关键词: 浙江双栉蝠蛾, 毛竹, 空间分布格局, 幼虫密度, 环境指标, 频次比较法

Abstract: This paper dealt with the spatial distribution pattern of Bipectilus zhejiangensis larvae and the relationship between the occurrence and environmental factors in 11 field plots of bamboo (Phyllostachys heterocycla cv. pubescens) forest sampled in Shaowu, Fujian province by positive/counter comparison frequency and discriminant analysis methods. Positive comparative frequency analysis showed that the spatial distribution pattern of B. zhejiangensis larvae fitted the negative binomial distribution in total 550 bamboo shoots sampled in the plots. Taking each plot as a unit and analyzed by counter-comparison frequency method, it was found that plots 1, 2, 4, 5 and 8 fitted the Neyman distribution, plots 7, 9, 10 and 11 fitted the negative binomial distribution, and plots 3 and 6 fitted the Neyman or the negative binomial distribution. The method of discriminant analysis could be 100% exact to discriminant function. The importance of the six environmental indexes from high to low were in the sequence of soil humus (X5), forest health (X6), slope position (X3), slope orientation (X4), bamboo structure (X2) and stand density (X1) according to the F values. It was concluded that the spatial distribution pattern of B. zhejiangensis larvae belongs to the aggregation type with nonuniform distribution whether sampled by bamboo shoot or by plot. The density of B. zhejiangensis larvae in plot with thick soil humus and bad forest sanitation were larger than in other place. The effects of the single index such as the stand density, bamboo structure, slope position and orientations on the density are not significant but their integrated effects are significant. More information can be obtained by the counter-comparison frequency method than by the aggregation index for analyzing spatial distribution pattern of insects.

Key words: comparative frequency analysis, Bipectilus zhejiangensis, Phyllostachys heterocycla cv. pubescens, spatial distribution pattern, larval density, environmental index