84th AMS Annual Meeting

Wednesday, 14 January 2004
An Exploratory Study of Corn Earworm Immigration into the Northeast US Via Air Currents
Hall AB
Matthew Welshans, Penn State University, University Park, PA; and S. Fleischer, P. Knight, and D. Miller
The northeast United States accounts for over 100,000 acres of sweet corn, or about 1/3 of the total crop in the United States. The crop in this region is valued at over $147 million according to data from 2000. Insects, such as the corn earworm (Helicoperva zea), European corn borer (Ostrinia nubilalis), and the fall armyworm (Spodoptera frugiperda), can inflict extensive damage, resulting in loss of yield and economic value, as well as excess insecticide usage.

As part of an ongoing research and extension project, a network of over 425 pheromone traps have been set up across the northeastern United States to track trends in the annual reinvasion of corn earworm into this region. Volunteers monitor the number and frequency of captures and record these results weekly. These observations are captured into an online database and analysis tool, PestWatch, that graphically displays the dynamic spatial distribution of the corn earworm over a period of time (www.pestwatch.psu.edu).

It has been hypothesized that two of these pests (H. zea and S. frugiperda) may be carried point-to-point by way of upper air currents. In order to test this hypothesis, we have applied the NOAA Air Resources Laboratory HYSPLIT4 Model. This model uses preexisting weather data from various weather models to produce a predicted trajectory showing changes in pressure, elevation, and parcel velocity.

In this study, the ETA computer weather forecasting model was chosen because of its availability, small grid size, and accurate simulations of short term air motions. . H. zea was chosen as the test species due to it’s widespread distribution in 2002. The model was run once every 12 hours to ensure the most spatial continuity. This was accomplished by backtracking the air motion for every 12 hours such that the beginning point of one model run is the ending point of the next model run. the model results were compared to the actual spread of the corn earworm from the PestWatch observations to analyze trends. Initial comparisons between the HYSPLIT4 model predictions and the actual data show a discernible trend that the corn earworm travels at some height and is impacted by the direction of the air currents. From this information, the general paths of travel may be predicted. Our poster will summarize the results of this exploratory study and show how this information could be used by the agriculture community to prepare for pest infestation and reduce risks to yield and economic losses.

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