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Chinese Journal of Applied Ecology ›› 2011, Vol. 22 ›› Issue (11): 3053-3059.

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Spatial distribution pattern and time series dynamics of Panonychus ulmi Koch in an apple orchard of Liaoning Province, Northeast China.

YAN Wen-tao1, QIU Gui-sheng1, ZHOU Yu-shu2, ZHANG Huai-jiang1, CHEN Han-jie3,ZHANG Ping1, LIU Chi-lin1 , ZHENG Yun-cheng1   

  1. 1Research Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng 125100, Liaoning, China; 2College of Plant Protection, Shenyang Agricultural University, Shenyang 110161, China; 3Zhengzhou Fruit Research Institute,Chinese Academy of Agricultural Sciences, Zhengzhou 450009, China
  • Online:2011-11-18 Published:2011-11-18

Abstract: Panonychus ulmi Koch is one of the important pest insects of apple production in China. To clarify the spatiotemporal dynamics of P. ulmi on the apple tree crowns in an apple orchard of Liaoning, Northeast China, an investigation with random sampling was conducted on the pest mite number at each direction and each layer of the crowns in the whole growth season from May to November 2007. The spatial distribution pattern and time series dynamics of  P. ulmi were analyzed by calculating the indices of aggregation and using the parameters of Iwao model. In the early and mid growth periods of apple tree,  P. ulmi  within whole crown fitted negative binomial distribution, presented an aggregated pattern, and its fundamental component was the group composed of several individuals that attracted each other. The aggregation intensity showed a negative fluctuation with population density, namely, high population density but low patchiness density, and low population density but high patchiness density, and there existed definite differences at different crown directions and layers, i.e., the patchiness density was the highest in south direction and the lowest in west direction, and was higher in mid and lower layers than in upper layer, and in inner layer than in outer layer.

Key words: Panonychus ulmi Koch, spatial distribution pattern, time series dynamics, aggregation