A group of researchers developed a new methodology to predict how plant growth and water quality would change in the aftermath of wildfires.
Soils have an impact on water quality and are essential for plant growth. However, it has been difficult to predict how wildfires would affect plant growth and water quality. A team of Colorado researchers has now developed a new methodology to enable such predictions. The study was published in the American Society for Microbiology journal Applied and Environmental Microbiology.
“To make practical predictions about recovery, we had to use a modern artificial intelligence tool called statistical learning,” said John Spear, Ph.D., professor, Civil and Environmental Engineering, Colorado School of Mines, Golden, Colo. “When we fed data about the microbes and nutrients into this model, we were able to predict how soil is changed by fire far more accurately.”
Spear emphasized that combining information on the types and quantities of microbes and nutrients improved accuracy. Another intriguing finding was that including microbiota that are uncommon in soil – those that made up less than 1% of the microbiome – was critical to the accuracy of the predictions.
To make practical predictions about recovery, we had to use a modern artificial intelligence tool called statistical learning. When we fed data about the microbes and nutrients into this model, we were able to predict how soil is changed by fire far more accurately.
Prof. John Spear
“This apparent contradiction is a fascinating outcome of our study and runs counter to the common wisdom that if we measure 99 percent of what’s living in soil, we’ll have a good sense of how that soil will behave,” said first author Alexander S. Honeyman, Ph.D., research associate at the Colorado School of Mines.
The investigators were also able to predict water quality by analyzing the microbiome for species that affect both soil regeneration and downstream waters, said Spear, who added that the methodology may lead to a better understanding of both terrestrial and aquatic ecosystems recovery post-wildfire.
“We went out to two active wildfires in Colorado in 2018 and 2019, and collected soil shortly after the smoldering stopped,” Spear said of the study. “It was as easy as dumping soil into a bucket. We returned to the same sites for three summers [2018, 2019, and 2020], collecting additional samples and monitoring the landscape’s recovery from the black of burn to the green of new growth.”
Back in the lab, the researchers took measurements of soil carbon, nitrogen, and other important molecules. They also conducted a microbiome census, identifying the species present and the quantities of each in the soils.
“The trick,” said Spear, “was to do this over and over in a thorough fashion for 3 years, generating a dataset of more than 500 soil samples. Then, we wanted to see if the pattern of recovery of soil after fire could be predicted from this unique dataset, using statistical learning.”
The methodology worked, despite the fact that the dataset is quite diverse — representing different severities of wildfire and various soil types and seasons. “That’s good news for our approach, because [the methodology] appears to work on many different conditions of soil,” said Spear.
Honeyman’s decade of volunteer firefighting experience, as well as the loss of his home in a Colorado wildfire in 2010, inspired the study. This experience raised serious concerns for him. Would soil be able to recover nutrients lost in a fire? The researchers also wanted to know if the water quality would be restored. “We asked ourselves how we could describe recovery in a way that is actually useful to land managers,” Spear explained, adding that “our forest service coauthors, who are land managers, really liked this work.”
As climate change contributes to more frequent fires, it is critical that we understand how to manage burned soil recovery, particularly in the western United States, according to Spear. Spear speculated that the methodology could be applied to agriculture to increase food production “while using less water and fertilizer, thus saving money.”
