Soil texture for infiltration parameters: postfire soil hydrologic and biogeochemical response and recovery in northern California, USA

California’s wildfires are setting historic records for length, size, and severity (Safford and others, 2022, Kreider and others, 2024). These wildfires are altering soil processes like infiltration rates and carbon cycling over increasingly large areas (Staley and others, 2017; Kelly and others, 2020; Baur and others, 2024; Dow and others, 2024). In northern California, it is unclear how wildfire might increase runoff hazards or limit ecosystem recovery. To understand postfire soil response and recovery, we characterized the short and long-term effects of wildfire on soil infiltration and biogeochemical cycles using burned and nearby unburned sites. We seasonally conducted field measurements or collected soils for lab measurements to quantify soil hydrological and biogeochemical recovery for at least 3 years following the fire. Understanding the interaction between rocks, microbes, and water is key to identifying areas of elevated risk postfire and prioritizing postfire mitigation. Here are soil texture data from the 41 (31 burned, 10 unburned) soil hydrology monitoring sites across the 2020 LNU Lightning Complex, Walbridge, and Glass Fires and the 2021 Dixie Fire. NOTE: soil texture data from the 2019 Kincade Fire are also included. 

We collected soil samples during the initial visit for textural analysis at the USGS. Samples were air-dried, disaggregated using a mortar and pestle. Any coarse fragments greater than 2 mm were removed using a screen mesh and weighed separately. The remaining sample less than 2 mm was then split using a stainless-steel sample splitter and a 16-part spinning riffler to achieve a representative sample. Samples were processed without organic or deflocculant pre-treatments to maintain the field texture, however, we also pretreated a set with sodium hexametaphosphate (SHMP) as a comparison. We analyzed the samples by optical diffraction (Gee and Or, 2002) using a Beckman-Coulter LS-13-320 Particle Size Analyzer. The device calculates particle size distribution in the 0.00004-2 mm range by measuring the laser diffraction pattern while the sample is suspended in water over 3 sequential runs. The diffraction pattern is converted to particle sizes using a mathematical algorithm (Fraunhofer diffraction model), which assumes spherically shaped particles. Standards were run prior to and following batch sample runs to ensure machine accuracy. The percent of each textural class (clay, silt, very fine sand, medium sand, coarse sand, very coarse sand, and gravel) is reported here. The USDA soil textural classification was determined based on the adjusted sand, silt, clay percentage that excludes gravel (the greater than 2 mm percentage) and reported here.

For more information on the site locations and associated hydrological and biogeochemical data, refer to the project landing page: https://www.sciencebase.gov/catalog/item/680fa722d4be022940539f4d

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

References:
Baur, M.J., Friend, A.D., and Pellegrini, A.F.A., 2024, Widespread and systematic effects of fire on plant–soil water relations: Nature Geoscience, v. 17, no. 11, p. 1115–1120, at https://doi.org/10.1038/s41561-024-01563-6.

Beckman Coulter, Inc., 2011. LS 13 32 Laser Diffraction Particle Size Analyzer Operator's Manual. Brea, CA: Beckman Coulter, Inc. Available at: https://www.beckmancoulter.com/wsrportal/techdocs?docname=B05577AB.pdf&…;

Dow, H.W., East, A.E., Sankey, J.B., Warrick, J.A., Kostelnik, J., Lindsay, D.N., and Kean, J.W., 2024, Postfire Sediment Mobilization and Its Downstream Implications Across California, 1984–2021: Journal of Geophysical Research: Earth Surface, v. 129, no. 8, at https://doi.org/10.1029/2024JF007725.

Gee, G.W., and Or, D., 2002, Particle-Size Analysis, in Dane, J.H. and Topp, G.C. eds., Methods of Soil Analysis: Part 4--Physical Methods: Soil Science Society of America, Madison, WI, p. 255–293.

Kelly, L.T., Giljohann, K.M., Duane, A., Aquilué, N., Archibald, S., Batllori, E., Bennett, A.F., Buckland, S.T., Canelles, Q., Clarke, M.F., Fortin, M.-J., Hermoso, V., Herrando, S., Keane, R.E., and others, 2020, Fire and biodiversity in the Anthropocene: Science, v. 370, no. 6519, at https://doi.org/10.1126/science.abb0355.

Kreider, M.R., Higuera, P.E., Parks, S.A., Rice, W.L., White, N., and Larson, A.J., 2024, Fire suppression makes wildfires more severe and accentuates impacts of climate change and fuel accumulation: Nature Communications, v. 15, no. 1, p. 2412, at https://doi.org/10.1038/s41467-024-46702-0.

Safford, H.D., Paulson, A.K., Steel, Z.L., Young, D.J.N., and Wayman, R.B., 2022, The 2020 California fire season: A year like no other, a return to the past or a harbinger of the future? Global Ecology and Biogeography, v. 31, no. 10, p. 2005–2025, at https://doi.org/10.1111/geb.13498.

Staley, D.M., Negri, J.A., Kean, J.W., Laber, J.L., Tillery, A.C., and Youberg, A.M., 2017, Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States: Geomorphology, v. 278, p. 149–162, at https://doi.org/10.1016/j.geomorph.2016.10.019.