By Andi Anderson
A recent study from Michigan State University, published in Scientific Reports, reveals the strong potential of using multi-model ensembles (MMEs) to guide regenerative agriculture practices. The research team, led by Dr. Bruno Basso, includes top experts in sustainable agriculture and modeling.
The study tested eight crop system models across 12 Midwest states, covering over 46 million hectares. These models evaluated both traditional and regenerative farming practices, including cover cropping, crop rotations, no-till, and precision fertilization.
This allowed researchers to better estimate how these practices affect soil organic carbon (SOC) storage and nitrous oxide (N₂O) emissions.
By using multiple models together, researchers reduced uncertainty and provided a more reliable way to measure farming impacts on the environment.
Dr. Alex Ruane from NASA GISS, a co-author of the study, emphasized that the research helps identify which areas and practices have the greatest potential and points to where further studies are needed to reduce uncertainty.
The team found that while some regenerative practices increase soil carbon, they can also lead to higher N₂O emissions. This study provides a more complete picture of how farming practices affect the climate by considering both carbon storage and greenhouse gas release.
Dr. Basso explained that AgMIP’s pioneering use of multi-model approaches helps show how soil, genetics, management, and climate interact. “Our goal is to help farmers, policymakers, and businesses make better decisions to increase farm resilience and resource use efficiency,” he said.
The findings will serve as a foundation for new research efforts, including a large project coordinated by Columbia University and supported by AgMIP. It will also help test practices not yet widely used, offering valuable tools to support future farm decisions.
Photo Credit: gettyimages-oticki
Categories: Michigan, Education