Thu, Aug 18, 2022: 2:30 PM-2:45 PM
516B
Background/Question/MethodsMega-fires of unprecedented size, intensity, and socio-economic impacts have surged globally due to climate change, fire suppression, and development at the wildland-urban interface. Soil microbiomes are critical for post-fire plant regeneration and nutrient cycling, yet how mega-fires impact the soil microbiome remains unclear. We had a serendipitous opportunity to obtain pre- and post-fire soils from the same sampling locations after the 2016 Soberanes mega-fire burned with high severity throughout several of our established redwood-tanoak plots in the Big Sur region of California. We sampled the top 10 cm of soil with ~250mL corers from 12 subsamples from 3 plots (2 burned and 1 unburned) pre- and post-fire and used Illumina MiSeq sequencing of 16S and ITS1 rRNA genes to assess changes in bacterial and fungal richness and community composition. We used CONSENTRAIT to identify if bacterial and fungal lineages that positively or negatively responded to fire were phylogenetically conserved. We identified pyrophilous “fire-loving” bacteria and fungi by assessing which microbes massively increased in abundance post-fire. This is the first study to examine microbial fire response in redwood-tanoak forests, and one of the only studies to have pre- and post-fire samples from the same plots after a mega-fire.
Results/ConclusionsFire led to a massive reduction in richness, large changes in composition, and an increase in dominance for both bacteria and fungi. Bacterial richness was reduced by 40-50% and fungal richness was reduced by 38-70% in burned plots, with richness unchanged in the unburned plot. Fire altered composition by 27% for bacteria and 24% for fungi, whereas the unburned plots experienced no change in fungal and negligible change in bacterial composition. Pyrophilous taxa that positively responded to fire appeared to be phylogenetically conserved in both bacteria and fungi, suggesting shared evolutionary traits. While most taxa negatively responded to fire, the bacteria Firmicutes and Actinobacteria positively responded to fire at the phylum level and dominated bacterial post-fire communities. Fungi positively responded to fire at the class level, with fire increasing the Ascomycota classes Pezizomycetes and Eurotiomycetes and the Basidiomycota class of heat-resistant Geminibasidiomycete yeasts. Fire also shifted dominant fungal taxa from mostly basidiomycetes and ectomycorrhizal fungi to largely saprobes and pyrophilous ascomycetes also observed after pine forest fires. We built from Grime’s Competitor-Stress tolerator-Ruderal framework and its recent microbial applications to show how our results might fit into a trait-based conceptual model to help predict generalizable microbial responses to fire.
Results/ConclusionsFire led to a massive reduction in richness, large changes in composition, and an increase in dominance for both bacteria and fungi. Bacterial richness was reduced by 40-50% and fungal richness was reduced by 38-70% in burned plots, with richness unchanged in the unburned plot. Fire altered composition by 27% for bacteria and 24% for fungi, whereas the unburned plots experienced no change in fungal and negligible change in bacterial composition. Pyrophilous taxa that positively responded to fire appeared to be phylogenetically conserved in both bacteria and fungi, suggesting shared evolutionary traits. While most taxa negatively responded to fire, the bacteria Firmicutes and Actinobacteria positively responded to fire at the phylum level and dominated bacterial post-fire communities. Fungi positively responded to fire at the class level, with fire increasing the Ascomycota classes Pezizomycetes and Eurotiomycetes and the Basidiomycota class of heat-resistant Geminibasidiomycete yeasts. Fire also shifted dominant fungal taxa from mostly basidiomycetes and ectomycorrhizal fungi to largely saprobes and pyrophilous ascomycetes also observed after pine forest fires. We built from Grime’s Competitor-Stress tolerator-Ruderal framework and its recent microbial applications to show how our results might fit into a trait-based conceptual model to help predict generalizable microbial responses to fire.