Journal of Geophysical Research: Biogeosciences最新文献

High-resolution environmental monitoring is necessary to record, understand, and predict biogeochemical and ecological changes particularly in coastal systems but brings significant challenges in processing and making rapidly available the resulting data. The COMPASS-FME project established a network of coastal observational sites across the Chesapeake Bay and western Lake Erie regions extensively instrumented with soil, vegetation, and weather sensors logging data every 15 min. Our data processing framework, written in R and completely open source, prioritizes rapid model-experiment iteration and makes biogeochemical data rapidly available for quality assurance/quality control, analysis, and model ingestion. This pipeline is distinguished by a standardized and modular approach to data curation, extensive metadata and documentation, and its high performance. These attributes combine to make biogeochemical data rapidly accessible across COMPASS-FME and the broader community. Flexible, powerful, and reproducible approaches to handling high-volume environmental data are crucial for accelerating biogeosciences research.

Climate change-induced increases in sea ice retreat and coastal erosion affect polar biogeochemical processes of persistent organic pollutants. This study investigated the distribution and fate of traditional and emerging Polychlorinated biphenyls (PCBs) in the sediments of the East Siberian Sea (ESS) and Chukchi Sea (CS). PCB 11 was the most dominant PCB congener detected in the sediments. PCB concentrations were higher in the open sea of the CS and along the ESS shelf break than in the ESS coastal region. Based on the correlation between PCB concentrations and total organic carbon (OC), as well as the result of the Positive Matrix Factorization model, the release of historical PCBs from eroded soils along the Siberian coast dominated in the ESS coastal region, whereas biogenic deposition of emerging PCBs prevailed in open sea areas. These findings highlight that the spatial heterogeneity of OC with varied origins determines the fates of PCBs in the high-latitude marginal seas.

Peat soils are a critical component of the global carbon cycle as natural producers of biogenic greenhouse gases (e.g., methane and carbon dioxide) that accumulate within the soil and are released to the atmosphere. Previous studies have showed the ability of ground-based minimally-invasive geophysical methods such as ground-penetrating radar (GPR) to characterize carbon dynamics in peat soils. However, ground-based GPR is limited by scale of measurement and soil disturbance potentially altering gas releases during deployment. Here, we explore the potential of drone-based GPR for identification of hot spots and hot moments of gas accumulation and release in subtropical soils. We collected drone-based GPR data sets across two grids (∼17,500 m²) in the Everglades during January (dry season), September, and November (wet season) of 2023 to characterize peat thickness and seasonal variability of gas content. Results show that drone-based GPR is effective and efficient for: (a) capturing the temporal variation of in situ biogenic gas content in peat soils with changes between 1% and 25 % volumetric gas content over repeatable grids; (b) inferring a total peat thickness between 0.8 and 1.2 m; and (c) estimating flux releases of 63 and 135 mg CH₄ m⁻² day⁻¹ for specific locations and periods that are strikingly consistent with our coincident gas trap measurements. This work also indicates that (a) spatial distribution of gas content in the Everglades is strongly controlled by landscape morphology such as ridges and sloughs and (b) the temporal variation of gas content is seasonal with increased gas production during the wet season.

Microorganisms catalyze the turnover of reactants in the subsurface, determining the fate of major groundwater constituents and contaminants. Yet our quantitative understanding of microbial dynamics lags behind its importance. Functional molecular-biological methods offer a powerful tool (box) to quantify microbial dynamics in the environment. Their quantitative potential has only recently been probed via the integration of DNA-synthesis and RNA-transcription processes into reaction models. Here, we present the results of an experiment where we actively stimulated the microbial community via nitrate injection into an anaerobic aquifer and monitored concentrations in an extraction well 1.6 m apart. We installed microbial trapping devices (MTDs) to monitor the sediment-associated microbial community (16S rRNA gene sequencing and qPCR) over time. A nitrate-driven exponential increase in napA and narG gene copies and a shift in the relative abundances of the microbial community toward known denitrifying taxa in the trapping devices highlight the fast response of the microbial community throughout the 17-day experiment. We developed a gene-explicit reaction model that simulates the concentration dynamics measured at the extraction well and considers an additional electron-donor limitation that explains the observed drop in gene abundances despite nitrate availability. Our model also yielded a relationship between measured denitrification genes and computed rates, confirming previous predictions that the gene-rate relationship is non-linear and hysteretic. While the MTDs provided easy access to microbial biomass, our model shows that the kinetics therein differed from those in the aquifer. Thus, MTDs may not be truly representative of the conditions experienced by microbes in the aquifer itself.

Redox-active organic matter (RAOM) reduction is an important control on methane production in northern peatlands, but it is unclear how global climate change will affect RAOM reduction. We investigated the effects of water-table levels on RAOM reduction by leveraging a long-term water-table manipulation experiment in an Alaskan fen, which includes Lowered and Raised treatment plots relative to a Control. Common substrate peat was incubated in each plot during one summer of experimental manipulation and another summer of site-wide flooding. During experimental manipulation, common substrate RAOM was more reduced in the Raised plot than the Lowered plot at both 10–20 cm (19.1 ± 0.8 vs. 0.7 ± 0.3 μmol e⁻ g⁻¹ dw peat, p = 0.003) and 30–40 cm (18.0 ± 0.5 vs. 3.6 ± 1.2 μmol e⁻ g⁻¹ dw peat, p = 0.011). During site-wide flooding, differences in common substrate RAOM persisted with greater RAOM reduction in the Raised plot than both Control and Lowered plots (p < 0.05) and greater methane production from Raised plot common substrate. A comparison of the chemical composition of Raised and Control peat during an anaerobic laboratory incubation showed that the compounds removed during microbial processing differed between plots with a higher double bond equivalence to carbon ratio for the Raised plot (0.54 ± 0.13) compared to the Control plot (0.44 ± 0.17). Together, these field and laboratory results suggest that long-term increases in water-table levels can have complex effects on RAOM beyond oxygen availability with the potential to impact methane production from northern peatlands.

One of the key steps in the origin of life is the polymerization of nucleotides into nucleic acids like RNA. We have quantified the energetic impact of temperature, pressure, and composition on the polymerization of nucleotides into RNA using the Gibbs function. These Gibbs energies have been used to calculate the probability that a nucleotide could be found in an RNA polymer, as well as the expected length distribution of RNA molecules. Results show that increasing pressure increasingly favors RNA formation of greater lengths. The degree to which pressure provides an energetic drive for polymerization depends on temperature, pH, ratio of nucleotides to RNA in the solution, and activity of water. Temperatures above 25°C largely diminish the push toward polymerization; lower pH enhances the energetics of polymerization, and higher pH greatly reduces the thermodynamic drive toward polymerization. Although higher ratios of nucleotides to RNA increasingly favor polymerization under all other physicochemical conditions, at 5,000 bars (0.5 GPa), equal concentration of nucleotides and RNA still render RNA formation exergonic. As for the length distribution of polymers, for Gibbs energies of polymerization of −5.4 kJ mol⁻¹, about 9% of the nucleotides in solution are predicted to be in RNA molecules, and 3.8% of the nucleotides are predicted to be in RNA polymers 10 units or longer. The calculations summarized here provide a quantitative environmental context for an important step in the origin of life that can be applied to asteroids, meteorites, early Earth, or other planetary bodies.

Understanding how ecosystems function and respond under climate change is crucial. Drylands, covering over 40% of the global land surface, significantly contribute to global carbon (C) budget variations and biodiversity but face various threats. Blue C ecosystems, though limited in area, play a vital role in regulating Earth's climate but are stressed due to sea level rise and the associated coastal squeezing. At the two ends of the dryness spectrum, responses of drylands and blue C ecosystems to extremes are very complex. Therefore, a newly established group is applying pulsing paradigms to understand how the timing, frequency, and magnitude of pulses shape their ecosystem-atmosphere fluxes. We explore it by strategically planning mobile eddy-covariance towers to improve the representation of spatial heterogeneity. Via combining flux data with multiple measurements, we aim to better understand the effects of unconventional water inputs, soil vapor adsorption in drylands and saltwater intrusion in coastal ecosystems, on ecosystem functioning. Lastly, we target less investigated pulse events but ones also with critical implications for ecosystem-atmosphere interactions, such as wildfire smoke and altered precipitation patterns. In addition, rooted in ground measurements, we are devoted to provide guidance on leveraging physics-informed machine learning techniques to extract insights from flux and multiple data streams. Ultimately, we strive to unlock the potential of flux data, providing deeper insights into ecosystem functioning and advancing our knowledge of ecosystem-atmosphere interactions when facing more extremes. This will also offer actionable solutions to tackle present and future environmental challenges.

Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience spatial and temporal variability in biogeochemical processes, driven by marsh-to-upland gradients and hydrological fluctuations. These fluctuations make it difficult to understand and predict biogeochemical processes in these highly dynamic systems. We studied coastal soil biogeochemistry and its variability (a) at regional scales and (b) across transects from upland forest to marsh, in two contrasting regions—Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity-related analytes were a key source of variability in soil biogeochemistry, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI—however, contrary to expectations, transition soils were not consistently intermediate between upland and marsh endmembers; the non-monotonic trends of C, P, Fe along our transects suggest that these do not behave as expected and may be difficult to model and predict—thus these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients (e.g., Ca, K, CEC, and TS) may act as precursors to ecosystem shifts. Our comprehensive soil characterization represents a snapshot of a single timepoint of surface soils and provides essential data for mechanistic modeling of ecosystem dynamics across coastal transects.

Surface water is a significant source of carbon dioxide (CO₂) emissions to the atmosphere, yet knowledge gaps remain, particularly in high-altitude plateau mountain river systems. This study investigates the spatio-temporal variability of CO₂ partial pressure (pCO₂) and CO₂ efflux across the Yarlung Zangbo River (YZR) basin to better understand the primary drivers of CO₂ emissions in high-altitude river systems. Specifically, we assess pCO₂ levels, CO₂ efflux at the water-air interface, and the factors influencing pCO₂ distribution in the river, with an emphasis on the river's role in the regional carbon cycle. Our findings reveal that the average pCO₂ was 813 μatm during the low-flow season and 690 μatm in the high-flow season. The CO₂ flux range averaged 3,323 mg C (m² d)⁻¹. Correlation analysis suggests a limited role of aerobic respiration in controlling pCO₂ while a strong correlation underscores the influence of altitude on CO₂ distribution. We estimate that CO₂ emissions from the YZR mainstream are 2.18 (±0.76) teragrams of carbon per year (Tg C yr⁻¹), accounting for 18.63 (±6.49)% inland water CO₂ emissions of Tibetan Plateau rivers, and comparable to the estimated dissolved inorganic carbon flux of the YZR (1.74 Tg C yr⁻¹). These emissions are notably higher than carbon uptake from chemical weathering and about six times the CO₂ absorption by local lakes. This finding positions the YZR basin as a “weak source” of CO₂ in the regional carbon cycle, contributing valuable insights for refining global CO₂ emission estimates.

Anthropogenic impacts such as land use change are increasing dissolved nitrogen (N) loading to streams and rivers, degrading downstream water quality. Denitrification, where nitrate (NO₃⁻-N) is converted to dinitrogen gas (N₂), serves as a permanent N sink. While stream denitrification is well studied, its role in larger rivers remains understudied, despite rivers playing a key role in reach-scale N retention. Moreover, it remains uncertain how denitrification rates differ throughout the year. We compared stream and river denitrification rates across seasons using an open-channel N₂-exchange method in the Tippecanoe River and its tributary, Shatto Ditch. Areal denitrification rates were higher in the stream than the river in spring (stream = 148.0, river = 5.8 mg N m⁻² h⁻¹), summer (76.2 vs. 0.95), and fall (65.5 vs. 18.6). Rates were strongly influenced by NO₃⁻-N concentrations (R² = 0.93), which were higher in the stream. When scaled per km of channel length, river N removal was comparable or higher to the stream: summer (stream = 167.8, river = 56.7 g N km⁻¹ h⁻¹), spring (325.6 vs. 348.0), and fall (144.0 vs. 1116.5). These results confirm that streams have high biogeochemical reactivity, but they also reveal that when we account for size discrepancies, rivers can contribute a similar or greater amount of N removal because of their relatively larger size and volume. This work expands our knowledge of denitrification in fluvial ecosystems and demonstrates that both rivers and streams in agriculturally impacted areas can mitigate excess N loading to downstream ecosystems, which is needed to improve water quality.