchmark is the existing fleet size and structure, input-based measures of overcapacity^[55] are derived rather than output-based measures.

The model solution was based on key management objectives in place in the fishery. Conservation objectives are over-riding, and all solutions are sustainable in the long run. The economic objectives were specified as maximizing profits in the fishery, with each country having a separate profit target, based on its own potential maximum profit. (See Pascoe and Mardle, 2001.) Employment objectives were also included by setting target employment levels based on their current levels in the fishery. Finally, the EU principle of relative stability was imposed so that each country could not incur a greater proportion of benefit (or loss) than the other. Multiple objectives were incorporated into the model through specification of an “achievement function”. Deviations away from the targets for each objective can then be minimized using a technique known as goal programming.

Multi-objective optimization

The model was run with the dual objectives of both increasing economic profits and maintaining employment. The economic profit objectives were taken as the maximum economic profits that could be achieved in each country. (See Pascoe and Mardle, 2001.) The employment objectives were taken as the current level of employment in each country. The additional objective - that each country can only incur the same proportion of the potential social cost - was also imposed to ensure that relative stability was maintained.

Essential to the achievement function was the definition of the weights associated with each goal. Different weights are likely to result in different optimal solutions. Because deviations from all goals are undesired, one appropriate method is to set all weights to unity since there is no need to differentiate their importance (Ignizio and Cavalier, 1994).

A number of different weights were applied in the model. The model was run with equal weights applied to both profit and employment goals. The model was also run with a lower weight on economic profits and with a lower weight on employment. A common weight was used for both countries with each objective. This ensured that neither country was given preference relative to the other.

Table E.1 - Multi-objective optimization results

a) Includes revenue from English Channel fleet generated outside the Channel.b) Channel fleet only.

As would be expected, the optimal fleet configuration depends on the relative weights given to the profit and employment objectives (Table E.1). An optimal fleet with a higher weight on employment was characterized by a large number of smaller boats, particularly in the United Kingdom. Conversely, increased weight on economic profits results in the total capital (and employment) in the fishery decreasing. Comparing the current situation with the case in which employment was given greater weight than profits (i.e. w_profit=0.5, w_employment=1), economic profits could be increased by 65 percent, with only an eight percent reduction in employment.

Extent of overcapacity

As noted previously, the extent of any overcapacity in the fishery will depend on the actual objective of fisheries management. From the above analysis, several different fleet configurations were identified based on different levels of importance assigned to each objective. Potentially, an infinite number of “optimal” fleets can be identified, but only one will be truly optimal.

The percentage of overcapacity can be estimated by dividing the current fleet number by the “optimal” fleet (Table E.2). From this, it can be seen that the estimate of overcapacity varies substantially based on the objectives of management. For example, if maximizing employment was the main objective, there is no overcapacity in the inshore fleet, but if maximizing profit was a main objective, there was considerable overcapacity in this sector.

Table E.2 - Extent of overcapacity in the UK fleet segments of the Channel fishery (%)

Usefulness of the results

The use of bio-economic models to assess the extent of overcapacity needs to be undertaken with some caution. Most optimization models are sensitive to the data provided, and a small change in the main parameters may result in a different optimal solution. For example, if the price of the fish species targeted by the otter trawlers increased, then the optimal number of vessels in this segment may also increase. Similarly, if fuel prices decreased, the optimal number of all mobile gear boats (otter and beam trawlers and dredges) could increase. Because prices and costs are likely to change in the future, the results of the models should not be seen as prescriptive, but rather, indicative of problem areas within a fishery.

Many biological parameters in the model are also subject to uncertainty. This again would affect the optimal fleet size and structure if errors were introduced into the model through inaccurate biological parameters. The robustness of the results to uncertainty in biological and economic parameters can be examined through either sensitivity analysis or stochastic simulation. Such techniques were not presented in this paper in order to keep the analysis fairly simple, but a stochastic analysis of the model results was presented in Pascoe and Mardle (2001).

With these limitations in mind, the development and use of bio-economic models can provide useful information to managers on the extent of overcapacity by fleet segment in a multispecies, multigear fishery.