Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient.

Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO2 and CH4 porewater variations. Our study showcases insights gained by using feature-level data and microorganism-metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.

Microbial polyphenol metabolism is part of the thawing permafrost carbon cycle.

With rising global temperatures, permafrost carbon stores are vulnerable to microbial degradation. The enzyme latch theory states that polyphenols should accumulate in saturated peatlands due to diminished phenol oxidase activity, inhibiting resident microbes and promoting carbon stabilization. Pairing microbiome and geochemical measurements along a permafrost thaw-induced saturation gradient in Stordalen Mire, a model Arctic peatland, we confirmed a negative relationship between phenol oxidase expression and saturation but failed to support other trends predicted by the enzyme latch. To inventory alternative polyphenol removal strategies, we built CAMPER, a gene annotation tool leveraging polyphenol enzyme knowledge gleaned across microbial ecosystems. Applying CAMPER to genome-resolved metatranscriptomes, we identified genes for diverse polyphenol-active enzymes expressed by various microbial lineages under a range of redox conditions. This shifts the paradigm that polyphenols stabilize carbon in saturated soils and highlights the need to consider both oxic and anoxic polyphenol metabolisms to understand carbon cycling in changing ecosystems.

Microbiome assembly in thawing permafrost and its feedbacks to climate.

The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost-climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post-thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw-mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well-suited to thrive in changing environmental conditions. We predict that on a short timescale and following high-disturbance thaw (e.g., thermokarst), stochasticity dominates post-thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower-intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post-thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.

Altered microbial structure and function after thermokarst formation.

Permafrost thaw could induce substantial carbon (C) emissions to the atmosphere, and thus trigger a positive feedback to climate warming. As the engine of biogeochemical cycling, soil microorganisms exert a critical role in mediating the direction and strength of permafrost C-climate feedback. However, our understanding about the impacts of thermokarst (abrupt permafrost thaw) on microbial structure and function remains limited. Here we employed metagenomic sequencing to analyze changes in topsoil (0-15 cm) microbial communities and functional genes along a permafrost thaw sequence (1, 10, and 16 years since permafrost collapse) on the Tibetan Plateau. By combining laboratory incubation and a two-pool model, we then explored changes in soil labile and stable C decomposition along the thaw sequence. Our results showed that topsoil microbial α-diversity decreased, while the community structure and functional gene abundance did not exhibit any significant change at the early stage of collapse (1 year since collapse) relative to non-collapsed control. However, as the time since the collapse increased, both the topsoil microbial community structure and functional genes differed from the control. Abundances of functional genes involved in labile C degradation decreased while those for stable C degradation increased at the late stage of collapse (16 years since collapse), largely driven by changes in substrate properties along the thaw sequence. Accordingly, faster stable C decomposition occurred at the late stage of collapse compared to the control, which was associated with the increase in relative abundance of functional genes for stable C degradation. These results suggest that upland thermokarst alters microbial structure and function, particularly enhances soil stable C decomposition by modulating microbial functional genes, which could reinforce a warmer climate over the decadal timescale.

The Transition From Stochastic to Deterministic Bacterial Community Assembly During Permafrost Thaw Succession.

The Northern high latitudes are warming twice as fast as the global average, and permafrost has become vulnerable to thaw. Changes to the environment during thaw leads to shifts in microbial communities and their associated functions, such as greenhouse gas emissions. Understanding the ecological processes that structure the identity and abundance (i.e., assembly) of pre- and post-thaw communities may improve predictions of the functional outcomes of permafrost thaw. We characterized microbial community assembly during permafrost thaw using in situ observations and a laboratory incubation of soils from the Storflaket Mire in Abisko, Sweden, where permafrost thaw has occurred over the past decade. In situ observations indicated that bacterial community assembly was driven by randomness (i.e., stochastic processes) immediately after thaw with drift and dispersal limitation being the dominant processes. As post-thaw succession progressed, environmentally driven (i.e., deterministic) processes became increasingly important in structuring microbial communities where homogenizing selection was the only process structuring upper active layer soils. Furthermore, laboratory-induced thaw reflected assembly dynamics immediately after thaw indicated by an increase in drift, but did not capture the long-term effects of permafrost thaw on microbial community dynamics. Our results did not reflect a link between assembly dynamics and carbon emissions, likely because respiration is the product of many processes in microbial communities. Identification of dominant microbial community assembly processes has the potential to improve our understanding of the ecological impact of permafrost thaw and the permafrost-climate feedback.

Heavy metals in the Arctic: Distribution and enrichment of five metals in Alaskan soils.

Metal contamination of food and water resources is a known public health issue in Arctic and sub-Arctic communities due to the proximity of many communities to mining and drilling sites. In addition, permafrost thaw may release heavy metals sequestered in previously frozen soils, potentially contaminating food and water resources by increasing the concentration of metals in freshwater, plants, and wildlife. Here we assess the enrichment of selected heavy metals in Alaskan soils by synthesizing publicly available data of soil metal concentrations. We analyzed data of soil concentrations of arsenic, chromium, mercury, nickel, and lead from over 1,000 samples available through the USGS Alaskan Geochemical Database to evaluate 1) the spatial distribution of sampling locations for soil metal analysis, 2) metal concentrations in soils from different land cover types and depths, and 3) the occurrence of soils in Alaska with elevated metal concentrations relative to other soils. We found substantial clustering of sample sites in the southwestern portion of Alaska in discontinuous and sporadic permafrost, while the continuous permafrost zone in Northern Alaska and the more populous Interior are severely understudied. Metal concentration varied by land cover type but lacked consistent patterns. Concentrations of chromium, mercury, and lead were higher in soils below 10 cm depth, however these deeper soils are under-sampled. Arsenic, chromium, mercury, nickel and lead concentrations exceeded average values for US soils by one standard deviation or more in 3.7% to 18.7% of the samples in this dataset. Our analysis highlights critical gaps that impede understanding of how heavy metals in thawing permafrost soils may become mobilized and increase exposure risk for Arctic communities.

The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities.

Microbial community structure is highly sensitive to natural (e.g., drought, temperature, fire) and anthropogenic (e.g., heavy metal exposure, land-use change) stressors. However, despite an immense amount of data generated, systematic, cross-environment analyses of microbiome responses to multiple disturbances are lacking. Here, we present the Microbiome Stress Project, an open-access database of environmental and host-associated 16S rRNA amplicon sequencing studies collected to facilitate cross-study analyses of microbiome responses to stressors. This database will comprise published and unpublished datasets re-processed from the raw sequences into exact sequence variants using our standardized computational pipeline. Our database will provide insight into general response patterns of microbiome diversity, structure, and stability to environmental stressors. It will also enable the identification of cross-study associations between single or multiple stressors and specific microbial clades. Here, we present a proof-of-concept meta-analysis of 606 microbiomes (from nine studies) to assess microbial community responses to: (1) one stressor in one environment: soil warming across a variety of soil types, (2) a range of stressors in one environment: soil microbiome responses to a comprehensive set of stressors (incl. temperature, diesel, antibiotics, land use change, drought, and heavy metals), (3) one stressor across a range of environments: copper exposure effects on soil, sediment, activated-sludge reactors, and gut environments, and (4) the general trends of microbiome stressor responses. Overall, we found that stressor exposure significantly decreases microbiome alpha diversity and increases beta diversity (community dispersion) across a range of environments and stressor types. We observed a hump-shaped relationship between microbial community resistance to stressors (i.e., the average pairwise similarity score between the control and stressed communities) and alpha diversity. We used Phylofactor to identify microbial clades and individual taxa as potential bioindicators of copper contamination across different environments. Using standardized computational and statistical methods, the Microbiome Stress Project will leverage thousands of existing datasets to build a general framework for how microbial communities respond to environmental stress.

Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change.

Global climate change is already having significant impacts on arctic and alpine ecosystems, and ongoing increases in temperature and altered precipitation patterns will affect the strong seasonal patterns that characterize these temperature-limited systems. The length of the potential growing season in these tundra environments is increasing due to warmer temperatures and earlier spring snow melt. Here, we compare current and projected climate and ecological data from 20 Northern Hemisphere sites to identify how seasonal changes in the physical environment due to climate change will alter the seasonality of arctic and alpine ecosystems. We find that although arctic and alpine ecosystems appear similar under historical climate conditions, climate change will lead to divergent responses, particularly in the spring and fall shoulder seasons. As seasonality changes in the Arctic, plants will advance the timing of spring phenological events, which could increase plant nutrient uptake, production, and ecosystem carbon (C) gain. In alpine regions, photoperiod will constrain spring plant phenology, limiting the extent to which the growing season can lengthen, especially if decreased water availability from earlier snow melt and warmer summer temperatures lead to earlier senescence. The result could be a shorter growing season with decreased production and increased nutrient loss. These contrasting alpine and arctic ecosystem responses will have cascading effects on ecosystems, affecting community structure, biotic interactions, and biogeochemistry.