[ Objective ] The paper was to study the spatial distribution of Endoclyta signifer Walker Larva. [ Method] The larvae distribution in eucalyptus planta- tion in Beiliu and Luchuan counties of Guangxi province were in...[ Objective ] The paper was to study the spatial distribution of Endoclyta signifer Walker Larva. [ Method] The larvae distribution in eucalyptus planta- tion in Beiliu and Luchuan counties of Guangxi province were investigated. Ten standard plots were set, and the spatial distribution pattern of E. signifer larva was confirmed using six different aggregation indexes and regression model analysis method. [ Result] The larvae mainly distributed in the base of tnmk lower than 1 m, and its spatial distribution pattern was mainly aggregated distribution, which was caused by the enviromnental factors. The optimum sampling formula of E. signifer larva under different population densities was n = t2 （ 1.1/m ＋ 0. 674 4）/D2, and limited sequential sampling decision model was T＇0（n）, T＇0（n） = n ＋ 1. 332√n（ m0 = 1 ）. [ Conclusion] The result provided scientific basis for sampling and forecasting of E. signifier.展开更多
基金Supported by Natural Science Foundation of Guangxi Province "OccurrenceMechanism of Major Pests and Diseases in Eucalypt Plantations"(GKZ0832093)~~
文摘[ Objective ] The paper was to study the spatial distribution of Endoclyta signifer Walker Larva. [ Method] The larvae distribution in eucalyptus planta- tion in Beiliu and Luchuan counties of Guangxi province were investigated. Ten standard plots were set, and the spatial distribution pattern of E. signifer larva was confirmed using six different aggregation indexes and regression model analysis method. [ Result] The larvae mainly distributed in the base of tnmk lower than 1 m, and its spatial distribution pattern was mainly aggregated distribution, which was caused by the enviromnental factors. The optimum sampling formula of E. signifer larva under different population densities was n = t2 （ 1.1/m ＋ 0. 674 4）/D2, and limited sequential sampling decision model was T＇0（n）, T＇0（n） = n ＋ 1. 332√n（ m0 = 1 ）. [ Conclusion] The result provided scientific basis for sampling and forecasting of E. signifier.
