Location: Crop Improvement and Protection Research
Title: Timing matters: Remotely sensed vegetation greenness can predict insect vector migration and therefore outbreaks of curly top diseaseAuthor
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LEE, HYOSEOK - University Of California |
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Wintermantel, William - Bill |
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TRUMBLE, JOHN - University Of California |
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NANSEN, CHRISTIAN - University Of California |
Submitted to: Journal of Pest Science
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 2/25/2024 Publication Date: 2/25/2024 Citation: Lee, H., Wintermantel, W.M., Trumble, J.T., Nansen, C. 2024. Timing matters: Remotely sensed vegetation greenness can predict insect vector migration and therefore outbreaks of curly top disease. Journal of Pest Science. https://doi.org/10.1007/s10340-024-01771-4. DOI: https://doi.org/10.1007/s10340-024-01771-4 Interpretive Summary: Many economically important crop diseases are caused by insect-vectored viruses. Outbreaks of plant-pathogenic viruses have become increasingly unpredictable due to changes in migration patterns of the insects that transmit these viruses driven by variations in temperatures, drought, and rainfall that vary among years. Beet leafhoppers are the primary vectors of beet curly top virus (BCTV), a major plant-pathogenic virus in tomato and other crops. In California, beet leafhoppers are known to overwinter in the coastal foothills and migrate into the Central Valley during spring. In this study, we experimentally manipulated drought regimes of individual plants and acquired plant reflectance profiles determine the amount of green coloration in vegetated areas. Plants were experimentally infested with beet leafhoppers, and we found the likelihood of leafhopper migration was inversely correlated with greenness of vegetation for two plant species that serve as common hosts. In related field studies, sticky card trapping at three field locations during two tomato growing seasons found a significant negative correlation between satellite observations of EVI and spring migration timing of beet leafhoppers. A predictive model was developed and used to examine trends in spring migration over a 22 year period and their relationships with the incidence of BCTV symptoms surveyed in the Central Valley. We found that spring migration timing was negatively correlated with the regional incidence of BCTV symptoms. The spring migration model accurately predicted major BCTV outbreaks in 2013 and 2021, years that were characterized by unusually early spring migration from the coastal foothills. Technical Abstract: Many economically important crop diseases are caused by insect-vectored viruses. Outbreaks of plant-pathogenic viruses have become increasingly unpredictable due to changes in migration patterns of insect vectors driven by variations in temperatures, drought, and rainfall that vary among years. Beet leafhoppers (Circulifer tenellus) (Hemiptera: Cicadellidae) are the primary vectors of beet curly top virus (BCTV), a major plant-pathogenic virus in tomato and other crops. In California, beet leafhoppers are known to overwinter in the coastal foothills and migrate into the Central Valley during spring. In this study, we experimentally manipulated drought regimes of individual plants and acquired plant reflectance profiles to generate standardized indices of greenness (enhanced vegetation index, EVI). Plants were experimentally infested with beet leafhoppers, and we found a significantly negative correlation between EVI and flight propensity for two plant species that serve as common hosts. In related field studies, sticky card trapping at three field locations during two tomato growing seasons found a significant negative correlation between satellite observations of EVI and spring migration timing of beet leafhoppers. A predictive model was developed and used to examine trends in spring migration timing over 22 years and their relationships with the incidence of BCTV symptoms surveyed in the Central Valley. We found that spring migration timing was negatively correlated with the regional incidence of BCTV symptoms. The spring migration model accurately predicted major BCTV outbreaks in 2013 and 2021, years that were characterized by unusually early spring migration from the coastal foothills. |