Two other approaches are also used to help formulate long-term strategy: 

 1) statistical models of yield (or population abundance) and long-term 

 environmental trends and 2) gross energy budgets. Use of environmental trend- 

 fishery yield correlations requires a long consistent time series of data, and 

 is fraught with risk as experience has shown time after time. Energy budgets 

 are another way of helping analyze long-term strategies, particularly through 

 estimation of limits to total fish yield in an ecosystem. However, they are 

 either heavily dependent on theoretical transfer efficiencies between trophic 

 levels, or they require a very comprehensive data base on actual production 

 (not yield) and food consumption rates of all major biological components of an 

 ecosystem. Such data bases, particularly the predator-prey interactions, are 

 not available for full scale ecosystems. 



Environmental Quality 



Quality of the environment is, in the long run, the most important aspect 

 of ecosystem-fishery management since it controls carrying capacity. Effects 

 of overfishing generally are reversible and usually can be mitigated within a 

 relatively short time simply by reducing fishing pressure. In contrast, effects 

 of a degraded environment may not be reversible, or only after a long recovery 

 period, assuming cause of degradation is removed. 



Numerous environmental impact models have been constructed to deal with 

 short-term effects of oil spills, power plant discharges, and other pollution 

 such as acid wastes, sewage, etc. In all cases, these models have utility 

 assuming worst case estimates for target organisms. However, their predictive 

 power is generally poor because the cumulative synergistic effects on the 

 ecosystem are not known, and even for target species (e.g., fish), the effects 

 are only local and often do not apply to the entire population. Thus, it is 

 usually impossible to estimate the real significance of a pollution impact, 

 particularly for continental shelf populations. Detailed knowledge of hydro- 

 dynamics as well as biological effects are required for quantitative modeling 

 in these cases, and input data are seldom adequate for ocean environments. 



The same general models are applicable in the case of chronic pollution, 

 but the problem of estimating biological effects is even more difficult than in 

 the short-term case because of the enormous expansion of the relevant scales of 

 time, if not also space. Nevertheless, since we are dealing with chemical 

 effects on organisms, biological effects of pollutants can be measured in 

 laboratory experiments for a limited but controlled set of environmental 

 conditions and then extrapolated to the natural environment using the model and 

 ambient concentrations of the pollutant in the animals and environment. Direct 

 verification of pollution effects on organisms at the population level in the 

 natural environment is, however, extremely difficult. 



Summary of Models 



A brief outline of the various types of models was prepared by the Panel 

 and is summarized in table 1. General research priorities were assigned 

 according to expected payoff in terms of improved predictive capability taking 

 into account cost-benefit considerations for various kinds of research. In 

 this case, research implies a new initiative, i.e., developing new methodology 

 (model) or obtaining new ecological information. 



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