Population dynamics and management of diamondback moth (Plutella xylostella) in China: the relative contributions of climate, natural enemies and cropping patterns
文献类型： 外文期刊
作者： Li, Z. 1 ; Zalucki, M. P. 2 ; Yonow, T. 3 ; Kriticos, D. J. 3 ; Bao, H. 1 ; Chen, H. 1 ; Hu, Z. 1 ; Feng, X. 1 ; Furlong, M. 1 ;
作者机构： 1.Guangdong Acad Agr Sci, Inst Plant Protect, Guangzhou 510640, Guangdong, Peoples R China
2.Univ Queensland, Sch Biol Sci, Brisbane, Qld 4072, Australia
3.CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia
关键词： age-structured population modelling;biological control;crop pest;DYMEX;IPM;population dynamics;population outbreaks
期刊名称：BULLETIN OF ENTOMOLOGICAL RESEARCH （ 影响因子：1.75； 五年影响因子：2.007 ）
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收录情况： SCI
摘要： Diamondback moth or DBM is the major pest of Brassica vegetable production world-wide. Control has relied on insecticides, and DBM resistance to these compounds has evolved rapidly. We review and summarize data on DBM population dynamics across a large latitudinal gradient from south west to northeast China: DBMis, onaverage, more common in southern locations than in northern locations. The species' phenology is consistent: in southern and central locations there is a decline during hot summer months, while in the north, the species can only exist in the summer following migrations from the south. Acohort-baseddiscrete-time model, driven by daily maximum and minimum temperatures and rainfall, which was built using the DYMEX modelling software, captures the age-structured population dynamics of DBM at representative locations, with year round cropping and threshold-based insecticide applications. The scale of the simulated pest problem varies with cropping practices. Local production breaks and strict post-harvest crop hygiene are associated with lower DBM populations. Biological control appears to improve the management of DBM. Of the management strategies explored, non-threshold based applications of insecticides with reduced spray efficacy (due to poor application or resistance) appear the least effective. The model simulates the phenology and abundance patterns in the population dynamics across the climatic gradient in China reasonably well. With planned improvements, and backed by a system of field sampling and weather inputs, it should serve well as a platform for a local pest forecast system, spanning the range of DBM in China, and perhaps elsewhere.
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