Species with a relatively short annual breeding season tend to show more dramatic seasonal variations in numbers. The abundance of “perennial” species, such as most large fish, also depends on biotic factors and environmental changes that effect recruitment. For longer-lived commercial-sized marine organisms, variations of at least an order of magnitude usually occur in recruitment over a period of several years (Ricker, 1975; Beverton and Holt, 1957). These changes in level of recruitment from year to year due to environmental changes are often exaggerated due to their influence on the level of harvesting and fleet size following years of peak earnings. Such a ‘lagged’ effect accentuates year to year changes in the level of landings (see Caddy and Gulland, 1983 and Fig. 7).
The most important of these factors and changes tend to operate early in the life history of the fish (Cushing, 1982, 1988). For example, the survival of eggs and larvae is particularly sensitive to ecological factors, and recruitment of surviving young fish to the adult or fished stock is often related to marine weather patterns, oceanic conditions, the size of the broodstock (and, to close the circle), to fecundity, spawning success and other factors.
Short-term (seasonal) and long-term (interannual to decadal) environmental variations, producing comparable variations in abundance of sardines and other species (Lluch-Belda et al., 1992), preceded the influence of man (e.g. Cushing, 1990; UNEP 1994). They must, nevertheless, be taken into account to achieve sustainable - and optimal - development.
Long-term variations in the marine environment due to climate change have been documented and changes in fish abundance have been correlated with them. For example, it is known from fish scales in cores of bottom sediments that different species replaced each other even prior to man's influence on marine ecosystems (Holmgren-Urba and Baumgartner, 1993). Also the “little ice age” in the Northern Hemisphere during the early Middle Ages, apparently caused by abnoralities in the sunspot cycle, was a period during which cod populations off Greenland declined and were replaced by seals and other fully Arctic species.
The foregoing type of considerations must be taken into account in evaluating changes in the oceanic environment due to human activities. The amplitude and pace of the expected global climate changes (see section 5.10) will be superimposed on an already wide natural variation in conditions, and it is therefore difficult to forecast their effects on fisheries and aquaculture. Although particular stocks may be adversely affected, large changes in total marine fish production are not expected.
Changes in rainfall patterns, river run-off and sea-level rise will especially affect life in enclosed and semi-enclosed seas, coastal wetlands, estuaries, lagoons, mangroves and other important coastal nursery areas. Land erosion may increase, leading to coastal siltation, reduction of the marine photic zone and further degradation of coral reefs and sea-grass beds.
Coastal aquaculture will also be affected, especially in southeast Asia and India from where most of the world's marine and brackish-water aquaculture production now comes. The cost of moving and rebuilding coastal aquaculture infrastructures and resiting seaweed and mollusc beds cannot be calculated at present but would be enormous.
The WMO-UNEP Intergovernmental Panel on Climate Change has made a comprehensive scientific assessment of climate change (IPCC, 1992); some of its findings are considered in section 5.10.
There are limits to what can be done to mitigate future adverse effects of climate change without the full support of governments and of people in the areas at risk. Financial consequences are still hard to predict and it is difficult to convince governments and institutional donors to commit funds until better forecasts are available. Premature, ill-informed decisions could be costly and dangerous but there is also a risk in taking no action at all. It is important to reduce the present level of uncertainty.
