Dynamic modelling of a traditional African chicken production system

A dynamic stochastic model, SimFlock, was developed with the purpose of simulating the dynamics of a traditional African chicken flock at smallholder level. The model simulates outputs, e.g. total number of chickens produced, egg production and net return after entering flock, or area-specific biological parameters. Biological parameters include hatchability, egg production, growth and survival of various age groups, full-grown weights as well as some decision parameters like farmers' need for meat consumption, and slaughtering and selling age of chickens. A simulation job is defined by 'states of nature' (biological parameters specified directly or drawn at random from the hyperparameters), number of replications and number of days to be simulated. Three simulation jobs were selected to demonstrate the use of the model: one with the default settings; one with collection of eggs for 20 days; and one in which growth rate was increased to double. After simulation, the results of each job were compared in relation to total number and weight of chickens produced, egg production and net return. SimFlock could be used as a management or extension tool to identify the biological parameters of major influence on production. Improvement of these parameters will have the largest impact on output.