Hu, Gao, Lu, Ming-Hong, Reynolds, Don R. ORCID: 0000-0001-8749-7491 , Wang, Hai-Kou, Chen, Xiao, Liu, Wan-Cai, Zhu, Feng, Wu, Xiang-Wen, Xia, Feng, Xie, Miao-Chang, Cheng, Xia-Nian, Lim, Ka-Sing, Zhai, Bao-Ping and Chapman, Jason W. (2018) Long-term seasonal forecasting of a major migrant insect pest: the brown planthopper in the Lower Yangtze River Valley. Journal of Pest Science, 92 (2). pp. 417-428. ISSN 1612-4758 (Print), 1612-4766 (Online) (doi:https://doi.org/10.1007/s10340-018-1022-9)

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Abstract

Rice planthoppers and associated virus diseases have become the most important pests threatening food security in China and other Asian countries, incurring costs of hundreds of millions of US dollars annually in rice losses, and in expensive, environmentally harmful, and often futile control efforts. The most economically damaging species, the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae), cannot overwinter in temperate East Asia, and infestations there are initiated by several waves of windborne spring or summer migrants originating from tropical areas in Indochina. The interaction of these waves of migrants and synoptic weather patterns, driven by the semi-permanent western Pacific subtropical high-pressure (WPSH) system, is of critical importance in forecasting the timing and intensity of immigration events and determining the seriousness of subsequent planthopper build-up in the rice crop. We analysed a 26-year data set from a standardised light trap network in Southern China, showing that planthopper aerial transport and concentration processes are associated with the characteristics (strength and position) of the WPSH in the year concerned. Then, using N. lugens abundance in source areas and indices of WPSH intensity or related sea surface temperature anomalies, we developed a model to predict planthopper numbers immigrating into the key rice-growing area of the Lower Yangtze Valley. We also demonstrate that these WPSH-related climatic indices combined with early-season planthopper catches can be used to forecast, several months in advance, the severity of that season’s N. lugens infestations (the correlation between model predictions and outcomes was 0.59), thus allowing time for effective control measures to be implemented.

Item Type:	Article
Additional Information:	© The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Uncontrolled Keywords:	Nilaparvata lugens, Windborne insect migration, Atmospheric circulation, Rice pests, Planthopper risk prediction, Western Pacific subtropical high-pressure system
Subjects:	S Agriculture > S Agriculture (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Natural Resources Institute Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Last Modified:	13 May 2019 15:27
URI:	http://gala.gre.ac.uk/id/eprint/21220

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