Complex modeling by UNR-led research team predicts wildfires may decline, eventually | Carson City Nevada News

RENO – Researchers trying to predict how wildfire risk will change in the coming decades for a variety of reasons have some good news and some bad news. The good news is that wildfires will decrease in number and frequency in the future. The bad news: The reduction likely won’t happen for another 50 years, and wildfire risk will likely get worse before it gets better.

“There are so many factors that we need to explore and understand more about if we want to predict how the frequency, size and intensity of wildfires will change,” said Erin Hannan of the University of Nevada, Reno, a researcher at the university’s test site. and Assistant Professor in the College of Agriculture, Biotechnology and Natural Resources. “Our two studies looked at how changes in temperature, precipitation, and atmospheric carbon dioxide interact with and affect plant growth, transformation, and decay, and how those processes in turn affect fuel load and fuel moisture in different plant communities. These are two key issues in the Western world. Factors that drive wildfires”.

Making the case for more detailed research on plant decomposition

Hannan is an author on two related journal articles about the study. She is the lead author of the first article in the Journal of Advances in Modeling Earth Systems, which focuses on how plants decompose or break down under different climatic conditions. Garbage on the ground that can be burned.

“Decomposition algorithms with many models from small experiments and specific locations may not always be accurate,” Hannan said. “The accumulation of fine fuels and the rate at which the fuels or plant parts degrade are very sensitive to many factors such as temperature and rainfall. That’s what this study proved. Therefore, unless we are better able to estimate fuel load, or accumulation, and fine fuel decay under different climates, it will be very difficult to build accurate models that predict future wildfire regimes.

A case study of semiarid watersheds in central Idaho leads to a good-news-bad-news prediction.
Armed with this information, Jianning Ren, a postdoctoral scholar in Hanan’s lab group, plans to precisely examine the various ways future climate conditions in semi-arid basins may affect temperature rise, moisture change, and atmospheric CO2. Fuel loading, fuel moisture and wildfire regimes.

Wren, Hannan and other researchers combined climate data with complex general circulation models, using data from a representative semi-arid watershed in central Idaho, Trail Creek, which experiences cool, wet winters and warm, dry summers. The altitude in the basin ranges from 1,760 to 3,478 meters, which creates many different plant communities – grasses, shrubs, forests, mixed plants and areas with small plants.

An article detailing the research published in Earth’s Future, of which Ren is the lead author, contains detailed graphs showing the potential effects of fire regimes on different plant communities. The results were strongly influenced by these observations:

– Increased plant growth or fuel load due to increased carbon dioxide in the atmosphere (plants absorb carbon dioxide and convert it into energy for growth).

– Decreased plant growth or fuel load due to climate warming (plants struggle to grow when the environment is too dry).

– Increased rates of decomposition of plants, which reduce the fuel load, as well as in the climate (plant materials break down faster in the heat)

– Drying fuels, or plants, due to the increase in temperature

“We found that these effects can sometimes work together to create a synergistic effect, or they can counteract each other depending on the context,” Ren said. “In short, our models project

– In the 2040s, higher CO2 will stimulate the net growth of vegetation, despite possible reductions due to warming and related droughts, so the result is an increase in fuel loads and an increase in fire risk.

– Using data for the 2070s, climate warming and drying will be so intense that they will outpace the increase in CO2 and reduce the potential for CO2 growth. Therefore, in the models of the 2070s, the burnt area and the possibility of it will be reduced. And even though fire weather is likely to increase during that period, reduced fuel loads — through increased decomposition and reduced vegetation productivity — will ultimately reduce wildfires for this period. she said.

Ren and Hannan noted that results were very consistent across each of the major plant communities — grasslands, shrubs, forests — which adds to the validity of the findings.

“In the grasslands we modeled, the change in temperature didn’t make as much of a difference as the fuel load,” Renn said. “It was completely dependent on oil cargo, which makes sense. The lawns in this area are always dead and dry. That’s their cycle. For grass land, it’s just a matter of how much fuel you have to burn.

In contrast, Renn noted that changes in fuel dryness and fuel loading significantly influenced wildfire predictions in areas dominated by shrubs and trees. But Hannan and Ren both stress that much more research is needed to make the models more reliable.

“This is really just the beginning,” Hannan said. “And, the longer the predictions, the less reliable they naturally become. We hope to do more research on erosion and expand the research we did at Trail Creek to other watersheds and improve the models and scale them over larger areas. What we really hope is that all of this will stimulate more integrated research and modeling and get people talking. For a long time, the combustion community and the biochemistry community weren’t necessarily on speaking terms. I think that’s starting to change. We are seeing the importance of thinking, discussing and measuring all these different factors as a multidisciplinary team.

Funding for these studies was provided by the National Science Foundation under award numbers DMS-1520873, DMS-1520847, and DEB-1916658. Other members of the research team are Maureen C. Kennedy, University of Washington, Tacoma; John T. Abatzoglou and Crystal A. Kolden, UC Merced; Christina (Naomi) L. Tague, UC Santa Barbara; Mingliang Liu and Jennifer C. Adam, Washington State University; Maurice C. Johnson, US Forest Service; and Alistair MS Smith, University of Idaho.

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