Özet:
In this study, two simulation models are built to study the long term usefulness ofgenetically modified agriculture via two GM crops: insect resistant (Bt-corn) and herbicide tolerant (HT canola). Using system dynamics modeling methodology, agriculturalsustainability is analyzed under different policies and scenarios, by focusing on thefundamental feedback mechanisms in the environment. The most critical feedbackmechanism is the evolution of resistance in pests and weeds via natural selection. The effect of Bt-crops on increasing the rate of pests' resistance evolution is found to benotable. Depending on the initial level of resistance in the pest population, resistance canevolve in ten seasons of Bt-corn farming whereas it would take fifty seasons withconventional pesticides under the same conditions. Refuge strategy is tested under different scenarios. Results show that benefits from the refuge strategy declineconsiderably if pest develops cross-resistance to the pesticide that is used to treat therefuge. Furthermore, refuge strategy becomes futile if heterozygote pests show some levelof resistance or if the initial level of resistance alleles in the pest population is high and there is no "fitness cost" of resistance. Agriculture with HT crops is analyzed bysimultaneous comparison with conventional crops. Two cases of herbicide use areanalyzed: in the first case, herbicide is sprayed as a function of weed density and in thesecond one it is used at a predetermined amount. It is found that superweed emergence increases the rate of resistance evolution in the weed population. Under the constantherbicide strategy, GM crop turns out to be more effective than the conventional one, inspite of superweeds. However, this strategy results in a higher rate of resistancedevelopment in weeds and more herbicide usage compared to the variable herbicide strategy. In terms of long term cumulative yield losses, rate of resistance development andherbicide usage, the best policy is discovered to be planting conventional crops with thevariable herbicide application strategy.
