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Prediction of airborne immigration of rice insect pests
Akira Otuka, Tomonari Watanabe, Yoshito Suzuki, Masaya Matsumura, Akiko Furuno, and Masamichi Chino
The whitebacked planthopper Sogatella furcifera and the
brown planthopper Nilaparvata lugens are major pests of rice
in eastern Asia. They migrate from southern China into Japan
mainly in the Bai-u rainy season in June to July every year
(Seino et al 1987). Generally, the prediction of planthopper
migration provides farmers and plant protection advisers with
information about the migration source as well as area of migration.
It is especially important to know the migration source,
which helps to understand the immigrant’s characteristics such
as biotype, pesticide resistance, etc. Conventional prediction
methods used 6- or 12-hour two-dimensional wind data
(Rosenberg and Magor 1983, Watanabe et al 1990), but their
prediction quality was limited. A three-dimensional simulation
method using a boundary layer model was developed
(Turner et al 1999). However, a prediction system based on
this model has not yet been developed.
To achieve high-precision migration prediction, a realtime
prediction system was developed using three-dimensional
simulation models. This paper presents the simulation method
and its evaluation results.
Materials and methods
Planthopper behavior
Sogatella furcifera and N. lugens are tiny insects about 3–4
mm in size and 1–3 mg in weight (Ohkubo 1973). Many field
observations have shown that the planthoppers take off at either
dusk or dawn (e.g., Ohkubo and Kisimoto 1971). A radar
observation showed that S. furcifera and N. lugens flew to an
altitude of several hundred to 1,000 m above the ground at an
estimated upward speed of 0.2 m s –1 (Riley et al 1991). The
species fly at about 1 m s –1 , whereas the wind speed when
migration occurs is typically more than 10 m s –1 (Seino et al
1987). Laboratory experiments of tethered N. lugens adults
indicated that they have the ability to fly for up to 23 hours in
air of high humidity (Ohkubo 1973). N. lugens ceases flying
at cooler temperatures; half of them stop beating their wings
when the air temperature is below 16.5 °C (Ohkubo 1973).
Their postmigration landing process is not yet fully understood.
Planthopper migration simulation model
Takeoff area. Because information on the planthopper’s density
in source regions was not available, it was assumed that
the population density in June to July was high enough for the
planthopper to take off from source regions. In the simulation,
several takeoff areas of 50–100 km 2 were set up in southern
China and Taiwan. These takeoff areas were located in paddy
fields, and covered the major source regions.
Model. The migration simulation model originates from
a particle dispersion model, GEARN, developed by the Japan
Atomic Energy Research Institute (JAERI), which calculates
atmospheric dispersion of radioactive particles in case of a
nuclear accident (Ishikawa and Chino 1991). GEARN was
modified to model the planthopper’s migration behavior. Figure
1 shows a schematic model. This model calculates the position
of many planthoppers, and doesn’t discriminate between
N. lugens and S. furcifera. Nearly 2,000 planthoppers for each
takeoff area took off randomly within the area at 10 or 21 UTC
(Universal Time Coordinate), which locally corresponds to
dusk or dawn, respectively. They then flew up at a speed of
0.2 m s –1 for 1 hour. Taking off ceased 1 hour later, at 11 or 22
UTC. During their flight over the sea, the planthoppers moved
at the same speed as the wind because they are slow fliers.
Vertical diffusion was taken into account by a random walk
model, but horizontal diffusion was not because preliminary
results showed too much horizontal diffusion over Japan. Since
the planthoppers don’t like cooler air, a temperature ceiling of
16.5 ºC was set up, and they could not go beyond that ceiling.
Wind, temperature, and vertical diffusion coefficient data were
given by numerical weather forecasts. Simulation duration was
48 h. The model calculated the relative aerial density of
planthoppers based on their position on the model grid. The
horizontal resolution was 33 km. Areas of relative density larger
than zero in the lowest level, which was less than 100 m above
the ground, were used for prediction. These areas were called
“migration clouds” (Fig. 2).
Prediction system
First, the latest meteorological data were supplied online to an
advanced numerical weather prediction model, MM5 (Grell
et al 1994). The model forecast atmospheric fields for the next
72 hours at 1-hour intervals. Second, these forecast fields were
supplied to the planthopper migration simulation model,
GEARN, which calculated displacement of a number of modeled
planthoppers and predicted relative aerial density. The
data were converted to PDF files at 3-hour intervals and sent
to the project’s Web site. These processes were conducted automatically.
The system predicted migrations over the next two
days. The maps of relative aerial density provided information
on the timing and area of arrivals. The system also gave
possible migration sources.
Results and discussion
Evaluation
Figure 2 shows an example of predicted migration clouds. An
evaluation was conducted using daily catch data obtained at
three sites in Kyushu, western Japan, in 2003 and 2004. The
sites were Saga (33.17°N, 130.33°E), Kumamoto (32.95°N,
130.78°E), and Kagoshima (31.52°N, 130.50°E). The system
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