Weeds are an important factor in every agronomic system. The Weed Seed Wizard is a simulation model that has been developed to help co-ordinate management of weed seed within the seedbank. The model uses field management and weather records, and simulation of important aspects of seed biology, to track and predict the number, ages, soil depth, dormancy levels, viability and germination of seeds in the soil, in order to predict the amount of weeds appearing each year. In this paper, we explain the structure of the model and discuss how it can simulate the effect of decisions regarding choice of crop, sowing date, seeding rate, tillage, grazing management and herbicide application on weed germination, weed density, crop yield and the long-term sustainability of the system. We also explain how the seed dormancy, germination requirements, competitiveness, and herbicide resistance of different weed species or populations can strongly affect the dynamics of the system, and thus the choice of an appropriate management strategy.

Results from a series of related field trials confirm that Western Australian crop varieties do not increase screenings with increased seeding rates contrary to the general belief held by farmers. This has management implications for weed control as increasing the crop density can substantially reduce weed growth and seed production in the absence of in-crop herbicides. In one trial, seeding rates of up to 400 kg ha of 4 cereals (oats, barley, wheat and triticale) were investigated as a management tool to control annual ryegrass and wild radish. All 4 cereals were successful in reducing weed seed production to manageable levels at high seeding rates. The yields of both wheat and triticale decreased when seeding rates increased, due to the extremely dry finish to the season in 1998, but only triticale increased screenings. The earlier maturing oats and barley were unaffected. Other trials investigating seeding rates and/or seeding pattern and row spacing with different varieties of wheat have corroborated the uniformity of screenings with seeding density.