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Early forecasting of rice panicle blast is critical to the management of rice blast. To develop early forecasting models for rice panicle blast, the relationship between the seasonal maximum incidence of rice panicle blast ( PBx) and the PBx in the preceding crop, weather conditions, location, and acreage of susceptible varieties was analyzed. Results revealed that PBx in the preceding crop, acreage of the susceptible varieties in class ( SVC), altitude, weather conditions 120 to 180 days before the PBx date (dbPBx) and 30 to 90 dbPBx were significantly correlated with the PBx. Subsequently, a logistic model and a two-step hurdle model were developed to predict rice panicle blast. The logistic model was developed to predict whether the PBx was 0 or not based on the preceding PBx, altitude, acreage of susceptible varieties, the longest stretch of days with soil temperatures between 16 and 24°C for the period 120 to 150 dbPBx, and the longest stretch of rainy days in the period 120 to 180 dbPBx. The hurdle model predicted if the PBx was greater than 0 at the first step, and if the prediction was greater than 0, then a regression model was developed for predicting PBx based on the preceding PBx, SVC, altitude, and weather data 180 to 30 dbPBx. Validation with the test datasets showed that the logistic model could correctly predict whether PBx was 0 at a mean test accuracy of 78.39% and that the absolute prediction error of PBx by the two-step hurdle model was smaller than 6.16% for 90% of the records. The model developed in this study will be helpful in management decisions for rice growers and policy makers and offer a useful basis for further studies on the epidemiology and forecasting of rice panicle blast.

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. Electronic supplementary material The online version of this article (10.1007/s10340-018-1022-9) contains supplementary material, which is available to authorized users.

Sometimes, extreme weather is vital for the population survival of migratory insects by causing sudden population collapse or outbreak. Several studies have shown that rice planthopper migration was significantly influenced by typhoons in eastern Asia. Most typhoons occur in the summer, especially in August. In August, brown planthopper Nilaparvata lugens (Stal) migrates northward or southward depending on wind direction, and thus typhoons can potentially influence its migration process and population distribution. However, this has not yet been studied. This paper reported a case study on the effects of Typhoon Soudelor on the summer migration of N. lugens in eastern China in 2015. The migration pathways of N. lugens were reconstructed for the period under the influence of a typhoon by calculating the trajectories and migration events in 8 counties of the Yangtze River Valley region with ancillary information. Trajectory modelling showed that most migrants took short distance migrations (less than 200 km) under the influence of the Typhoon Soudelor. Numerous N. lugens migrants were concentrated and deposited at the rear of the typhoon during the last 5 days of Typhoon Soudelor on August 9–13 due to horizontal convergence, and this led to an outbreak population. These results indicated that the N. lugens population was redistributed by the typhoon in the summer and that the population dynamics at the rear of a typhoon should be kept under close surveillance. This study provided insight into migratory organisms adapting to atmospheric features. This article is protected by copyright. All rights reserved

Southern rice black-streaked dwarf virus (SRBSDV) caused serious rice losses. After the first outbreak in 2009 in northern Vietnam and southern China, the virus ravaged crops again on enormous scales in 2010, but infections have decreased sharply since 2011. We presumed that the sudden epidemics and fadeout of SRBSDV would be closely related to the migratory events of the insect vector, Sogatella furcifera. This study sought the source area of SRBSDV using the trajectory analysis method, and revealed the relationship between SRBSDV dynamics and migration of S. furcifera populations via an in-depth analysis of meteorological background of S. furcifera migration fields. The results showed that Northern Vietnam was the direct virus source area of the SRBSDV infection in China, and South Central Coast of Vietnam was the original source area of SRBSDV. Southwesterly winds were prevalent in spring of 2010 and carried large numbers of viruliferous S. furcifera to China from northern Vietnam. This infestation of S. furcifera was the direct cause of the SRBSDV outbreak in China in 2010. In 2011, the winter-spring temperatures were abnormally low and southeasterly and easterly winds dominated; therefore, the number of viruliferous S. furcifera that entered China was small, and consequently, the occurrence area of SRBSDV was rapidly reduced. The return of viruliferous S. furcifera to South Central Coast of Vietnam was an important factor that affected the occurrence scale of SRBSDV in the following year.

Seasonal weather systems that establish prevailing winds and seasonal rainfall on a large scale largely determine insect migration patterns, especially for micro-insects with completely windborne migration. Recent studies indicated that the summer migration of the brown planthopper (BPH, Nilaparvata lugens) in eastern China is related to the strength and position of the Western Pacific Subtropical High-Pressure (WPSH) system and its associated wind and rainfall patterns. Compared with the BPH, the white-backed planthopper (WBPH, Sogatella furcifera) has a similar diet, analogous body size, and strong long-distance migration ability. Thus, the migration pattern for the WBPH can be speculated to be similar to that of the BPH. However, the migration pattern of the WBPH and how this pattern relates to climatic conditions have scarcely been described. Based on almost three decades of data (1977&ndash, 2003), it was suggested that the WBPH in southern China (south of approximately 27&deg, N) migrates into the middle and lower reaches of the Yangtze River after the abrupt movements of the WPSH in mid-June, similar to the BPH. By contrast, the emigration of the WBPH in southern China begins in late May. Further analysis indicated that the migration of the WBPH in late May and early June was short or unsuccessful due to heavy precipitation during the preflood season in southern China from late May to middle June. The results herein demonstrate the differences in migration patterns between two rice planthoppers in the eastern Asia migration arena. We also provide new information that could assist with forecasting outbreaks and implementing control measures against these migratory pests.

Rice stripe virus (RSV) disease causes severe damage to rice plants. RSV is transmitted via Laodelphax striatellus and is found in hot and humid environmental conditions. While the occurrence and prevalence of RSV are highly dependent on the amount and viruliferous rate of L. striatellus during the early paddy stage, they are also closely associated with temporal and spatial distributions of meteorological elements in the aerial layer. The wind speed, relative humidity, and insolation are the three important meteorological parameters associated with RSV occurrence and epidemics. High wind speed ensures enough ventilation and causes dryness in the field; hence, RSV cannot cause pathogenicity. However, high relative humidity is beneficial for the occurrence and spreading of RSV. Furthermore, a long insolation duration causes evaporation and drying and is not conducive to RSV breeding and spreading. This virus is responsible for causing rice cancer, one of the most serious diseases in rice, in the middle and lower reaches of the Yangtze River, China. In this study, the data related to RSV and its viruliferous pest (L. striatellus) obtained from the Dongtai Plant Protection Station and daily meteorological data obtained from Dongtai Meteorological Observatory Station in Jiangsu Province between 2002 and 2010 were analyzed to assess the impact of biological and meteorological factors on RSV occurrence and prevalence. Several key parameters were identified based on correlation analyses between the rate of diseased plants and the amount of viruliferous L. striatellus, as well as between the rate of diseased plants and meteorological elements. Short-term forecasts of the rate of plants affected by the rice stripe disease per pentad were conducted using three different models: stepwise regression, back propagation neural network, and support vector machines. The accuracies of the three short-term forecasting models were determined. The study results were as follows: First, the amount of viruliferous L. striatellus was identified as the key biological factor, and relative humidity, wind speed, and insolation duration in the aerial layer were the most important meteorological factors. These two groups of factors were the key predictors of the rate of plant infection with the RSV in the current pentad. Second, the average prediction accuracies of stepwise regression, a back propagation neural network, and support vector machines were 77.35%, 93.75%, and 98.95%, respectively. The latter two models were more reliable and thus were considered useful for developing forecasting models for predicting the short-term pentad rate of plants affected by the RSV at a single station. Third, the accuracies of retrospective testing and forward forecasting of both the back propagation neural network and support vector machines were considerably better than that of stepwise regression for the short-term forecasts of the pentad rate of rice stripe disease; in particular, support vector machines were more accurate and stable than the back propagation neural network.

Mass landings of migrating white-backed planthopper, Sogatella furcifera (Horváth), can lead to severe outbreaks that cause heavy losses for rice production in East Asia. South-central China is the main infestation area on the annual migration loop of S. furcifera between the northern Indo-China Peninsula and mainland China; however, rice planthopper species are not able to survive in this region over winter. In this study, a trajectory analysis of movements from population source areas and a spatiotemporal dynamic analysis of mesoscale and synoptic weather conditions from 7 to 10 May 2012 were conducted using the weather research and forecasting (WRF) model to identify source areas of immigrants and determine how weather and topographic terrain influence insect landing. A sensitivity experiment was conducted with reduced topography using the WRF model to explain the associations among rainfall, topography, and light-trap catches of S. furcifera. The trajectory modeling results suggest that the source areas of S. furcifera immigrants into south-central China from 8 to 10 May were mainly southern Guangxi, northern Vietnam, and north-central Vietnam. The appearance of enormous catches of immigrant S. furcifera coincided with a period of rainstorms. The formation of transporting southerly winds was strongly associated with the topographic terrain. Additionally, the rainfall distribution and intensity over south-central China significantly decreased when topography was reduced in the model and were directly affected by wind circulation, which was associated with mountainous terrain that caused strong convection. This study indicates that migrating populations of S. furcifera were carried by the southwesterly low-level jets and that topographically induced convergent winds, precipitation, low temperatures, and wind shear acted as key factors that led to massive landings.

Windborne migration of insects is significantly influenced by meteorological factors and phenomena, such as seasonal atmospheric circulation. Large‐scale movement of air provides the background for all weather and climate events. Hence, population abundances of migratory insects may fluctuate due to variations in seasonal atmospheric circulation, but little is known about this process. The western Pacific subtropical high pressure (WPSH) is the major circulation system that affects weather and climate in eastern Asia. Annual migration of the brown planthopper (BPH, Nilaparvata lugens [Stål]) in East Asia and the WPSH was investigated. Based on almost three decades of data (1977–2003), it was determined that swarms of BPH migrate into the lower Yangtze Valley in July and form an outbreak population under strong WPSH conditions. An intense WPSH enhanced southwesterly airstreams in southern China to provide a high‐speed vehicle promoting BPH long‐distance migration. In addition, increased precipitation in the Yangtze and Huai valleys formed a rain‐belt barrier that forced BPH landing in the lower Yangtze Valley. Results herein demonstrate that the population abundance of a migratory insect fluctuated in response to climatic conditions caused by seasonal atmospheric circulations.&nbsp

Sometimes, extreme weather is vital for the population survival of migratory insects by causing sudden population collapse or outbreak. Several studies have shown that rice planthopper migration was significantly influenced by typhoons in eastern Asia. Most typhoons occur in the summer, especially in August. In August, brown planthopper Nilaparvata lugens (Stål) migrates northward or southward depending on wind direction, and thus typhoons can potentially influence its migration process and population distribution. However, this has not yet been studied. This paper reported a case study on the effects of Typhoon Soudelor on the summer migration of N. lugens in eastern China in 2015. The migration pathways of N. lugens were reconstructed for the period under the influence of a typhoon by calculating the trajectories and migration events in eight counties of the Yangtze River Valley region with ancillary information. Trajectory modelling showed that most migrants took short distance migrations (less than 200 km) under the influence of the Typhoon Soudelor. Numerous N. lugens migrants were concentrated and deposited at the rear of the typhoon during the last 5 days of Typhoon Soudelor on August 9-13 due to horizontal convergence, and this led to an outbreak population. These results indicated that the N. lugens population was redistributed by the typhoon in the summer and that the population dynamics at the rear of a typhoon should be kept under close surveillance. This study provided insight into migratory organisms adapting to atmospheric features.

An effective control strategy for migratory pests is difficult to implement because the cause of infestation (i.e., immigration or local reproduction) is often not established. In particular, the outbreak mechanisms of the brown planthopper, Nilaparvata lugens (Stal), an insect causing massive losses in rice fields in the Yangtze River Delta in China, are frequently unclear. Field surveys of N. lugens were performed in Jiangsu and Zhejiang Provinces in 2008 to 2010 and related historical data from 2003 onwards were collected and analyzed to clarify the cause of these infestations. Results showed that outbreaks of N. lugens in the Yangtze River Delta were mostly associated with an extremely high increase in population. Thus, reproduction rather than immigration from distant sources were the cause of the infestations. Although mass migration occurred late in the season (late August and early September), the source areas of N. lugens catches in the Yangtze River Delta were mainly located in nearby areas, including the Yangtze River Delta itself, Anhui and northern Jiangxi Provinces. These regions collectively form the lower-middle reaches of the Yangtze River, and the late migration can thus be considered as an internal bioflow within one population.

Mass landings of migrating white-backed planthopper, Sogatella furcifera (Horvath), can lead to severe outbreaks that cause heavy losses for rice production in East Asia. South-central China is the main infestation area on the annual migration loop of S. furcifera between the northern Indo-China Peninsula and mainland China; however, rice planthopper species are not able to survive in this region over winter. In this study, a trajectory analysis of movements from population source areas and a spatiotemporal dynamic analysis of mesoscale and synoptic weather conditions from 7 to 10 May 2012 were conducted using the weather research and forecasting (WRF) model to identify source areas of immigrants and determine how weather and topographic terrain influence insect landing. A sensitivity experiment was conducted with reduced topography using the WRF model to explain the associations among rainfall, topography, and light-trap catches of S. furcifera. The trajectory modeling results suggest that the source areas of S. furcifera immigrants into south-central China from 8 to 10 May were mainly southern Guangxi, northern Vietnam, and north-central Vietnam. The appearance of enormous catches of immigrant S. furcifera coincided with a period of rainstorms. The formation of transporting southerly winds was strongly associated with the topographic terrain. Additionally, the rainfall distribution and intensity over south-central China significantly decreased when topography was reduced in the model and were directly affected by wind circulation, which was associated with mountainous terrain that caused strong convection. This study indicates that migrating populations of S. furcifera were carried by the southwesterly low-level jets and that topographically induced convergent winds, precipitation, low temperatures, and wind shear acted as key factors that led to massive landings.