Migratory moths (Lepidoptera) comprise many major agricultural pest species that pose serious threats to global food security. Accurate prediction of their migration trajectories forms the foundation for effective pest prevention and control. During migration, these insects often form concentrated layers at specific altitudes, facilitating long-distance movement. However, the adaptive mechanisms and benefits underlying this behavior remain unclear, which limits the accuracy of migratory pest trajectory predictions. We developed a high-spatiotemporal-resolution observational system in China’s Bohai Bay, an important corridor for East Asian migratory insects, measuring fine profiles of both insect density and meteorological variables at unprecedented 1-min × 10-m resolution. Focusing on moths, and based on three years of observations (2022–2024), we found 86.0% of insect layers formed within ± 150 m of either temperature inversion tops (TITs) or wind-jets (WJs). As temperatures rose, the probability of layering near WJs instead of TITs increased, reaching 50% at 14.5°C and 90% at 28°C. Insects near WJs exhibited 1.5 times higher flight energy efficiency (FEE) than those near TITs. These results demonstrate that rising temperatures shift insect layering strategy from seeking favorable thermal conditions toward enhancing wind-assisted FEE, revealing an adaptive mechanism that enhances migration efficiency and survival. Based on these findings, we developed a model that predicts layering based on wind and temperature data with 80.6% accuracy, thereby improving migration trajectory forecasting and pest early-warning systems.
Wang et al. (Fri,) studied this question.