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Abstract
The general objective of this thesis is to formulate a general model for fish production in integrated ponds and ricefields as a means of obtaining a better understanding of these production systems. Integrated culture systems produce fish without large industrial energy inputs and have positive effects on the whole farm system. A main characteristic is their environmental variability, notably dissolved oxygen concentration and temperature. A systems approach using mathematical models is advocated because it can lead to insights that have universal applicability while avoiding the pitfalls of site- and species-specific, expensive experimental work. Two modelling approaches are distinguished: descriptive models, generally the result of statistical analysis of datasets; and explanatory models, based on knowledge of the biological processes underlying fish production.
Multiple regression analysis (a descriptive modelling technique) was used for the analysis of data from 15 integrated rice-fish production experiments with the Nile tilapia (Oreochromis niloticusL.) in the Philippines. Results showed that this technique led to insights that had not been obtained through separate analysis of the experiments. Main drawback of this method was that the models were not applicable to other production environments.
An explanatory model (called Fish Growth Simulator, or FGS) for growth of O. niloticus was developed on the basis of an existing simulation model for the African catfish Clarias gariepinusBurchell (1822). After parameterization and calibration, the model gave good predictions of fish growth in independent datasets. Parameterization and calibration of the same model for the rainbow trout Onchorhynchus mykiss (Walbaum) demonstrated the generality of the model and it was concluded that, provided that enough data are available, the model may be used to predict growth in a wide range of fish species. Food amount and composition, and temperature were the environmental variables upon which the model based its predictions.
FGS was expanded with a dissolved oxygen module to accomodate oxygen as an environmental variable. The module was based on the hypothesis that oxygen is needed in sufficient amounts for aerobic metabolism, and that gill surface area limits the supply of oxygen to fish. The resulting model allowed the simulation of fish growth under low dissolved oxygen concentration and also provided an explanation for differences in the final weight of fishes, both within and between species.
FGS was used for simulation of food and oxygen limitations in waste-fed fish ponds in Honduras, Thailand and Rwanda. The model simulated fish growth for various combinations of environmental conditions: temperature, food availability and dissolved oxygen concentration. Validation, using data from Indonesia and Panama, was not successful because estimates of the food consumption rate in these countries were not reliable.
In the last chapter methodology, the role of oxygen in fish metabolism and growth, model implications for the management of integrated agriculture-aquaculture systems and implications for further work are discussed.
