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PART II(Continued)


We have already described the pelagic environment as a dynamic, contagiously aggregated, system which reflects diurnal, seasonal as well as historical processes. It is perhaps reasonable to consider the upper actively migratory component of this oceanic food web as system “integrators”. They smooth out the discontinuities in biomass by travelling relatively quickly between abundance centres, harvesting these, and thereby reducing them in abundance to a lower “background level”. Any location which is a seasonal feeding ground for migratory or nomadic predators with temporary peaks in abundance of forage species, is “smoothed” to a great degree by these visits, leaving “growing room” for all levels of the food web.

The concept of “steady - state” interactions of species in any food web could only persist if the many fluxes of material between the different components by death, emigration, growth and recruitment all balance each other out, and continue to do so in the face of human harvesting. We have already seen that reproduction or survival success is not only seasonal but annually variable in most species, and that there is little evidence for a general coordination or synchrony between spawning success of food web components. Because of this, any attempt to try and “balance” the production and consumption terms for a food web are unlikely to be fully successful, but this does not reduce the value of such a diagrammatic representation as a clue to possible dynamic interactions.

We might infer that the majority of individuals that reach large sizes in tropical systems do not come up against the kinds of food limitations imposed at higher latitudes by strong seasonal cycles of primary production, where toward the end of each winter, the available food is low, and hence growth is slowed or stopped. In the tropical habitat however, despite the continuous trophic productivity and the continuous grazing on it, quasi-steady population growth of prey with sporadic or continuous reproduction, is associated with patchy prey distributioin and higher metabolic rates. Continuous recruitment to prey sizes occurs, which could ideally promote continuing and relatively rapid growth for higher predators. These may need to be highly mobile, however, to satisfy their energy needs, especially in oceanic waters, due to the relatively low densities of suitable prey sizes in many time-area strata.

In the higher latitudes the larger predators, e.g., cod, tend to disperse after the main production bloom is past, possibly simply to facilitate search and feeding outside the main centres of production. Fishes in higher latitudes tend to overwinter in near torpid states, with metabolism minimized through temperature effects. Many species select low temperatures sites for overwintering.

What is clear is the contrast between the seasonal speed - up and slow - down cycles of high latitude ecosystems, and the continuous rapid turnover of tropical systems. Whereas higher latitude predator - prey interactions have been given a lot of attention (Anderson and Ursin, 1977; Ursin, 1982), the tropical pelagic system has only recently begun to be studied in a similar fashion.

Recent studies of feeding of tropical tunas by Olson (1982) have begun to better formulate the problems and possible interactions of higher predators and their prey in the tropical pelagic-oceanic environment. Recognising that there have been several attempts to study these processes qualitatively in tuna ecology (Blackburn, 1968; Williams, 1966; Magnuson and Heitz, 1971), it is satisfying to see the increased utility of this information, once quantitative information on the items consumed becomes available.

Figure 57

Figure 57 Generalization of interspecific and intraspecific feedback mechanisms (predation and cannibalism) for density-dependent population control in upwelling systems

For example, yellowfin tuna are opportunistic predators which reside in the upper thermocline and mixed layer of the tropical oceans of the world. From rough approximations of their level of activity (especially swimming, growth and background metabolism), Sharp and Francis (1976) estimated that an individual yellowfin tuna (of 85 cm body length: 12.1 kg body weight), expends only 9.5 percent of its consumption energy on growth, and 19 percent on background metabolism. About 71.5 percent of food energy is expended in swimming.

Olson (1982) has followed up on this study by examining yellowfin tuna stomach contents, their calorific values, and evacuation times. Olson used an Index of Relative Importance (IRI) in integrating information on frequency (F), volume or weight (W) and number (N) of food items in the stomach, where IRI = (%N + %W)%F (Figure 58).

A methodology still commonly used today in estimating daily food intake is based on work by Bajkov (1935). In Bajkov's method the amount of food eaten during some time interval is determined by measuring the amount of food in the stomach at the beginning and end of the interval, and correcting for the amount evacuated from the stomach during the same interval. Bajkov (1935) assumed that fish feed continuously and that gastric evacuation rate is linear and constant for all types of food consumed, and suggested that the daily meal (1) be given by D = 24 A/n, where A = mean amount of food in the stomach and n is the number of hours to complete stomach evacuation. Numerous workers have since established that the rate of gastric evacuation in fishes more often fits an exponential model, and that it is significantly affected by changes in food type and food particle size (Elliot and Persson, 1978; Windele, 1978; Fange and Grove, 1979). Eggers (1977) and Elliott and Persson (1978) show mathematically that substituting an instantaneous gastric evacuation rate “yields a correct and robust estimator” of the daily meal. If frequent stomach samples are taken over the entire day in order to detect any diel periodicity in feeding activity, and the amounts of food in the stomachs at the beginning and end of the 24 - hour period are equal (Elliott and Persson, 1978; Eggers, 1977), then the daily meal D is given by:

D = 24AiRi

where A is the average amount of food species i in all stomach samples, and R is the instantaneous gastric evacuation rate per hour for food species i. Since yellowfin tuna are presumed to feed only during daylight hours (Reintjes and King, 1953; Schaefer, Broadhead and Orange, 1963), stomach samples from purse seine caught fish may be used for this analysis. Assuming daylight feeding, this would only change the above equation to the following:

D = 12AiRi

Olson points out that different types of food organisms may be digested and evacuated at quite different rates, and that it is desirable that gastric evacuation rates of a representative variety of natural food organisms be measured in the laboratory if the quantitative rates of food consumption are to be estimated, which is essential for studies of energetics.

Such measurements were made on captive yellowfin tuna, and the weight of stomach converted to calories (the calories per gram of the various food items being either determined by bomb calorimetry, or taken from the literature). A wide range of calories per stomach content was found in yellowfin at any given fork length. Estimated daily meals ranged from 0 to about 480, 2 600, 5 600 and 17 000 Kcal/day in age - classes, 1,2,3 and 4+ years, respectively.

These daily consumption figures are considered underestimates since they are based on the amount of food found in tuna stomachs after the fish had been enclosed in a purse seine for a number of hours, frozen aboard the vessel, partially or completely thawed prior to unloading, then sampled, refrozen, thawed and examined. These processes and an unknown rate of regurgitation prior to death would reduce the volume of food found in the stomach samples below that found in freshly-caught fish. Therefore, the true daily meal sizes are undoubtedly greater; but how much greater is unknown.

Although the daily meal estimates based on stomach samples are quite low, Olson used them to derive purposely conservative estimates of prey biomass consumed by yellowfin. The calories eaten per day were converted back to grams of food, and daily meal values shown separately for different age - classes in Table 11. The estimated total prey biomass eaten per fish - day was then partitioned by prey type based on the relative proportions in which they occurred in the 1970 stomach samples. These preliminary estimates suggest that a yellowfin in the 4+ age - class may eat at least 730g of frigate tunas (7.3 individuals of 20 cm average size), 440 g of nomeids (146 individuals of 3 g average weight) and about 233 g of other prey per day. Yellowfin in age-class 3 appear to eat an average of at least 235 g of frigate tunas (2.4 individuals), 100 g of nomeids (33 individuals) and about 125 g of other prey per day. Fish in age - class 2 eat at least 80 g of frigate tunas per day on the average (Figure 58).

Table 11
Estimates of prey biomass eaten by the CYRA (Commission Yellowfin Regulation Area) yellowfin tuna population per day and per year in 1970 derived by multiplying daily meal (prey biomass consumed per fish - day) by the number of individuals in four age - classes estimated by cohort analysis
 Age group
Prey biomass eaten fish-1 day-1(g)887304611 403 
Number of individuals in CYRA (Sharp and Francis 1976)31 731 10014 257 7306 406 0503 661 63056 056 510
Scombridae 1 1611 5052 6865 352
Gonostomatidae (Vinciguerria lucetia)1 2214261221801 949
Nomeids (Cubiceps sp.) 3526491 6082 599
Cephalopoda (squids, octopus, argonauts)1 151372197881 808
Exocoetidae (flying fishes)87346239179851
Pleuroncodes planipes (red crabs)264155113102634
|Unidentified fishes 757588238
Balistidae (trigger fishes)  216990
Total prey biomass eaten/day (in t)2 7922 9172 9525 13813 799
Prey biomass eaten/day (in '000 t)1 0191 0651 0771 8755 036

An important caveat needs to be added here. This data set and analysis are based on mean stomach contents assumed to be maintained over a 24 hour feeding period. We do not know what the relative proportion of feeding is between night and day for this species, but feeding rate is likely be less at night than that determined from these daytime collections. In this case, the proportional daily consumption rates would be less than those presented. However, if maximum rations at each size grouping are used, (all stomachs as full as the fullest in each size class), Olson (personal communication) estimates that the four size groups would consume 16.0%; 15.7%; 19.0%; and 16.7%; per day using the 12 hour feeding model and 32.0%; 31.3%; 38.0%; and 35.5% per day using a 24 hour feeding model. The 12 - hour rations model corresponds exactly to the results of feeding experiments by Magnuson (1969) in which skipjack tuna were offered food ad libitum over 12 - hour periods. Olson remarks:

“One can begin to get a feel for the tremendous numbers of frigate tunas (Auxis sp.) that are consumed by the entire yellowfin population”. Some rough estimates were made of food consumed by the yellowfin population of the Commission Yellowfin Regulatory Area (CYRA) in 1970 (Table 11). The per - individual biomass consumption estimates were multiplied by the number of individual yellowfin in each age - class in the CYRA as calculated by cohort analysis (Sharp and Francis, 1976). These estimates indicate that at least 13 799 metric tons of food were eaten per day by the population: 5 352 metric tons of which were frigate tunas (= about 53.5 million individuals). A total of at least 5 million metric tons of food were consumed during the year, about 2 million tons of which were frigate tunas. Again, these are undoubtedly underestimates of the tremendous numbers of Auxis consumed by yellowfin tuna annually.

Figure 58

Figure 58 Showing relative proportions of different food items in the stomach contents of yellowfin tuna in the eastern Pacific (From Olson, 1982)

The significant new insight into tuna energetics gained through detailed analyses of this type is that:

  1. yellowfin have an overall ecological efficiency (biomass consumed to biomass growth) of about 0.15 percent, due to their extremely expensive method of locomotion (Sharp, 1983);

  2. the amount of food consumed by tuna (and hence the production, and even the standing stock of prey) must be very high. This also has serious implications for the real levels of production in offshore areas, which may have been significantly underestimated.

Of course, all of this needs to be kept in perspective. In a related approach Sharp and Dotson (1977) used fat content measurements and hydrodynamic experiments to determine that the flux in fat content in albacore could be accounted for by the energy expended in “directional migration” alone, while any day - to - day activities would be accounted for within the daily diet and energy conversion.

The question of resident versus migrant components has been bothersome in studies on many widely distributed resources. Fat content and growth rates can be useful in identifying new migrants, i.e., what proportion of available fish at any one time might be entering grazing/fishing areas. Values for fat content ranging from 2 to about 18 percent of total body weight have been measured in albacore (Dotson, 1978; Sharp and Dotson 1977), indicating the dynamic nature of fat reserves, and perhaps also the mosaic nature of populations. Coastal fish of 63 cm average length had lost an average of 404 g of fat on entry to the fishery compared to fish of the same size sampled about 1 000 nautical miles offshore prior to the commencement of the coastal fishery. Two weeks after their initial arrival on the coast, fish of similar size were sampled again in the coastal fishery and their fat content was back in the range of the offshore material. These observations obviously fit well with the role of highly mobile predators as large system integrators.

The above account can be compared with a similar and equally interesting series of studies on larval fish swimming energetics. Vlymen (1974, 1977) showed that Engraulis mordax (California anchovy) larvae have a relatively high proportional expenditure of their total respiration due to swimming, i.e., 24.6 percent under average activity level conditions for a 1.4 cm larvae. Smaller anchovy larvae are less efficient due to their sporadic swimming behaviour, but efficiency increases as they grow larger and settle into their pump - and - glide mode of swimming.

Vlymen's (1977) analysis of food microdistributions, growth and behaviour for anchovy larvae illustrates immediately the relevance of scales of turbulence and other oceanographic discontinuities to survival of larval fishes. (These concepts are further examined in IOC Workshop Report No. 28). There are discontinuities and contagion of particles and organisms in the marine environment (Sheldon and Parsons, 1967; Sheldon, Prakash and Sutcliffe, 1972; Platt and Denman, 1975, 1977; Owen, 1980), which have profound effects on local processes, and particularly on local abundance of the primary through tertiary predators some time after the initial bloom in primary production has occurred (Sharp, 1981b). In general, the scale of events in space and in time in food webs in the ocean are correlated (Figure 59; Carlenton, 1985). The relative energetic efficiency of the more mobile, secondary and tertiary predators, e.g. the tropical tunas, which search for one bloom of prey species after another, is far lower than for larval fishes, or even for adult neritic fishes. This is shown for example, by Sharp (1983), Sharp and Dotson (1977), and Sharp and Francis (1976).

Figure 59

Figure 59 Scale relations in the pelagic environment among phytoplankton (P), zooplankton (Z), and most adult fishes (F) (Redrawn from Carlenton, 1985)

In reviewing the topic of energetic interactions with the intention of adding ammunition to the stockpile of fishery tools, it became clear that there are several semi - mythological concepts in fishery science which need scrutiny, particularly in relation to predator - prey effects.

One of the first of these is the assumption that harvesting the adults of species A will a priori make room for more younger, faster-growing, more productive members of the same species. This tenet will not always prove to be correct, and stems from the concept of “carrying capacity” inherent in most ecological and fishery population models. This assumes a finite biomass of individuals of a given species can be supported by the environment. This situation is only approximated when either a stable age distribution, hence fixed requirements exist, or when the population is comprised of identical individuals, e.g., single cells in a stable, nutrient - rich environment. These assumptions may be incorrect for fish populations in nature due to the behavioural and energetic discrepancies between the various species and size/age groups of most fish. Adults are rarely in direct competition with juvenile or earlier stages, and may occupy different loci in the food web. Except for scombrids which do not exhibit such features as a gas bladder or fat deposition, e.g. Katsuwanus and Euthynnus, and hence have higher energetic requirements with increased size, fish growing to large sizes, i.e., over 10 kg, may actually be more ecologically efficient than smaller individuals. The more usual case however, is that any vacuum resulting from harvesting species A will be filled by another species, let's say species B, with higher reproductive capacity, faster growth, and a generally more efficient energetic turnover rate, i.e., more ecologically efficient.

These comments of course beg the issue as to just what the “carrying capacity” limiting the size of any species might be. It might only be reached in the adult stages during periods of low or zero fishing, and extremely high abundance. The more usual “population limitations” may however be fixed by the available “survival habitat” for larval fish. In most years the carrying capacity (K) for the species may simply have no sensible adult limit, or may severely constrain only the larval or early juvenile stages, such that fishing the adults has little substantial impact on changing population productivity.

The assumption often employed in simple single species fishery models, that fish species live in a biological vacuum with few or no effects on other species of relevance to management, is less easy to make nowadays. Fluctuations of stock size noted for predatory, migratory species such as bonitos (Sarda species), mackerels (Scomber species), barracudas(Sphyraena species) certainly mean that there may be major fluctuations in natural mortality of their prey species, at all size and life history stages.

This brings us back to the yellowfin and Auxis puzzle described by Olson (1982) and Sharp (1983a).

As an example of potential predator feedback effects in oceanic systems, the studies of Olson (1982) show that for the year 1970, the exploited yellowfin tuna in the eastern Pacific Ocean consumed at a minimum 13 800 t of forage per day, comprising about 2 000 t each Vinciguerria sp. and cephalopod species, over 2 500 t of nomeids and over 5 300 t per day of another tuna, namely Auxis species. The Auxis alone represents about 2 million tons per year of a major oceanic predator consumed by the exploited yellowfin population, (this is equivalent to the entire tuna harvest by man every year). The Auxis biomass is likely to be of the order of 5 million tons or more in the eastern Pacific, and harvesting yellowfin leaves an additional million tons in the ecosystem to be eaten, or to eat other species. Auxis are certainly among the more voracious and ecologically inefficient of the scombrids, consuming well over 20 percent of their biomass per day. so that we can perhaps expect as much as 70 million metric tons of scombrid food to be consumed by the extra Auxis surviving to forage, due to the yellowfin harvest (this is largely equivalent to man's total annual harvest from the seas: FAO, 1984). Since Auxis are suspected to be cannibalistic and/or eat yellowfin tuna larvae or juveniles, we might reflect on the impact of feed - back loops between Auxis and T. albacares populations due to man's removals of adult yellowfin tunas: paradoxically, harvesting T. albacares should result in a reduction of its recruitment because of better survival of Auxis!

Auxis are indeed capable of preying on larval yellowfin, but their feeding habits in the eastern Pacific have not yet been studied. Yokota et al. (1961) examined stomachs of 30 Auxis thazard caught in Japanese waters in 1959 and found that their diet included young Auxis and skipjack tuna. Squid are also described by Arnold (1979) as “voracious predators feeding when young on macroplankton and subsequently on small fish.” Hurley (1976) theorises that larval squid are probably important predators of larval fishes. We should begin looking at the feeding habits of these important members of the pelagic food chain leading to the tunas in order to identify the possible predator - prey relationships that are so important to natural population fluctuations (Olson, 1982); (see also Caddy, 1983 for details of cephalopod interactions).

Probably more important is the fact that Auxis efficiency as a converter of food energy into biomass, is even lower than for the yellowfin tuna discussed in an earlier section. This suggests that besides lowering the mean size of predators in the eastern Pacific by intensively harvesting the larger yellowfin tuna, man may also be decreasing the overall production of desirable species like yellowfin tuna by shifting the ecosystem to a more “dissipative” mode, and therefore to less ecologically efficient species such as Auxis. whether this fundamental conundrum can be solved in practise, and Auxis, (or Vinciguerria, nomeids or cephalopoda for that matter), can be harvested, is another question. It Is obvious that major resource biomasses exist, and may even have Increased In size since harvesting the high value tunas began, but it is also evident that the energy used in harvesting these smaller species would be far higher, and their potential for marketing less promising than for tunas.

Perhaps one of the most fundamental changes in recent years in our perception of the application of food webs to commercial fisheries, is the realization that although the biological productivity of marine environments is higher than previously estimated due to the role of smaller photosynthetic cells (cyanobacteria), whose abundance has not previously been measured by oceanographers, a significant part of the energy of the food web passes through components not usable by fisheries, e.g., through “jelly” organisms such as Salps and Medusae. These gelatinous predators are not adequately represented in most sampling gears, and are quite capable of absorbing, without dramatic changes, the food energy no longer used by seriously depleted commercial stocks of smaller pelagic fish.

Together with the importance of recycling of energy by e.g. detritivores, this reinforces the conclusion that food webs centred on commercial species in nature as opposed to lab experiments, must be regarded as open ended or 'leaky', with the real possibility that even after the main linkages in the food web have been elucidated, some as yet undefined trophic linkages could be significant. It is also clear that new pathways in these food webs can become important as a result of interventions in the system.

The question of feed - back loops in marine ecosystems can only be addressed properly by sending readers to recent relevant literature. To summarize is to lose the subtle and remarkable nature of these processes. Perhaps the best point to start the survey is with the article by Ursin (1982), in which he examines the relative stability of marine ecosystems. He discovers that “triangular” food web subcomponents actually can be great stabilizing influences. These occur at all levels from unicellular or colonial predators, up through fishes, and illustrate that at each level in food webs, abundance of individual components is locally constrained. Some examples of these (from Ursin) are given in Figure 52. In the fisheries context, it is important to note that as the dominant predator is fished down, there is normally scope for the subdominant fish predator Co increase in size and (partially) replace it. This is one of the reasons why removing top predators has not resulted in the startling increases in yield of their forage fish predicted by simple food web models.

Figure 60

Figure 60 Triangular food - web components in marine ecology (After Ursin, 1982)

What is also evident from these triangular food webs components is the dominant impact of size in modelling food webs. (See Borgmann, 1983 and Figure 46).

Jones (1982; 1982a) considered the situation where individual organisms may find themselves located outside their “best” habitat and are subject to higher predation than the rest of the population: this provides some degree of feedback to compensate for short - term changes in relative abundance.

In functional terms, omnivory (here used in a more general sense, of the consumption of food from two or more trophic levels), should help to stabilize marine food webs. Here we are back considering the impact of predator biomass on their prey as overriding food limitations on predator biomass. Predator control might apply when predator biomass is large relative to prey biomass, but also if the predator is not totally dependent on one or two food organisms. Alternatively, the controlling Impact of prey biomass is likely to be greatest when the predator is an obligate feeder on the species in question. In their simplest form, these reciprocal effects are adequately modelled by developments of the Lotka - Volterra predator - prey cycles; e.g., Shiraklhara and Tanaka, 1981).

The problem of finding food efficiently when production shows seasonal peaks is solved in a number of ways: migratory feeding (moving from one peak prey density to another, which is temporarily and spatially segregated); opportunistic feeding (moving from one target prey species to another, depending on abundance), and omnivory (feeding on more than one trophic level and/or size range). Other alternatives are to feed intermittently (e.g., intertldal organisms), or to adapt to feeding on large meal sizes at low densities (e.g., deep water and abyssal species, which often can consume organisms of close to their own size), or to become commensal symbiotic or parasitic (e.g., remoras being carried by sharks from one meal to the next).

Another 'grand scale' ecosystem model other than that of Anderson and Ursin (1977) which is of general interest, is that being developed by Taivo Laevastu and associates (Laevastu and Favorite, 1980; Laevastu and Larkins, 1981), in which both environmental factors, fishing and predator - prey bookkeeping are attempted, and where population rates (of growth, mortality, etc.), are made functions of biomass change as opposed to changes in numbers as in cost population models (i.e., ponderal rates are defined). The magnitude of competition between man's harvests and fish consumption by other marine mammals, is one of several stimulating results of this approach, showing how conflicts of Interest arise as complex feed - back loops in marine systems. For example, efforts to rehabilitate marine mammal populations can only decrease the harvestable fish portion of the high latitude ecosystems for human consumption. Implying a societal choice. The physical principles are simple enough, but defining the desireable 'point of balance' from a socio-political point of view is much less so, and the various objectives need to be considered in toto, not just as separate, unrelated “problems”, each to be resolved by special interests.

Recognition of the complexity of interractlons in the sea can only help in ordering our thinking processes about what to expect from the sea In the way of a harvest from a system with continuously changing state variables. Ursin's “relative stability” does not imply steady - state thinking Is always more appropriate; it implies only that energy is not wasted.


Quite simply stated, the total productivity of an ecosystem is the sum of the productivities of the components. However, this statement in no obvious way simplifies the procedure of integrating trophic levels and their products in order to arrive at a single figure for the productivity of a given system. The problem lies in the differences in the efficiencies of the various inter - and intra - trophic level components, their distributions in time and space, the typical number of interactions that occur within the food web, and the life history pathways followed. The variable efficiencies of various trophic groups require first, a series of comparisons and contrasts of distributions, behaviours, and life histories.

To deal realistically with ecosystems one must recognize the inherent variety and plasticity of biological responses to physical - chemical perturbations. It seems unlikely, especially in the tropics, that the classical terrestrial concept of successlonal change can be uncritically applied, but each change in the system will be seized by one or more species as a one - time opportunity which will successively affect all future states. Fortunately this aspect of ecology is blessed with abundant recent reviews, and we therefore defer comments by recommending that those interested in:

  1. development of species diversity, consult Huston (1979);

  2. development of food webs, consult Odum (1968), Pomeroy (1974) and Place, Mann and Ulanowicz (1981); and

  3. biological adaptability and ecosystem stability, consult Conrad (1972, 1976) and Johnson (1981).

Ecological efficiency

Ecological efficiency is usually expressed in terms of the change of biomass of a species compared to the weight of biomass consumed. This can be calculated in terms of calories, dry weights, or wet weights.

The efficiency of any ecosystem component depends upon several factors:

  1. abundance and concentration of each component's food sources in relation to its own abundance and concentration;

  2. vulnerability of these food sources;

  3. work done to encounter (search for, or blunder into) and capture these food sources;

  4. proportions of food sources which are assimilated into useful energy, growth, and/or vital nutrients;

  5. the proportion of the assimilated food source available to each component for somatic or reproductive growth;

  6. the complexity of somatic organization of the organism itself.

Any individual component's energetic requirements, i.e., its utilization of energy or foodstuffs, can be described in this fashion:

I = M + G + E

where I is energy input in the form of light, proteins, carbohydrates, fats, which can often be monitored in the transfer of trace elements, nitrogen, carbon, oxygen, etc., depending upon the organisms or systems being studied;

where M is metabolic energy which may usefully be divided into numerous kinds of metabolic work resulting from internal biochemical conversion and leading ultimately to external work, displacement heat and simple turbulence remaining for a short period after an organism has expended work against gravity, or has moved. (Note: the same symbol M, is used by field biologists for Natural Mortality rate: illustrating yet again the lack of standardization of concepts between field and laboratory biologists);

where G is growth in terms of biomass, either of somatic or reproductive products, and is the only variable which can be either positive or negative; and

where E is excretion, secretion or sloughing off of biogenic materials, (e.g., crustacean exoskeletons).

The energy requirements for either optimal or maximal energy flow through an organism depend to a great degree on the system characteristics, particularly for fishes (poikilotherms). Temperature and available oxygen (also environmental carbon dioxide or hydrogen sulphide levels depending upon the organism), determine the respiratory limits of the majority of living aquatic forms. Although it is not our intention to discuss here questions relating to the field of physiological ecology, it is worth noting that the oxygen uptake or respiration of an ecosystem is a direct measure of its rate of biological production (McNeill and Lawton, 1970). In response to the variations encountered in these variables, diverse adaptations and specializations have evolved to assist or buffer against stress, such as elaborate respiratory surfaces, respiratory pigments, and biochemical/genetic and circulatory specializations. The abilities of organisms to persist in uncertain and stressful environments will have been determined by adaptations to environmental gradients, and to the patchy distributions of food organisms. The storage of excess energy in the form of carbohydrates (e.g., glycogen), plus lipids and proteins for use in metabolic work, increases the organisms' resilience to varying food availability, as well as fulfilling various stasis requirements; e.g., buoyancy increases with lipid content.

The importance of motility or mobility at different life history stages of the various food web components is rarely given adequate consideration. In fact, the relevance of time and distance scales of biophysical influences has only recently been given appropriate hierarchic place in the ecosystem framework (Fasham, 1980; Owen, 1980; Sharp, 1980a; 1980b). Simpson et al., 1979; Iles and Sinclair, 1982; Bakun and Parrish, 1980; Parrish, Nelson and Bakun, 1981). Perhaps the most informative place to start an evaluation of ecological efficiencies, is with an examination of energy expenditures on mobility with respect to size of organism. As noted already, this often though not always, relates to the organisms' trophic position.

From Rheinheimer's (1980) review of marine micro - organisms we find that many marine bacteria are flagellates. The typical marine bacterium has a temperature optimum within the range 18° -22°C, although a full range of optima exist including facultative psychophils with temperature optima as low as 0°C. Bacteria are usually aerobic but are facultatively anaerobic in most cases. There are few organic substrata from which they cannot derive nutrients, and inorganic compounds can also be utilized as energy sources by some. One important source of nutrients is the leakage or excretion of nutrients needed for bacterial growth from primary producers (phytoplankton) as well as from any other organism, living or dead. The activities of individual bacteria are restricted to small scales, but these are not major limiting factors in their distribution. Obviously, small particles are primarily dispersed by turbulent mixing at all scales, up to ocean - scale currents. This provides opportunities for bacteria to encounter “local” food sources, as well as making bacteria accessible to organisms that feed on them.

Bacteria are supreme opportunists, with among the highest potential conversion efficiencies possible: of the order of 50 to 60 percent. Marine bacterias are found in highest densities in coastal zones, and in sediments, where many benthic organisms directly depend upon them for nutrition. Copepods also other small crustacea (eg. lobster larvae) in the zooplankton feed in part on bacteria (Rheinheimer, 1980). Cycles of abundance and scarcity due to grazing are readily observed in bacterial, as in predator populations. Benthic cyanophytes are grazed by rotatoria, nematodes, crustaceans and others micro- and meiofauna, and planktonic cyanophytes are eaten by plankton and fish as supplements, but are of decreasing importance as the predators increase in size.

Many phytoplankton organisms are not motile, and therefore their survival is a strict function of the local conditions in which they find themselves, i.e., light, nitrogen and other essential nutrients, local turbulence and system level transport must be in acceptable ranges. In contrast, there are motile phytoplankton, (flagellates), and even some bacteria, which are theoretically capable of resisting turbulent dissipation or disruption at low energy levels. All of these species depend to a great extent upon system transport physics for their distribution, physiological requirements, and for encounters with their food in order to remain productive. In this sense they are very “efficient” as individuals, sampling a vast, uncertain volume, and do not need to dissipate large proportions of their metabolic energy in swimming, as do many species at higher trophic levels.

Larval fish and planktonic stages of other organisms may graze heavily on unicellular and colonial phytoplankters. Their conversion or production rates vary enormously, depending on species mobility (Theilacker and Dorsey, 1980), and on such factors as the distribution or contagion of appropriate food particles (Vlymen, 1970; Beyer, 1981; Beyer and Laurence, 1981). The quantification of productivity in fish populations is not dealt with easily in the larval through adult stages, since once the post - larvae and juvenile stages become mobile, they become very difficult to sample. Many larval fishes are also difficult to sample due to their cryptic or very dispersed distributions.

An interesting illustration of the importance of detrital recycling in the planktonic environment relates to the small crustacea making up such an important component of these systems. Lasker (1966) notes for the euphausid shrimp Euphausia pacifica, that moulting occurs every three-eight days depending on temperature, irrespective of the amount of food eaten. The contribution to detritus made by the molted exoskeleton is 10% of the animals (dry) body weight: i.e. equal to the average biomass of the euphausid population every fifty days: a figure of 1.5 g/m2 has been mentioned. Together with cast exoskeletons from other planktonic crustaceans, this component must form a significant share of the energy budget of detritivores, marine food chains, in addition to faecal material and food particles lost in ingestion.

There are many differences in modes and relative abilities of swimming in planktonic organisms, from passive drift, to near independence of local physical transport. For example, Vlymen (1970) calculated the proportional energy expenditures of Labidocera trispinosa, a calanoid copepod, due to vertical migratory behaviour, and to those short - burst accelerations characteristic of avoidance behaviour. The relative value of total expenditure of energy due to activity as a proportion of total respiration, is of the order of 0.1 to 0.3 percent. These incredible efficiencies are directly related to the high accelerations that copepods exhibit.

In a similar series of studies on larval fish swimming energetics, Vlymen (1974, 1977) showed that Engraulis mordax (California anchovy) larvae show a relatively higher proportional expenditure of their total respiration budget due to swimming; 24.6 percent under average activity level conditions for a 1.4 cm larvae. Weihs (1980) also showed that the reason that just-hatched Engraulid larvae swim in bursts of activity for the first few days, is that this is a more efficient mode for fish under 5 mm total length. Above this size, the pump-and-glide mode becomes more efficient if continuous swimming. However, the carangiform species, i.e., scombroids, are more efficient if they sustain continuous swimming motion than are the anguilliform fishes (eels), hence the different modes of swimming for engraulids and mackerels.

Vlymen's (1977) analysis of food microdistribution, growth and larval behaviour for anchovy larvae, brings one immediately to the relevance of scale, and disruptive turbulence phenomena on survival of larval fishes. As we have said, there are widespread discontinuities in distribution of particles and organisms in the marine environment (e.g., IOC Workshop Report No. 28. Sheldon and Parsons, 1967; Sheldon, Prakash and Sutcliffe, 1972; Platt and Denman, 1975, 1977; Owen, 1980). These have profound effects on local processes, and particularly on local abundance in the primary through tertiary predators some time after the initial bloom in primary production occurs (Sharp, 1980b). The relative energetic efficiency of the more mobile secondary and tertiary predators which search from one primary bloom to the next, is far less than for larval fishes, or even for adult neritic fishes.

Caloric conversion efficiencies will depend on the energy dissipated due to swimming, on the caloric or nutritional value of the food, and on the food distribution. Laboratory experiments on two Engraulis species show the adult efficiencies of caloric conversion to be about 12 percent (Hunter and Leong, 1981). These authors also discuss the proportion of this food which is partitioned among growth and reproduction by age classes of female northern anchovies. A condensed table is given below:

Table 12
Allocation of ration to growth and reproduction with age in the anchovy
Percent of RationRation

The growing proportion of food diverted to reproduction is generally associated of course, with the reduction in growth rate for most species approaching maturity. Large quantities of research data have been summarized by Brett and Grove (1979), Brett (1979) and Ricker (1979) on growth and physiological energetics in the laboratory and in controlled habitats (e.g., aquaculture). The “average observed” energy budget of fishes shown by Brett and Groves (Fig. 18, p. 337, 1979) is summarised as follows:

Table 13
Indicative values for marine fish of partition of energy ingested
Gross Energy Ingested100% 
Faeces 20%
Digestible Energy80% 
Non - faecal losses 7%
Metabolisable Energy73% 
Lost as heat 14%
Net Available Energy59% 
For Metabolic Maintenance 7%
Lost as heat 30%
Net available energy for Growth and Activity (the Conversion Efficiency):22 percent

Note that growth and activity components of metabolism are on the same line, since they are completely interrelated: (activity level determines growth for a given physical milieu and level of food consumption). The actual figure for efficiency, as noted elsewhere in this document, depends greatly on body size and activity level. Jones (1982) notes that efficiency of conversion of assimilated energy into body tissue (growth), is highest for juvenile stages, and decreases with size and age to close to zero for old fish. In general however, he suggests that for adult fish (of close to commercial size) the value of 10% due to Slobodkin (1961) may not be inappropriate.

Recent attempts to directly relate metabolism expenditures on activity to observed growth rates (Kerr, 1982) need to be re - examined in the light of what is now known on the relationship between swimming energetics and the non - uniform distribution of food resources. Whereas a fish with a passive feeding strategy (e.g., one held in the laboratory), responds positively to food presentation up to its satiation point, in nature continuously swimming fishes have to balance energy expended in moving between food patches, and to integrate the availability - vulnerability of their food resources in the environment as a whole (Vlymen, 1977; Sharp and Dotson, 1977; Sharp and Francis, 1976; Olson, 1982; Carey and Olson, 1982). Certainly, seasonal thermal and oxygen changes, long short - term variations in contagion and distribution of prey species, and the local density of competitor species determine the expenditure on activity, whereas growth and development of reproductive cells simply reflects the accumulation of energy above and beyond that required for metabolic maintenance and foraging. As a general evolutionary strategy, under conditions of stress, fish will also trade off energy used for somatic growth and that available for reproduction.

In nature, physiological parameters such as the rates of respiration, excretion, reproduction and growth in nature can only be taken as constants under prespecified conditions. To paraphrase Ricker (1979), it is unlikely that simple relationships exist between ingestion rates and subsequent growth or production for aquatic species. Data on growth should be collected and portrayed in the context of ambient conditions: temperature being the primary controlling variable. However, as we have just noted, the spatial distributions and abundances of food items and the work done by an organism to obtain them, are also important.

Although many general considerations have been summarized regarding costs of locomotion, particularly in fishes (Hoar and Randall, 1978; Webb, 1975), it is still an unusual paper which directly estimates “work done” as a variable in a close to natural context, rather than using literature or laboratory - derived estimates of these extremely variable energetic expenditures. Much more effort will be required before these variables can be realistically quantified, and what is intended in this chapter, is principally to provide an introduction to these important yet difficult - to - quantify, concepts.

Many, or even most organisms in the marine environment start life in the plankton, and sub-sequently make the transition with size into higher trophic levels. Although growth and capacity for persistence are overriding objectives among living organisms, at small time and distance scales, superior efficiency is needed to satisfy these energetic requirements, while being sufficiently abundant in a risky environment to be individually expendable.

The general relationship between size at reproduction and turnover time in the marine environment is a clear indication that despite wide variations in body size and form, behaviour, mobility and food preferences, certain energy limitations exist at each scale in order to ensure an organism's persistence and colonisation potential.

Developing from simple fission reproduction, and proceeding to encapsulation of larger embryos or live - bearing strategies, the evolutionary motivation for complexities in reproduction and life history, seems to be one of investing as much energy as necessary in order to place fertilized eggs into a “safe” nurturing environment (Alvarino, 1980; Sharp, 1980a; 1980b). Paraphrasing the chicken - egg truism, this is equivalent to defining an organism and its life strategy, as an egg's way of ensuring survival of another egg! In practical terms, reproductive strategies and adaptations appear to be geared toward optimizing either the numbers of eggs spawned into the immediate environment, or optimizing the selection of those larval or post - larval stages and life history characteristics which would give the best chance for the gametes to be placed into a less uncertain, more surely nurturing, situation. The elimination of (individually) high risk, by internal fertilization, is a solution which stabilises the environment of the embryo, and permits the young to enter the ecosystem at larger, apparently more secure sizes. The nurturing of young in the case of species exhibiting parental care, shifts the emphasis of natural selection from the developmental problems of short time and distance scales, i.e., those pertaining to the distribution of the eggs and larvae, to those pertaining to the adults. This would suggest that the energy spent per individual adult fish, might well be less in the highly evolved livebearing fishes or those exhibiting parental care than those producing millions of eggs and few survivors. However, numbers of young produced by live bearers are less numerous, (K - strategists) and this limits the rate of colonization of vacant environments. This is in sharp contrast to the situation for the highly fecund species with pelagic eggs (r - strategists). These differences in capabilities of pelagic larvae and liveborn young certainly sets the stage for very different environmental requirements of juveniles, as well as conditioning the very different selection pressures involved.

The oviparous species' eggs, like phytoplankton, are carried about by turbulence unless they are spawned on substrates, either floating, (as for flying fish Hirundichthys), or laid on bottom, e.g., herring (Clupea species), or are demersal, i.e., more dense than sea water, and sink close to the bottom where turbulence plays a more subtle role in their development. These latter types of eggs are from about 0.5 mm to 3.5 mm in size range, with pelagic eggs being about 1 mm in diameter. The larvae hatch after various times, depending primarily on temperature (Theilacker and Dorsey, 1980), and have from a few days to about ten days after hatching in which to use their yolk for further development. After the yolk is finished, they have from a few days to a week to locate food. The timing of hatching in relation to the availability of appropriate food and abundance of predators, is obviously critical (eg., Alvarino, 1980).

Parrish, Nelson and Bakun (1981) describe the zoogeographic discontinuities within the California current, leading to the various pelagic habitats, each with its local transport characteristics. Where offshore transport dominates, the major fish species do not have epipelagic eggs, but live bearers (e.g., Sebastes, and embiotocid species) are abundant, and species producing demersal eggs predominate. Wherever closed gyral systems occur, pelagic fishes with epipelagic eggs and larvae are found. Other, more migratory pelagic species appear seasonally, entering the coastal system in search of appropriate nursery areas. They then spawn, and depart. As seen from each organisms's own perspective of its habitat, the problems of transport of energy and materials into and out of local situations is one of mobility, or of scale of the habitat, for each of the various predators and their food components.

Plankton communities vary tremendously in relative motility, with motile forms ranging over kilometers in the course of periods of a week or less, but the basic dispersion of these groups is still related to the physical transport processes of the water column occupied.

The less mobile marine forms, small invertebrates, fish eggs and larvae and their forage, are known to carry on their interactions on the meter - day scale (Sharp, 1980a) whereas the more mobile post - transformation fishes explore kilometers over periods of days to weeks. Large, more widely-migratory (exploratory) species range over oceans on time scales of years, grazing down “local” abundances, i.e., smoothing out patches and adding or removing energy and materials, which are then transported or dissipated over very great distances. Each of these situations requires consideration when sampling the population or interpreting sample data from field or laboratory experiments.


Considerable progress has been made recently in our understanding of marine systems, and the reader is referred to texts such as Longhurst (1981), (Platt, Mann and Ulanowicz, 1981) for a description of recent thinking in biological oceanography. Some broad outlines and mechanisms underlying biological production in the ocean are evident, but as yet, the ability to make predictive statements on how much, of this production and in what form, is translated into fishery yield, is still limited. From an examination of the available information on landing trends for those fisheries with significantly long periods of historical catch data, Caddy and Gulland (1983) distinguished empirically between four classes of fish stocks:

  1. those for which steady - state assumptions seem to have applied for a significant period of time;

  2. cyclical fisheries characterized by fluctuations in landing of an apparently regular periodicity;

  3. those showing strong irregularities in landings from year to year; and

  4. fisheries characterised as spasmodic or transient. Obviously this classification is empirical, in that landing trends are affected both by “pulses” in fishing effort (Caddy, 1983) and by environmental factors per se, acting through fluctuations in recruitment success from year to year (see, eg., Holden, 1978 who documents these for one of the more stable marine areas, the North Sea).

The main point of interest here however, is that viewed in retrospect, the fisheries statistics of this century suggest that the species (and areas) where steady state assumptions appear to be valid are relatively limited in number extent and duration. Conversely, areas of high but irregular fish yields (eg., the upwelling off Peru, eg. Rasmusson, 1984) and the Kuroshio current, (Kondo, 1980, Kawasaki, 1980) are among the most productive of fishery areas. Strong long-term variations in hydrographic conditions, and hence in production levels and dominant species seem to be the norm, and the organisms present have accomodated their life cycles to this situation (Table 10). Needless to say, human fishing pressure and variations in exploitation patterns (e.g., Figure 61), can also significantly influence the species composition present even in these areas, but should be placed in their appropriate context of a variable ‘carrying capacity’ of the environment for the species in question.

The point can also be made that resource assessments, largely from a lack of suitable data over a long enough time period, have tended to make simplifying “equilibrium assumptions”over the medium - term period of 10 - 12 years. Multispecies interactions, and their perturbation by fishing and by processes beyond human control, are other factors that suggest caution be exerted in the uncritical application of equilibrium assumptions in single species stock evaluations, before the ecological and environmental context of the species in question has been considered.

Figure 61

Figure 61 Changes in percentage species composition of landings in the Senegalese trawl fishery. The arrows indicate the appearance of new targets in the fishery (From Gulland and Garcia, 1984)

In general, the relative ‘success’ of each generation of fish is determined by how well it satisfied a hierarchic series of the survival requirements characterizing each life history stage. The situation is complex, and Bakun et al. (1980) refer to the “just right” period as a “survival window”. In high latitudes the possibilities for massive completion of early life histories are framed by the short seasonal production cycle; the spring bloom. Nearly all species schedule the time of their periods of reproduction in relation to this bloom, and many species have homing mechanisms to help them locate ideal spawning conditions or locations. One result of this is that relatively few species have evolved to take advantage of these short term, localized constraints compared with the number of species found in tropical latitudes. This imposes no absolute limit to the potential productivity of high latitude systems however, since the lower ambient temperatures, less complex food webs, and longer - lived species with limited migrations tend to make high latitude systems ecologically more efficient than tropical systems, i.e., more biomass is produced per unit energy turned over.

The enormous productivity of for example, the Peru Current prior to the decline in the Peruvian anchoveta, can likely be attributed to the large size of the upwelling system, but also to the anchoveta's lower position in the food web compared to, for example, herrings or sardines. Without abundant anchoveta to consume the productivity of the Peru Current, the sardine bloom in Peru and Chile in the early 1980's only reached a small fraction of the biomass which the anchoveta attained in previous years. This can be explained in part as a consequence of the different positions each species holds in the food web, as well as by differences in ecological efficiency resulting from the different swimming modes employed by anchoveta and sardines respectively (Sharp, in press; Weihs, 1973; Ware, 1975, 1980). Ursin (1982) has suggested that since the decline of the anchoveta stock, there is reason to expect that invertebrate herbivores have taken up the “slack” left by the abscence of anchoveta, resulting in less energy available for commercially exploitable fishes. Both mechanisms seem likely to be acting together, and the above change in species dominance may reflect yet another variable: the poleward shift of the preferred habitat of small pelagics. (It is interesting to note, however, that by 1986, after a period of low effort exerted on anchoveta, during which more favourable conditions for population growth of this species were evident, there has been a significant recovery of the anchoveta stock.)

Until recently, preconceptions as to the stability of tropical multispecies systems have rarely been questioned, except in the context of the effects of overfishing. There are however several examples in upwelling areas of small pelagic fish (eg., Opisthonema and Cetengraulis) undergoing remarkable fluctuations in abundance off Central and South America and in Baja California under little or no fishing pressure, and similar observations have been made elsewhere (Troadec, Clark and Gulland, 1980). Spectacular changes in species dominance such as the explosion of Balistes stocks in the Gulf of Guinea (Figure 62) for example, may be related in part to overfishing of Sardinella, but other environmental factors also seem relevant.

Figure 62

Figure 62 Trends in anomalies in the trawl fishery, river output, plankton abundance, salinity anomalies, and fishery events in the Côte d'Ivoire in relation to the changes in species composition of the resource (Sardinella collapse, Balistes eruption) (From Gulland and Garcia, 1984)

In the case of coastal or shelf fisheries in the tropics, such as those in the South East Pacific, the numbers of species taken in any given location may be relatively large in contrast to the higher latitude coastal or shelf fisheries, but the variations between contiguous areas are also likely to be considerable in tropical areas due to the relatively more numerous species, and their smaller, mosaic - like distributions. The integration of catch for coastal species statistics over a large area would tend to smooth out these variations, and obscure the scale and patterns of local breeding populations, thus arguing for tropical coastal resources, for a high degree of regionalization of resource management.

Ecological measures of diversity and stability are usually defined for relatively small areas in terrestrial contexts also: with units of pattern having dimensions of metres to kilometers for e.g., grassland biomes, as opposed to tens to hundreds of kilometers for most high latitude fisheries management units (see review in Pielou 1969 for theory). Enumeration of species and population descriptions are ideally carried out over homogenous areas, and the portrayal of changes, or differences, should ideally be associated with habitat discontinuities. The major problems posed by the ‘remote sampling’ nature of most fisheries investigations (e.g., the “integration” of two or more fish communities in a single bottom trawl haul over several miles), makes this ideal sampling approach difficult to attain, but still important to have in mind when attempting to analyse results of such surveys.

In planning fisheries field investigations, insufficient weight may be given to financing overall survey and identification exercises, even though such a preliminary “mapping” of habitats, communities and resources, and analysis of the resulting information has been suggested (Caddy and Garcia, in press), as essential to stock assessment as well as, coastal resource planning and pollution impact studies. Such detailed investigations of the structure of marine communities have usually been confined to near - shore marine environments where much of the transfer of the methods of terrestrial ecology to marine science has occured. These investigations, especially of reef or outcrop areas (epifaunal or ‘live bottom’ communities), have suggested that the “fine structure” of bottom communities on the shallow shelf is of the same order of scale to terrestrial communities, as anyone who has swum over a coral reef can testify. This is not the case for level bottom infaunal communities of the shelf and deep ocean (see e.g., Thorson, 1957), although here also, ecological units of pattern are probably smaller than is apparent at first sight.

Measurements of stability and diversity are thus as sensitive to scale (time and space) as is their conceptualization. A study of communities with numerous migrant species will show stability when sampling is integrated over a year, whereas they will appear far less stable on the basis of monthly sampling. Choosing geographic coordinates in lieu of habitat characteristics for statistical boundaries can have a dramatic impact on the characterization of marine situations. The 1982–83 El Niño phenomenon has had marked affects on the fauna of coastal equatorial islands in the Pacific, with some species disappearing from atolls and reef communities completely due to changes in the wind field and subsequent current shifts. The coastal transition zones delimiting the tropical and subtropical waters had also shifted steadily poleward since about 1970 in the eastern Pacific (Sharp and Csirke, 1983). These changes would have confounded any geographically - based sampling or management system if the question was whether or not to limit catches of particular species in the transition zones. While stability - diversity studies on both Pacific islands, and at coastal sites on continental land masses, tend to show a phased disappearance of some species, with changing stability and diversity indices; sampling by large, fixed geographical units would not have told us the real tale of species displacement. Some stocks would have seemed to decline, and new stocks and species would have unexpectedly become abundant in other statistical areas, but movement of species boundaries would have been less evident. Such phenomena seem also to have occurred in West Africa in recent years.

Examples of major changes in abundance, distribution and species composition for neritic fisheries throughout the world are given in Sharp and Csirke (1983). Even though single fisheries tend to aggregate more than one stock and species into exploitation units which may or may not be single breeding populations, the instabilities of many neritic populations are quite evident from fishery data, both for so - called demersals and for pelagics. As noted earlier, the continuously stable population is a relatively rare case over historical time scales, and therefore ecological diversity will also be subject to changes in environments where unstable populations are fished. The aggregation of resource populations due to the mobility of the fishing fleet often obscures the true scale of spatio - temporal variability of these populations, and requires that fisheries data bases classify landings by area/time of origin rather than (the easier option), by boat and port of landing.

As we have suggested, the single - year life cycles of many species living on tropical shelf areas set the scene for very high fluctuations in abundance, and these populations share some features of the “bloom and decay” characteristics - typical of shorter - lived planktonic forms at high latitudes. This feature is in part due to the lack of correspondence between catch composition or relative species abundance of fisheries separated by as little as fifty nautical miles; (e.g., in the Indonesian archipelago; Pauly, personal communication; Bakun et al., 1980). If this is indeed the case, then it is likely that what we may be encountering at any one time is the result of differentially successful “local colonizations” by different species from an array of opportunistic species operating in an uncertain spawning context. The magnitude of change in dominant species abundance from year to year, and location to location, can often be considerable. Whether the specific early life history requirements are met or not, the presence or absence of predators, and the impact of locally intensive harvesting or closed seasons for inshore fishing, all set hurdles at which the larvae, juveniles or adults can be removed from the system, or alternatively allowed the time to grow and reproduce. What appears as relative stability in catch statistics at a national or regional level, may simply be the result of over - integrating the picture, i.e., looking at too great a part of the picture at any one time. This may be inevitable or even desireable from a national resource economics perspective but will lead to problems if not taken into account in deciding on the ‘appropriate scale’ of marine resource investigations, or more practically, in guiding the management authority as to the appropriate field of action of management measures for resources of a given bay, gulf, estuary, etc.

The above considerations can also be extended to include open ocean species such as the tunas. In the northwestern and eastern Pacific Ocean there has been a continual estimation of recruitment from yearly statistics of catch by age, but little subregional stratification has been officially reported. The impression generated from this large scale integration of catch data, is that tunas do not exhibit population fluctuations of the same order as other pelagic species; i.e., there are only 2–3 times changes in biomass or recruitment over the entire eastern Pacific yellowfin fishery, or over the skipjack fishery in the northwest Pacific.

However, in the eastern Pacific Ocean yellowfin tuna fishery there are regions which appear to support primarily “local” populations in some years, and mixtures of various independent cohorts which consist of both local and nomadic yellowfin from adjacent areas, in others. In Table 14 from Sharp and Francis (1976), there is a description of annual variations in cohort catches within three sub - regional areas. These can be considered to include “local” plus nomadic components of the eastern Pacific Ocean yellowfin population. The largest ratio between catches from any two semestral cohorts (fish recruited in the same 6 - month period; any years) within any of the three sub - regions, is about 5X, whereas between sub - regions for the same recruitment period the variation approaches 19X. The catches of yellowfin tuna taken together along the entire coastal zone of the eastern Pacific have been relatively stable since the full development of exploitation of this zone in 1961. Considering the catch of yellowfin within 200 miles of the coast from 1961 to 1976. The ratio of greatest to smallest catch is less than 3X. This shows the regional stability characteristic of populations with large nomadic components when integrated over large areas, in contrast to local or sub-regional variations.

Table 14
For the years 1964–71 the data are presented for catch in short tons by semestral cohort in the three areas (N,5,S) within the CYRA (Commission Yellowfin Regulation Area). Also given are the percent of the total catch (SA + SB + Big) by cohort within the areas. The category “Big” represents fish over 145 cm which we felt could not be aged under the present system.
The percent of the individual semestral cohorts (SA or SB) caught in the three areas is also given. Note the erratic shifting of the dominantcohorts, semester A or semester B, in the catch as well as the shifting distributions of these cohorts in and among years
Total BTotal
A + B
196427 4529 4015 20942 06233 5615 88117 51556 95799 0192 921
% total A + B26. 2.9
% total A or B65.322.412.4 58.910.330.8   
196518 96713 5126 40638 88524 06414 1648 38646 61485 4994 543 5.0
 48.834.716.5 51.630.418.0   
19667 76923 12820 17651 0730 29211 39414 77136 45787 5303 626
 8.525.422.156.011.312.516.240.0 4.0
 15.245.339.5 28.231.340.5   
196720 6999 5647 66437 92729 4828 57211 86749 92187 8481 802 2.0
196816 36123 92113 55253 83433 91722 1323 12859 177113 0111 602
 14.320.911.847.029.619.32.751.6 1.4
 30.444.425.2 57.337.45.3   
166922 43720 0349 03051 50134 88729 5875 64870 122121 6234 888
 17.715.87.140.727.623.44.555.4 3.9
 43.638.917.5 49.842.26.1   
197039 19715 94210 52965 66843 47613 25711 12567 858133 5269 176
 27.511.27.346. 6.4
 59.724.316.0 64.119.516.4   
197112 37218 71914 45345 54417 35725 28315 71258 352103 8969 277
 10.916.512.840.215.322.313.951.6 8.2 29.743.326.9   
Table 15
Trajectories of catch trends from 1970–77 for some key world pelagic resources
Peak Catch
Catch Ratio
Caranx hipposWest Africa28 2211 03627. +
Orcynopsis unicolorWest Africa2 60010026. -
Trachurus capensisSouthwest Africa690 16462 30011. +
Trichiurus lepturusSouthwest Africa28 5453 8007.5 +
Trachurus trecaeSouthwest Africa273 70031 2988.7 -
Sardinella spp.Southwest Africa142 20020 9866.8 - +
Scomber japonicusPeru65 0008 7007.5 +
Scomber japonicusNortheast Atlantic39 0006 2626.2 -
Rastrelliger spp.Eastern Indian Ocean16 3002 0008.2 +
Rastrelliger kanagurtaEastern Indian Ocean203 10035 4035.7
AnchoviesWestern Indian Ocean118 06216 9007.0 -
Psenopsis anomalaNorthwest Pacific Ocean13 0001 9947.0 -
Sardinops melanostictusNorthwest Pacific Ocean1 420 51216 90084. +
Engraulis mordaxEastern Pacific Ocean289 00244 6006.4 +
Cetengraulis mysticetusEastern Tropical Pacific168 08115 55110.8 +
Trachurus symmetricusEastern Pacific Ocean50 1499 4005.3 +
Sarda chiliensisSoutheastern Pacific Ocean74 7004 34117.2 -
Scomberomorus sierraPeru2 2794005.7 +
Engraulis ringensPeru13 059 900807 17516. +
Sardinops sagaxPeru - Chile1 467 55568 60021. +
Trachurus trachurusPeru - Chile839 805111 3007.6 +
Thyrsitops lepidopodesChile7 20063011.6 -
Cetengraulis edentulusVenezuela4968505.8 - +
Decapterus russelliMalaysia - Thailand109 3379 80011.2 +
Scomberoides spp.Indonesia - Philippines5 18650010. +

Plus and minus signs in the Table represent directions of trends during the reference period. The indication - + implies sharp changes in both directions of the order indicated

Examples of pelagic fisheries which have had annual catch peaks of more than 5X the lowest catches during the period 1970 to 1977 are tabled above (Table 15). It is expected that some of these catch variations are due to changes other than those interactions believed to be environmentally induced (i.e, which are due to changes in fishing effort, or to unreported catches). However, many of these fluctuations reflect real recruitment and consequent biomass fluctuations, which stem to some degree from local habitat variation; particularly large increases in catch during this period.

Paloheimo and Regier (1982) have pointed out the different considerations of scale which would be relevant and appropriate in approaching the multispecies fisheries of, for example, the Great Lakes and the Grand Banks of Newfoundland. They suggest that in order to cope with multispecies-ecosystem related fisheries, research will have to adopt empirical approaches if it is going to be of practical value to fisheries management. Highly theoretical approaches are only of relevance when either very little is known about a system, or very much is known. They also point out that many management related studies tend to be vague about what has happened as a result of previous management actions, or what to expect from them in the future. Although fisheries can induce dramatic changes, the major causes of large scale system effects are still variation in abiotic properties of the ecosystem. The biotic changes will be responses to these. Figure 15 from Regier and Henderson (1973) is provided here to show that this way of classifying the numerous approaches used in fishery studies also implicitly explains the rather low precision characteristic of management - related research. It is also noted that this low precision is not all due to the unpredictability of fish populations but is due in part to the failure to consider appropriate environmental covariates that would partly explain the “apparent random noise” in multispecies fisheries.

As was also concluded in Sharp and Csirke (1983), Paloheimo and Regier (1982) observe that:

“Any attempt to explain changes in multispecies fisheries that ignore concomittant changes in the abiotic variables appear to be futile. Similarly, any modelling of the freshwater or marine system without incorporating the role of environmental variables also seems to be doomed to fail”.

This emphasizes the importance of comparative fisheries research. Careful examination of biomass composition changes in local or regional fisheries often shows a relatively stable total biomass, with compensatory changes occurring among the various species components. This nearly constant condition is only likely to occur in most marine systems as long as the primary production remains relatively stable, and where the replacement species are ecologically equivalent.

The statistical data base we have on most industrial fisheries in the tropics is very brief in duration; dating from the 1960's or even the early 1970s in most cases. These data illustrate the short - term variations in catch from pelagic populations. What changes can be expected in the longterm will only become evident as the data series and experience with these fisheries accumulates.

The trends in regional catches and relative abundances of the oceanic opportunist species such as the tropical tunas, large billfishes and other cosmopolitan species, vary in the order of two to three times, but rarely as much as five times. Where records indicate changes of such magnitude for cosmopolitan oceanic species, they usually correspond to changes in economic factors or in effort distribution patterns, rather than representing relative abundance changes.

For demersal fish it has been noted that specific bottom type and depths may each have a characteristic fish fauna (e.g., Grady, 1971; Domain, 1972; Caddy and Iles, 1973) although here the concept of specific fish “communities” that have a tendency to share common population ranges appears less convincing than for bottom infauna. The use of the term “fish community” tends now to be more commonly applied to specifically recognizable “live bottom” areas, e.g., coral reefs, eel grass or kelp beds. Even here it may be regarded as being broadly descriptive, and rather difficult to verify statistically since, for example, coral reefs contain a number of different habitats, each with its group of more or less characteristic species.

As noted by Parrish and Zimmermann (1977), reef fish can themselves be classified into four categories: Reef restricted species that only occur on reefs, reef related species that spend at least some but not all of their time on or around reefs, reef indifferent species that may or may not spend some time around reefs, and non - reef or occasional species that are atypically found there.

More generally, one may first classify species into residents and transients - the latter, often important, species only occurring in a “community” on a seasonal basis (e.g., Tyier, 1971). Even for benthic invertebrates, it is clear that with successive sampling, the total number of species encountered goes up in a generally assymptotic fashion with number of samples taken (Figure 63), so that to define the number of species in an area for calculation of diversity indices, etc., it will be necessary to define the number of samples taken.


Sampling and Fishing: Methods and Constraints

Basic information on the numbers and species of fish populating a given marine area is obtained for the most part indirectly, that is by inference from fish catches, in particular by fishing gear (“remote sampling devices”) of various types, each with its own specific efficiency and selectivity for species and sizes. More “direct” observation techniques such as sonar, under-water photography, and observations from vehicles such as submersibles or by scuba, have been used in some areas for quantitative estimation of fish and shellfish populations, but also have their particular difficulties and limitations, being susceptible to problems in identification and calibration, and to the effects of the observer on behaviour of the fish being observed. For visual methods, the general limitation is also on the area of action of the sampling device, given that although average fish densities per area of sea surface may be in the order of 1–10 fish/m2 overlying dense schools, they may average 1 fish per 10–1 000 m2 over the whole fishing ground, and of course much lower “average” densities are the case for large high seas predators such as tunas.

Figure 63

Figure 63 Illustration of how species numbers approach an assymptote with sample frequency or area sampled (Redrawn after Smith and Tyler, 1973)

It is important to remember however, that the effectiveness or “fishing power” of vessels sampling a fish population are not just functions of gear design: a skipper who has special knowledge of areas of higher density has a competitive advantage and in general, predators take advantage of patchiness of prey in this way to increase their “benefit - cost ratio”. Thus, a shipper's knowledge is a significant component of his vessel's fishing power, which can be at least as important in practical terms as the vessel engine horse power in determining the catch rate of those species available to the gear.

This second quantity, “availability” or “vulnerability” to fishing is again, a factor that determines the possibility of sampling or commercial fishing with a given vessel/gear type, and may change from time to time. The high vulnerability of herring, cuttlefish, grouper and many other species to fishing while spawning, is of course a factor that a manager needs to take into account in deciding on fishing seasons, closed areas etc., not only in designing sampling programmes.

Distribution Patterns

Sharp and Francis (1976) estimated the average density of yellowfin tuna larger than 40 cm in fork length in the eastern Pacific to be 34.5 mg/m2. Of course tunas of 40 cm or more weigh considerably more than 34.5 mg, and also occur in schools. Sharp (1978) estimated that the typical tuna school sought by modern fishing gear is a composite of “core” schools, i.e., groups of fish of similar size and similar or unique history, comprising 2 000 to 3 000 kg units. The fishery in the eastern Pacific samples schools which are greater than some threshold size (specific to each fishing captain's criteria). In examining several localized series of data for insights into environmental effects on school size, Sharp (1978) noted that in two periods which were characterized by different thermal profile regimes, the proportions of different size schools captured changed dramatically. The following table shows these results:

The observed change is in the decreased numbers of small sets (0–10 tons) made and in the proportions of sets containing more than 20 tons. Of the 881 sets made from 1 March – 1 April, only 9 percent were greater than 20 tons; in the second period there were 499 sets and 22 percent were larger than 20 tons.

The point Sharp (1978) makes is that school sizes shift with suitable habitat volume, hence local “core school” density and interaction rates change. During the latter period referred to above, the habitat volume was less than that for the earlier period, hence more core schools met and aggregated. This example causes one to consider that in sampling fish stocks, system dynamics, as well as availability and selection by the samplers, in this case the fishing captains, must all be considered.

Table 16
Percent total successful purse seine sets in class
Short Tons =0–1020304050607080100>100
Mar 1 – Apr 1571214211    
Apr 16 – May 30592084222112

As a simplistic example, again looking at the eastern Pacific yellowfin tuna in its context as a dominant nomadic predator in this large system, consider that the 2–3 ton core school represents about 50/80 km2 of ocean surface, and that a not unusual 200 ton aggregation comprises the entire expected biomass of about one half a 10° longitude by 10° latitude area of the eastern tropical Pacific. In these schools there is an inverse relation between average fish size and its probability of occurrence in larger aggregations. Consider a 200 ton school of 50 cm fish, consuming at least 10 percent per day biomass equivalents, in order to sustain itself: at normally observed densities of coastal resources, such predator removals of 20 tons per day would represent a significant perturbation of the local fish resource and food webs.

What this illustrates again is that fish are not randomly but contagiously dispersed in their habitat; the degree of contagion to a large extent being dependent on both the life history stage and on the size of the unit area sampled. The statistical distribution that perhaps provides the best general description of the probability of a given number of organisms being captured in a unit sample is the negative binomial distribution (Figure 64), and this has also been found to provide a good description of the number of fish in successive samples taken with an otter trawl (e.g., Taylor, 1953)1, and well describes the distribution of benthic populations also (see Elliott, 1971). Sampling fish with “swept area” type of gear (trawls, dredges) poses special problems in interpretation of data, even if these may be less pronounced than for capture methods that depend on fish attraction (traps, baited hooks) or for pelagic fishing gear (gill nets, seines and weirs) where an adequate sampling theory has, by and large, yet to be developed. The problem with all fishing gears is basically one of defining their selectivity and the availability of different sizes and species to the gear, before allowing for it in assessment of the true abundance of fish; bearing in mind that most successful fishing gears have been developed (often over long periods) to provide the maximum differentiation between desirable and undesirable sizes and species.

Sampling demersal communities

The bottom trawl is probably the best understood type of fishing gear, and also perhaps the gear that for demersal fish comes closest to satisfying the main sampling requirement, namely, that catch rate for a given species in an area is usually roughly proportional to abundance. However, even in this case, species differences in behaviour, e.g., in response to herding by the warps, and differing effectiveness of escape responses, together with mesh size, all dictate the species composition of the catch. Trawling characteristics such as direction relative to the tide, and speed of tow, headline height, and presence of rollers or covers, also affect the catch composition. Perhaps, however, the most important of all factors in relation to a study of demersal fish “communities” (defined as those groups of species that generally occur together in the same habitat) is the duration of the tow, since for long tows (over several kilometers), the trawl may be artificially “blending” several groups of organisms, each originally occupying a distinct subarea of sea floor within the total path swept by the trawl.

As noted by Thorson (1957), level (theoretically “trawlable”)2bottoms make up at least 90 percent of the sea floor of the world's oceans and are inhabited by a mosaic of distinct groups of bottom - dwelling invertebrates. Thorson suggested that each group of organisms is made up of a relatively fixed number of species, making up a “community”: the “communities” differing with sediment type and depth.

As noted already one may first classify species into residents and transients - the latter, often important, species only occurring in a “community” on a seasonal basis (e.g., Tyier, 1971).

1 It has also proved a useful description of several other important statistical distributions in fisheries science; e.g., the probability distribution for the size of annual recruitments for a single species population (see, e.g., Hennemuth, Palmer and Brown, 1980)

2 Most of these level bottom areas are of course abyssal and not trawlable!

Figure 64

Figure 64 The negative binomial distributions compared to the limiting form, the Poisson. Each distribution has a mean of 10 and consists of 1 000 observations (From Taylor, 1953)

Even for benthic invertebrates, it is clear that with successive sampling, the total number of species encountered goes up in a generally assymptotic fashion with number of samples taken (Fig. 63), so that to define the number of species in an area for calculation of diversity indices, etc., it will be necessary to define the number of samples taken.

For this sort of reason, and because, unlike the term community, it leads to field studies of a more objective kind, the concept of a fish “assemblage” has been coming more into favour in recent years. Based originally on work by terrestrial botanists (e.g., Whittaker, 1967), the concept of gradient analysis became accepted, whereby apparent changes in flora (and of course associated fauna) were explained in terms of a common response to gradients in environmental parameters (e.g., altitude, pH, temperature, drainage, etc.). As a consequence, a group of species typically occurring together were considered to be responding to a common environmental variable, rather than from any intrinsic “attraction” between them. Many exceptions may be found of course, e.g., those that fall under the terms parasitism, commensalism, symbiosis, and obligate predation, where two or more species co - occur independently of the environment so long as this is not wholly unfavourable. The gradient concept and the associated idea of species assemblages (i.e., those organisms that due to independent but common responses and environmental preferences tend to occur together) has a lot of attraction, especially since unlike the community concept, it allows statistical testing of the underlying hypotheses, and encourages study of the physiological ecology of marine organisms.

The fish assemblage may in practice be considered an alternative form of classification to that discussed elsewhere in this paper, namely the food web, and it may be worthwhile spelling out some of the differences, while noting that the two approaches are strictly complementary and should together logically underlie any approach aimed at understanding multispecies fisheries.

The fish assemblage consists of those species available to sampling in an area, which from statistical analysis can be shown to occur together on a recurrent basis. Not all of these species will necessarily be linked trophically, although many will be (either as predator - prey, or by sharing common predators or prey). In fact, since the components of an assemblage will reflect the method or methods of sampling used, they may (unlike food web components) tend to be of a relatively restricted range of individual sizes as adults.

Various statistical tools have been used to show the degree of co - occurrence of species in a series of samples, and a number of indices of similarity between different samples have been used (see, e.g., Greig - Smith, 1964; Whittaker, 1967; Day and Pearcy, 1968; Pielou,1969). These can be resolved into groups of stations with similar fauna, or groups of species with similar spatial distributions, by using cluster analysis e.g., Romesburg, 1984 to show the hierarchical similarity of different groups of stations (e.g., Figure 65). Various routines exist (see, e.g., Davies, 1971) for arrangement of a matrix of similarity indices in a hierarchical fashion as a dendrogram or contingency table, if systematic sample data exist. Methodologies of treatment of multispecies sampling are progressing rapidly, and in particular, Principal Component Analysis is coming into widespread use (see Mahon et al., 1984). Even before such systematic approaches are tried, as noted earlier, separate maps can often be prepared for resident (as well as on a seasonal basis for transient species), to show the degree of overlap of different resources and their fisheries.

Figure 65

Figure 65 Dendrogram for hierarchical classification of stations (from Hughes and Thomas, 1971): the letters represent subgroups of stations

Characterizing fish assemblages in this way, even approximately, appears to be one necessary precondition to the understanding of multispecies stocks, and could usefully be accompanied by the approach to analysis of stomach contents, and the preparation of food webs in the preliminary form suggested in this paper.

As pointed out by Tyler, Gabriel and Overholtz, 1982, “Fishery agencies in many parts of the world already have enough distributional data to map assemblages …(and) … there are already enough data already collected … so that regulars may be distinguished from seasonals. There are also enough fish stomach analyses in many important fishery regions to construct first approximations of energy usage groups …”. These “energy usage groups” consist of the (one or more) trophically linked subset of “regulars” (year - round resident species) in an area, and Tyler suggests that these subsets form the natural multispecies management units for a fishery (e.g., Figure 66). This will require a particular approach to research and management of fish stocks namely, management by “Assemblage Production Units”(APU's), each consisting of several species. These demersal “energy user groups” are considered to be affected by three main driving functions: the fishery, the physical environment and its fluctuations, and the impacts of the transient species (as occasional predators, prey or competitors). This preliminary categorization thus goes a long way towards elucidating the likely interrelationships between important species. Although the concept of assemblages consisting of year - round residents, may be rather restrictive for (eg. estuarine and upwelling) areas where oceanographic conditions make year - round residence impossible, MacDonald et al. (1984) have discribed assemblages that retain their identify despite seasonal bathymetric displacements. There is also some evidence (Overholtz and Tyler, 1985) that assemblages will persist over significant period of time despite drastic changes in relative abundance of the constituent components.

Figure 66

Figure 66 Schematic approach to research and management by fish stock assemblage (After Tyler, Gabriel and Overholtz, 1982)

We should also bear in mind (as shown in Figures 7 and 8) that a food web is a static representation of a recurring sequence of events in the sea. As implied by these illustrations, the biomass of a given component at the present time, should in theory if not in practise, be translatable backwards to the period of time when synthesis originally occurred, if we were to know the efficiencies of transfer of material between different components, and its rate of usage for metabolic purposes by marine organisms. This time sequence of events is not always clear, however, because of the existence of “loops” in the form of scavengers, detritivores, and by cannibalism, which delay the“upward” movement of material in the food web. Nonetheless, Figure 8B can be regarded as an analogue to single species cohort analysis, and is perhaps a visual equivalent to the multispecies cohort analysis proposed by Pope (1979)

For demersal and pelagic fish also, it has been noted that specific bottom type/depths/water masses may each have a characteristic fish fauna (e.g., Grady, 1971; Domain, 1972); and that fish aggregations are dynamic and occur in response to environmental gradients, but also in response to spawning and feeding, so that the concept of specific fish “communities” that have a tendency to share common population ranges appears less convincing as a general rule than for bottom infauna. The use of the term “fish community” tends to be more commonly applied to specifically recognizable “live bottom” areas, e.g., coral reefs, eel grass or kelp beds. Even here it may be regarded as being largely descriptive, since, for example, coral reefs contain a number of different habitats, each with more or less characteristic species.


The relationship between feeding rate and growth has been a major preoccupation of marine biologists for the last 30 years or so, and a wide and varied literature exists (see Ivlev, 1961; Winberg, 1960 for early key references). Much less attention has been paid to the effects of feeding rate on the mortality rate of those species in the trophic level immediately below, that form the food of the species in question.

Conover (1978) summarized a representative set of data on feeding rates in relation to body size and temperature for a range of invertebrates and marine fish, and although he concluded that sweeping generalizations on the rate of feeding in large particle feeders macrovores are difficult to make if the whole data set is taken together, he arrived at two main conclusions:

  1. an increase in temperature increases the feeding rate;

  2. small fish require a proportionally larger ration (i.e., percent body weight consumed per day) under given conditions than large fish.

Looking at correlations between body size and food consumption, even within taxonomic groups, is unlikely to be a very fruitful exercise if the normal level of activity of a species is not taken into account. Since activity contributes greatly to metabolic rate and increases with temperature, inclusion of ambient temperature in any comparison improves our ability to estimate feeding rate. The majority of available data are from tank experiments whereas most swimming activity is in response to feeding, hence producing usually relatively low “maintenance” levels of activity and feeding rates, although the contrary tendancy of “feeding to saturation” characteristic of aquaculture operations for example, to some extent compensates for this.

Despite the above, there are obvious basic differences between the level of activity and hence feeding rate between for example, inactive and active perciformes, e.g., a flatfish and a mackerel, or between an octopus and a squid (both cephalopods), even at the same temperature and body size. This is seen clearly in Figure 67 where the feeding rate is plotted against body weight for the data from Tables 5–24 of Conover (1978), (all diets combined). The squids and mackerels have feeding rates that are at least two times higher than for the less active bottom dwellers, the flatfish and octopus. From preliminary examination of these data, it seems that there is relatively less variation in feeding rate for fish in a given ecological niche or activity pattern. Bearing this in mind, we looked more closely at the most extensive series of data that was available, namely for a range of predatory bottom-dwelling fish (flatfish, gadoids, groupers, etc.) shown as circles in Figure 67, feeding on a variety of diets which are not distinguished in this analysis.

Expressing this relationship empirically by a multiple regression, we can fit

loge(rT, W) = A+B loge () + C (T)

A preliminary calculation of the parameters of this equation for a limited set of 59 data points taken from Table 5.25 of Conover (1978) (and ignoring the nature of the diet), was carried out. We find for 13 species of demersal fish ranging in size from 20–633 g under ambient temperatures of from 8.6–20°C, the following multiple regression of the above form:

loge (rT, W) = 1.841 - 0.286 loge () + 0.048 …(A)

where (rT, W) is the feeding rate (% body weight per day) and and are mean (or in some cases, the median) body weight and temperature respectively. An R2- of 0.55 suggests that the variables considered explain only about one half of the variation observed; and this relationship should be re - examined when a larger size range and bigger data set are available. Despite this, our preliminary analysis also suggests that of the two independent variables, body weight is the more significant, explaining almost 40 percent of the variation - a smaller percentage being explained by ambient temperature. Specific effects of activity pattern and type of diet probably account for a significant part of the remaining unexplained variation1, but even if a quantitative data set were available or could be easily defined which included these unknowns, it seems unlikely that they would individually be more important than body size in determining feeding rate.

1 The concept that the “resting” or maintenance level of metabolism and food consumption is roughly half that of a species in its natural environment is due to Winberg (1960), but does not take into account difference in specific activity level of different species

Figure 67

Figure 67 Relationship between body weight (g) and ambient temperature, and the consequent consumption rate (% body weight per day) for a range of fish and invertebrate species (data from Conover, 1978). The multiple regression shown by dashed lines is fitted to the demersal fish data only. (Points for pelagic fish and invertebrates added for comparison only)

In relation to the data set used, although it is not always specifically stated, we can probably assume that the majority of the data points are derived from tank experiments (especially since the size range is limited), and that therefore food supply was not the limiting factor, but activity probably was. In nature, food is more liable to be limited and/or patchy in availability, but we may not be greatly out of line to use values obtained from equation A to obtain first estimates of natural feeding rates, recognizing that these are possibly lower bounds and that activity levels will determine the more realistic values.

Olson (personal communication) provided the following table (Table 17) of daily ration estimates from field studies which shows the importance of seasonality in some species. The dominant role of body size in defining factors of ecological importance can also be illustrated by Figures 11 and 12, which shows the relationships between intrinsic rate of increase in population size (indirectly a function of feeding rate) and body size, and the relationship between body size and the theoretical concentration of “particles” (including living organisms) in sea water.

The relationship suggested by Table 17, although based on a rather limited data set, suggests that over the usual commercial size ranges, a suprisingly limited range of feeding rates of from 1–5 percent body weight per day should cover most of the variation for most (relatively inactive) demersal fish species (Figure 67). Consideration of pelagic fish species is limited by the available data set, but for two species for which we data are available (a scombrid and a carangid respectively) we have:

Pneumatophorus japonicusSeriola quinqueradiata
feeding onfeeding on
Engraulis japonicusTrachurus meat
= 334 g = 323 g
= 21.5 C = 24.6
rT =11.1rT = 8.6

The feeding rate in the two cases is 4.2 and 2.7 times that predicted for less active fish of the same size at the same temperature. This suggests that the feeding rate of active small - medium sized pelagic predators (e.g., mackerel, jacks), can be 2–4 times greater than that for comparable demersal fish in the same area. This differential is even greater for the most active oceanic predators, the tunas (Sharp and Francis, 1976). These fish provide a practical upper limit to the feeding rate, and from a model based on skipjack active metabolism measurements at 24°C, Sharp and Francis (1976) give a range of estimates of feeding rate from 11 to 21 percent of body weight/day for a 1 kg yellowfin. This is quite outside the range of our observation set, and suggests that extreme caution be used in predicting feeding rate for organisms (e.g., tuna and oceanic squid) where locomotory activity takes up a high proportion of the energy budget.

The feature that is most striking about the data set for bottom fish, is the relatively small variation in feeding rate at any given size, and the lack of trend in feeding rate as a percentage of body weight from 30 g upwards. Despite the few data points above 500 g body/weight, feeding rate per body weight of larger fish in the same environment can be expected to be lower, but not greatly so.

The implications of these observations for population dynamics and predator-prey relationships deserve some consideration. Firstly, at a given relative abundance of a predator and its prey, the following points can be made:

  1. The natural mortality M is not likely to vary rapidly with individual predator size for a given predator/prey biomass ratio, above the individual size of prey consumed (20/50 g?) by 300 – 500 + g fish. (This tends to support the conventional assumption of a constant M for exploited size ranges, often made in population dynamics).

  2. The natural mortality rate for a given organism will generally go up with temperature. This is already seen in the relationship postulated for M by Pauly (1978) from examination of a large body of data 1 namely,

    log10M = - 0.2107 - 0.0824 log10 W + 0.6757 log10K + 0.4687 log10

  3. The natural mortality rate exerted by a stock of pelagic predators on a given prey is likely to exceed that exerted by a similar sized population of bottom fish occupying the same feeding niche.

  4. Following from 3, the proportion of a given quantity of lower trophic level productivity (e.g. of a “forage” fish) recoverable from a stock of demersal predators is likely to be higher than by harvesting a pelagic stock sharing the same “forage” species.

1 This equation suggests that temperature is more important than body weight in determining the values of M1 and this is generally in accord with our results. What is less clear from this formulation is what would be the effects of changes in abundance of predator on M for its prey species

Table 17
Daily rations (percent of body weight) of fishes calculated by several investigators using field data, ordered by increasing ration
SpeciesAverage size (g or cm)Water temperature °(c)Month or seasonDaily rationSource
Northern pike Esox lucius32–49 cm (standard length)2
Diana (1979)
American plaice (age 11 females) Hippoglossoides platessoides256 g2–3Mar - Apr
MacKinnon (1973a, 1973b)
Yellowfin tuna Thunnus albacares2 629 g
8 603
22 655 g
Olson (present study)
Walleye Stizostedion vitreum vitreum219 g
354 g
Swenson and Smith (1973)
Several centrarchids40 cm - pike
16 cm - others
6–26Summer1–2Seaburg and Moyle(1964)
Mako shark Isurus oxyrinchus63 000 g18.8-3.2Stillwell and Kohler (1982)
Diamond turbot Hypsopsetta gluttulata96 g12.5–24.0All3.8Lane (1975)
Laneet al. (1979)
Perch Perca fluviatilis>20 cm
(total length)
-June–July 1971
August 1971
September 1971
June 1972
August 1972
Thorpe (1977)

a Males
b Females
c Given in kcal/kg/day or kcal/fish/day - converted to % body weight/day assuming 1 000 kcal/kg

Environment and recruitment

Most juvenile and adult fishes have in general more options available to them than do the less mobile early life history stages. A set of questions that constantly reappear are those about relationships between temperature, larval fish development time, and predation.

The absolute temperature of the environment within the normal range that a species is adapted to, is not critical to survival of larvae in most cases, since although for metabolic reasons, intermediate to cool temperatures within a larval fish's normal temperature range promote better survival for individual larvae given adequate food, predators in warmer habitats also follow the same thermal laws. Hence invoking Q10 as a biological quotient which can be applied in many situations, means that the logarithm of a predator's activity increases in proportion to increased temperature, so that predators are especially voracious in a “warm” habitat; cancelling nearly all benefits a larval fish might derive from developing rapidly from egg to larval stages.

In conclusion, upon hatching fish larvae are faced with a trade off between higher rates of development at higher temperatures, and higher rates of predation for precisely the same reason. The conclusion seems to be developing, particularly in the tropics, that lower to average temperatures may even be an advantage for development of fish larvae. The following table gives the essence of the problem:

Table 18
Relationship between temperature, and the activity and respiration/feeding rate
Habitat Temperature (°C)Activity IndexRespiration/Feed Index

If we take the 26°C isotherm as a likely centre point for egg/larval hatching and development in the tropics, and use the requirements in food/respiration at this temperature as a baseline, the effects of temperature alone on activity level can be indexed as a simple function of Q10 and are shown to range from + 41.4 percent above the 26°C value with a five degree Celsius ambient temperature increase, or conversely to be only 29.3 percent with a five degree decline below 26°C. However, the energy expenditure based on activity alone for a continuously swimming larval or post-larval fish varies as the cube of the swimming speed. As one can quickly see, this results in dramatic food/respiration differences.

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