Economic thresholds (ET) were originally developed and applied to insect management during the 1970s. Traditional ET methodologies have sporadic success in weed management scenarios and are not globally appropriate for weed management especially in presence of herbicide resistant species. Historically, the economic threshold equation has been static and myopic, ignoring any multiple-period impact or the soil seed bank. The evolution of herbicide resistant weed species has prompted scientists to reconsider economic thresholds for weed management; and intuitively have chosen zero-tolerance for potentially herbicide-resistant weed species. The weed science and economics literature addressing resistant weed management supports zero-tolerance, especially when dynamic optimization techniques were applied to the problem. Although dynamic programming techniques do not equate to zero-tolerance recommendations, single-period static cost-benefit analyses tend to support non-zero economic thresholds in scenarios where zero-tolerance was the optimum strategy. The objectives were to present an ET model suitable for accurately modeling weed control strategies with herbicide resistant species. Preliminary results suggest the multiple-season dynamic framework is the best management practice for weed management.


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