Climate change, nitrogen deposits and wildfire together can boost the release of nitrous oxide from the soil, which in turn can accelerate global warming, according to a new study by NAU researchers and released this week in PLoS One, an online journal for research.
“Soils are the major source of nitrous oxide in the atmosphere,” said Jamie Brown, graduate student in biological sciences at Northern Arizona University and co-author of the study. “So increased soil emissions of nitrous oxide will accelerate global warming.”
The study is significant because it measured the impact of several factors simultaneously, unlike previous studies that studied the impact of one element at a time.
Brown worked with colleagues from NAU, Stanford University, the University of Paris and the University of Lyon. The study used an experimental grassland at Stanford, where researchers exposed the grassland to simulated environmental changes—heat, extra carbon dioxide in the atmosphere, more rain, more nitrogen deposition, and, when part of the experiment accidentally burned, wildfire.
“Alone, the treatments had little influence on nitrous oxide emissions, but what was really surprising was the interaction with wildfire, causing a huge burst of nitrous oxide production,” said NAU professor Bruce Hungate, Brown’s thesis adviser and co-author on the study. Nitrous oxide is a potent greenhouse gas, Hungate explained.
In some parts of the world, like the western United States, wildfires also are becoming more frequent and more intense. “Increasing wildfire frequency and the changing climate could cause these soil micro-organisms to release more nitrous oxide into the atmosphere, accelerating global warming,” Brown said.
The experiment examined the complexity to simulate a realistic situation, where all factors are changing together. “The design is complex, with each treatment by itself in every possible combination with the other treatments,” Brown said.
With such a complex design, researchers can see if the effects of two or more global changes together can be predicted from their effects in isolation.