Structure of a dynamic simulation model for beef cattle production systems

A dynamic deterministic model for simulating beef cattle production systems is developed to evaluate the effects of production traits and management strategies on the bioeconomic efficiency of beef production systems. The model, named Alberta Beef Production Simulation System (ABPSS), is composed of four major submodels: herd inventory, nutrient requirement, forage production, and economic submodels. The herd inventory submodel is used to simulate population dynamics and feed requirements in the herd. The nutrient requirements submodel is mainly based on the 1996 version of the National Research Council (NRC). It is used to evaluate nutrients and feed requirements for calves and cows depending on their physiological status (maintenance, growth, lactation and gestation) and the climatic condition. The forage production submodel is used to predict forage growth rate, cattle grazing rate, available forage biomass and total hectares required for grazing. The economic submodel measures bioeconomic efficiency, as net return per cow, by subtracting total cost from total return. The nutrient requirements predicted by ABPSS were compared with those recommended by the NRC for testing. The results that were predicted by the NRC model and ABPSS model were similar, as expected. Sensitivity analyses showed that cow mature weight, milk production, calf weaning weight and feed prices were the most critical input parameters in the model. It must be noted that the model was developed based on available experimental results and data fi om the literature and, due to the unavailability of a suitable data set, the model could not be validated. We suggest that the ABPSS has the potential for providing a useful method for simultaneous consideration of many factors in an integrated system, which could be helpful to beef cattle extension specialists and cow-calf production managers for assessing the potential effects of different management and selection strategies on bioeconomic efficiency.