D3122: Risk assessment models for predicting seedcorn maggot (Delia platura) emergence and distribution in New York State

Risk assessment tools for agricultural pests have primarily relied on climate data. However, we know landscape composition and farm management also affect pests. Recent New York State legislation limiting the sale of neonicotinoid-coated corn, soybean, and wheat seeds raises the need for predictive tools to pinpoint when and where certain pests may become a problem. One such pest is the seedcorn maggot (Delia platura), which is a polyphagous pest that threatens many crops, including corn, beans, and cereals. It is difficult to detect the underground damage caused by D. platura larvae. Improving our ability to predict when and where D. platura adults will emerge and larvae will pose a risk using a combination of climate, landscape, and management data will be essential to future control. We determined which factors had the greatest influence on the spring emergence of adults. We used sticky card data from over 50 farms, degree day calculations, farm management, and landscape data. Additionally, we trapped larvae using wire mesh traps baited with lima beans and corn seeds. For adults, we found that cooler temperatures, wetter conditions, cover cropping, and a greater proportion of corn in the landscape increased abundance. However, larvae were sporadic, low in abundance, and not correlated with the number of adults. Therefore, the factors that increased D. platura adult abundance do not necessarily increase damage risk. We show that landscape and local management practices, in combination with climate, influence D. platura adult emergence, demonstrating their value as variables in risk assessment models.