Mississippi State University’s forestry team wins $590K USDA grant to model timber-market risk in U.S. South

A Mississippi State University forestry research team has won a $590,000 grant from the U.S. Department of Agriculture’s National Institute of Food and Agriculture to study market dynamics, price volatility and storm risk in the southern U.S. timber sector, the largest timber-producing region in the world.

The project, titled “Southern Forest Market Outlook: Exploring Market Dynamics and Risks,” is led by Sabhyata Lamichhane, an MSU assistant professor and Extension forest economics specialist. It brings together researchers from MSU, Louisiana State University AgCenter, North Carolina State University, the University of Georgia and the USDA Forest Service Forest Products Laboratory.

Lamichhane said southern forest markets face “increasing uncertainty driven by price volatility, shifting product demand, economic disruptions and major storm events.” The team plans to develop data-driven forecasting tools combining artificial intelligence and machine learning methods to analyze interactions among forest inventories, market conditions and environmental drivers.

For fertilizer-sector observers, the grant is a marker of how AI-driven commodity forecasting is increasingly being applied beyond row crops to adjacent natural-resource markets. The team will examine long-term scenarios using the Forest Resource Outlook Model, including how timber supply and hurricane risk interact with shifts in forest ownership, management strategies, and demand for forest products under different socioeconomic pathways.

“Our goal is to provide a comprehensive, data-driven outlook for Southern forestry,” Lamichhane said. “By integrating economic trends, natural disturbance risks and future socioeconomic scenarios, we aim to deliver a forward-looking perspective that helps stakeholders understand not only what might happen next, but how and why forest markets respond over time.”

The grant adds to a growing portfolio of USDA-NIFA awards backing AI and machine learning applications across U.S. agricultural and natural-resource forecasting. The project has not disclosed a public release timeline for its forecasting outputs.

Source: MSU Extension Service