Prediction of weed density: the increase of error with prediction interval, and the use of long-term prediction for weed management.
Abstract
This paper addresses the errors that are associated with the long-term prediction of weed densities, and the effect of these errors on the performance of weed management decisions based on those long-term predictions. A model of weed population dynamics was constructed and its parameters were estimated from experimental observations of population dynamics of Stellaria media in winter wheat-sugarbeet-winter wheat crop rotations in the Netherlands. The observations showed that estimates of weed population growth rate differed between two locations. The model was used to analyse error propagation for predicted weed densities in an enlarged prediction interval. It is concluded that errors due to an uncertain population growth rate increase linearly with the length of the prediction interval, and thus pose an upper limit to the horizon for long-term predictions. It was shown that a limited ability to predict weed densities does not necessarily impair the practical use of weed population dynamic models in planning for long-term weed control programmes.