Abstract
Abstract In this study, we developed a series of logistic regression models for forecasting gypsy moth defoliation. The models were parameterized by using data collected over a small scaled 100m× 100m gridarea; the independent variables included egg mass density, male moth trap, previous year defoliation, and distance to the nearest cell which was defoliated in the previous year. We simulated the decision‐making by using these models; this method essentially simulated the application of current gypsy moth management decision‐making. The results indicated that these models can be more reliably applied to actual management decision.
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