Using a simulation model to assess the significance of temperature and host availability for population dynamics of Drosophila suzukii (Diptera: Drosophilidae) - John B. McCulloch; Joshua A. Grant; Ye Chu; Ashfaq A. Sial (PLoS ONE, 2026)
Spotted-wing drosophila, Drosophila suzukii Matsumura (Diptera: Drosophilidae) (SWD), is an important pest of soft-skinned fruit around the globe because of its propensity to oviposit into ripe fruit, directly impacting the marketable portion of a crop. Temperature and host availability are two major factors that influence SWD population dynamics, but predictive tools are absent for blueberries in southern Georgia, USA, where multiple non-crop hosts occur in habitat adjacent to blueberry farms and where high summer temperatures present challenges for SWD population growth. We used temperature and crop and non-crop host phenology in southern Georgia, USA, to drive a physiological age-structure simulation to assess the importance of these factors for SWD. We used the Kolmogorov-Smirnov (KS) test to assess how different simulation conditions compared to trap catch data from 2015–2017. The standard simulation, in which crop host availability peaked in late spring and non-crop host availability peaked in autumn and winter, predicted the decline in trap catches in early summer but did not predict the increase in trap catches during the autumn and winter. High summer temperatures and reduced or declining host availability constrained SWD reproduction, as indicated by increased proportions of adults and decreased proportions of immatures in the simulated population during these periods. The KS test showed that simulation conditions with only non-crop hosts available to SWD matched the trap data the best, compared to the standard simulation with crop and non-crop hosts. Further research to describe adaptations of SWD populations to local conditions and the importance of non-crop hosts for sustaining SWD populations is necessary to improve our understanding of SWD. Improving our knowledge of SWD in these regards will increase the accuracy of predictive tools and advance sustainable management of this worldwide pest.