Temperature is an important driver of insect growth and development and is widely utilized to predict insect pest activity in agricultural systems. For ambrosia beetle pests, accurately forecasting mass attacks could improve management by targeting the most damaging flight period. Xylosandrus germanus Blandford (Coleoptera: Curculionidae) is an invasive ambrosia beetle with a broad host range, including fruit trees. In New York apple orchards, X. germanus exhibits 2 dispersal flights each year, with the most pronounced occurring in spring. During the spring flight, females often engage in synchronized mass attacks, which lead to tree dieback and economic losses in apple production. However, predicting flight activity has been challenging because it is influenced by environmental cues such as temperature, relative humidity (RH), and time of day. To address these gaps, we integrated field and laboratory approaches. First, a bi-hourly trapping experiment was conducted during the spring peak flight to capture circadian flight patterns while recording temperature and RH. Second, a temperature-controlled flight mill study quantified flight distance and speed, to identify the optimal thermal range for flight. We found X. germanus flight to be most frequent at approximately 24.2 °C and 70.45% RH, with a pronounced temporal peak at 7 PM. Findings establish a predictive framework describing X. germanus flight suitability across temperature ranges and time of day, enabling more targeted monitoring for improved timing of control strategies. Ultimately, our research advances precision pest management and supports more sustainable orchard production.
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Sandra Lizarraga
Victor Alves
Krzysztof Szejbak
Environmental Entomology
Cornell University
University of California, Davis
University of Idaho
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Lizarraga et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69df2cf7e4eeef8a2a6b20a9 — DOI: https://doi.org/10.1093/ee/nvag030