Development of a total systems approach to multi-pest management decision analysis

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Montana State University - Bozeman, College of Letters & Science


The concentration of wheat production in the Northern Great Plains has resulted in the development of specialized multitrophic agricultural pest complexes whose members interact in both positive and negative ways. In this context, management recommendations based on the traditional single-species pest control paradigm may lead to undesirable outcomes. Our goal was to develop a modeling framework to make multi-pest management decisions that take into account the existence of direct and indirect interactions among pests. We a Bayesian decision theory approach in combination with a analysis where observed intermediate nodes were replaced with error terms. This model holds several advantages current decision models, in particular it allows intuitive of coefficient estimates as the total, direct and through pest interactions, impact of management on the. We evaluated interactions between Bromus tectorum), Fusarium crown rot, and Cephus cinctus (wheat stem sawfly) as well as assessed the joint response of these pests to wheat seeding rates, cultivar competitiveness, and cultivar stem sawfly tolerance. Results indicate that yield differences be more readily explained as a result of the effects of on pests and multi-pest interactions, rather than just by direct effect of any particular management scheme on yield. Our provides a framework for finding the balance between simplicity and the complexity of the process being modeled, also bridges the gap between making inferences from experimental observational studies and ecological management decisions.




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