Abstract
Rio Grande do Sul is the southern state of Brazil. The Southern part of the Rio Grande do Sul state, an area of approximately the size of England, is part of the Campos sub-region of the Rio de La Plata temperate sub-humid grasslands ecosystem. Beef cattle and the rice crop are the main economic activities in this region.
The main goal of this thesis was to simulate the dynamic nature of the farm with the partnership between finishing beef cattle and the rice crop that can be carried out in Rio Grande do Sul, Brazil. To achieve this goal, crop, livestock and economic models were developed and integrated to simulate farm conditions in the South of the Rio Grande do Sul state
Models as tools for decision support need to be dynamic in concept to simulate the real farm environment. The information base is classified as “natural” and “simulated”. The “natural” results from past experience. The “simulated” is based on quantitative formal scientific information. This work presents a framework that deals with adaptive behaviour as a response to natural and simulated information. Decisions about animals, pasture, soil, land use and economics are incorporated. These decisions impact on the biological and economic models and generate scenarios resulting from these decisions. As the farmer’s decisions are sequential and dynamic, the model simulates the bio-socio-economic environment in which farm decisions occur at established time-steps. The Farm Integrated Decision Model (FIDM) supplies the farmer with information about economic and biological aspects of the farm and asks the farmer about each decision. Therefore, when a farmer takes a decision the “natural” state is a pre-condition of the simulation.
Case study simulations were made, and the results of the proposed methodology are presented to demonstrate the potential use of this approach, generating different scenarios for the farmer. Dialogue between extension worker and farmer permits the interactive evaluation of existing technologies. Flexibility in model construction will allow incorporation of new technologies as and when information becomes available.
