Submitted to: Journal of Economic Entomology
Publication Type: Peer reviewed journal
Publication Acceptance Date: 6/8/2000
Publication Date: 6/12/2001
Citation: Mitchell, P.D., Riedell, W.E. 2001. Stochastic dynamic population model for northern corn rootworm (coleoptera:chrysomelidae). Journal of Economic Entomology 94:599-608. Interpretive Summary: Corn rootworms continue to be the most damaging insect pest complex of corn in the United States. Northern corn rootworm and western corn rootworm are the main species of economic concern in the U.S. corn belt. Throughout this region western corn rootworm is generally the more problematic species, but the northern corn rootworm persists and in some areas it predominates. Recent developments have renewed interest in corn rootworm population models. Both northern and western corn rootworm have adapted to common corn rotations to become problems even in first-year corn. Seed companies are currently field testing transgenic corn resistant to corn rootworm, and resistance management strategies will be part of the registration process. Rotational resistance and transgenics need to be incorporated into integrated pest management. Thus, scientific, policy, and economic questions arising from these and similar developments can be addressed with corn rootworm population models. The objectives of this study were to develop a multiple season model of northern corn rootworm population dynamics, make this model stochastic, and evaluate model performance.
Technical Abstract: A stochastic dynamic population model for the complete life cycle of northern corn rootworm, Diabrotica barberi Smith & Lawrence, is described. Adult population dynamics from emergence to oviposition are based on a published single-season model for which temperature- dependent development and age-dependent advancement determine adult population dynamics and oviposition. Randomly generated daily temperatures make this model component stochastic. Stochastic hatch is 50 plus or minus 8 percent. A stochastic nonlinear density- dependent larval survival model is estimated using field data from artificial infestation experiments. A regional model of corn phenology is estimated to incorporate the effect of dispersal on adult mortality. Random daily weather is generated using parameters for Brookings, SD. Model performance is evaluated with deterministic simulations, which show that the population converges to zero unless adult mortality is reduced by the availability of corn pollen from the regional model of corn phenology. Stochastic model performance is evaluated with stochastic daily weather, egg hatch, and larval survival in various combinations. Sensitivity analysis is conducted to evaluate model responsiveness to each parameter. Model results are generally consistent with published data.