Interacting Agricultural Pests and Their Effect on Crop Yield: Application of a Bayesian Decision Theory Approach to the Joint Management of Bromus tectorum and Cephus cinctus

Worldwide, the landscape homogeneity of extensive monocultures that characterizes conventional agriculture has resulted in the development of specialized and interacting multitrophic pest complexes. While integrated pest management emphasizes the need to consider the ecological context where multiple species coexist, management recommendations are often based on single-species tactics. This approach may not provide satisfactory solutions when confronted with the complex interactions occurring between organisms at the same or different trophic levels. Replacement of the single-species management model with more sophisticated, multi-species programs requires an understanding of the direct and indirect interactions occurring between the crop and all categories of pests. We evaluated a modeling framework to make multi-pest management decisions taking into account direct and indirect interactions among species belonging to different trophic levels. We adopted a Bayesian decision theory approach in combination with path analysis to evaluate interactions between Bromus tectorum (downy brome, cheatgrass) and Cephus cinctus (wheat stem sawfly) in wheat (Triticum aestivum) systems. We assessed their joint responses to weed management tactics, seeding rates, and cultivar tolerance to insect stem boring or competition. Our results indicated that C. cinctus oviposition behavior varied as a function of B. tectorum pressure. Crop responses were more readily explained by the joint effects of management tactics on both categories of pests and their interactions than just by the direct impact of any particular management scheme on yield. In accordance, a C. cinctus tolerant variety should be planted at a low seeding rate under high insect pressure. However as B. tectorum levels increase, the C. cinctus tolerant variety should be replaced by a competitive and drought tolerant cultivar at high seeding rates despite C. cinctus infestation. This study exemplifies the necessity of accounting for direct and indirect biological interactions occurring within agroecosystems and propagating this information from the statistical analysis stage to the management stage.