Landscape and climatic effects driving spatiotemporal abundance of Lygus lineolaris (Hemiptera: Miridae) in cotton agroecosystems

Abstract

Lygus lineolaris populations have become increasingly problematic in Virginia cotton since 2013. Although production practices have changed, changes in landscape composition and climatic conditions are also anecdotally associated with increasing populations. To better understand the recent increase in L. lineolaris infestations in Virginia cotton, 56 commercial cotton fields were sampled weekly in 2017 and 2018 for a nine-week period during the growing season. Insect density was measured using sweep net and black drop cloth sampling, targeting adult and nymphal populations, respectively. Geospatial crop production and forest disturbance data were used to measure the composition and management history of landscapes adjacent to sample fields. We also used spatial climate data sets to document the relationship between increasing L. lineolaris and temperature variation. We investigated the significance of landscape composition and climatic effects increasing L. lineolaris infestation intensity using a regression modeling approach. We found the best overall predictor of L. lineolaris abundance was higher annual minimum temperatures. Several crop components in the landscape were significant, specifically corn and double-crop winter wheat and soybeans, but these habitat patches did not explain high levels of variability. Results of this study suggest that increasing minimum temperatures will favor L. lineolaris and may translate into elevated infestation intensity and increasing dependence on insecticide inputs to manage this problematic pest of cotton. Results of this study will be important to describe short- and long-term factors driving L. lineolaris infestation risk in cotton agroecosystems.