Abstract
Many pests have detrimental effects on wheat; some of the most predominant ones are aphids. Four species of aphids that have damaging effects on cereal crops are: Diuraphis noxia, Metopolophium dirhodum, Rhopalosiphum padi, Sitobion avenae. Count data for these four species were collected over 17 years via suction traps at 12 wheat fields throughout Idaho. Species specific nonlinear, logistic growth models were fit to each suction trap location to model the aphid accumulation process during the wheat growing season. The model was parameterized to provide inference on three main parameters: 1. the maximum accumulated aphid abundance, 2. the onset of aphid accumulation, and 3. the rate of aphid accumulation. Suction trap locations were aggregated into 5 environments using clustering based on climate data. Species specific models were then fit to each of the 5 environments. The maximum yearly aphid abundance was determined to have a lag 1 autocorrelation structure. A full model was then fit to the entire data set using dummy variable regression to analyze the environmental variation in the aphid accumulation process. The four full models were successfully validated both externally and internally. Statistical models similar to that developed here can potentially be used to help us better understand the accumulation process of wheat pest aphids in Idaho.