Global Biogeochemical Cycles最新文献

The strength of the Biological Carbon Pump (BCP) to sequester atmospheric CO₂ in the East Indian Ocean is unclear due to lack of studies. Here, we estimated Particulate Organic Carbon (POC) export flux by using ²³⁴Th as a flux proxy in the upper Indian Ocean (0–300 m depth), including the East Indian Ocean. In seawater, the soluble parent radionuclide, ²³⁸U (t_1/2 = 4.47 × 10⁹ yr) decays to produce a particle-reactive daughter, ²³⁴Th (t_1/2 = 24.1 d), which surface adsorbs onto particles, and sinks from the euphotic zone to the sea bottom. Disequilibrium between ²³⁸U and ²³⁴Th in seawater and POC/²³⁴Th ratio in sinking particles is used to estimate POC export flux. In this study, euphotic depth integrated ²³⁴Th deficit fluxes and the estimated POC export flux varied from negligible to 2,025 ± 87 dpm m⁻² d⁻¹ and negligible to 6.6 ± 0.6 mmol C m⁻² d⁻¹, respectively. The BCP efficiency varied from negligible (in coastal Arabian Sea) to 14% (near equator), except for the Andaman Sea (0%–80%). Temporal decoupling of primary productivity and POC export flux in the Andaman Sea resulted in a high export ratio. Compilation of spring intermonsoon ²³⁴Th based POC export flux and export efficiency from JGOFS and GEOTRACES showed high export flux and efficiency in the open Arabian Sea and in the Equatorial Indian Ocean but low POC export flux and efficiency in the Bay of Bengal, Andaman Sea, East Indian Ocean, and South Indian Ocean. Although low in magnitude, the Equatorial Indian Ocean sequesters atmospheric CO₂ like the equatorial- Atlantic and Pacific Oceans.

Artificial reservoirs significantly alter the natural transport of suspended particulate matter (SPM) from rivers to oceans, thereby reshaping the global carbon cycle through changes in particulate organic carbon (POC) dynamics over decadal to millennial timescales. Here, we investigate dam-induced perturbation of POC composition, transport, and fate within the Changjiang (CJ) River basin in response to the operation of cascade mega-reservoirs (CMRs) along the Jinshajiang (JSJ) in the upper CJ. The CMRs have introduced new perturbations to SPM and POC delivery, compounding the effects of the Three Gorges Dam (TGD). We analyzed elemental, stable, and radiogenic isotopic compositions of POC, as well as the inorganic chemistry of SPM collected from both the upper and lower CJ. Since the construction of CMRs, POC sequestration in artificial reservoirs reaches approximately 6.6 megatons carbon per year (MtC yr⁻¹), 3.8 MtC yr⁻¹ of which being POC of biospheric origin (POC_bio). Notably, the flux of POC trapped in the TGD declined from 1.6 to 0.4 MtC yr⁻¹, while CMRs sequestered 0.7 MtC yr⁻¹. This shift highlights the relocation of POC burial sites from the TGD and estuary to upstream reservoirs. The rapid burial of terrestrial POC in large mountainous river reservoirs is expected to enhance POC preservation by minimizing mineralization caused by prolonged transport to estuaries. The significant reduction in sediment load and the increased proportion of POC_bio due to reservoir retention have substantially altered the composition and flux of exported POC, impacting downstream and estuarine carbon cycles.

Nitrate is an essential nutrient for phytoplankton growth and is a primary component of ocean carbon cycling. In this study, we developed a neural network constrained by the high spatial and temporal coverage of BGC-Argo floats to predict nitrate in a consistent way throughout space and time in the Southern Ocean, a key area for ocean carbon uptake and controlling global ocean nutrient distributions. After correcting for physical and sampling biases using the Biogeochemical Southern Ocean State Estimate model, we show that annual net community production (ANCP), originally calculated from seasonal nitrate drawdown, reveals the greatest production around the 45–55°S meridional band, and an average basin-wide ANCP of 3.91 ± 0.13 PgC y⁻¹ with a significant increase of 0.67% y⁻¹ from 2004 to 2022. We also highlight that using the common nitrate seasonal drawdown method to derive ANCP might underestimate the true carbon export at depth by about one third. Our findings align with previous studies, which indicate an increase in surface satellite chlorophyll-a and model export fluxes. Our results demonstrate the potential of leveraging machine learning constrained by BGC-Argo observations to study long-term changes of biogeochemical processes in the ocean.

The ocean accounts for ∼20%–30% of global nitrous oxide (N₂O) emissions, with coastal upwelling systems estimated to contribute disproportionately to the sea-air flux of this potent greenhouse gas. To investigate the mechanisms of and controls on N₂O production in coastal upwelling systems, we measured the concentration and nitrogen and oxygen isotopic composition of N₂O (δ¹⁵N-N₂O and δ¹⁸O-N₂O) along a cross-shelf transect in the Southern Benguela Upwelling System (SBUS). At the shelf bottom, N₂O concentrations increased from the outer shelf toward the shore (11–32 nM) inversely to dissolved oxygen (182 ± 17 to <1 μM) and in concert with the remineralization tracers, apparent oxygen utilization (108 ± 21 to 221 ± 33 μM) and nitrogen (N)-deficit (up to 20.4 μM). These observations suggest that both nitrification and denitrification may be involved in N₂O production on the SBUS shelf. The δ¹⁵N-N₂O implicates both processes as potential N₂O sources on the shelf, with high δ¹⁸O-N₂O values (≤57.2‰) specifically incriminating sediments as the primary N₂O source to the water column. Isotopic changes across the shelf delineate three discrete domains with distinct N₂O sources. Sedimentary nitrification and/or denitrification dominate N₂O production on the midshelf, while coupled nitrification-denitrification explains N₂O production on the inner-shelf. At the shallow inner-shelf where oxygen is depleted, both water column and sedimentary denitrification account for the production and partial consumption of N₂O. This study illuminates the disproportionate contribution of sedimentary N cycling to N₂O production on the SBUS shelf.

Northern peatlands are key carbon reservoirs and natural sources of methane (CH₄). However, the environmental controls of CH₄-related processes remain unclear, making modeling the emissions a challenge. In this study, we first evaluated the process-based CoupModel with unique long-term (2001–2023) in situ measurements from a pristine sedge-dominated peatland in northern Sweden. Results show that the calibrated model can reproduce the hourly CH₄ fluxes (r² = 0.63) and CO₂ flux, and the abiotic variations well. The CH₄ flux showed significant sensitivity (66% relative importance) to parameters related to CH₄ transport, followed by production and oxidation. We further showed that CH₄ fluxes respond to temperature and water table depth (WTD) with a seasonal hysteresis, suggesting a 35% higher temperature sensitivity during below-average WTD compared to above-average WTD, and a two times higher sensitivity of CH₄ to lowering WTD than to elevating WTD. The hourly growing-season CH₄ fluxes response to temperature also displayed a hysteresis in the diurnal cycle, with nighttime CH₄ fluxes being 14%–23% higher than the daytime fluxes. We presented a CH₄ budget for the site and estimated the annual mean methane emissions from 2014 to 2023 to be 12.2 ± 1.2 gC/m²/yr, identifying the emissions predominantly contributed by diffusion. We conclude that CoupModel can effectively simulate the CH₄ emission and its controls for the northern pristine peatland. Our study reveals the importance of hysteresis in the response of methane fluxes to environmental changes and highlights the need for considering the temporal and hydrologic variability in CH₄-temperature dependencies in peatland management.

We report hydrographic and biogeochemical measurements from a meridional transect performed along 150°W, 30°S to 60°S in the Southern Ocean, plus Polar waters to the east. Both of these areas are sites of annual high-reflectance features in ocean color remote sensing, which were heretofore never confirmed with in situ measurements. This study aimed to document factors driving phytoplankton productivity and coccolithophore calcification within the circumpolar coccolithophore-rich band known as the Great Calcite Belt (GCB). We measured concentrations of particulate inorganic carbon (PIC) and biogenic silica (BSi), two common biominerals, sources of ballast for organic matter, and contributors to optical reflectance. Results demonstrated that integrated euphotic standing stocks of PIC were highest in the GCB and at the Polar Front south of 54°S. BSi concentrations were highest south of 54°S. Integrated calcification rates were highest near the Polar and Subantarctic Fronts, whereas peak photosynthesis rates were observed in Subantarctic waters of the GCB, near the site of Subantarctic Mode Water formation. South of ∼54°S, optical particulate backscattering (b_bp) of BSi dominated over PIC b_bp by 10×, while in the GCB, PIC b_bp dominated over BSi b_bp by a similar magnitude. The slope of the particle size distribution function became less negative with depth, a trend that reflects larger particles becoming more abundant relative to smaller particles. Moreover, typical relationships between the particle size distribution slope and beam attenuation were only observed in the top 50 m depth, suggesting a fundamental difference in particle composition and size for deeper suspensions in this region.

Soil respiration (Rs) is defined as the emission of carbon dioxide from soil into the atmosphere, which represents a critical carbon flux within terrestrial ecosystems. Precipitation change significantly influences Rs, generating feedback mechanisms pertinent to global climate change. Nevertheless, the global distribution and environmental determinants of precipitation's effects on Rs remain uncertain. We compiled a database encompassing 570 Rs observations from field experiments that manipulated precipitation, derived from 221 published studies. Utilizing this comprehensive data set, we conducted a meta-analysis to elucidate Rs responses to precipitation alterations. Subsequently, we employed a machine learning approach to provide a globally spatially explicit quantification of precipitation change effects on Rs under future climate scenarios. Our findings revealed that increased experimental precipitation markedly enhances Rs, while decreased precipitation inhibits it. Furthermore, Rs responses to precipitation change exhibited variability across ecosystems and climatic regions. This study also confirmed that the Rs responses vary based on the intensity and duration of precipitation change, with short-term or heavy precipitation fluctuations exerting the strongest effects. Environmental conditions influenced the reaction of Rs to precipitation change, as factors such as soil type, vegetation, and climate worked together to mediate spatial differences. Projections based on bioclimatic predictors suggest that future climate scenarios significantly amplify Rs responses to precipitation change, potentially increasing uncertainties in greenhouse gas emissions estimates. Overall, our analysis emphasizes the significance of context dependencies and offers a spatially explicit assessment of precipitation change impacts on Rs on a global level, providing a comprehensive reference for comprehending ecosystem carbon dynamics.