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PART II(Continued)


In conventional fisheries analysis of the dynamics of single species, we are accustomed to assuming that natural mortality rate M can be treated as a constant through time for the exploited phase of the life history. This assumption is necessary in order to solve the catch equation, even though it can usually be shown by sensitivity analysis that the yield predicted by this equation is particularly influenced by variations in this difficult to measure and varying parameter. The assumption of a constant M is tolerable for single species assessments, and may be seen as a logical consequence of the slow rate of change of feeding rate with size for predators above a size of 50 g or so, shown in Figure 67. This conclusion is valid however if relative abundances of predator and prey remain roughly constant, which is not always the case. From the point of view of an attempt to understand multi - species interractions, it may be a logical alternative to the ‘static’ assumptions of (e.g.) the ECOPATH model to regard the value of M as an output variable resulting from the relative abundances and feeding rates of predator and prey species in the ecosystem. The main point to be borne in mind is that concluded at the recent ICLARM/CSIRO workshop on Theory and Management of Tropical Multispecies Stocks, namely that for fisheries where multi - species effects are beginning to seriously bias single species assessments, we need some tools, however crude, that allow us to base our conclusions on events at the whole system level. An approach to modelling M as an output parameter, determined by the intensity of predation, (in its simplest terms, a function of relative predator and prey abundance and predator feeding rate), would be a useful preliminary to understanding system dynamics.

Another option that may be used to simplify multispecies models, is to express growth, mortality and migration rates in terms of biomass as opposed to numbers (e.g., Laevastu and Larkins, 1981). These latter authors noted that in data - poor areas, the use of ponderal rates can be preferable to number - based models, even if this necessarily sacrifices an ability to integrate results easily with age - structured models. These authors propose definitions for e.g.:

Biomass (Bn) in year n:

Bn = Bn-1 exp (gn - Zn)

where: Zn is the mortality rate in year n,

Bn-1 is the biomass the previous year, and

gn is the exponential rate of biomass growth in year n.

Similarly, for natural mortality caused by predation:

Mp= -loge (1- D/)

where D is biomass consumed by predation and is the mean biomass in the year. These concepts are developed a little further in the next section in suggesting simple indices, particularly for ranking the likely impact of different predators on the natural mortality of the prey.

The relationship between predator and prey biomasses and the natural mortality rate of prey

The relationship between predation and natural mortality rate in the prey population was expressed as a function of predator biomass by Munro (1979, 1982) as:

M = Mx + gP … (1)

where P = biomass of predators, and Mx is mortality due to natural causes other than predation (e.g., disease, senescence, etc., where this does not result in prey consumption by the usual predators). Evidently in this context, Mx is likely to be very small, since senescence and disease usually result in an increasing probability of predation, and from a trophic viewpoint these two types of factors simply act to facilitate transfer of biomass from prey to predator, and we would probably be justified in writing:

M ≤ gP … (2)

This second equation assumes however that predator biomass P act in an analogous way to fishing effort (f) in the equation F = qf. This is somewhat misleading, since equation (2) either assumes a constant abundance of prey, or that a given biomass of predators acts “catalytically” to induce a given prey mortality, independent of the biomass of prey. In view of the trophic needs of the predator, prey biomass must also be a term in the equation; especially since from the predator-prey theory, we know that predator + prey biomass each tend to oscillate out of phase with the other. Evidently, as prey biomass declines with above average predator biomass, M must increase if the predator's food requirements are to be satisfied. However, a rather intuitive yet admittedly crude approach can be formulated, again looking in the simplest case at an obligate relationship between a single prey and its single predator in an unexploited system, and ignoring problems of availability. One can postulate after Laevastu and Larkins (1981), a relationship between predator and prey mortalities such that the proportion of prey consumed in an interval will be a function of the relative predator and prey biomasses or densities within any given framework.

Assume first that the food requirements of the predator in unit time can be expressed as a simple fraction (or multiple) of their own biomass = aBi+1.

At the end of the time interval, ignoring the effects of growth of predators and prey, the original prey biomass B'i is reduced to (B'i- aBi+1), and the corresponding rate of decline in biomass due to predation M'iis then :

B'i - aBi+1 = B'i e-M'i

This formulation of course assumes that we can define mortality rates in terms of biomass rather than numbers. Such a rate (M') has been referred to as a ponderal rate, and is not necessarily identical with the numerical natural mortality rate, M. This approach may be acceptable as a first approach, but size - specific predation and age composition of predator + prey will need to be allowed for, as suggested earlier. Also the assumption of a constant feeding rate implied by constant a ignores density - dependent changes in energetics of feeding with season and size, and takes no account of the different energies needed to capture different prey species, and the different calorific values of different prey. Despite this, equation (3) appears to be a reasonable point of departure for a very simple treatment of the problem, and as we have noted, a similar expression has been used by Laevastu and co - workers.

Looking briefly at some of the difficulties with the simple formulation outlined above, one may first suggest that as long as we discuss predator - prey relationships in terms of quasi long - term average abundances of species in the ecosystem (the “equilibrium assumption” that underlies most currently used fisheries theory), implying that predator - prey ratios remain relatively stable, then the surplus production due to growth and reproduction of the prey not harvested by man, will on average, be roughly equivalent to the increment in biomass of predators, (after allowing for conversion efficiency of prey to predator biomass). It may be acceptable therefore under these assumptions to substitute mean biomass in equation (3). This formulation:

then gives us a simple first - hand way of deriving orders of magnitude for M, given some idea of trophic interrelationships (i.e., a food web), and an idea of the relative biomass of predator and prey; such as, for example, might be obtained from stratified trawl or acoustic surveys if these can be shown to be measures of relative biomasses.

Prey mortalities due to predation

Looking at interelationships between a single prey and its single predator, and ignoring problems of availability, one can postulate relationships between a predator and the mortality it exerts on its prey, such that the proportion of prey consumed in an interval will be a function of relative abundance of predators to prey biomass. On the other hand, if prey abundance falls below predator food requirements, prey switching, migration of predators from the system, or even in the extreme case, natural deaths of predators due to starvation could occur, which cannot be accounted for in this simplistic approach.

In all of these circumstances, the above simple mathematical approach breaks down. However, assuming that Figure 67 in this paper gives some idea of the magnitude of the mean annual feeding rate (i.e., a' = 365 a), then it is instructive to see what order of magnitude or M is predicted from equation 4.

Consider a predator - prey pair where a predator A with mean individual weight of 700 g and mean biomass of 1 000 t is the only predator, and feeds exclusively on species B', a prey species with biomass 15 000 t, at ambient temperature 10°C. Applying equation 4, the predicted annual value of M for species B' due to predation would be:

Assuming the ambient temperature increased to the level which doubled the feeding rate of A:

then MB' = 1.42

and if the biomass of B' is now reduced to 600 t by fishing (prey biomass and temperature constant):

MB' = 0.61

Obviously the actual values resulting must be considered with some scepticism, but this approach may be useful in predicting effects of important changes in relative biomass or temperature, or in comparing impacts of resident and migrant species on a common prey. For this latter purpose, the equation could presumably be modified to give some idea of the impact of seasonal predation by multiple predators on the value of M for prey species B'. Thus, for i = 1,2, 3 …n predators of biomass Bi, each of which spends a fraction Δti of the year feeding on common prey species B' at a daily rate ai, and where Pi is the proportion of the diet made up by B', then if the same logic holds,

Thus, if a biomass of 10 000 t of prey species A, and three predators C, D, and E make up part of a simple “assemblage production unit”, with characteristics as below:

Daily FeedingProportion of yearProportion of A inBiomass
Ratefeeding on Astomach contents(t)

What is the predicted value of M? From the above MB' = 0.28.

Perhaps in conclusion, the value of this type of approach is more that it allows a prediction of the effects of certain types of population change on the unknown or known values of M, rather than as a method of estimating the value of M itself. The approach also seems to have some merit in providing first estimates of parameters to simple models such as the ECOPATH approach, and in comparing relative impacts of residents and transients for example, on a common prey. It also, seems to provide an approach to tackling the ‘non - equilibrium’ problems in fisheries, since a change in natural mortality rate of species in a food web is one likely cause of the changes in species composition often seen is some heavily fished systems.


Although diagrams can only supplement numerical models, one of the aspects we have emphasized in this report is the utility of diagrammatic approaches for communicating information on ecosystem interactions and the food web. Despite the variety of conventions used in depicting flow diagrams however, there are two aspects of trophic relationships in the sea that are not normally represented, although they are of major importance. The first of these illustrates the spatial component of energy transmission - a major theme of this report being the food web as a “dissipation structure”, in which specific areas and habitats play a key role in biomass production and dissemination (see Fig. 3 for an example of the spatial representation of food web linkages, and Laevastu and Larkins (1981) for a discussion of the importance of spatial distributions and hydrographic factors). A second characteristic of most marine food webs that is rarely represented, is the fact that most components at all trophic levels start off life at close to the same size range, and apical predators for example, almost inevitably move upwards trophically in the course of their life history. We have concluded that size relationships (as noted for spatial considerations above), are essential to understanding ecosystem processes, but are rarely represented in food webs. All of this prompts us to tentatively suggest an approach to food web representation that takes these spatial and size - related elements into account, together with that other important information element; the species biomass.

Figure 68 attempts to portray the relationship between dominant (A) and subdominant predators (B) and their common prey (C) in a manner that makes explicit the size interrelationships as well as the biomasses involved (both shown on a logarithmic scale). The possibility of “reciprocal” predation by adult prey on the juveniles of their predators (the cod - herring example), is easily accommodated by this convention. It is also possible to sum all biomasses (not their logarithms!) laterally to show the biomass spectrum of the subsystem in question. The “kite” diagrams in Figure 68 for each species obviously are ‘doubles’ of the biomass spectrum for each species. Such biomass spectra, (here, obviously incomplete for lower trophic levels), could be portrayed prior to and after exploitation of one or more components, and are analogous to the pyramid of numbers shown in Fig. 2.


Differences in Vulnerability to Fishing

Much of fisheries theory as we have already noted, still operates on the assumption that individual components can be managed separately from their preys, predators and competitors, and the persistence of this school of thought and practice for over a half century since Baranov's earlier work, shows that this may not always be a totally incorrect perspective in some ecosystems for much of the time. It may be worth speculating that this could be true because of the ‘damped’ nature of many marine systems, where individual food web components tend to overlap with others in the same system giving a certain resilience to the food web, in the face of the exploitation of one component; or perhaps because at moderate levels of exploitation, production by the exploited species is in fact increased by fishing.

Critical Habitats and Refugia

In trying to put an order of priority to our concerns with species management in an ecosystem context, the complexity of marine ecosystems makes it seem problematic that except for very simple systems, we will be able in the near future to guarantee a given impact from a particular intervention at a specified ‘node’ in a food web. Thus, although for example, by selective fishing, we can in theory, remove “undesirable” components, this would not only be difficult to justify economically, but from the few examples where this has been tried, such as the attempt to remove dogfish (a low - value predator on salmonids) in the northeast Pacific by a ‘bounty’ system, or to control starfish and gastropod predators in shellfish culture, these efforts are rarely crowned by lasting success, even if (as often happens), a market for these “pests” subsequently develops.

Large - scale experiments have in fact been carried out in ecosystem manipulation all over the globe, namely by single species commercial fisheries. Although these have not been aimed at species eradication, in a relatively low proportion of cases globally have measures other than a decrease in economic yield at low abundance, protected the target species from possible extinction. There have of course been cases where valuable species have been driven to extinction or rarity (especially those with high vulnerability and long - life spans), but there have been a surprising number also which have shown a significant degree of resilience to the effects of such interventions.

Figure 68

Figure 68 Showing a food web for three species components, with logarothms of biomass shown as “width”, and arrows indicating trophic exchanges between given size ranges. Reciprocal control of larval recruitment of “predator” A by (planktivore?) “prey” B is shown; also the biomass spectrum for the whole subsystem. (Arrows without origins indicate unspecified nits lower in the food web)

More detailed examination of both categories seems to show that two types of intervention are more likely to lend to drastic stock declines and overfishing:

  1. The exploited phase of a population goes through a period (usually when the stock is concentrated in a given area), where it is highly vulnerable to fishing. Such areas may be called “critical habitats”. Commonly cited examples of critical habitats are the spawning grounds of species such as cuttlefish, herring, grouper and marine turtles where much of the adult biomass is concentrated in a small area over a limited period of time, and hence vulnerable to high levels of exploitation where fishing success is largely independent of stock biomass.

  2. The species passes through a phase in its life history associated with a particular habitat, e.g., mangrove swamps and shallow lagoons for some shrimp and crab species, grass beds or macrophyte stands for some lobster species, etc. The “health” of the “substrate” species then has an overriding influence on the associated organisms.

In the contrary sense, where a species resists heavy exploitation, it may be because capture efficiency is proportional to density, or because a “refugium” exists which protects the species from heavy exploitation over part of its size range and geographical extent.

A species “refugium” is less easy to define, but may consist of an area of rocky untrawlable bottom, or for a small boat fishery, an area of strong currents distant from shore. It may also occur as a result of fishing with gear such as traps or gillnets which have a particular size selectivity, such that the dominant mesh size or entry hole dimension of the gear forms a “refugium” for those animals that avoid capture long enough to grow to larger, mature, sizes.

Figure 69

Figure 69 (A) Showing evolution of a cohort with age from many small individuals to a few large ones

(B) Standing stock of the biomass of this same cohort with time or with age

(C) The rate of change in biomass (dB/dt) with age (II marks the age at maximum biomass, given the growth and mortality rates that apply, and I and III mark respectively, the times at which the biomass is growing and decaying fastest

(Redrawn from Alverson and Carney, 1975)

Biomass at Size Distribution and Stock Recruitment

The importance of information on the length spectrum of a species for analysis of population trends, and estimating population parameters, has become more appreciated in recent years, and the equivalent in terms of biomass is of corresponding importance for trophic calculations. The biomass distribution with size and age for a species shows an increase to a maximum at the age/size when growth in weight is just balanced by mortality due to all causes, before subsequently declining with size (Figure 69). For exploited resources, this point of maximum biomass would be the ideal size for instantaneous harvesting. In practice, however (and here the yield per recruit methodologies of e.g. Beverton and Holt, 1957 came into play), it is usual for a given natural mortality rate (M) assumed constant for exploited sizes), to calculate the rate of exploitation that would provide the maximum yield per recruit for a given size at first capture, or the impacts of a change in mesh size or size at first capture. The possible impact that heavy exploitation might have on prey or predator populations of the species in question, is not considered in the approach.

One of the other limitations of this type of calculation which has major practical implications, is that the predicted effects of changes in size at first capture do not always take into account whether or not a species begins to be exploited before sexual maturity: this could of course have an impact on the average level of recruitment, if in the extreme case, exploitation is heavy and begins before maturity. This type of effect is dealt with by so - called stock recruitment models (see Ricker 1975 for details). These models which usually attempt to predict the average level of recruitment from a given spawning stock size alone, don't usually take into account variations in the physical and biotic environment the spawners and pre - recruits are subject to, and as a consequence show a high variance in predicted number of recruits. What is important to note from the perspective of trophic analysis however, is that the ‘loss’ of commercial - sized animals in yield per recruit evaluations due to natural mortality (the proportion M/Z of all deaths) returns material to the food web. This is true also for spawner - recruit models: thus although the number of recruits successfully produced per unit biomass of spawners drops off with total spawner biomass the ‘losses’ in gametes and pre - recruits implied here, re - enter the food web; but at a generally smaller prerecruit size.

In practical terms therefore, although we should not abandon the useful single - species methodologies that have been developed over the last 50 years or so, some attempt should be made to place these types of analyses in their correct ecological context, i.e., every single species assessment should ideally be preceded by a qualitative statement about:

  1. The physical system, and what we know of its stability, seasonality, extent and productivity.

  2. What we know about the other major biological components in the system and their interactions (trophic or otherwise) with the species in question.

  3. The variability in production of the resource in question and of the other key resources considered under (b), and some idea whether the present biomass is currently in the upper, middle or lower quartiles of the historical range.

Following the single species assessment therefore, should come a qualitative statement which puts the ‘ifs and buts’ around the numerical conclusions, so that the manager can make some judgement as to how applicable it may be, and for how long. This statement could draw upon a body of experience from outside the particular fishery in question, and one may suggest that it would not be premature to look retrospectively at the history of industrial fisheries over the last few decades: a cursory examination (e.g., Caddy and Gulland, 1983), may suggest that the “Theory of Catastrophes” rather than the concept of “population equilibrium” is a more applicable one in some cases!


Several of the earlier sections have dealt with ecosystem components and their characteristics, which may have led to the mistaken impression that the properties of an ecosystem are simply the sum of the properties of their individual components. This is not true, since there are “emergent properties” of ecosystems which cannot be forseen from those of the individual components. Thus, on the most practical level, the multispecies yield from a system is significantly less than the sum of the maximum yields of the individual species if harvested alone. Mann (1982) notes that static diagrams of food webs, particularly compartment models, are doomed to failure as quantitative predictors, largely because the emergent properties of such systems are not revealed, although these diagrams still remain useful descriptors of how food and energy flows through the system.

This leads to consideration of the main alternative approach; namely the application of empirical approaches to marine ecosystem assessment. We could look for example, for a marine equivalent of the morphoedaphic index (Figure 70); which estimates freshwater fish production in lakes as a function of easily measured physical factors. This of course has two major problems: the first being that marine systems are all ‘open ended’ to varying degrees; the second, that changes in the ‘state’ of the subsystem concerned on which the index is based, throw the time series of catch and environmental information out of gear forcing a re - examination of underlying structural questions.

Figure 70

Figure 70 Predicted yield curves as functions of the morphoedaphic index for sets of natural lakes in six of the world's climatic zones (Adapted from Henderson, Ryder and Kudhongania, 1973)

A variety of ecologists have addressed emergent properties of ecosystems, and although perhaps the most fundamental law of ecology is that the more sweeping the generalization, the more exceptions to it will be found, the following perspectives are offered which will hopefully prove useful in discussing responses at the ecosystem level.

One place to start is with the statement of Margalef (1978) who suggested that “all or most of the ways in which man interferes with the rest of nature produce coincident or parallel effects”… .....“diversity is reduced and the ratio of production/iomass is increased”. If this is true, it certainly makes for a simplification of many apparently diverse problems, and the idea has been developed further in what appears to be a new field, namely “stress ecology” (Barrett, Van Dyne and Odum, 1976). Some of the basic concepts and terminologies used here (Rapport, Regier and Hutchinson, 1985) derive from work on the response of individual organisms to stress; which although not a precise term in this context, embraces the idea of a perturbation imposed on the system from the “nominal” state; presumably taking it away from an original “equilibrium” or “pseudo - equilibrium” state of the system, in the sense in which these terms are used in population dynamics. Rapport, Regier and Hutchinson (1985) point to the three stages postulated by Selye (1974) for the response of an individual organism, namely “an alarm reaction”, then a stage of “resistence to stress” and finally “exhaustion” or passive compliance with the stress, as having some parallels from a cybernetic point of view, at the ecosystem level (Figure 71).

Figure 71

Figure 71 Three phases of the general - adaptation syndrome in organisms: (A) alarm reaction; (B) stage of resistance; (C) stage of exhaustion (From Rapport, Regier and Hutchinson, 1985)

Five types of stresses seem to include most human impacts on ecological systems, which are not exclusive of human interference, since natural causes may produce similar effects:

  1. Harvesting

  2. Pollutant discharges, (perhaps distinguishing man - made toxins where this generalization does not apply, from pollution by natural organics)

  3. Changes of terrain, bathymetry, degree of shelter etc., (e.g., the effects of shoreline development, land reclamation, dredging and marine gravel extraction, etc.)

  4. Introduction of exotic species

  5. Devastating events (hurricanes, oil spills, coastal pollution, etc; (but see (2))

Under (5) the above authors include wars as well as natural catastrophes: (it may be noted here in passing however, that our best information on the rate of recovery of fisheries systems from stress, which has led to much current population dynamics theory, came as a result of the virtual cessation of fishing in the N.E. Atlantic during two world wars). The importance of degradation of the marine environment (pollution) by human activities is reviewed, e.g., in Anderson, 1981.

The diagnostic changes for ecosystem stress recognized by Rapport, Regier and Hutchinson (1985) included:

  1. an increase in the rate of loss of nutrients from the system (i.e., partial break down of the dissipation structure or food web),

  2. changes in primary productivity (as noted in upwelling zones, or when increased leaching of sediments and fertilizers takes place into coastal zones from agricultural development),

  3. increase in production/biomass ratios,

  4. decreases in species diversity,

  5. retrogression. This is defined as a shift in species composition to those organisms best adapted to new and more difficult environmental conditions; in our context, to short-lived r - selected organisms, as noted earlier. (If regarded from the point of view of ecological succession and the concept of climax in biological communities, this would imply a movement to “less mature” communities),

  6. changes in size composition, often towards smaller mean sizes and shorter life spans: again, consistent with the shorter life span of r - selected species, and the higher P/B ratio mentioned in (3). (In the contrary sense however, the failure of recruitment may lead to an increase in mean size becoming an index of population stress),

  7. other signs of distress, such as the “biological distress syndrome” may occur, and could include all of the above, plus disease, changes in growth rates, and mass mortalities.

In fisheries, changes in the ratio searching/fishing time (e.g., Condrey, 1984), or in the number and location of spawning areas, may all be indicators of stressed conditions or changes in population size, distribution and abundance. The disappearance or progressive rarity of indicator species for unstressed systems, and their replacement by parallel more resistent species, may be another type of “alarm reaction” as mentioned above. These changes may also show up on the local fish market as increases in the relative price of popular (stressed) species and their replacement by alternative (formerly low grade species); again suggestive of ecosystem changes, although here changes in trade or consumption patterns may be the causative agents of higher exploitation.

Perhaps the least optimistic but quite realistic view of the potential use of current approaches to modelling trophic interactions, is that expressed by Gulland and Garcia (1984), who note in relation to the question of interaction and stability in multispecies fisheries, that although these matters deserve increased practical and theoretical attention, the theoretical studies have done little so far except “open the door on a complex image of interrelated problems”. A similar view was expressed by Sainsbury (1982), who after a comprehensive review of mathematical modelling approaches up to and including the ICLARM/CSIRO Workshop in 1981, concluded that “close examination of ecological and fishery theory indicates that at, present there is no ecologically adequate model of community dynamics, and that no “coherent body of methods and rules” which might be applied to management of tropical multispecies fisheries is apparent in the approaches he reviewed. As we have noted, to some extent the complexity of the subject results from the scientific approach adopted by the academic world, which places a high priority on innovative as opposed to synthetic activities: given that as was pointed out by Kuhn, and well exemplified by ecological theory, science consists of a series of separate disciplines each of which vie competitively in the literature, and for funds in the “scientific market place”.

Despite the pessimistic view expressed above as to of the possibilities in the near future of producing a generalized multispecies model, (which is itself an overambitious project given the wide diversity of multispecies fisheries see e.g., Pauly and Murphy (1982), Gulland and Garcia (1984) for examples); this does not imply that a concentrated approach to understanding one particular fishery will not meet with a degree of success. What we have tried to do in this review, is to illustrate some of the ideas and concepts that might be considered in such an approach. Quite evidently however, multispecies systems cannot be tackled with any degree of success unless a significant commitment is made; ideally on a broad cooperative basis.

Thus, although there are no simple recipes for success, there seem to be some general guidelines for viewing a multispecies fisheries system in an objective way that may prove useful in a given situation, even though a fixed plan of action that applies in all circumstances is not possible.

  1. The first suggestion we have is that an attempt be made to categorize the main assemblages or communities present, (separating resident species from transients), and map them on a chart of the fishing grounds. Even if this is done on a very preliminary basis, it illustrates the spatial relationships of these assemblages to the main fishing ports, and can be the basis for a fisheries statistics system that attempts to the extent possible, to determine the removals from each fishing area separately. Satellite imaging now provides a rapid approach to characterizing coastal zones, water masses and local areas of high production, and can help in this process.

  2. Where possible, the historical data base for the fishery, including ancedotal information from fishermen as well as from searches of the available literature, should help establish files for the key species, their habits, trophic interrelationships and life cycles. The occurrence of major changes in abundance and species dominance in the past, (even if qualitative), should be documented; together with area - specific information on fishing effort, fleet size, fishing grounds and past removals, and such historical data as are available on catch rate and size composition.

  3. Where possible also, without making this a major program in manpower - limited situations, limited observations on stomach contents of key commercial species of known sizes, seasons and areas, may be collected in order to build up some idea of species interactions in the system.

  4. One key aspect of the application of ecological concerns to fisheries problems, is the identification of the major sources of biological production, and the areas where these centres are located in relation to human activities.

  5. One tentative suggestion that arises in this regard, is that an attempt be made to map critical habitats and the centres for ecosystem “dissipation structures”, in the manner portrayed on the cover of this report, with a view to assigning a high priority to their conservation, even if the details of food web interactions are not yet resolved. This type of action may be regarded as preserving the ‘options for the future’, when the necessary fisheries ecological studies have been carried out.

Strategies of harvesting multispecies ecosystems

The estimates of total fish production based on commercial yield statistics, are probably underestimates of the potential yield which would result if the fishery were exploited with the balanced diversity of gears needed to evoke the highest yield (Marten and Polovina, 1982). What strategy is implied by this statement?

In theory, a food web could be maintained ‘in balance’ by fishing each component in proportion to the rate of natural predation it is subjected to.

This ‘utopian’ strategy for exploiting a food web might be considered as equivalent to satisfying the requirement:

i.e., a constant proportion of the total production pi = MiBi for species i = 1, 2, 3 … n is removed as yield (Yi), where Mi is the natural mortality rate, and Bi the biomass. This can be shown to be equivalent to setting the ratio Fi/Mi at some constant level for each species, in what is effectively a form of effort control by species.

As for any simplistic scheme, a number of serious objections can be raised as to its practicality:

How could you measure all the parameters accurately, let alone control the species - specific rates of fishing?

What would be the ‘safe’ levels of Fi/Mi to use?

Caddy and Csirke (1983) show that FMSY/M values in the literature vary widely, and that larger values well below 1, and even as low as 0.33 for some species groups, would seem appropriate from the limited parameter sets available.

It is obviously dangerous as we have seen, to assume that the abundance, or even nature of the components of a food web are constant: with too high an F/M ratio, species replacement would seem a distinct possibility, especially since when mean sizes of food web components change, this changes the effective position of a species in the food web, and makes surplus food organisms available for colonization of the ecosystem by a ‘new’ predator or species group.

Since many larger species of marine fish pass through sequential trophic levels in their life history, the idea that we can increases the total production of the system by removing the top predators, and then harvesting the ‘forage’ species lower down in the food web more intensively for greater yields, does not seem to work in practice in most cases.

It appears (e.g., Regier and Henderson, 1973, Ursin, 1982) that as fishing increases on a dominant or apex predator, its role as a controlling agent is replaced, at least in part, by the next predator down; the older individuals of which are able to move into a higher trophic category than formerly. Certainly, experience in large lakes (Regier and Loftus, 1972) shows that cropping the large predators may increase yield by less than 100%, as opposed to the 5–10 fold increases predicted by laboratory experiments assuming a fixed fish dietary composition.

An alternative strategy of fishing all species indiscriminately by broad - spectrum fishery gear such as trawls, should favour broad niche, opportunistic species with high fecundity. It seems clear from experience however, that the response of the system to fishing is less easy to predict, given that fishing as an economic activity may depend for its success on which of two “broad - spectrum” predators is favoured: the lower valued sculpins or the higher valued cod - like fishes?

Pauly (1979) summarized some of these “food web management options” in a semi - humorous form, among which the following frequently occur in the real world, and some of which, at least implicitly, have been referred to earlier. Using Pauly's descriptive titles, a selection of these are:

  1. The “Null” strategy:

    Here the resource is left in a virgin state.

  2. The “Tuna” strategy:

    Basically, this is the strategy of skimming off the MSY from the peak predators by fishing methods selective for large fish. As noted earlier, by May et al. (1979), such a strategy, though not providing the maximum ecosystem yield, is sustainable.

  3. The “North Sea” strategy:

    Pauly (1979) characterizes this strategy as the systematic overexploitation of peak predators until predation on prey species becomes negligible. This should lead to an increase in prey species biomass to a maximum; (see however Ursin's hypothesis!), but this is prevented by then fishing the prey species; thus transferring their production to fish catch. This may be the most productive strategy in northern latitudes where there are larger number of generalized feeders, and may even be sustainable in those areas.

  4. Gulf of Thailand strategy:

    This consists of fishing both predators and prey with very small mesh gear at high effort levels. In the final analysis, this results in collapse of both predator and prey stocks, and increases in plankton and benthic biomass, and of certain generalized, rapidly - reproducing r - selected species, such as squid and small flatfish.

Other variants may be considered, but these last three strategies in some ways span most of the feasible spectrum, with the addition of the “Null strategy” which strangely enough is practical in association with one of the others, namely, the preservation of part of the virgin ecosystem intact by means of Marine Parks or Reserves, particularly for critical habitats.

In a previous section, we have postulated one further strategy namely the “Utopian” strategy, which would seek to balance overall exploitation, by selective fishing of all food web components so that the multispecies balance is preserved. Perhaps the Japanese inshore fishery is closest to a real - world example of this, where a tradition exists of using a much wider spectrum of marine products then in some other parts of the world. This may prove a useful concept to keep in mind when discussing alternatives for multispecies management.

In the real world, a mixture of strategies may be the best approach. For example, a combination of (1) and (3) or or (1) and (4) might be considered, where some critical habitats are entirely closed to fishing, or at least closed on a seasonal basis.

In attempting to compare the feasibility of ecosystem manipulation (or the vulnerability of ecosystems to change), there is a strong temptation for open sea ecosystems to place the various types of interventions we have discussed in the following order, by feasibility and impact:

Feasibility Type of manipulation Vulnerability
High- Impacts that affect critical habitats High
High- Impacts on ‘substrate’ speciesHigh
Medium- Impacts that affect major sources of biological production (dissipation structures)Medium
Low-High- Introduction of disease vectors and exotics(Depends on the situation)
MediumPredator controMedium
LowControl of competitorsLow
LowControl of prey speciesLow

The above order of feasibility contains a high degree of subjectivity with obvious exceptions, but is based on the conclusion that single species manipulations, with the exception of exotics, whose introduction in some marine ecosystems has had dramatic (and usually adverse effects), are more uncertain in their effectiveness than manipulation of critical habitats, and of substrate species (e.g., coral reefs, mangroves and grassbeds). By the same token, it is considered that habitat protection or habitat improvement is more likely to be effective in marine ecosystem management than direct intervention in food webs by single - species control of the type mentioned lower in the above list. Critical habitat protection has the further advantage that it requires less detailed knowledge of species interactions, and at least preserves the options for future more sophisticated interventions in the food web that may appear feasible in the future.


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