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Title: RUSSIAN WHEAT APHID ECOLOGY AND MODELING IN GREAT PLAINS AGRICULTURAL LANDSCAPES

Author
item Elliott, Norman - Norm
item HEIN, GARY - UNIV OF NEBRASKA
item CARTER, M - NORTH CAROLINA STATE UNIV
item Burd, John
item HOLTZER, T - COLORADO STATE UNIV
item ARMSTRONG, J - COLORADO STATE UNIV

Submitted to: Thomas Say Publications in Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/24/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary: This a review article summarizing available information on population ecology of the Russian wheat aphid and defining areas for future research on that topic. No new research is reported; no interpretive summary is required.

Technical Abstract: The Russian wheat aphid, Diuraphis noxia (Mordvilko), is a major pest of wheat and barley in the southern and central Great Plains. Climate and the spatial and temporal availability of host plants play major roles in determining patterns of abundance and pest status of the aphid in the Great Plains. Oversummering is limited by the abundance and temporal patterns of growth of non-cultivated host plant species. Overwintering is limited primarily by the extremes and duration of cold temperatures. Even though landscape structure plays an important role in Russian wheat aphid population dynamics, determining and predicting how it combines with climate to reproduce observed patterns of Russian wheat aphid abundance is difficult because of the number of interacting variables and the complexity of agricultural landscapes. Simulation models that extrapolate population processes to a landscape or larger geographic scale will play an important role in elucidating how the above-mentioned abiotic and biotic variables interact to generate observed patterns of abundance. Use of remote sensing, geographic information systems, and simulation modeling are required in order to develop spatial population dynamics models with resolution sufficient to permit comprehensive understanding of the aphid's population ecology and prediction of population outbreaks.