• Energy Research

AbstractControls on the fate of ~277 Pg of soil organic carbon (C) stored in permafrost peatland soils remain poorly understood despite the potential for a significant positive feedback to climate change. Our objective was to quantify the temperature, moisture, organic matter, and microbial controls on soil organic carbon (SOC) losses following permafrost thaw in peat soils across Alaska. We compared the carbon dioxide (CO2) and methane (CH4) emissions from peat samples collected at active layer and permafrost depths when incubated aerobically and anaerobically at −5, −0.5, +4, and +20 °C. Temperature had a strong, positive effect on C emissions; global warming potential (GWP) was >3× larger at 20 °C than at 4 °C. Anaerobic conditions significantly reduced CO2 emissions and GWP by 47% at 20 °C but did not have a significant effect at −0.5 °C. Net anaerobic CH4 production over 30 days was 7.1 ± 2.8 μg CH4‐C gC−1 at 20 °C. Cumulative CO2 emissions were related to organic matter chemistry and best predicted by the relative abundance of polysaccharides and proteins (R2 = 0.81) in SOC. Carbon emissions (CO2‐C + CH4‐C) from the active layer depth peat ranged from 77% larger to not significantly different than permafrost depths and varied depending on the peat type and peat decomposition stage rather than thermal state. Potential SOC losses with warming depend not only on the magnitude of temperature increase and hydrology but also organic matter quality, permafrost history, and vegetation dynamics, which will ultimately determine net radiative forcing due to permafrost thaw.

AbstractArctic and subarctic ecosystems are experiencing substantial changes in hydrology, vegetation, permafrost conditions, and carbon cycling, in response to climatic change and other anthropogenic drivers, and these changes are likely to continue over this century. The total magnitude of these changes results from multiple interactions among these drivers. Field measurements can address the overall responses to different changing drivers, but are less capable of quantifying the interactions among them. Currently, a comprehensive assessment of the drivers of ecosystem changes, and the magnitude of their direct and indirect impacts on subarctic ecosystems, is missing. The Torneträsk area, in the Swedish subarctic, has an unrivalled history of environmental observation over 100 years, and is one of the most studied sites in the Arctic. In this study, we summarize and rank the drivers of ecosystem change in the Torneträsk area, and propose research priorities identified, by expert assessment, to improve predictions of ecosystem changes. The research priorities identified include understanding impacts on ecosystems brought on by altered frequency and intensity of winter warming events, evapotranspiration rates, rainfall, duration of snow cover and lake-ice, changed soil moisture, and droughts. This case study can help us understand the ongoing ecosystem changes occurring in the Torneträsk area, and contribute to improve predictions of future ecosystem changes at a larger scale. This understanding will provide the basis for the future mitigation and adaptation plans needed in a changing climate.

Abstract Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms mediate methane cycling, yet knowledge of their conservation across wetlands remains scarce. To address this, we integrated 1,118 16S rRNA amplicon datasets (116 new), 305 metagenomes (20 new) that yielded 4,745 medium and high-quality metagenome assembled genomes (MAGs; 617 new), 133 metatranscriptomes, and annual methane flux data across 9 wetlands to create the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This new resource was leveraged to link microbiome compositional profiles to encoded functions and emissions, with specific focus on methane-cycling populations and the microbial carbon decomposition networks that fuel them. We identified eight methane-cycling genera that were conserved across wetlands, and deciphered wetland specific metabolic interactions across marshes, revealing low methanogen-methanotroph connectivity in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and was a strong predictor of methane flux, demonstrating the potential broad relevance of methylotrophic methanogenesis in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux and provide an extensive publicly available database to advance future wetland research.

Permafrost soils store over half of global soil carbon (C), and northern frozen peatlands store about 10% of global permafrost C. With thaw, inundation of high latitude lowland peatlands typically increases the surface-atmosphere flux of methane (CH _4 ), a potent greenhouse gas. To examine the effects of lowland permafrost thaw over millennial timescales, we measured carbon dioxide (CO _2 ) and CH _4 exchange along sites that constitute a ∼1000 yr thaw chronosequence of thermokarst collapse bogs and adjacent fen locations at Innoko Flats Wildlife Refuge in western Alaska. Peak CH _4 exchange in July (123 ± 71 mg CH _4 –C m ^−2 d ^−1 ) was observed in features that have been thawed for 30 to 70 (<100) yr, where soils were warmer than at more recently thawed sites (14 to 21 yr; emitting 1.37 ± 0.67 mg CH _4 –C m ^−2 d ^−1 in July) and had shallower water tables than at older sites (200 to 1400 yr; emitting 6.55 ± 2.23 mg CH _4 –C m ^−2 d ^−1 in July). Carbon lost via CH _4 efflux during the growing season at these intermediate age sites was 8% of uptake by net ecosystem exchange. Our results provide evidence that CH _4 emissions following lowland permafrost thaw are enhanced over decadal time scales, but limited over millennia. Over larger spatial scales, adjacent fen systems may contribute sustained CH _4 emission, CO _2 uptake, and DOC export. We argue that over timescales of decades to centuries, thaw features in high-latitude lowland peatlands, particularly those developed on poorly drained mineral substrates, are a key locus of elevated CH _4 emission to the atmosphere that must be considered for a complete understanding of high latitude CH _4 dynamics.

AbstractNorthern peatlands are a globally significant source of methane (CH4), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ13C‐CH4) being a powerful tool for characterizing these drivers. Given that δ13C‐CH4 is used in top‐down atmospheric inversion models to partition sources, our ability to model CH4 production pathways and associated δ13C‐CH4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ13C‐CH4 values from high‐latitude peatlands. We measured porewater and emitted CH4 stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ13C‐CH4 was strongly associated with peatland type, with δ13C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ13C‐CH4 was best explained by sedge cover, CH4 concentration, and the interactive effect of peatland type and pH (r2 = 0.50, p < 0.001). Emitted δ13C‐CH4 varied greatly but was positively correlated with porewater δ13C‐CH4. We calculated a mixed atmospheric δ13C‐CH4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ13C‐CH4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Abstract Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides the first example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.