Soybean aphid (Hemiptera: Aphididae) population dynamics are associated with the temporal scale and pattern of soil moisture in soybean fields.

Understanding and predicting pest outbreaks is central to sustainable crop management, yet field evidence linking belowground abiotic conditions to aboveground herbivore dynamics remains limited, particularly regarding the temporal scales relevant to plant physiological responses. Using an Internet of Things sensor network in a soybean field in Taiwan, we combined high-temporal-resolution soil monitoring with field surveys of soybean aphid (Aphis glycines Matsumura) to evaluate how soil moisture and soil electrical conductivity (EC) were associated with weekly sampled soybean aphid abundance across multiple temporal aggregation windows, from same-day values to 7-d rolling averages, over 2 growing seasons. Because this single-site field study was observational, we interpret the results as conditional field associations and do not treat them as direct causal evidence. After detrending for seasonal progression and plant ontogeny, soil moisture showed more consistent, although generally weak, associations with soybean aphid abundance than soil EC. Short-term moisture metrics (daily to 3-d means) were most consistently positively associated with soybean aphid abundance, whereas associations at longer integration periods (5 to 7 d) were weaker and more season dependent. Predictive analyses showed higher cross-validated performance for moisture-based models than for EC-only models, whereas adding EC provided little improvement beyond moisture alone. These results suggest that the temporal window used to summarize soil water availability can affect inference about soybean aphid-soil associations and that high-frequency soil sensing may add soil context to phenology- and weather-based soybean aphid monitoring.