Population dynamics and management of diamondback moth (Plutella xylostella) in China: the relative contributions of climate, natural enemies and cropping patterns. Issue 2 (23rd December 2015)

• Record Type: Journal Article
• Authors: Li, Z.; Zalucki, M.P.; Yonow, T.; Kriticos, D.J.; Bao, H.; Chen, H.; Hu, Z.; Feng, X.; Furlong, M.J.
• Is Part Of: Bulletin of entomological research. Volume 106:Issue 2(2016)
• Page Start: 197
• Page End: 214
• Publication Date: 2015-12-23
• Subjects: age-structured population modelling, -- biological control, -- crop pest, -- DYMEX, -- IPM, -- population dynamics, -- population outbreaks; Entomology -- Periodicals; 595.7
• DOI: 10.1017/S0007485315001017
• Languages: English
• ISSNs: 0007-4853

Abstract

Abstract: Diamondback moth or DBM is the major pest of Brassica vegetable production worldwide. 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 southwest to northeast China: DBM is, on average, 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. A cohort-based discrete-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.