SCIENCE AND DECISION-MAKING IN FISHERIES REGULATION

by

Ray J.H. Beverton

International Federation of Institutes for Advanced Study (IFIAS-ABC) 55 Sandown Avenue Swindon, Wilts SN3 1 00 United Kingdom

Resumen

Se comentan algunos de los problemas que se encuentran al tratar de entender mejor la relación entre la ciencia y la toma de decisiones en la explotación de recursos pesqueros. Los conceptos sobre rendimiento máximo sostenible, la teoría del rendimiento de equilibrio y la ordenación pesquera se consideran como aspectos fundamentales en la comunicación entre estos dos sectores y se discuten en esta perspectiva. Se hace referencia en los distintos factores que deben ser tomados en cuenta para poder hacer un enfoque socio-económico integral al sistema pesquero y se intenta una primera clasificación del riesgo de explotación. Se discuten también algunas de las implicaciones que deben ser tenidas en cuenta en el proceso de toma de decisiones.

INTRODUCTION

Having been for a decade or so away from the mainstream of fisheries research, I am not infrequently asked what I make of events during that time (i.e. from 1965 to 1980, give or take a year or so). Sometimes the question is accompanied by the comment you will no doubt have noticed that the same old problems are still with us. It is, indeed, a somewhat sobering thought that the theme of this Conference - except for its geographical slant and the word ‘neritic’- could well have been that of an ICES Special Meeting as far back as the 1930's.

As is true of so much human endeavour, progress in fisheries research has been like the curate's egg - good, in parts. Our understanding of some aspects of the ecological basis of fish populations has advanced greatly, as have our techniques for sampling and analysis of data. No less spectacular have been the theoretical developments, and I scan modern fisheries mathematics with awe and a large degree of incomprehension.

The accumulating stock/recruitment data have provided a bonanza for the curve-fitters, an activity which has attracted some justified scepticism. Nevertheless, we really do know a great deal more about the relationship between parent and progeny in fish populations than when Sidney Holt and I at Lowestoft and Bill Ricker at Nanaimo were trying to extract the last ounce of information from the limited data we then had. The high variability of S/R data may be ‘noise’ to the statistician but to the biologist it should hold the secret to much of what we want to know about fisheries - if he knows where and how to look for it. The fact remains, however, that we still have only clues here and there as to the environmental causes of recruitment fluctuations, and even less of the natural compensatory mechanisms, if any, in the major marine fish populations.

351 Perhaps these “failures”, if that is a correct description, have been at least partly responsible for what seems to be to have been a more disturbing development in the last decade. I refer to the crisis of confidence which has built up in some quarters concerning the fundamental validity of the scientific basis for fisheries management. These doubts have been eloquently expressed by some of the leading fisheries scientists of my, as well as the younger, generation. The concept of maximum sustainable yield (MSY) as the objective of management has come in for particularly strong criticism (e.g. Larkin, 1977); Holt (1980) goes further, challenging the whole idea that man can “manage” living marine resources on scientific principles.

In view of the surprises and disappointments of recent years this reaction is understandable. Nature has a way of giving us embarrassing reminders of how easily our best laid plans can come unstuck; fisheries is no exception, especially when some of our plans have not been that well laid. But that does not mean for a moment that a rational approach to the utilisation of our fish resources is not possible or necessary, or that science does not have a major role to play. Whatever the frailties in fisheries science and management that may have been exposed by recent events, the destructive power of unrestrained modern fishing operations, backed by economic and political pressure, has become only too painfully obvious.

Not the least of the problems that are still with us, perhaps even more acutely, is that of communicating scientific assessments of fisheries to the decision-makers. This paper is offered as a small contribution towards finding a way forward in this grey area, which necessarily involves the socio-economic dimension and the treatment of uncertainty and risk. It extends certain concepts I put forward in the Santiago seminar of August 1982 co-sponsored by FAO and IOC (Beverton, in press); and draws in particular on the chapter on the Societal Value of an El Niño forecast, by Michael Glantz, in Resource and Environmental Uncertainty; John Wiley, 1981.

MANAGEMENT AND MSY

It is frequently claimed that the concepts of MSY and equilibrium yield theory are obsolete. This issue is central to the communication between science and decision-making, as is the concept of “management” of fisheries: it is worth checking on where we stand, and return later.

In my time we did not use the word “management” nor the term MSY. I was brought up in the Michael Graham school of “rational exploitation”. By this was meant harvesting (the agricultural analogy was intended) the natural productivity of the fish stocks in a sensible way, i.e. letting fish grow to a reasonable size before catching them, and not making the future worse by wasting time and money fishing unnecessarily hard. In view of the intrinsic tendency to the contrary in any common property resource, we thought primarily of “regulation”, i.e. a means of restraining this otherwise inevitable drift of the fishery towards self-immolation, rather than the more positive and comprehensive control conjured up by the word “management”.

The equilibrium yield theory as Sidney Holt and I developed it, both as yield per recruit and as absolute yield incorporating a stock-recruitment relationship, was intended to formalise this principle of fisheries regulation and provided a basis for action. Fig. 1 illustrates this approach. We worked on the premise that if the equilibrium yield curve had a maximum (at Fmax) and if the present F1 was manifestly higher than that, then more of the potential natural productivity of each cohort would be utilised at less cost if F were reduced to Fmax and kept there, or thereabouts.

352 Fig. 1. Hypothetical illustration of relative improvement by regulation of fishing effort, F being reduced from F1 to Fmax.

Depending on how that reduction was brought about so, we supposed, would the long-term economic situation be improved (by most criteria). Future recruitment, and hence catches, would of course continue to fluctuate, as they always had, for reasons beyond man's control. We did not attempt to forecast what actual catches would be in the future. We simply said that if F were reduced (or age at first capture increased, e.g. by a larger mesh) then catches (and catch per unit effort even more so) would be that much greater than they would have been had the reduction in F (or increase in mesh) not been made. Admittedly, this was not an easy option to sell to the industrial decision-makers, even though the resultant marginal gain (provided it was not dissipated in other ways) could have made all the difference between a weak and a strong fishing economy. But it was a start.

The concept of Maximum Sustainable Yield (MSY), in absolute units, as the prime objective of fisheries management, arose I believe during the 1960's in response to a need for simple legal definition. MSY seems at first sight simple, practical and politically neutral, with catch limits as the means of control. The criticism of the economists that MSY would rarely coincide with the conditions for maximising economic rent was valid but not an overriding objection, at least for fisheries which were already overfished. In fact, by redefining the objective as actual maximum yield instead of the operational requirements (fishing rate and selectivity) for achieving a more rational exploitation, the rules of the “management game” became subtly but fundamentally altered. “Sustainable” became synonymous with “steady”, and success or failure of management became linked with the much more demanding - usually impossible - task of maintaining a constant catch rate despite often extreme natural fluctuations. The fisheries biologist, for one, was in trouble.

Whether this explains the drift into the more ambitious concept of “management” instead of “regulation”, with man as the benign controller of the natural systems (and, by implication, of the socio-economic counterpart also), I do not know. If it does, then care is needed if we are to carry the confidence of the decision-makers with us in dealing with any but the simplest and most stable of fishery conditions.

353 Density-dependent complications, including stock/recruitment, may modify but do not invalidate the equilibrium or “average expectation” concepts, provided one can work on a long-term basis and accept variation in recruitment as part of the game. There are, however, some clear limitations to this approach, among them:

(a) policy for fisheries in the early stage of development. Caddy (1983) gives a good analysis of these non-equilibrium situations, as do Sharp, Csirke and Garcia (this volume).

(b) policy for fisheries which exist in unstable oceanographic conditions, with major periodic or episodic perturbations, as exemplified by the Peruvian anchovy and Californian and Japanese sardine.

(c) policy for fisheries which are liable to collapse under heavy fishing, as exemplified by the North Sea and Atlanto-Scandian herring.

In all these cases biological assessment alone is not sufficient. Decisions are, or ought to be, made on a trade-off between possible gains and losses measured in different units and different time- scales. Some aspects of socio-economics, and probably politics as well, must therefore be allowed for. How and by whom is for consideration.

INTRODUCTION OF SOCIO-ECONOMICS: THE TOTAL FISHERY SYSTEM

The factors to be taken into account in addition to those used in conventional fishery assessment will depend very much on the circumstances, but a general list might include the following:

1. Prospects in alternative stocks and “costs” of switching. 2. Costs of fishing, capital and recurrent. 3. Shore facilities, storage and transport. 4. Markets, demand and prices. 5. Availability and skill of manpower. 6. Alternative commodities, e.g. frozen foods other than from the sea. 7. Overall financial prospects; loans etc., national and international. 8. Administrative and legal policy at national and international level.

It would be possible, but unhelpful, to represent the interactions between these and the physico- biological fishery sub-system by drawing a multitude of boxes linked by a network of lines and arrows. I am, however, indebted to my colleague Professor Rolando Garcia1 for pointing out to me that this kind of socio-economic system does have a general structure which can be represented for analysis in terms of processes happening at three levels of integration, characterised by their dimensions of space and time and by the extent to which they are influenced by factors external to the system itself. I have found that the same kind of 3-level structure can be used to represent the physico-biological part of the fishery system, the two being linked at one level only (see also Glantz, this volume).

Fig. 2 represents the physico-biological and socio-economic limbs of the overall fishery system on these principles, much of which is self-explanatory. As it stands, this does not solve anything, but it may help to clarify ideas because it shows that certain “rules” must be followed in attempting to bring socio-economics into the picture. Thus,

1 Head of Dept. of Epistemology at the Metropolitan University of Mexico City: formerly Dean of Sciences at University of Buenos Aires and Director of the Argentinian Meteorological Service. In Drought and Man, Pergamon Press, 1982 and pers. Comm. 354 (a) The only direct interaction between the two sub-systems is at the “hinge of the book”, between levels 1A and 1B. This interaction consists of the flow of fish caught, from 1Aĺ1B, which is soon transformed into its monetary equivalent; and of time, hardware, and skills via the operations of the fishing fleet in the other direction 1Bĺ1A (also with a monetary equivalent).

(b) Materials, animate and inanimate, and “influence” in the form of “decisions”, flow across both pages into the hinge, i.e. 3ĺ2ĺ1. By means of loops and feedbacks, there is a reverse interaction - more limited (absent 2Aĺ3A) but in some cases critical in determining the dynamics of at least the immediately adjacent levels.

(c) Conventional fishery assessments establish the functional relationships across the boundaries 2AЁ21AЁ2;1B. Occasionally, if economic considerations are involved, they extend to level 2B in a limited way.

(d) Cross-flow of materials and “influence” between the pages without going through the hinge is permissible only by introducing a wholly new factor into the system. For example, if the stocks are replenished by some form of cultivation, the link would go from the appropriate B level (either 2B or 3B) into level 3A (nutrients), 2A (eggs and larvae) and 1A (post-recruit fish). The diagram reminds us that the effect on the overall system could not be assessed unless the input level is specified and the inter-level interactions towards the hinge (3Aĺ2Aĺ1A) are known.

(e) In contrast, information about the physico-biological system does pass direct to various levels in the socio-economic sub-system (i.e. between the pages), with or without the scientific interpretation. The timeliness and competence of that information flow obviously has a major influence in the fluctuations of the overall system.

This representation of the interlocking between the physico-biological and the socio-economic components of the total fishery system cannot show explicitly the dimension of time which characterises the various flows and feedbacks. This aspect, and especially the occurrence and consequences of time-lags in the dynamics of fisheries, is well analysed by Caddy. It will not be further mentioned here except to observe that time-lags in the socio-economic sub-system, just as in the physico-biological sub-system, apply at various levels and have analogous and often control effects on the dynamics of the overall system.

355 Fig. 2.- Diagrammatic representation of total fishery system, comprising the physico-biological and the socio-economic sub-systems interlocking as shown. See also text.

CLASSIFICATION OF “EXPLOITATION RISK”

The decline, collapse and even recovery, of major fisheries in recent decades, for whatever reason, immediately raises a number of fundamental questions for the decision-makers. Those with which I am concerned here centre around the questions:

(a) Could such events have been forecast in real time; and if so, for how long ahead, with what reliability and what is the diagnostic evidence?

or if that is not possible; -

(b) Could the possibility of collapse at some time have been anticipated from the characteristics of the fishery; and if so, what are these characteristics?

These questions are valid even if MSY is not the objective, since they strike at the root of the stability of the fishery industry, to maintain which must surely be a priority objective of management in almost all circumstances. What can we offer the decision-makers on this?

Regulation by catch quotas has made it necessary to have estimates of future year class strength as far ahead as possible. In practice this usually means 1–3 years depending on the length of the pre-exploited phase and the feasibility of estimating reliably the abundance of the pre-recruits. This might help tactical decision-making (i.e. at level 1B of Fig. 2), but is insufficient for decisions on commitment of major capital resources at high levels. In the present state of knowledge we must discount the practical possibility of making ‘real-time’ forecasts of future year-classes from

356 oceanographic conditions, except in special cases (of which the E1 Niño phenomenon may be one). Nevertheless, we ought to be able to say something from experience about the risk involved in exploiting the main types of stocks and associated fisheries.

It was this line of thinking that led me to attempt such a classification for the Santiago conference. Caddy2 has been working on the same lines and cites Kawasaki (1979) similarly. The latter confines his criteria to biological characteristics of the stock, but this is only part of the story. Caddy groups fisheries into several categories primarily on the basis of the historical pattern of trends and periodicities in catches, together with a knowledge of the environmental stability. This makes for a better diagnosis, but trends and fluctuations in catch alone can be very misleading, as recognized by Caddy, especially in mixed fisheries when effort can switch from one species to another or is affected by external events such as fishery restrictions or economic factors.

I believe, however, that a further development of this approach is possible and potentially useful to the decision-maker in devising his medium to long-range fishery strategy in both new and established fisheries. It is best visualised with reference to the overall fishery system represented in Fig. 2. Instability can be generated in or between any levels in either the physico-chemical or the socio-economic sub-system, or, more especially, at the interaction between the two main sub- systems (e.g. at the spine of the ‘book’ of Fig. 2). The more critical of these potential sources of instability would seem to be the following:

(a) environmental conditions as they affect the integrity of the life-cycle, as manifest notably but not exclusively by the variability of recruitment (1Aĺ2/A).

(b) degree of compensation in the generation-to-generation transfer, i.e. in the stock- recruitment relationship, as mediated through the life-time dynamics (growth, mortality and maturation) of each cohort (2AЁ21A).

(c) behaviour of individual fish; particularly their shoaling propensities, detectability and use of habitat protection from fishing activity (1A).

(d) efficiency of fishing operations; particularly fish detection technology, group searching tactics and capacity to switch to alternative species (1B).

(e) elasticity of supply and demand, market preferences, mobility of capital investment (1BЁ2 2B).

(f) long-term status of the fishing industry in the national economy; competing products, responsiveness of the regulative framework (2BЁ23B).

Application of the first four of these criteria to characterise six well-documented fisheries in terms of “exploitation risk” is shown in Table 1, taken from Beverton (in press). The additional socio- economic factors (e) and (f) in the above list have nothing to do with the fish resources as such, but in certain circumstances could be important destabilisation factors and certainty would be, or ought to be, taken into account by the decision-makers.

Commenting in turn on the first four criteria, several kinds of environmental characteristics can be identified from experience as having been instrumental in causing or triggering dramatic fishery changes in stocks living at the extremes of their range which are likely to be most susceptible. Thus, the warming of the North Atlantic in the 1920's was followed by the rise of the West Greenland cod fishery (at the northern limit of the range of the species, Gadus callarias) the disappearance of the Plymouth herring fishery (at the southern limit of the range of the herring)

2 J.F. Caddy An alternative to Equilibrium Theory for Management of Fisheries. FAO Expert Consultation on the Regulation of Fishing Effort, 1983. 357 (Clupea harengus harengus) and its replacement in the English Channel by the pilchard (Sardinops pilchardus) spreading northwards from further south. (See Beverton, R.J.H. and Lee, A.J., 1965). Stocks living in or close to a major current system are clearly in an uncertain environment, as instanced by the virtual disappearance of the Japanese sardine (S. melanosticta) in the 1940's, following changes in the course of the Kuroshio current in which it had previously spent the early part of its life-history (Kondo, 1980). Again, the precarious state of stocks living in upwelling systems, e.g. the California sardine (S. sagax caerulea) and the Peruvian anchovy (Engraulis ringens) is well established (see, e.g. Glantz, et al., ibid.).

The degree of compensation in the stock-recruitment relationship, i.e. the extent to which recruitment remains effectively independent of stock size, has a powerful effect on the stability of the fishery. As a general guide, those species that spend part of their early life-history in shallow, confined nursery areas (typified by flatfish in temperate regions) are likely to show high compensation (Ursin, 1982). A much better diagnosis is possible if good stock-recruit data are available. No sophisticated theory or curve-fitting is needed to bring out the high degree of compensation in the stock recruitment arrays shown in Figs. 3 (a), (b) and (c) for the North Sea sole (solea solea) and herring compared with the weakly compensated Peruvian anchovy. Trends in catches are shown also for comparison. Yet although both the sole and herring have been heavily fished only the latter has collapsed-so far, at least. Strong compensation, though necessary for stability, is evidently not a sufficient protection on its own.

Criteria (c) and (d) provide the clue. The sole is a demersal species which can remain partially buried in the sea-bed; it does not shoal and is undetectable by sonar. All these characteristics mediate the extreme impact of fishing but are not possessed by herring. Explicit proof of a tendency for the catchability coefficient q to increase as stock size declines is not easily demonstrated for the North Sea herring, since a variety of gears have been used in the years (see, e.g. Pope, 1980). There is, however, strong inferential evidence that it does, since a nearly hyperbolic function of q with stock size has been found in several other purse-seine fisheries for pelagic species, notably by Ulltang (1980) for the Norwegian spring spawning herring, by MacCall (1976) for the California sardine and by Butterworth (this volume) for the South West African pilchard.

It is not difficult to see how a nearly hyperbolic relationship between q and stock size, acting synergistically with the other criteria listed above, can lead to virtual certain collapse for a fishery unless drastic remedial action is taken, and in time. Fig. 4 is a simple representation of this positive feed-back system. Suppose that a fishery has been in a reasonably steady condition under moderate fishing for some years, generating the mean stock-from-recruit line A intersecting with the mean recruit-from-stock curve at S1, R1 as shown. Suppose now that a transient environmental perturbation causes recruitment to fall to r1. This poorer year-class will cause the stock to fall which in turn will cause q to increase and steepen the recruit-from-stock line to B. The stock is now more vulnerable to a second fortuitously weak year-class r2, which leads to a further decrease in stock and increase in q. Eventually, the stock-from-recruit line is displaced to D, at which it no longer intersects with the recruit-from-stock curve at any point. The stock now proceeds to extinction unless fishing is drastically curtailed or stopped altogether.

358 Table 1: Classification of exploitation prospects for six selected fisheries. (From Beverton, in press) NORTH SEA NORTH SEA NORTH SEA ATLANTO- PERUVIAN CALIFORNIA PLAICE HADDOCK HERRING SCANDIAN ANCHOVY SARDINE HERRING MARINE Stable Stable Stable Moderately Unstable Unstable ENVIRONMENT stable (Upwelling) (Upwelling) FISH POPULATION

DYNAMICS - Degree of S-R compensation High Indeterminate Fairly high Moderate Low Very low - Variability of R Low Very high Moderate Spasmodically Low-Moderate Moderate high - Life-span Long(20+yrs) Medium(12+yrs) Medium(12+yrs) Medium-Long Short(4+yrs) Medium(10+yrs) (15+yrs) - Pre-mature phase Long(3&ndash4yrs) Medium(2yrs) Medium(2yrs) Medium(2yrs) Short(1yr) Medium(2yrs) - % of growth(wt) span Large(90%) Large(80%) Small(40%) Medium(60%) Short to Medium(50%) after recruitment Medium(50%) FISH BEHAVIOUR - Habit demersal demersal pelagic pelagic pelagic pelagic - Environmental partial partial none none none none "shelter" - shoaling tendency slight some strong very strong strong strong - Ease of detection undetectable limited easily easily easily easily - Dependence (inverse) none probably none probably none very strong strong strong of catchability on abundance - Vulnerability resilient resilient vulnerable very vulnerable very vulnerable very vulnerable toescalation of F OVERALL FISHERY Steady and dependable Highly erratic in short to Fairly Steady in short to Spasmodic; long- Unreliable in medium Unreliable; unstable PROSPECTS in short and long-term medium-term; probably medium-term; long-term term reliability to long-term, with in the long-term reliable in long-term reliability uncertain suspect sudden changes INCREASING EXPLOITATION RISK

359 Fig. 3.- Long-term trends in landings (left-hand diagrams) and the stock-recruitment arrays (right hand diagrams) for the fisheries for: (a) North Sea sole (stable) (b) North Sea herring (collapsed) (c) Peruvian anchovy (unstable). These diagrams show that neither trends in landings nor the shape of the stock-recruitment arrays is alone sufficient as diagnosis of the stability characteristics of fisheries (see also text). Data from Garrod (1982), Saville Bailey (1980), and Csirke (1980).

360 IMPLICATIONS FOR DECISION-MAKING

In conclusion, let us consider a few of the problems posed to the decision-maker in the light of the above analysis of fishery systems, and the contribution of the scientists to their solution.

Fig.2 illustrates the obvious point that to pass from between the two sub-systems in the direction 1Aĺ1B requires, at the least, transformation of the key variables of effort and catch into monetary equivalents. Despite the significant contributions to fishery dynamics from the economics profession in recent years, it is not immediately apparent in the fisheries literature that any general relationships have been established between these variables. Perhaps I have been looking in the wrong place, yet much of the significance to the decision-maker of stock variability is lost, or at least greatly modified if, for example, the relationship between weight of catch and its price is strongly elastic. Gulland's (1980) analysis of long-term trends in the value of North Sea landings is one of the few of this kind and illustrates this latter point well.

The possible objectives for the management of established and reasonably “reliable” fisheries (see Table 1) have been discussed in the literature with a thoroughness not matched by the clarity with which they are usually defined in practice. It is sufficient here to observe that one way of posing the general problem starts with the premise that there is a potential maximum economic rent that could be gained over time from a fishery (on one or a complex of stocks) if it is managed appropriately. The ultimate choices then lie between:

(a) enabling that maximum rent to be realized directly as profit, which implies a firm limitation of the amount of fishing, or

(b) allowing rather more fishing so that part of that potential rent is dissipated as may be desired, e.g. in larger average catches (possibly, but only within limits), and a larger fishing community in the catching and operational sectors.

As thus formulated, choosing the objectives of fisheries management has a strong political element, to which neither the fisheries scientist nor even the economists can contribute much. There is clearly no generally applicable prescription, although wherever the fishing industry is a major factor in the natural economy or is expected to function as a fairly self-sufficient unit within the national economy, a high priority will be given to achieving a reasonable stability for the fishery system as a whole. Put in these terms, management necessarily involves some form of risk assessment in the way discussed above, with stock variability a dominant factor-and the scientist has a crucial role to play.

This point is well illustrated by returning again to the question of how to keep a fishery reasonably clear of the kind of collapses typified by the herring fisheries cited above, and the “price” to pay for what may be called “prudent exploitation”. The decline of the Norwegian spring spawning herring fishery over the decade from 1960 to its eventual collapse in 1970, with the attendant changes in the size and structure of the stock, have been well documented by the scientists of the Bergen Laboratory (e.g. in Dragesund, Hamre and Ulltang, 1980; and summarised by Bakken, this symposium). This evidence provides a real-life demonstration of the sequence of events illustrated in Fig. 4.

361 Fig. 4. Hypothetical stock-recruitment relationship to show how a succession of three poor year- classes (r1, r2, r3) working through an inverse relationship between q and density, can cause a progressive increase in F and hence, steepening of the stock-per-recruit lines (AĺBĺCĺD) resulting eventually in stock extinction (line D no longer intersecting with the recruitment-stock curve at any point). See also text.

Fig. 5 shows how F changed with stock size during this period, the rapid escalation of F at low stock levels being due not to an increase in the amount of fishing but to the nearly inverse relationship between q and stock abundance in this fishery (Ulltang, 1980).

From this diagram it is evident that to keep clear of the rapidly ascending limb of the curve, the stock should not be allowed to fall below about 4 million tons. This corresponds to an F of about 0.3, which is already higher than in the most productive earlier years of the fishery and about twice the value of M. This stock size is located on the stock-recruitment array for the Norwegian spring spawning herring by the vertical broken line of Fig. 6. The variability of recruitment is such that a rather higher stock size, perhaps in the region of 6 million tons, would be needed to reduce to an acceptable level the risk of another year-class as small as that of 1965 setting in motion the collapse feed-back loop. A proper risk assessment, showing the probability of collapse against stock size, could be made from the observed variability of recruitment using Horwood's (1982) method or by repeated runs on a computer.

The decision-maker then has the unenviable task of weighing various probabilities of collapse against the implications of restraining the fishery to a lower operational level than that at which is would otherwise have been under the influence of the usual short-term incentives. The price to pay for this more prudent exploitation might include a little smaller average yield, although an F in the region of 0.3 is probably close to the mode of the “equilibrium” yield curve for the fishery: such differences as there might be would be lost in the “noise” of fluctuations in R and price elasticity.

More significant is that the somewhat smaller fishery would be operating at a substantially higher mean catch per unit effort than would otherwise have been the case: effective regulatory measures would therefore be needed to ensure that the effort does not gradually creep up to the danger zone.

362 Fig.7 shows a hypothetical illustration of prudent exploitation in the case of fishery which is liable to “collapse”. Figure 7 (a) is the equilibrium yield (effort curve incorporating the stock-recruitment curve of Figure 7 (b). Fig. 7 (c) is the corresponding biomass/effort curve. The depth of shading is an indication of the risk of collapse, i.e. if the fishery is being forced by one or two poor recruitment into the positive feed-back loop illustrated in Fig. 4, as happened in the Norwegian fishery. It would clearly be more “prudent” for the fishery to operate at, say, point B then at the MSY point A; and although the total yield would be smaller, the catch per unit effort would be higher.

The difficulty for the administrator of introducing such restraints, and for the scientist of convincing him and the fishermen that it is in their longer-term interests to do so, is clearly formidable. At the time, before the collapse, it was virtually impossible (see Saetersdal, 1980). But now, taking a global view, we are sadder but wiser--or should be, if the lesson is put across effectively. Thus, it is significant that although the stocks of both the Norwegian spring spawning herring and the Icelandic summer spawners were reduced to very low levels, fishing was stopped by decree while a stock remnant still remained (Jakobsson, 1980). The same is true for the North Sea herring and the British Columbia herring (Hourston, 1980). All those are showing signs of recovery, albeit slowly in the first three cases. In contrast, fishing continued unrestrained until the bitter end in the Icelandic spring spawning herring fishery and in the California sardine fishery; both these stocks disappeared completely.

I am indebted to Dr. S. Tanaka for telling me that in both the two classic cases of collapse of Japanese fisheries, the Hokkaido herring in the 1930's and the sardine in the late 1940's, fishing intensity remained high on the dwindling stocks until it was no longer worthwhile for the fishermen to put to sea. The Hokkaido herring disappeared and has never recovered; the sardine has recovered but only after a lapse of some 30 years.

The assessment of exploitation risk is an example of the kind of decision that arises in modern fisheries “management”, involving both equilibrium and transient states. No doubt many other examples could be cited which are at least or more complex, e.g. those arising if more positive management of multi-species is attempted along the lines practiced in Canadian and US fisheries. It is pertinent to ask whether the conventional structure of and communication between the scientific and decision-marking sides is capable of providing the requisite liaison.

363 Fig. 5. Relationship between stock size and fishing mortality coefficient F in the Norwegian spring spawning herring fishery in 1971. The vertical broken line shows the stock level at which the rapid escalation of F begins. (Data from Dragesund, Hamre and Ulltang, 1980).

Fig. 6. Stock-recruitment array for the Norwegian spring spawning herring fishery over the same period as Fig. 5. The vertical broken line indicates the critical 4 m. tonne stock level of Fig. 5; but to reduce the risk of the fishery becoming unstable through a year class as poor as that of 1965, a stock of some 5 or 6 m tonnes would be required (see text).

364 Fig. 7. Hypothetical illustration of the concept of “prudent exploitation” in a fishery with a strong inverse relation between q and density, a weakly-compensated stock-recruitment and a moderate to highly variable recruitment. Prudent exploitation would require the fishery to operate at B of Fig. 7 (a0 compared with the maximum equilibrium yield point A. Figs. 7 (b) and (c) show the implications of points A and B on the stock-recruitment and c.p.u.e. curves, respectively, for the fishery in question.

One difficulty at this point is the opacity of the processes at key links in the socio-economic sub- system. How science affects the way decisions are reached in the board rooms of the major fishing companies, or how it affects the attitude of individual owner-skippers with a heavy mortgage to pay on their boat, is not readily available. What happens at the decision-making level in government or in the international fisheries bodies is not necessarily any more visible. The International Council for the Exploration of the Sea (ICES), I am glad to see, still provides first-stage scientific assessments to the European Commission on fisheries within the latter's jurisdiction, which are openly published as Reports of the Advisory Committee on Fishery Management. But what happens thereafter, as the scientific assessment is moved up the hierarchy inside the Commission to the ultimate decision-making by the Council of Ministers, is known to a privileged few only.

This situation might not matter if the scientific basis for decisions were easily and quickly tested against results. It is characteristic of natural resource systems, and highly variable fisheries in particular, that this is not so. A high degree of mutual trust and confidence between the scientists and the decision-makers is called for if fishery collapses of the kind we have witnessed during the last decade are to be avoided. Still more will this be true if we are to move into more positive fishery management such as advocated by Gulland (1980) for the North Sea.

My impression - admittedly vague and with only limited support from hard evidence (but see, e.g. Glantz 1981; and Saetersdal 1980) - is that the decision-makers still take only passing notice, most of the time, of what the scientists have to say. If that is right, perhaps we should be giving some thought as to how to get the massage across rather better in the future. It seems to me that one essential step is to acknowledge that the first stage assessment of the fishery is a sophisticated exercise in the application of the scientific method to the analysis and interpretation of complex data from various sources and of uncertain reliability. It requires also a sound understanding of the natural history of the species and of the ecology of the population in question. That being so, there is everything to be gained from publication of those assessments so that they are open to scrutiny by the competent scientific community, just as would be any regular research findings. Not only 365 would this improve the standard of the investigations; it would also give those who have to use them the added confidence that they have run the gauntlet of open scientific peer review, which is the furnace in which the steel of all good scientific research is forged.

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