Researchers at the Prairie Research Institute have developed a data-driven framework to better predict how environmental systems in the critical zone — from the bedrock layer beneath the Earth’s surface to the tree canopy — behave over time and under different influences.
The National Science Foundation-funded project focuses on how intensively managed agricultural landscapes differ from natural landscapes, using data on stream chemistry, soil-gas concentrations, and land-atmosphere exchanges. An understanding of different parts of the landscape, such as the river, soil, and surface, helps scientists make more accurate predictions about how nutrients move through these systems and how they store and release CO2, water, and energy.
The study is detailed in the journal AGU Advances.
A prairie landscape includes many different types of plants with varying photosynthetic characteristics, root depths, and temperature and moisture sensitivities. An agricultural landscape, by comparison, will be home to fewer types of plants and requires attention to factors like planting and harvest timing, crop growth phases and growing season length, nutrient application timing, and periods of bare soil.
Over time, both managed and natural landscapes encounter natural fluctuations, such as seasonal transitions, drought, and flooding events.
The researchers compared data collected at a high frequency, every half hour, from sites in Illinois, Nebraska, Kansas, and France to learn more about critical zone behaviors and develop a framework to analyze them.
Lead author Allison Goodwell, a research scientist at the Illinois State Water Survey, said one goal of the research is to improve predictions, such as how a nutrient like nitrate moves from a field in Illinois to streams and rivers, and eventually to the ocean, lakes, and reservoirs — including those used for community water supplies. Excessive nitrogen and other nutrients can cause harmful algal blooms and dead zones downstream. Similarly, it is important to predict exchanges of CO2 between the land and the atmosphere because these determine whether a landscape is a source or a sink of carbon.
“These environmental systems are notoriously complex,” Goodwell notes. “For example, one reason nitrate is so complicated is the challenge of considering the many factors that influence it, like agricultural practices and the relative timings of application, rainfall events, uptake by plants, or bacteria breaking it down in the soil or as it moves downstream. These types of drivers can act together or at different times to influence what ultimately happens to the nitrate — as well as other nutrients, gases, energy, and more.”
Goodwell worked closely with Prairie Research Institute co-authors Brian Saccardi, Andrew Stumpf, Erin Bauer, Steve Sargent, and Praveen Kumar, as well as Jennifer Druhan and doctoral student Jinyu Wang, both in the Department of Earth Science and Environmental Change at the University of Illinois, and researchers from the University of Nebraska Omaha and Purdue University.
The paper “Detecting Regimes of Critical Zone Processes, Drivers and Predictability With a Data-Driven Framework” is available online.
The Prairie Research Institute at the University of Illinois Urbana-Champaign provides scientific expertise and transformative research to the people of Illinois and beyond. PRI is home to the five state scientific surveys: the Illinois Natural History Survey, Illinois State Archaeological Survey, Illinois State Geological Survey, Illinois State Water Survey, and Illinois Sustainable Technology Center.