These site-specific temperature measurements, when merged with insect-development models, allow researchers to predict when insect pests at a given site will emerge or enter a key stage of development. ZedX Inc., an information technology company based in Bellefonte, Pennsylvania, provides daily weather data that Calvin feeds into the insect-development models. “We take the weather data from ZedX, merge it with our insect models, and estimate when, for example, European corn borer is going to hatch or transition into a stage,” he says. “Essentially, our models move the insect from stage one to stage two and on through the life cycle based on whether it’s a warmer or cooler year.”

These forecasting models span across every geographical area in North America, making the college an international leader in pest forecasting-model research. Calvin’s team uses weather data that’s been spatially interpolated, which means it has been made relevant for a specific point on the landscape by taking into account elevation, longitude, latitude, and other factors. Based on these variables, the researchers can modify temperature predictions for greater accuracy. The insect prediction models that run every day have a resolution of 10 square kilometers, or about 6.2 square miles, meaning researchers can make pest predictions for every 6.2 square miles in North America.

The information generated by forecasting models is reflected on maps created by ZedX. Users of these maps, which have been available on the Internet for the past four years, include extension educators, individual growers trying to manage crops more effectively, and various businesses such as seed corn companies and pesticide companies.

Growers who use biological controls can determine when to release biological control agents, according to the development stage of the pest.

The prediction models provide a seven- to tenday forecast, making them an effective early warning system. The information from models can save time and money by allowing growers to see when an insect pest is at a stage that causes damage in the field or when the pest is gone for the season and no longer a source of worry. Maps can also tell growers specifically when they should be scouting their fields for insect eggs, other life stages, or early damage symptoms. Growers who use biological controls can determine when to release biological control agents, according to the development stage of the pest. Organic and conventional growers can avoid damage from a particular pest by knowing the stage it will be in relative to when the crop is in the field.

“We also have models that ‘grow’ the corn plant so you can see the various stages of plant development,” Calvin says. “There are changes in the plant that make it attractive to pests. For example, corn rootworm adults prefer to lay their eggs in fields that are shedding pollen. Another model depicts plant-insect interaction and can predict corn plant yield impacts according to when it is attacked by European corn borer. We’ve quantified through field research and mathematical models how much loss there will be if they attack the plant at different heights, when the ears start to form, and so forth. We can tell the stage the corn will be in on any date, and we can tell the stage the insect will be in on any date. We can then merge the data and measure impact on yield. Using that information, growers can find the ideal window in which to plant.”

Another advantage offered by forecasting models is geographic specificity. For example, explains Calvin, “In a state like Pennsylvania, because of the climatic variation and the weather being affected by topography, events such as egg hatch could be three or four weeks earlier in the warmest part of the state compared to the coolest part. With our forecasting models, we can tell growers in, say, Potter County, which is cooler, that they’re still three weeks away from egg hatch. But if you’re down in Chester County, it’s happening right now.”