1. Problems with traditional approaches to fisheries management

In our previous article we pointed out that stock assessments do not provide a solution to the management problem for fisheries on their own. Rather they provide valuable quantitative inputs to management deliberations. Managers have to set goals for resource management, only then can mathematics and computer models provide assistance with the decision making process. Without clear goals, mathematics can run amok and produce wild and impractical, even dangerous, management “solutions”.

However, even given the existence of socio-political constraints, management authorities seldom follow the quantitative advice from computer models directly. This is not necessarily a bad thing, since even the most sophisticated stock assessment models involve a degree of guesswork and are subject to considerable imprecision and uncertainty. It should always be understood that fisheries science never has been and never will be a precise science.

It is common for example for a stock assessment model to produce a range of sustainable yield and resource biomass estimates, implying that there is a level of either biological or economic risk associated with the adoption of any particular scenario.

In the traditional approach to fisheries management, the management forum then has to decide which scenario to use as the basis for management decisions, e.g. a TAC for the forthcoming fishing season. This need to come up with a precise quantity for purposes of management, regardless of the imprecision of scientific knowledge, makes the decision making process very vulnerable to political interference, and also renders decision makers reluctant to follow quantitative advice directly.

The direct economic importance of the particular quantitative level of the management decision is often seen in sharp contrast to the imprecision of the quantitative scientific information, leading to interminable debates and conflicts at management meetings.

Some fisheries scientists have therefore argued that there is a need to reduce the amount of scientific time and effort incurred in the traditional decision making approach, in order to free research resources for “more important” issues. In the next few articles we will introduce and discuss a new approach to fisheries management which purports to avoid some of the uncertainty associated with traditional management approaches and the often unpleasant political fallout that ensues. These are the “management procedures” referred to briefly in our previous article.

2. A utopian solution?

What fishery scientists and managers are looking for is a management approach that will be safe, workable and acceptable even under high levels of scientific uncertainty and possible political interference. What should such a management program consist of?

1. It should have specific goals, which may in certain circumstances be expressed as a target or desirable resource biomass level. An example would be a biomass level 30% larger than at present, or, alternatively, a biomass which is 20% larger than the biomass which produces maximum sustainable yield.
2. It should have a timespan over which goals are achieved, e.g. the target biomass should be reached after 10 years.
3. It should include a TAC setting mechanism which allows the desired target to be reached in the specified timespan.
4. The TAC setting mechanism should include a self correcting component, such that if incoming resource abundance indices perform in an unexpected way, indicating that previous assumptions about resource productivity and/or size were incorrect, the TAC will adjust to keep the resource biomass on track towards its eventual target.
5. Interannual changes in TAC should be not too large. Relative stability in annual allocations ensures the efficient utilisation of existing fishing and processing resources, and prevents over-capitalisation.

In South Africa, this kind of management mechanism is referred to an Operational Management Procedure, or OMP for short. A number of fishing nations are presently experimenting with the implementation of these OMPs. Indeed the new South African Marine Living Resources Bill, Chapter 2 6c, states that “The forum (the Consultative Advisory Forum - CAF ) shall advise the Minster on any matter referred to it by him or her, and in particular…(c) The establishment and amendment of operational management procedures including management plans;”.

In background documents to this bill, an OMP is defined as: “a scientifically evaluated process defining the manner in which the available data on a resource is used to determine the level of control measures to be detailed in fisheries regulations to manage such resource in terms of sustainable harvesting, rebuilding strategies, etc. The procedure must therefore set the rules which specify the data to be collected, the analysis of such data, the management actions to be taken as a result of such analysis, and the means of analyzing the results of such actions”

At face value this sounds like the normal traditional approach to fisheries management (see above). However, on reflection, it should be clear to the reader that, taking this definition literally, the traditional approach to resource management cannot constitute an OMP, since it involves human judgement and decision making which cannot be “scientifically evaluated”. Indeed, proponents of the OMP approach in South Africa have made much of the phrase “scientifically evaluated”, implying that whatever the decision making processes, this must have been subjected to simulation studies using computers to evaluate the associated risks and trade-offs. It is therefore clear that the intent is to suspend and eliminate all human judgement and input during the period for which the OMP is to remain in place.

3. How OMP’s work

An important impetus behind the development of the OMP concept is the uncertainty inherent in biological systems. Uncertainty means that any trend in the data has to be dealt with carefully, because it could be misleading. Errors will be made if one either over-reacts or under-reacts to trends in incoming data. Coping with uncertainty like this requires intelligent hedging. In the development of an OMP one has to be explicit about exactly how this hedging is done.

The OMP itself is a relatively simple formula or model which is self-correcting because the TAC is adjusted in response to changes in resource indices so as to keep the resource biomass on a desired trajectory. Relevant examples of resource indices include: commercial catch rates, survey biomass estimates, catch age or size structure data, tagging data and catch sex ratios. Although the OMP often consists of a relatively simple formula, the rationale behind its development is both conceptually and computationally complex.

There is a close relationship between the OMP and its underlying development and rationale. Ideally the development of an OMP should follow the process proposed by the International Whaling Commission, i.e. it should contain the following steps:

1. Obtain an estimate of resource dynamics and present size from the best available interpretation of the available data. This will be chosen as “reality” for the purpose of evaluating different OMPs.
2. Obtain estimates of uncertainty in the available data (i.e. extent of fluctuations around true values and trends).
3. Identify promising candidate OMP formulae.
4. Adopt the model in (1) as a description of reality, and use this model to project forwards. Use the ‘uncertainty’ information in (2) to generate typical data on resource performance used in management. This is like throwing the dice.
5. Run the model ahead for a large number of ‘throws of the dice’, and summarise the performance of different candidate OMP formulae with respect to measures like average catch, % change in the “true” biomass, variability in the TAC.
6. Explore the implications of certain radical future events, e.g. recruitment collapse, using different OMPs.
7. Explore the implications of different ‘realities’ using different OMPs.
8. Choose the OMP which performs ‘best’. The term ‘robust’ is applied to a formula that achieves goals in the face of the range of uncertainty that one has to deal with.
9. Use the ‘best’ OMP to calculate the TAC over the next 3 to 5 years, hereafter a new OMP will be developed and implemented.

However, as alluded to in our previous article, and despite the philosophical appeal of this scheme, there are no magical solutions in fishery science and the management procedure approach has its own drawbacks. In the next two articles we will discuss the OMP approach and form an opinion on its merits. Before we even embark on this task, we should say that the OMP management approach in one form or another is likely to shape the future of fisheries management and one should therefore pay close attention to how it evolves in the next few years.