LAUSR

BACKGROUND To better understand the population dynamics of invasive species in their native range, we developed two predictive phenological models using the ubiquitous invasive insect pest, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), as the model organism. Our work establishes a zero-inflated negative binomial regression (ZINB) model, and a general additive mixed model (GAMM) based on 11 years of black light trap monitoring of H. halys at three locations in Japan. RESULTS The ZINB model indicated that degree days (DD) have a significant effect on the trap catch of adult H. halys, and precipitation has no effect. A data set generated by 1,000 simulations from the ZINB suggested that higher predicted trap catches equated to a lower probability of encountering a zero count. The GAMM produced a cubic regression smooth curve which forecasts the seasonal phenology of H. halys as following a bell-shaped trend in Japan. Critical DD points during the field season in Japan include 261 DD for first H. halys adult detection and 1,091 DD for peak activity. CONCLUSIONS This study establishes the first models capable of forecasting native H. halys population dynamics based on degree day. These robust models practically improve population forecasting of H. halys in the future and help fill gaps in knowledge pertaining to its native phenology, thus ultimately contributing the progression of efficient management of this global invasive species. This article is protected by copyright. All rights reserved.