Soil microbiome feedbacks during disturbance-driven forest ecosystem conversion.

Disturbances cause rapid changes to forests, with different disturbance types and severities creating unique ecosystem trajectories that can impact the underlying soil microbiome. Pile burning-the combustion of logging residue on the forest floor-is a common fuel reduction practice that can have impacts on forest soils analogous to those following high-severity wildfire. Further, pile burning following clear-cut harvesting can create persistent openings dominated by nonwoody plants surrounded by dense regenerating conifer forest. A paired 60-year chronosequence of burn scar openings and surrounding regenerating forest after clear-cut harvesting provides a unique opportunity to assess whether belowground microbial processes mirror aboveground vegetation during disturbance-induced ecosystem shifts. Soil ectomycorrhizal fungal diversity was reduced the first decade after pile burning, which could explain poor tree seedling establishment and subsequent persistence of herbaceous species within the openings. Fine-scale changes in the soil microbiome mirrored aboveground shifts in vegetation, with short-term changes to microbial carbon cycling functions resembling a postfire microbiome (e.g. enrichment of aromatic degradation genes) and respiration in burn scars decoupled from substrate quantity and quality. Broadly, however, soil microbiome composition and function within burn scar soils converged with that of the surrounding regenerating forest six decades after the disturbances, indicating potential microbial resilience that was disconnected from aboveground vegetation shifts. This work begins to unravel the belowground microbial processes that underlie disturbance-induced ecosystem changes, which are increasing in frequency tied to climate change.

Fire Impacts on the Soil Metabolome and Organic Matter Biodegradability.

Global wildfire activity has increased since the 1970s and is projected to intensify throughout the 21st century. Wildfires change the composition and biodegradability of soil organic matter (SOM) which contains nutrients that fuel microbial metabolism. Though persistent forms of SOM often increase postfire, the response of more biodegradable SOM remains unclear. Here we simulated severe wildfires through a controlled "pyrocosm" approach to identify biodegradable sources of SOM and characterize the soil metabolome immediately postfire. Using microbial amplicon (16S/ITS) sequencing and gas chromatography-mass spectrometry, heterotrophic microbes (Actinobacteria, Firmicutes, and Protobacteria) and specific metabolites (glycine, protocatechuate, citric cycle intermediates) were enriched in burned soils, indicating that burned soils contain a variety of substrates that support microbial metabolism. Molecular formulas assigned by 21 T Fourier transform ion cyclotron resonance mass spectrometry showed that SOM in burned soil was lower in molecular weight and featured 20 to 43% more nitrogen-containing molecular formulas than unburned soil. We also measured higher water extractable organic carbon concentrations and higher CO2 efflux in burned soils. The observed enrichment of biodegradable SOM and microbial heterotrophs demonstrates the resilience of these soils to severe burning, providing important implications for postfire soil microbial and plant recolonization and ecosystem recovery.

Wildfire-dependent changes in soil microbiome diversity and function.

Forest soil microbiomes have crucial roles in carbon storage, biogeochemical cycling and rhizosphere processes. Wildfire season length, and the frequency and size of severe fires have increased owing to climate change. Fires affect ecosystem recovery and modify soil microbiomes and microbially mediated biogeochemical processes. To study wildfire-dependent changes in soil microbiomes, we characterized functional shifts in the soil microbiota (bacteria, fungi and viruses) across burn severity gradients (low, moderate and high severity) 1 yr post fire in coniferous forests in Colorado and Wyoming, USA. We found severity-dependent increases of Actinobacteria encoding genes for heat resistance, fast growth, and pyrogenic carbon utilization that might enhance post-fire survival. We report that increased burn severity led to the loss of ectomycorrhizal fungi and less tolerant microbial taxa. Viruses remained active in post-fire soils and probably influenced carbon cycling and biogeochemistry via turnover of biomass and ecosystem-relevant auxiliary metabolic genes. Our genome-resolved analyses link post-fire soil microbial taxonomy to functions and reveal the complexity of post-fire soil microbiome activity.

Impact of beaver ponds on biogeochemistry of organic carbon and nitrogen along a fire-impacted stream.

Wildfires, which are increasing in frequency and severity in the western U.S., impact water quality through increases in erosion, and transport of nutrients and metals. Meanwhile, beaver populations have been increasing since the early 1900s, and the ponds they create slow or impound hydrologic and elemental fluxes, increase soil saturation, and have a high potential to transform redox active elements (e.g., oxygen, nitrogen, sulfur, and metals). However, it remains unknown how the presence of beaver ponds in burned watersheds may impact retention and transformation of chemical constituents originating in burned uplands (e.g., pyrogenic dissolved organic matter; pyDOM) and the consequences for downstream water quality. Here, we investigate the impact of beaver ponds on the chemical properties and molecular composition of dissolved forms of C and N, and the microbial functional potential encoded within these environments. The chemistry and microbiology of surface water and sediment changed along a stream sequence starting upstream of fire and flowing through multiple beaver ponds and interconnecting stream reaches within a burned high-elevation forest watershed. The relative abundance of N-containing compounds increased in surface water of the burned beaver ponds, which corresponded to lower C/N and O/C, and higher aromaticity as characterized by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The resident microbial communities lack the capacity to process such aromatic pyDOM, though genomic analyses demonstrate their potential to metabolize various compounds in the anaerobic sediments of the beaver ponds. Collectively, this work highlights the role of beaver ponds as biological "hotspots" with unique biogeochemistry in fire-impacted systems.

Statistical Learning and Uncommon Soil Microbiota Explain Biogeochemical Responses after Wildfire.

Wildfires are a perennial event globally, and the biogeochemical underpinnings of soil responses at relevant spatial and temporal scales are unclear. Soil biogeochemical processes regulate plant growth and nutrient losses that affect water quality, yet the response of soil after variable intensity fire is difficult to explain and predict. To address this issue, we examined two wildfires in Colorado, United States, across the first and second postfire years and leveraged statistical learning (SL) to predict and explain biogeochemical responses. We found that SL predicts biogeochemical responses in soil after wildfire with surprising accuracy. Of the 13 biogeochemical analytes analyzed in this study, 9 are best explained with a hybrid microbiome + biogeochemical SL model. Biogeochemical-only models best explain 3 features, and 1 feature is explained equally well with the hybrid and biogeochemical-only models. In some cases, microbiome-only SL models are also effective (such as predicting NH4+). Whenever a microbiome component is employed, selected features always involve uncommon soil microbiota (i.e., the "rare biosphere" [existing at <1% mean relative abundance]). Here, we demonstrate that SL paired with DNA sequence and biogeochemical data predicts environmental features in postfire soils, although this approach could likely be applied to any biogeochemical system. IMPORTANCE Soil biogeochemical processes are critical to plant growth and water quality and are substantially disturbed by wildfire. However, soil responses to fire are difficult to predict. To address this issue, we developed a large environmental data set that tracks postfire changes in soil and used statistical learning (SL) to build models that exploit complex data to make predictions about biogeochemical responses. Here, we show that SL depends upon uncommon microbiota in soil (the "rare biosphere") to make surprisingly accurate predictions about soil biogeochemical responses to wildfire. Using SL to explain variation in a natively chaotic environmental system is mechanism independent. Likely, the approach that we describe for combining SL with microbiome and biogeochemical parameters has practical applications across a range of issues in the environmental sciences where predicting responses would be useful.

River channel connectivity shifts metabolite composition and dissolved organic matter chemistry.

Biogeochemical processing of dissolved organic matter (DOM) in headwater rivers regulates aquatic food web dynamics, water quality, and carbon storage. Although headwater rivers are critical sources of energy to downstream ecosystems, underlying mechanisms structuring DOM composition and reactivity are not well quantified. By pairing mass spectrometry and fluorescence spectroscopy, here we show that hydrology and river geomorphology interactively shape molecular patterns in DOM composition. River segments with a single channel flowing across the valley bottom export DOM with a similar chemical profile through time. In contrast, segments with multiple channels of flow store large volumes of water during peak flows, which they release downstream throughout the summer. As flows subside, losses of lateral floodplain connectivity significantly increase the heterogeneity of DOM exported downstream. By linking geomorphologic landscape-scale processes with microbial metabolism, we show DOM heterogeneity increases as a function of fluvial complexity, with implications for ecosystem function and watershed management.

Examining the Potential of Forest Residue-Based Amendments for Post-Wildfire Rehabilitation in Colorado, USA.

Wildfire is a natural disturbance, though elemental losses and changes that occur during combustion and post-fire erosion can have long-term impacts on soil properties, ecosystem productivity, and watershed condition. Here we evaluate the potential of forest residue-based materials to rehabilitate burned soils. We compare soil nutrient and water availability, and plant recovery after application of 37 t ha-1 of wood mulch, 20 t ha-1 of biochar, and the combination of the two amendments with untreated, burned soils. We also conducted a greenhouse trial to examine how biochar influenced soil nutrient and water content under two wetting regimes. The effects of wood mulch on plant-available soil N and water content were significant and seasonally consistent during the three-year field study. Biochar applied alone had few effects under field conditions, but significantly increased soil pH, Ca, P, and water in the greenhouse. The mulched biochar treatment had the greatest effects on soil N and water availability and increased cover of the most abundant native plant. We found that rehabilitation treatments consisting of forest residue-based products have potential to enhance soil N and water dynamics and plant recovery following severe wildfire and may be justified where erosion risk or water supply protection are crucial.