Against a background of stabilizing or even falling catches from traditional capture fisheries, increasing human population and an ever-increasing global demand for food, there is now a major challenge in re-examining the nature and potential of the aquaculture sector, and to ask just how far aquaculture might go to satisfy the expected increase in demand for its products. Aquaculture is a notably diverse activity, and an appreciation of this diversity is fundamental to the understanding of the issues influencing its future development. This applies to an assessment of requirements for resources of all kinds, to the way aquaculture may develop independently from the fisheries sector, to the prospects for producers from all economic levels or locations, or to opportunities for developing new markets (Muir, 1995).
The present study is an attempt to satisfy part of the need for information on aquaculture potential in Latin America. This study builds on the experience gained in Africa in the analysis of factors important for aquaculture development and operation. (Kapetsky, 1994) and the implications of aquaculture development for food security (Kapetsky, 1995). At the same time, it integrates a growth model to improve the estimates of fish yields in order to estimate the potential for warm-water and temperate-water fish farming in the inland waters of Latin America.
This study was conducted for two purposes:
to stimulate improved planning for aquaculture development at the national level; and
to plan comprehensively for technical assistance activities by FAO and by other national and international organizations that provide both technical and financial assistance for aquaculture development.
This study was carried out using a geographical information system (GIS) for the basic analyses. A GIS is an integrated system of hardware, software and personnel that is used to manipulate, store, analyse and report spatial (geographic) data. By allowing manipulation of large spatial data sets and providing a rigid analytical framework, integration is possible of diverse knowledge that may be both qualitative and quantitative in nature, such as soil type, estimates of water requirements and yield potential by the use of models, etc. By scrutinizing Latin America for fish farming potential in relatively small units (i.e., grid cells of approximately 9 km × 9 km), GIS technology provides a means to ask “Where is the potential, of what quality and over how much surface area?”
GIS is being increasingly employed in aquaculture. An overview of GIS methodology appropriate for aquaculture is provided by Meaden and Kapetsky (1991) and a review of applications was made by Kapetsky and Travaglia (1994). Most applications in aquaculture are for site selection over rather limited geographic areas, but strategic assessments of aquaculture potential have been made for larger areas, such as countries by Kapetsky et al. (1991) and states (Kapetsky, Hill and Worthy (1990); Aguilar-Manjarrez and Ross, (1993); Aguilar-Manjarrez (1996)). However, the only continental-level strategic assessment of aquaculture potential is that by Kapetsky (1994).
The GIS approach can be complementary to other approaches, such as that used by Muir (1995) to estimate aquaculture potential worldwide on a country by country basis using income, resource and development indicators, and by Born, Verdegem and Huisman (1994), who looked at macro-economic factors that influenced world aquaculture production from one region to another.
Strategic assessments of regional pond aquaculture potential require estimates of fish yields that are possible at different geographical locations. In the above-mentioned study in Africa (Kapetsky, 1994), fish yields (expressed in terms of crops/y) were estimated on the basis of temperature thresholds established for the model species (Nile tilapia, Oreochromis niloticus). However, this approach is not readily extendible to other species that may be of interest. Moreover, the approach does not directly consider the effects of seasonal water temperature variation on fish growth and food consumption rates, nor does it account for the effects of other factors (e.g., feeding levels, photoperiod and fish size) on these rates. Bolte, Nath and Ernst (1995) have developed a fish growth model that accounts for the effects of all of these factors on fish weight, and therefore yields. Techniques have also been developed to automatically adjust the parameters of this model for different fish species (Bolte and Nath, 1996).
Water temperature is an important input variable required for regional-scale assessment of fish yields. One approach to water temperature involves the use of heat balance models (e.g., Fritz, Meredith and Middleton, 1980). Such models account for the effects of geographical variations in air temperature, and in other weather characteristics (solar radiation, cloud cover, wind speed and relative humidity) on pond water temperature. Nath (1996) has developed a heat balance model for use in pond aquaculture.
Both the heat balance and growth models cited above have been packaged in the decision support system POND ©1 (Bolte, Nath and Ernst, 1995; Nath, Bolte and Ernst, 1995), which runs under the Microsoft Windows operating system.
Inland aquaculture production in Latin America is rising, but in absolute terms it is small in relation to production from inland fisheries and somewhat less than mariculture production (Figure 1.1). For the most recent year for which information is available (1994), inland aquaculture amounted to 120 000 tonnes, while mariculture provided more than twice as much, 286 000 tonnes. Inland capture, at 500 000 tonnes, exceeded both kinds of aquaculture. In comparison, marine fisheries production was about 23 million tonnes.
Figure 1.1 Inland Aquaculture, Mariculture and Inland Fisheries Production from Latin America 1984 – 1994
Two types of rural aquaculture in Latin America are discussed by Martinez-Espinosa (1994, 1995). Type one is the “poorest of the poor” or subsistence aquaculture, which is characterized by very low cost accompanied by very low output. Producers who have excess production sell or barter it locally. The second type is “less poor” with low to medium costs and low or medium output. This type of aquaculture is conducted by farmers who add aquaculture to traditional agricultural activities. Most of the production is sold. A third type, “industrial”, can be a corporate, high-investment, stand-alone activity.
Of the various types, it is the low to medium investment, low to medium output type that apparently has excellent potential.
This study estimates potential in three categories that relate well to the above-described situation: small-scale fish farming and two levels of commercial farming. The first of these, small-scale, corresponds to very low investment, very low output. The first level of commercial farming is semi-intensive and it includes the farmer who would add aquaculture to traditional farm activities. The second level of commercial farming is intensive, and pertains to those who would undertake aquaculture at an industrial level.
