Pyrocosms to Measure Influence of Fire Intensity, Time, and Soil Depth on Microbial Succession, Cross-Kingdom Interactions, and Greenhouse Gas Emissions
Authors:
Maria Ordonez1, Ken Czapla1, Luke Hillary2, Basubi Binti Zhilik1, Peter M. Homyak1, Michael J. Wilkins3, Joanne B. Emerson2, Steven D. Allison2, Sydney I. Glassman1* ([email protected])
Institutions:
1University of California–Riverside; 2University of California–Davis; 3Colorado State University
Goals
Wildfires are increasing in frequency, size, and severity across the globe. Unlike ecosystem disturbances that primarily impact vegetation, wildfires kill microbes, thereby dramatically altering the composition, function, and abundance of post-fire soil microbiomes, with downstream impacts on soil nitrogen (N) cycling. Despite widespread microbial mortality during fires, post-fire environments can also favor the growth of pyrophilous, fire-loving, microbes. Pyrophilous microbes have been documented in widespread post-fire habitats, yet their traits and impacts on ecosystem nitrogen (N) losses remain largely uncharacterized. Here, researchers focus on how wildfire severity and pyrophilous microbial interactions regulate N cycling and the emission of greenhouse gases (GHG) like nitrous oxide (N2O), a powerful greenhouse gas with 300x the warming potential of carbon dioxide, with implications for long-term ecosystem recovery, regional air quality, and Earth’s climate. The overarching project goal is to answer the question: Do conserved genomic traits and cross-kingdom interactions drive post-fire N cycling across ecosystems?
Understanding how soil microbial interactions and traits govern N cycling is critical to forecasting post-fire soil N dynamics and ecosystem recovery. Using pyrophilous microbiomes as model systems, researchers will scale up across systems of increasing complexity, from individual genomes to more complex microbiomes, allowing researchers to predict the impacts of wildfire disturbance on ecosystem N cycling with the DEcomposition Model of ENzymatic Traits (DEMENT). Across three ecosystems that are experiencing increased fire frequency (Mediterranean grasslands, chaparral shrublands, montane coniferous forests) researchers ask: 1) how do microbial traits change during post-fire succession?; (2) how does fire severity influence microbial succession and gene expression of N cycling functions?; (3) how do cross-kingdom interactions change during post-fire succession?; and (4) how do traits and interactions affect ecosystem N fates and cycling?
Abstract
To answer these questions researchers are using experimental pyrocosms to simulate soil heating under controlled and replicable conditions. These pyrocosms will enable researchers to test how microbial succession and cross-kingdom interactions affect N cycling and greenhouse gas emissions under varying fire severities, biomes, and soil depths. In Fall 2023, the team burned soils collected from a Southern California Chaparral shrubland within the Cleveland National Forest adjacent to the 2018 Holy Fire burn scar where researchers have studied natural microbial succession post-fire. The team used three treatments, control, low, and high intensity fires, and sampled at seven timepoints ranging from pre-fire to 4 months post-fire (burns occurred on September 5, 2023, and the last sampling date was January 5, 2024). The experimental replicates yielded highly similar temperature profiles within treatments, with peak temperatures much higher in the high than low intensity treatments, and temperatures declining as expected with depth.
We were also successful in achieving very different soil surface temperatures for high and low intensity treatments that approximated natural fire conditions with high intensity treatments nearing 600°C and low intensity around 300°C. Temperatures declined linearly from surface to 10cm below the surface with very little variation between replicates.
So far, researchers have collected soils from two depths (5 and 10 cm below surface) at seven time points from pre-fire to 4 months of post-fire. Researchers have extracted DNA from all samples and conducted 16S and ITS PCRs and are awaiting Illumina MiSeq data detailing how bacterial and fungal richness changed over time post-fire. Researchers have also extracted viromic DNA and RNA from all samples and have submitted them for sequencing to determine how bacterial, fungal, and viral communities changed across time and depth after high and low intensity chaparral fires. Finally, the team performed extensive biogeochemical analyses to determine how N cycling and greenhouse gas emissions are impacted by fire intensity and time. Once the amplicon sequencing data is analyzed, researchers will select a subset to perform metagenomics and metatranscriptomics to determine how gene abundances and transcription changes across time and fire severity treatments.
Burning pyrocosms of sieved Holy Fire soil increased soil pH from 6.2 ± 0.0 to 7.0 ± 0.2 and increased KCl-extractable ammonium (NH4+) content from 2.7 ± 0.1 µg N/g soil to 48.2 ± 5.8 µg N/g soil 1 week after the burn in the top 10 cm of soil. Researchers also found that both soil pH and NH4+ content were positively correlated with peak burn temperatures. NH4+ content decreased as nitrate increased more rapidly in the low-burn treatment than the high-burn or control treatments during the 4 months after burning, suggesting that low-intensity wildfires may fuel high nitrification rates in chaparral soils. The team conducted high-resolution N2O, carbon dioxide (CO2), and NOx gas flux and isotope measurements for all seven timepoints and are currently processing these data.
The next goal is to burn a second round of pyrocosms at UC Riverside using soils collected from Southern California grasslands. The team has received the permit to collect the soil and will be burning grassland pyrocosms in Spring 2024. This will allow researchers to compare how microbial succession, cross-kingdom interactions, and greenhouse gas emissions are altered across fire severity and soil depth in two fire-prone dryland ecosystems.
Funding Information
This research was supported by the DOE Office of Science, BER Program, grant no. DE-SC0023127.