Short communication. Integration of emergence and population dynamic models for long term weed management using wild oat (Avena fatua L.) as an example

Weed emergence models and weed population models have shown to be important tools for decision making. However, there have been no attempts to integrate a weed emergence model with a population dynamics model to build an improved model with increased predictive capacity. In this paper, a method of integrating both types of model is presented and an application building a mathematical model based on previously reported seedling emergence and population dynamics data to simulate cohort-dependent population dynamics of wild oat is given. Three management scenarios (S1, S2, S3) were considered. In S1, farmers are not aware of the time of weed emergence make control decisions as a stochastic process. Under S2, farmers are aware of the time of weed emergence and make decisions considering the time of emergence. The effect of 100% control when 80, 90, 95 and 100% of wild oats had emerged was examined. In S3 there was «no control». In the absence of control the wild oat population grew in a sigmoid manner and reached an equilibrium density at about 16,000 seeds m in the soil seed bank. In S1, simulation resulted in an average population equilibrium at about 13,000 seeds m. This equilibrium position represented only a 19% reduction of the carrying capacity of the system. In S2, the 95% and 100% emerged weeds, produced population extinction after 16 and 6 years, respectively. In S2 with 90% and 80% of emerged weeds the carrying capacity of the system was reduced by 95% and 28%, respectively. Scenario S2 with minimum uncertainty always gave better results than S1. Integrating simple population models with emergence models would help farmers in long-term decision making for weed management. Additional key words: degree-days, Gompertz model, life-cycle model, logistic model, simulation, weed control.