Abstract

(1) A simulation model of brown planthopper (BPH) (Nilaparvata lugens Stal.) population dynamics on rice in Zhejiang Province, China, was constructed using field population data from this region together with information from the literature. (2) The purpose of the model was to assess the performance of BPH management options with a view to improving current practices. In this paper the model is described and its predictions compared with independent sets of field data. (3) For ten data sets, representing a range of BPH densities, the time of the peak in the BPH population was predicted within 5 days in nine cases (accuracy of observations + 5 days). The density of the population at its peak was predicted within 20% of the observed in seven cases. (4) Compared with the regression models currently used to predict BPH outbreaks, the simulation model was much more accurate when tested with the same data. The regression models use only the density of BPH early in the season. The simulation model also takes into account seasonal temperatures, the effects of transplanting time, and the pattern of BPH immigration into the crop. (5) Model parameters were varied within realistic limits in order to determine the sensitivity of the model. The model was sensitive to changes in BPH mortality, but a constant daily mortality rate, representing the effects of natural enemies, was sufficient to predict field population changes. (6) Summer and autumn temperatures, rate and pattern of BPH immigration, and transplanting time all had a significant impact on the size of modelled BPH populations. A cool summer, warm autumn, early transplanting time, and short concentrated period of BPH immigration, should result in damaging BPH populations even when the rate of immigration is moderately low.

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