当前位置: X-MOL 学术J. Pest Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Long-term seasonal forecasting of a major migrant insect pest: the brown planthopper in the Lower Yangtze River Valley.
Journal of Pest Science ( IF 4.8 ) Pub Date : 2018-07-24 , DOI: 10.1007/s10340-018-1022-9
Gao Hu 1, 2 , Ming-Hong Lu 3 , Don R Reynolds 4, 5 , Hai-Kou Wang 6 , Xiao Chen 1 , Wan-Cai Liu 3 , Feng Zhu 7 , Xiang-Wen Wu 8 , Feng Xia 9 , Miao-Chang Xie 10 , Xia-Nian Cheng 1 , Ka-Sing Lim 5 , Bao-Ping Zhai 1 , Jason W Chapman 1, 2
Affiliation  

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.
更新日期:2018-07-24
down
wechat
bug