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ABSTRACT Aerobes require dioxygen (O₂) to grow; anaerobes do not. However, nearly all microbes—aerobes, anaerobes, and facultative organisms alike—express enzymes whose substrates include O₂, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O₂utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O₂-utilizing enzymes, for example. These effects permit high-quality prediction of O₂utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content—e.g., triplets of amino acids—perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O₂gradient in the Black Sea, we found quantitative correspondence between local chemistry (O₂:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or “sense,” pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology—an organism’s capacity to engage metabolically with its environment—may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O₂levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O₂and other key facets of complex natural settings. 

Biogeochemical reactions modulate the chemical composition of the oceans and atmosphere, providing feedbacks that sustain planetary habitability over geological time. Here, we mathematically evaluate a suite of biogeochemical processes to identify combinations of reactions that stabilize atmospheric carbon dioxide by balancing fluxes of chemical species among the ocean, atmosphere, and geosphere. Unlike prior modeling efforts, this approach does not prescribe functional relationships between the rates of biogeochemical processes and environmental conditions. Our agnostic framework generates three types of stable reaction combinations: closed sets, where sources and sinks mutually cancel for all chemical reservoirs; exchange sets, where constant ocean–atmosphere conditions are maintained through the growth or destruction of crustal reservoirs; and open sets, where balance in alkalinity and carbon fluxes is accommodated by changes in other chemical components of seawater or the atmosphere. These three modes of operation have different characteristic timescales and may leave distinct evidence in the rock record. To provide a practical example of this theoretical framework, we applied the model to recast existing hypotheses for Cenozoic climate change based on feedbacks or shared forcing mechanisms. Overall, this work provides a systematic and simplified conceptual framework for understanding the function and evolution of global biogeochemical cycles. 

Abstract Permafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to <10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming. 

This document describes geomorphic relative age mapping and radiocarbon (14C) measurements used to construct floodplain age models for three locations within the Yukon River Watershed: Huslia, Alaska (65.700 N, 156.387 W), Alakanuk, Alaska (62.685 N, 164.644 W), and Beaver, Alaska (66.362 N, 147.398 W). We describe the field sampling protocols, geomorphic mapping of cross-cutting relationships (aided by digital elevation models (DEMs) and high-resolution satellite imagery), 14C and optically stimulated luminescence (OSL) lab analyses, Markov Chain Monte Carlo (MCMC) interpolation through the geomorphic–radiogenic age constraints, and the resulting floodplain terrain age models. 

The carbon stored in permafrost deposits represents the single largest soil carbon reservoir on Earth. Concerns about the instability and dynamics of this carbon reservoir during permafrost thaw associated with polar amplification of climate warming contribute a large part of the uncertainty in forecasting future climate. We have been studying the carbon dynamics of permafrost deposits contained in the floodplains of large Arctic rivers. Across Arctic floodplains, accelerating bank erosion can liberate permafrost organic carbon (OC) as carbon dioxide (CO2) or methane (CH4), and/or redeposit it in fluvial units. These different fates have very different implications for climate feedback. Determining OC stocks and their dynamics in Arctic floodplain cutbanks and point bars, as well as the OC load in fluvial transport, is essential to better understand the recycling and export of permafrost carbon. As part of a National Science Foundation (NSF) funded project to better understand the effects of erosion in the Yukon River Basin, floodplain sediments were collected between June and September 2022 at two locations underlain by discontinuous permafrost within the Yukon River Basin in Alaska: Beaver (65.700° North (N), 156.387° West (W)) and Huslia (66.362° N, 147.398° W). This dataset mainly reports OC contents for collected subsurface sediments in floodplains measured by elemental analyzer. The coupled mercury content can be found in Isabel et al., 2024 (https://doi.org/10.18739/A2RF5KH5J). 

Due to atmospheric circulation and preservation of organic matter, large amounts of mercury (Hg) are stored in permafrost regions. Due to rapid warming and thawing permafrost in the Arctic, this Hg may be released, potentially degrading water quality and impacting human health. River bank erosion in particular has the ability to quickly mobilize large amounts of Hg-rich floodplain sediments. As part of a National Science Foundation (NSF) funded project to better understand the effects of erosion in the Yukon River Basin, floodplain sediments were collected between June and September 2022 at two locations underlain by discontinuous permafrost within the Yukon River Basin: Beaver, Alaska (AK) (65.700 N, 156.387 W) and Huslia, AK (66.362N, 147.398 W). This dataset contains mercury contents for collected floodplain sediments measured by direct thermal decomposition. Sample metadata also includes information recorded in the field (location, visual grain size description, and sample collection depth) and collected post sample processing (water content and dry density). 

This dataset includes field measurements of above-ground biomass made between May and October, 2023 in three locations within the Yukon River Watershed: Huslia, Alaska(AK) (65.700 N, 156.387W), Beaver, AK (66.362 N, 147.398W), and Alakanuk, AK (62.685N, 164.644W). We measured a total of 11,335 trees, distributed in 190 field plots (approximately 10 meter (m) x 10 m). We apply allometric scaling relations to convert measurements of tree diameter to kilograms of dry biomass. We then link these filed measurements of above-ground biomass density to the mean forest canopy height (MCH), derived from airborne Light Detection and Ranging (LiDAR) data. We derive empirical regressions linking MCH to above-ground biomass in each of the field sites, and then apply these empirical relationships to the LiDAR datasets to obtain maps of above-ground biomass density. This dataset includes both the field observations (coordinates, tree type, and tree diameter of the 11,335 inventoried trees) and the processed above-ground biomass maps (georeferenced TIFF files, with a spatial resolution of 10 m). 

The file "riverfloc_datacompilation.csv" contains the data in csv format. The file "metadata.txt" contains the metadata describing the data in the csv file. This version corrects an error in which the ionic strength and relative charge density (variables 48 and 50) were underestimated by a factor of 1000. 

Fly ash—the residuum of coal burning—contains a considerable amount of fossilized particulate organic carbon (FOC ash ) that remains after high-temperature combustion. Fly ash leaks into natural environments and participates in the contemporary carbon cycle, but its reactivity and flux remained poorly understood. We characterized FOC ash in the Chang Jiang (Yangtze River) basin, China, and quantified the riverine FOC ash fluxes. Using Raman spectral analysis, ramped pyrolysis oxidation, and chemical oxidation, we found that FOC ash is highly recalcitrant and unreactive, whereas shale-derived FOC (FOC rock ) was much more labile and easily oxidized. By combining mass balance calculations and other estimates of fly ash input to rivers, we estimated that the flux of FOC ash carried by the Chang Jiang was 0.21 to 0.42 Mt C⋅y −1 in 2007 to 2008—an amount equivalent to 37 to 72% of the total riverine FOC export. We attributed such high flux to the combination of increasing coal combustion that enhances FOC ash production and the massive construction of dams in the basin that reduces the flux of FOC rock eroded from upstream mountainous areas. Using global ash data, a first-order estimate suggests that FOC ash makes up to 16% of the present-day global riverine FOC flux to the oceans. This reflects a substantial impact of anthropogenic activities on the fluxes and burial of fossil organic carbon that has been made less reactive than the rocks from which it was derived.