"Low-Intensity Fires Impacting Soil Bacterial Population Diversity" by Wallace Tonks
- Illuminate
- Oct 4
- 14 min read
Low-Intensity Fires Impacting Soil Bacterial Population Diversity
Wallace Tonks, Russell Sage College
Abstract: As forest fire frequency and severity increase, climate change becomes a focal point at the crossroads of debate for the economic and environmental future of the United States. Heat from forest and agricultural fires can both directly impact microbial populations and oxidize soil organic matter. This influences the dominant forms of soluble nutrients in the soil and alters microorganism populations long-term. Microbes play a large role in soil development, and disruptions in bacterial communities can have a lasting impact on future soil health, nutrient cycling, and agricultural output. This study aimed to analyze the immediate effects of small-scale forest brush and debris burning on gram-positive and gram-negative bacterial population diversity in the top 15 cm of soil. Soil samples were taken before and after brush burning, separated by depth, diluted in water, and grown on non-selective nutrient agar for 108 hours at 37°C. Gram staining and analyzing resultant growths under the microscope revealed that these low-intensity fires significantly decreased all bacterial diversity and impacted the relative gram-positive bacterial population size across the entire soil column. These changes in bacterial diversity suggest that certain species are less resistant to the burning conditions. Future forest fires may impact soil health by negatively impacting bacterial communities. Few studies have been conducted to look at the effects of temperate deciduous forest fires on soil bacterial populations. With the increasing occurrences of forest fires in the Northeastern United States, analysis of the immediate and long-term effects of these fires will grow in importance.
Introduction
The frequency and severity of wildfires are closely correlated with climate conditions (Flannigan et al., 2000; Gedalof et al., 2011; Liu et al., 2013; Peng et al., 2023). Precipitation, temperature, and humidity are commonly monitored and used to predict the probability and severity of wildfires in North America (Flannigan et al., 2000; Liu et al., 2013; Peng et al., 2023). Predictive models and current trends are revealing that much of the United States, now and for the foreseeable future, is facing higher temperatures and less precipitation in the summer (Liu et al., 2013; Peng et al., 2023). Mid-to-high latitude regions of the continental U.S. are expected to experience the greatest increases in average summer temperature, which will likely extend the length of fire seasons (Flannigan et al., 2000; Liu et al., 2013). Effects of these climatic changes have already been observed in the U.S., as burned land increased from 2 million hectares to 3 million hectares annually after 2001 (Liu et al., 2013; National Interagency Fire Center, n.d.).
Climate can also impact the behavior of wildfires by influencing vapor pressure, fuel moisture, and wind speed (Flannigan et al., 2000; Gedalof et al., 2011; Peng et al., 2023). The difference between the max vapor pressure and actual vapor pressure, known as vapor pressure deficit, has been used as a metric for atmospheric drought and is a strong indicator of potential fires (Peng et al., 2023). Higher vapor pressure deficit, low humidity, and low precipitation can cause drought-like conditions and decrease available moisture in plants and soils (Gedalof et al., 2011; Liu et al., 2013; Peng et al., 2023). Areas with these drought-like conditions have been shown to burn quickly in wildfires, and are more likely to catch fire in the first place (Gedalof et al., 2011; Liu et al., 2013; Peng et al., 2023). When paired with these conditions, wind speed has shown a strong correlation with wildfire growth (Flannigan et al., 2000).
Increasing frequency of wildfires can impact microbial populations both directly and indirectly, which in turn can have a lasting effect on soil health. Wildfires often reach temperatures over 800 ºC, which kills many soil microbes, as most do not survive temperatures exceeding 100 ºC (Flannigan et al., 2000). Fires can also remove soil moisture, increase pH through deposition of alkaline ash, and decrease soil organic carbon and substrate availability, which all indirectly and variably impact soil microbes based on their sensitivity to each factor (Flannigan et al., 2000; Srikanthasamy et al., 2021; Williams et al., 2012). Past studies have had varying results for the impact of fire on soil nutrients, particularly nitrogen. Nitrogen is important for both plant and microbial metabolism, which means nitrogen availability can also impact the carbon cycle (Flannigan et al., 2000). Fires can shift the dominant form of soluble nitrogen in the soil from ammonium to nitrate; in the case of more severe fires, it can completely remove nitrogen and carbon from the soil via volatilization (Barros-Rodríguez et al., 2021; Srikanthasamy et al., 2021). As soil nutrients change post-fire, so does the structure of the microbial community. Microbes that are more fit to survive in nutrient-limited environments and are capable of anaerobic processing have a higher chance of surviving post-fire conditions (Barros-Rodríguez et al., 2021; Niboyet et al., 2011; Srikanthasamy et al., 2021).
Past studies show contradicting results for changes in microbial biomass post-fire, with differences dependent on multiple factors. Fowler et al. (2024) reported greater resilience in fungi than bacteria and archaea in pile burn scars in West Yellowstone. However, Docherty et al. (2012) found that grassland fires in California reduced fungal biomass but hardly impacted bacterial biomass. Varying results on the impact on microbial biomass are likely due to the severity of the fire, as well as traits specific to the microbes, such as thermal resilience and growth rate (Docherty et al., 2012; Dooley & Treseder, 2012; Fowler et al., 2024). In the long term, gram-negative bacterial populations face a greater impact from fires, as much of their nutrient and carbon intake is reliant on plants that are often burned in the wildfire (Docherty et al., 2012; Lazaroaie, 2010). The short-term impacts of fires on microbial populations are less studied, but generally show a decrease in bacterial diversity with significant changes in the total biomass related to the severity of the fire (Docherty et al., 2012; Srikanthasamy et al., 2021).
As temperatures and drought frequency rise in the upper latitudes of the continental U.S., so does the need for further study on the impacts of wildfires in the Northeast. Changes in soil microbial populations can have long-term effects on soil health and development, impacting nutrient cycling and agricultural productivity. Presently, there are few studies looking at the immediate impacts of fire on soil microbial populations in temperate regions of the Northeast. This study used low-intensity, controlled fires to analyze the immediate effects of forest litter burning on gram-positive and gram-negative soil bacterial populations in upstate New York. It was hypothesized that total bacterial diversity and relative bacterial population size would decrease post-burn.
Methods
Sampling Site and Design
Sample collection took place on a private, rural property south of Schenectady, New York. Four sample plots were selected within one sampling site, the site being a field of primarily Kentucky bluegrass with deciduous forest on three sides of it, and cropland on the fourth side of the field (Figure 1a). The cropland was typically used for growing radishes or potatoes. The sample plots were one square meter each. Two of the sample plots were approximately 10 m from the forest, and two of the sample plots were approximately 10 m from the cropland. The soil in the field was classified as sandy loam with an average gravimetric water content of 7.59% across 15 cm of depth. Horizons were poorly developed with a brown A horizon of 4 cm, a more sandy, yellow B horizon of 8-10 cm, and a medium gravel C horizon underneath (Figure 1b).
Sampling was done in early November from 9 a.m. to 12 p.m. in sunny weather with 9 mph winds from the northwest, an average temperature of 43°F, and 54% humidity. The most recent precipitation was a week prior, and it was less than half an inch of rain. In the preceding month of October, Schenectady had less than 2 inches of precipitation (National Centers for Environmental Information, 2024).
Natural forest litter was used from the adjacent forest to make the fires. This was done to avoid introducing foreign bacteria to the sample plots. Branches from the ground were separated into three sizes: large (2-5 inch diameter), medium (0.5-2 inch diameter), and small (<0.5 inch diameter). Each fire was constructed in a conical shape from approximately 2825 g of large wood, 2025 g of medium wood, and 915 g of small wood (Figure 1c). Fires were ignited using a blowtorch and burned to completion in less than two hours. Fires were small and closely monitored to avoid any uncontrolled spread. Any fire that spread outside the square-meter plot was stamped out.
Sample Collection and Processing
A soil sampler probe was used to collect three 2.5 cm diameter and 15 cm depth samples of soil from the center of each plot before the burn. Each plot’s cores were divided into three depths (0-5 cm, 5-10 cm, 10-15 cm), and the triplicates of each depth were aggregated in a plastic Ziploc bag and hand homogenized. Rocks and debris were removed by hand. Samples were stored in an ice cooler in the field and a freezer in the lab until processing. Following the burning, sampling was repeated at each plot, separated by depth, homogenized, and stored in bags in the cooler. A total of 24 sample bags were collected, with 12 pre-fire and 12 post-fire samples.
Samples were processed within 10 hours of collection. Ten grams of each sample were placed in a vial, weighed, and put in an oven at 107°C for 8 days before re-weighing for the gravimetric water content. Nine grams of autoclaved water were put in 24 test-tubes, and 1 gram of each sample was added and mixed in a vortex mixer to achieve a 10⁻¹ dilution. A second dilution was conducted, and test tubes were mixed to achieve a final 10⁻⁴ dilution.
Using aseptic technique, each sample was inoculated onto a non-selective nutrient agar plate prepared the day before. A total of 24 inoculated nutrient agar plates were then incubated at 37°C and checked approximately every 24 hours for growth. The plates were incubated for a total of 108 hours to achieve visible colony growth. Following the incubation time, each plate was photographed, and growths were analyzed. Colony-forming units could not be counted because of expansive growth on many of the plates. Relative bacterial population size was estimated by comparing growth sizes across the different sample plates. Individual growths on each plate were scored with numbers from 1 to 5 based on their approximate diameter (< 5 mm, 5-9.5 mm, 10-14.5 mm, 15-19.5 mm, ≥ 20 mm, respectively). Scores for each plate were added up and used as an estimate to compare relative bacterial population size across the samples.
Every growth on each plate was sampled, with some of the larger growths sampled more than once to check for variations in bacteria type. Samples were smeared onto glass slides with water, allowed to air dry, and then heat fixed. Gram staining was performed with crystal violet as the primary stain, Gram’s iodine as the mordant, ethanol as the decolorizer, and safranin as the counterstain. Slides were stored in a slide case until they could be observed and photographed under oil immersion at 1000x magnification. Sample diversity was determined by identifying the number of different bacteria in each sample. Bacteria were differentiated based on colony shape, edge shape, surface texture or features, elevation, cell wall structure (Gram stain results), cell shape, and cell size. Microbes that appeared filamentous and had inconclusive Gram stains were not included in the results because they were either fungi or their cell wall structure could not be distinguished.
Statistical Analysis
Statistical analysis of results was performed using R software version 4.4.3. Measured parameters included gram-positive diversity, gram-negative diversity, total bacterial diversity (gram-positive and gram-negative diversity combined), relative gram-positive population size, relative gram-negative population size, and total relative bacterial population size (relative gram-positive and gram-negative population sizes combined). Simple linear regression was performed to analyze how each measured parameter related to depth and moisture before the fire (95% confidence interval). A paired t-test was conducted to compare the means of each parameter before and after the fire. Results were statistically significant for p < 0.05.
Results
Depth and Moisture
Diversity parameters counted the number of unique bacteria per plate before and after fire, and relative population size parameters were an estimate from comparing the size of growths across plates (Table 1). Parameter values before the fire were compared individually with soil depth and moisture using simple linear regression (Table 2). All parameters decreased as depth increased; significant correlation (p < 0.05) was found for gram-positive diversity and all relative population size parameters (Figure 2). All parameters increased as moisture increased, but only gram-positive diversity had a significant correlation (p = 0.003).
Diversity Post-Fire
Paired t-tests were conducted for each diversity parameter across the entire 15 cm depth (Table 3). Statistically significant decreases were reported for all measurements of diversity (Figure 3). When the differences before and after burning were separated into 5 cm depth intervals, there was no statistical significance except for the decrease in total bacterial diversity from 5-10 cm (Table 3). All other diversity parameters showed decreasing trends post-fire at all three depth intervals.
Relative Population Size Post-Fire
Paired t-tests conducted for each relative population size parameter in the entire 15 cm depth indicated that all measurements decreased post-fire (Table 3). A statistically significant decrease was observed only for the relative gram-positive population size (Figure 4). Relative population sizes showed mostly decreasing trends when separated into 5 cm depth intervals, but no statistically significant results were observed (Table 3).
Discussion
Significant results suggest that larger populations of microbes are higher in the soil horizons, with population sizes decreasing as depth increases (Figure 2). This may be due to the bulk of the soil nutrients residing in the top layer of soil, indicated by the darker A horizon (Figure 1b). Both moisture and depth were significant indicators of gram-positive bacteria diversity. While this might suggest that gram-positive bacteria are more dependent on available moisture levels, this goes against previous beliefs that gram-positive cell walls are inherently more resistant to moisture stress (Schimel et al., 2007). However, Sayer et al. (2021) speculate that gram-positive bacteria may respond negatively to plant drought stress signals, leading to a decrease in reproduction and growth. Initial soil water content and dry conditions during sampling could help explain the lower gram-positive diversity seen in these samples (Figure 3).
All measures for bacterial diversity decreased post-fire across the full depth of the sample (15 cm), while most of the relative population sizes were not significantly impacted post-fire (Table 3). This is in agreement with Docherty et al. (2012), who found that low-severity fires impacted grassland microbial community structures, but did not impact microbial biomass. The significant decrease in relative gram-positive population size post-fire likely indicates that gram-positive bacteria are less resistant to fire-induced stressors immediately following a fire. Gram-positive bacteria are more sensitive to toxic organic products of combustion than gram-negative bacteria (Lazaroaie, 2010). Polynuclear aromatic hydrocarbons can result from the incomplete combustion of wood and seep into the ground, directly causing the death of many gram-positive bacteria post-fire (Certini, 2005; Lazaroaie, 2010).
When post-fire results were separated based on depths of 5 cm increments, there was only a significant impact on total bacterial diversity from 5-10 cm. The change in statistical significance when separating the data into intervals may be due to the small sample size. The top 15 cm is generally the most aerobic layer and experiences the most microbial death from fires (Docherty et al., 2012; Srikanthasamy et al., 2021), but shrinking the areas of interest for the paired t-tests may have increased the amount of noise and variance in each interval.
This study found that bacterial biodiversity and relative gram-positive population size significantly decreased immediately after a fire. Future studies should begin to look at the long-term effects of fires in the Northeastern United States. Gram-positive populations may show signs of lower fire resistance, but current literature suggests that their resilience is higher than that of gram-negative bacteria. Post-fire, gram-negative bacterial populations tend to recover more slowly than gram-positive bacteria (Docherty et al., 2012). A probable explanation is that gram-positive bacteria have a high carbon use efficiency (CUE), which means they produce a high amount of biomass with the carbon they intake, while gram-negative bacteria have a lower CUE and require more available (and usually plant-supplied) carbon to increase their biomass (Wu et al., 2022). With slower growth rates and less post-fire vegetation to provide labile carbon, gram-negative bacteria would recover slower and thus be less resilient to the impacts of fire (Docherty et al., 2012; Guénon & Gros, 2013).
Limitations
This study had a small sample size that increased the chance of noise in calculations. The study would benefit from data to quantify the severity of the fire, such as temperature readings or loss on ignition (LOI). A measurement of LOI before and after the fire for organic matter as depth increases in the soil would provide a measurement of how deep the fire was able to burn organic matter. This study also lacked a precise measurement of bacterial population size, which can be determined through colony-forming unit counts or phospholipid fatty acid counts (Dooley & Treseder, 2012).
Conclusions
The low-intensity fires had significant negative impacts on total bacterial diversity, as well as individual gram-positive and gram-negative diversity, in the top 15 cm of soil. It also had a negative impact on the relative gram-positive population size. Differences in population size and diversity are likely a result of the varying resistance that different bacteria have to temperature, toxic hydrocarbons, and drought stress. Future studies with increased sample sizes can provide further data and might also explore the long-term effects of fire on bacterial populations and soil health.
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