Wildland fire smoke alters the composition, diversity, and potential atmospheric function of microbial life in the aerobiome

Fire conditions and particulate and bioaerosol emissions

Fire radiative power values estimated from satellite imagery ranged from 6 to 259 MW over three days of burning [19]. Smoke sampled above combusting vegetation contained high concentrations of PM₁₀ (mean ± s.e. 928.4 ± 140.6 µg m⁻³; Fig. 1). Microbial cells are a component of total bioaerosols, and their abundance can correlate with PM in ambient conditions [24] as well as in wildland fire smoke [6]. However, we observed that only the concentration of viable cells (and not total cells) correlated with PM_2.5 and PM₁₀ values (r² = 0.80, and 0.81, respectively; p < 0.03) in all air samples, while PM_2.5 and PM₁₀ were weakly correlated with viable cell abundance in smoke (p < 0.10). If cell aggregates are attached to individual particles as reported previously [6], it might be inherently difficult to detect linear correlations between these aerosol types.

Temperature, relative humidity (RH), and wind speed are conditions that influence microbial aerosol emissions, as well as their composition, abundance, and viability [25]. In general, temperature, wind speed, and RH are higher in smoke plumes compared to surrounding air masses [26]. During our flights, environmental conditions in-plume generally followed these expectations. However, none of the environmental variables measured could explain the variation in cell concentrations observed within either air type. Ground-level (2 m) wind speeds pre-burn and during smoke sampling flights did not differ significantly, (2.5 ± 0.1 m s⁻¹ vs. 4.0 ± 0.2 m s⁻¹, p < 0.05), suggesting any confounding effects of background (i.e. not fire-generated) winds on microbial aerosolization patterns were similar between ambient and smoke samples. It is likely that cell concentration variability was driven by a complex interaction of environmental conditions, fire behavior, and which fuels were undergoing active combustion at the time of sampling.

The concentrations of cells presented in Fig. 1 are based on the total number of cells observed per volume of air sampled minus the number of cells observed in procedural blanks. The cell concentration in smoke sampled during flights (mean ± standard error; 1.02 ± 0.26 × 10⁵ m⁻³) was significantly higher (Mann–Whitney U test; p < 0.02) than in air sampled prior to burning (2.6 ± 0.3 × 10⁴ m⁻³). The high coefficient of variation for the smoke cell data (25%) is similar to that of previous studies [6] and likely reflects the dynamic nature of fire behavior. For example, crown fire fuel types support both torching and intermittent crown fire that create highly variable and turbulent winds [27]. The cell concentrations observed in smoke are about twice those reported from ground-based samples of small, low-intensity prescribed fire smoke in grass/shrub fuels in Florida, USA [6]. The higher values in this study imply that differences in fuel composition/consumption coupled with a higher fire intensity and area burned produce higher cell concentrations, as is also observed for wildfire dust emissions [28]. In contrast to <5 Mg ha⁻¹ fuel consumption values typical of prescribed burns in the Florida fuel type [29], fuel consumption values determined in this study using aerial LiDAR averaged 59.7 Mg ha⁻¹, with a 90th percentile value of 127.2 Mg ha⁻¹ (Hudak & McCarley, personal comm.). Higher cell and particle concentrations may also be due to collecting aerosol data and samples directly above and from within smoke plumes, rather than downwind using ground-based sampling locations that were ~30 m outside the combustion zone in the Florida study [6]. Based on smoke modeling projections (FOFEM v 6.7: [22]) under typical 90% wildfire weather conditions, we estimate that 3.71 × 10¹⁴ cells ha⁻¹ were aerosolized, which is fivefold higher than values estimated for the prescribed burns in Florida [6].

Based on epifluorescence microscopy of samples stained with SYTO 9 and propidium iodide to distinguish total and dead cells, respectively, cell viabilities of 69 ± 17% were inferred for ambient air, whereas 78 ± 5% of cells in smoke appeared to be viable (Fig. 1). There were 3.4 times as many viable cells in smoke versus ambient air (6.2 ± 1.3 × 10⁴ m⁻³ and 1.8 ± 0.434 ×10⁴ m⁻³, respectively). Cell concentrations were not significantly different across sampling altitudes of 40 to 150 m above the combustion zone, indicating that microbial aerosols within the smoke plumes sampled were relatively well mixed. Although the abundance of microbial cells in smoke was higher than those reported in the afore-mentioned Florida burns, the fraction of cells inferred to be viable (Fig. 1) was similar (80%; (5)). Given the high intensity of the fires sampled and the sensitivity of many microorganisms to high temperatures, this result is unexpected. Although temperatures in crown fires can exceed 1000 °C [30], there is high variability of temperature at sub-meter scales [31, 32]. At scales applicable to particulate aerosols, microorganisms may be protected from high exposure to heat and water loss by the materials they are attached to (e.g. particles of mineral soil or plant tissue). Alternatively, the microbes found in smoke may be advected from soils and plant surfaces from outside the combustion zone and mixed with incompletely combusted particulate matter in the smoke plume as a result of “pyro-convection” [28].

Vertical air mixing due to combustion aerosolizes micro- to macroscopic particles [33] from plant material as well as organic and mineral components of soil [28, 34]. For example, the smoke plume of the high-intensity Biscuit Fire in Oregon, USA, was estimated to aerosolize 127 Mg·ha⁻¹ of fine mineral soil and transport it across the Pacific Ocean [34]. Field measurements indicate that as a fire front progresses, combustion increases air buoyancy that induces strong vertical lifting in smoke columns followed by a weaker subsidence forming behind the fire front [29]. A plume from the El Portal wildfire in Yosemite National Park, CA induced updraft winds of 13.5 m s⁻¹, and horizontal indraft into the convective column extended over a kilometer from the center of the plume [35]. Since wind speeds as low as 2–3 m s⁻¹ are sufficient to aerosolize microbial cells from soils or plant surfaces [25], higher values associated with intense fires should significantly increase the contribution of bioaerosols sourced both external and internal to the region of combustion.

Microbial diversity of wildland fire smoke

Bacterial and archaeal assemblages

The phylum-level taxonomic composition of the bacteria in smoke and ambient air was dominated by members of the Actinobacteria, which comprised 50.7 ± 2.9% and 36.1 ± 4.8%, respectively, of the total sequences (Fig. 2A; SI Appendix Figs. S2, S3). Bacteroidetes (5.3 ± 1%), Chloroflexi (4.4 ± 1%), Planctomycetes (3.6 ± 0.9%), Acidobacteria (2.6 ± 0.8%), and Deltaproteobacteria (1.3 ± 0.7%) were all more abundant in smoke than in ambient air (Fig. 2A, SI Appendix Fig. S2). Archaea were only recovered in smoke, with Thaumarchaeota representing 0.4 ± 0.2% of the read abundance. Firmicutes were significantly higher in ambient air (19.1 ± 4.2%) than in smoke (4.7 ± 0.8%). However, despite having overall lower abundance in smoke, there was higher diversity of distinct Firmicute families associated with the spore-forming orders Bacillales and Clostridiales in smoke [36] (Fig. S2). Elevated proportions of Actinobacteria, Firmicutes, and Proteobacteria have also been reported in other aerobiology studies, such as in clouds [37], intercontinental dust [38], and in rural versus urban centers [39, 40]. In our study, Actinobacteria were significantly enriched in smoke above background levels. This could be due to morphological features that facilitate aerosolization, such as the production of mycelial hyphae and spores in many known strains of Actinobacteria [41]. Furthermore, smoke was enriched with bacteria phylogenetically related to taxa with known associations to soils and the phyllosphere [6], such as ammonium oxidizing archaea within the Thaumarchaeota (Fig. 2A), Actinobacteria families Geodermatophilaceae, Kineosporiaceae, Intrasporangiaceae, Solirubrobacteraceae, and Pseudonocardaceae, and Alpha- and Betaproteobacteria families Sphingomonadaceae, Bradyrhizobiaceae, and Nitrosomonadaceae (Figs. 2A, 3, SI Appendix Figs. S4, S5). This observation is consistent with these bacteria being sourced from soil and plants within the local species pool, as suggested by Bowers et al. for non-smoke bioaerosols [40]. In ambient air, Lactobacillus sp. and Streptococcus sp. were found in higher read abundance over smoke samples (Fig. 3). Lactobacillus is commonly associated with fermentation products but along with many Streptococci is also associated with oral microbiota. However, numerous ASVs of Lactobacillus and Streptoccocus genera were also identified in environmental sources (soil, plants) characterized by Dove et al. in locations neighboring our study units [42], highlighting the relative ease by which these organisms may be transported in air.

A higher proportion of the bacterial phylotypes were unique to smoke than to ambient air (959 versus 150, respectively), with only a small fraction shared between the air types (Fig. 2B). Bacterial libraries also differed significantly between ambient and smoke with regards to community structure (r²_ADONIS = 0.06, p = 0.001; Fig. 2C) and diversity metrics (t-test, Hill-q₁: p < 0.001, Hill-q₂: p < 0.001; Fig. 2D), with Actinobacteria, Alphaproteobacteria, Firmicutes, and Bacteroidetes driving most of the inter-sample variation (SI Appendix Fig. S3). Together with observations that wildland fires aerosolize viable microbes (Fig. 1), the molecular results show that assemblages of bacteria and archaea in smoke are more diverse (Fig. 2) and distinct from those found in ambient air. Model simulations of airborne microbial dispersal suggests that intra-hemispheric transport of particles 10-20 µm in diameter can be successfully distributed over one year [43] and if shielded by inclusions within particulate matter, may be able to survive UV irradiation in the upper atmosphere [44]. As smoke contained numerous phylotypes closely related to potential human or plant pathogens, including Bacillus anthracis-cereus, Pseudomonas syringae, Streptococcus spp., Escherichia-Shigella coli, Corynebacterium jeikeium, Acinetobacter ursingii, Haemophilus haemolyticus-influenzae, and some Staphylococcus spp. (the last genus also appeared in ambient air), long-distance and long-duration transport of fire-vectored microbes may have implications for global health.

Eukaryotic assemblages

The structure and diversity of eukaryotic assemblages based on 18S rRNA gene sequence analysis differed between ambient and smoke samples (r²_ADONIS = 0.07, p = 0.01; Fig. 2B; t-test, Hill-q₁: p = 0.04, Hill-q₂: p = 0.08; Fig. 2C, D) although at a weaker significance level than observed for bacterial assemblages. The eukaryotic libraries were dominated by fungal taxa (78 ± 8.4 and 66 ± 4.2% Nucletmycea for ambient air and smoke, respectively; Fig. 2A, Fig. S6A), and differences in composition between the ambient and smoke samples was primarily due to the abundance of sequencing reads from the plant phylum Chloroplastida (9.9 ± 5.1% and 19.9 ± 3.9%, respectively; Fig. 2A, Fig. S6A). The relative abundance of Chloroplastida phylotypes in smoke did not correlate with the viable or total cell concentrations, with 61 sequences (74%) being closely related to Pinales. Sequences in the Pinales order comprised over 10.8% (75,851 reads) of the total 18S reads in smoke, compared to only 2.7% (6336 reads) in the ambient air. As Pinales includes a majority of the dominant tree species burned in the site (e.g., Abies, Picea spp.), this difference indicates that tree components (e.g., partially combusted litter, downed woody debris, live and dead standing trees, and pollen) associated with wildland fire were a direct source of bioaerosols in smoke. The low abundance of Pinales in ambient air (found only in one ambient sample vs. 11/17 samples in smoke) may indicate pollen serving as the source of genetic material collected under background conditions, as would be consistent for the season and location [45] and considering the unlikely potential for the low ambient wind speeds observed to aerosolize other plant materials during ambient air sampling. There is a critical need for approaches that accurately track specific combustion sources in smoke, and chemical speciation of aerosol-phase emissions has proved useful for this purpose [46], but the extent to which aerosol chemistry alone can be used for apportionment of biomass-burning constituents is limited. The results of this study indicate that genetic material from fuel sources remains sufficiently preserved in smoke for DNA sequence characterization, demonstrating the potential for a novel alternative for tracking the contribution of specific wildland fires (with known fuel types) to air pollution.

ITS-based characterization of fungal taxa showed that Ascomycota made up 68.7 ± 12.4% and 80.9 ± 6.4% of ambient and smoke libraries, respectively, and their prevalence over Basidiomycota has been reported in some [47, 48] but not all aerobiological studies [49, 50]. Basidiomycota were more abundant in ambient air (29.2 ± 12.7%) than in smoke (12.5 ± 3.9%) (Fig. S6B). ITS sequencing identified a total of 133 fungal taxa across all samples: 93 of these were only found in smoke, 31 taxa were unique to ambient air, and 9 taxa were shared between smoke and ambient samples (Fig. 2B). Although volume of air sampled here is significantly lower than in non-smoke aerobiology studies, these estimates of richness are only moderately lower than those reported in other aerobiology investigations based on aerosols derived from larger air volumes and longer sampling durations (e.g. >1000 L) [49]. For example, Frohlich-Nowoisky et al. [49, 51] reported 368 species resulting from filtering 3 M L of air in a single location in Europe four times over a year. The approximately fivefold difference in number of cells in smoke versus ambient air samples in this study likely explains the relatively high number of taxa found even in the low volumes of smoke.

Similar to previous culture-independent studies of fungal heterogeneity in non-smoke air, most (95%) of the phylotypes detected were found in only one sample (e.g. compared to 70% in previous work [49]). This suggests that either the actual richness of fungi in smoke was underestimated by the sampling strategies used in this study, or that the dynamic nature of fuels consumption (oscillating between surface and crown fuels) emits non-overlapping source assemblages of organisms as fire moves across a landscape. There were are no detectable patterns in the phylotypes aerosolized in relation to time of day or among samples collected synoptically. Moreover, as reported in a previous study of fungi in settled dust from across the USA [48], a significant portion of the fungal families was unclassified (42.8% in smoke, 39% in ambient air), suggesting considerable challenges to characterizing species richness in bioaerosol samples due to limited reference libraries [48]. This may help explain why the ITS libraries did not differ across air types in either community structure (r²_ADONIS = 0.04, p = 0.76; Fig. 2C) or diversity (Mann–Whitney U test, Hill-q₁: W = 55.5, p = 0.2, Hill-q₂: W = 57.5, p = 0.3; Fig. 2D).

The bulk of the Basidiomycota reads in smoke were members of the Agaricomycetes and Ustilaginomycetes classes (68% and 16%, respectively). Dothideomycetes comprised 55.5% of the total sequences in smoke with Eurotiomycetes making up 6.3% (Fig. S6B). Compared to a global analysis of the continental airborne fungi [50], smoke Basidiomycota were more evenly represented across multiple classes rather than being dominated by Agaricomycetes, which reportedly comprised 84% of Basidiomycota bioaerosols across multiple continents. The identities and relative composition of the fungal families aerosolized in smoke differed from those reported by Dove et al. [42] for a nearby (Utah, USA) microbiome and study of soil and phyllosphere microbiomes. Of the top ten classified families found in smoke in this study, Davidiellaceae, Dothioraceae, Malasseziaceae, Helotiales and Pezizomycotina were not among the top ten in the leaf, stem, or fine root samples examined in the same ecosystems at nearby locations. These results suggest that wildland fire emits fungal assemblages that differ from their source communities in species relative composition, as would be expected due to the temporal and spatial heterogeneity of fuels consumption as well as differences in heat/desiccation tolerance and aerosolization potential among taxa.

A total of 48 out of 101 classifiable genera were found in smoke compared to 27 out of 92 in ambient air. Cladosporium is a genus common in bioaerosols and was the most frequently observed genus shared between ambient and smoke air (found in 80% of samples), while Aureobasidium spp., Alternaria spp., and Elasticomyces spp. were the only genera found in three or more of the smoke samples. Read abundance in smoke was highest among Auerobasidium, Ramularia, and Dothidea genera. Potential allergens and plant or human pathogens found in smoke included Cladosporium spp., Alternaria spp., Ustliago hordei, Aspergillus spp., Aspergillus penicillioides, Cladophialophora spp., Ochroconis spp., and Candida sake; the latter four found only in smoke. If smoke aerosols containing viable cells of these microorganism are deposited within or beyond the burned area, post-fire dynamics may be impacted. Since Cladosporium and Alternaria include phytopathogenic species, sources that increase their abundance in the phyllosphere following high severity fire could have relevance to post-fire aspen recovery [42].

Variability of taxa between sample type and across domains

To investigate the distribution and variability of abundant and rare taxa within each air type and domain, the rank order of each ASV was plotted against its cumulative read abundance (i.e., individual organisms within each ASV) (Fig. 4). This analysis enabled a direct comparison of variation within smoke and ambient air types (i.e., prevalence and consistency of taxa observed within air types), diversity between each air type, and of data obtained using different molecular approaches (i.e., for bacteria, fungal, and eukaryotic taxa). Based on the small-subunit rRNA and ITS regions analyzed, smoke samples were more diverse, particularly within ≥80% cumulative read abundance. Among the top ten most abundant taxa, we observed a high degree of variation within each air type, indicating that taxa were not uniformly found in consistent proportions, apart from bacterial and archaeal smoke taxa. The consistent prevalence (i.e., the likelihood of consistently sampling aerosols with the same proportion of taxa) of bacteria and archaea across smoke samples (see lower variation in Fig. 4) suggests these taxa may possess physiological or trait-specific fitness advantages amenable to aerosolization and survival during atmospheric transport. This might imply that a deeper and/or more abundant source pool of bacterial single cells, hyphae, or spores are aerosolized more easily from native sources in association with combustion processes leading to a more consistent and diverse microbial assemblage introduced to the atmosphere. Conversely, it appears that stochastic factors may be driving the distribution of eukaryotes and fungi in both ambient air and smoke, as well as bacteria in ambient air. Beyond aerosolization through combustion, the proximal air currents generated are likely to have less of a mitigating effect on the physical constraints associated with aerosolizing large particles [43]. The role of smoke in microbial dispersal and ecosystem function has not been previously considered, and given that the odds of colonization increase when immigrating microorganisms are abundantly sourced [52, 53], it represents new and fertile territory for future investigations [52]. Since climate change is increasing the risks, scale, and severity of wildfires in many regions, research addressing the dispersal of microorganisms by smoke and its ecological effects where deposited is timely.

Ice nucleation particles and microbial composition

The concentration of INPs was significantly higher in smoke (n = 17) than in ambient air (n = 4; p < 0.05), and smoke contained a larger proportion of INPs that were active across all temperatures > −16 °C (Fig. 5a). Fold-changes in INPs were highest at temperatures of −13 °C to −11 °C, as well as at −9 °C (Fig. 5b). In smoke and ambient air, total INPs were correlated with PM_1.0 (Pearson’s r = 0.59; p < 0.05), but not to larger (PM_2.5, PM₁₀) particle size classes (p > 0.05). INPs were more abundant in warmer air masses with lower RH (r(21) = 0.62, p < 0.04 and r(21) = −0.64, p < 0.04, respectively), which corresponds to the conditions when smoke was sampled. The highest numbers of INPs corresponded to the sampling periods when observed fire behavior was most extreme (crown fire). The proportion of heat-sensitive INPs, inferred to be biological in origin [54] (labeled “Bio” in Fig. 5), was higher in smoke than in ambient air (Fig. 5; p < 0.05), similar to findings from low-intensity prescribed fire smoke [6] and higher altitude wildfire smoke plumes measured using manned aircraft [55]. Smoke from forest fires is a long-suspected source of INPs [12, 28]; however, only recently have data been available that show smoke-derived INPs are predominantly biological [6, 55].

Smoke samples with higher ITS phylotype richness correlated positively with the total (r(15) = 0.63, p = 0.009) and biological INP abundance (r(15) = 0.65, p = 0.007), while there was no correlation in samples of ambient air. Within the 18S assemblage, ASV read abundance of Chloroplastida and Nucletmycea taxa also correlated positively with total INPs (r(15) = 0.56 and 0.56, respectively, p < 0.02). Since cell concentration did not correlate with phylotype richness (p > 0.05) or number of reads (p > 0.10), this pattern in smoke is not easily explained by higher cell counts. Although the most well-known bacterial ice-nucleating species belong to the Gammaproteobacteria (e.g., species in the Pseudomonadaceae, Xanthomonadaceae, and Enterobacteriaceae families), this class was not at higher relative abundance in smoke samples and Pseudomonadaceae taxa were more abundant in the ambient air samples. Together, these results suggest that wildland fire emits atypical biogenic INPs that originate from diverse microbial sources.

Source: Ecology - nature.com