Global Biogeochemical Cycles最新文献

The chemical nature of river water significantly influences the coastal carbonate system, contributing to coastal acidification and creating suboptimal conditions for marine calcifiers. While several regional efforts have assessed observationally based riverine concentrations and fluxes of total alkalinity (TA) and dissolved inorganic carbon (DIC), these values in global ocean biogeochemical models have generally been simplified, often set to zero or balanced against global sediment calcium carbonate burial. To enhance our understanding of rivers' role in the coastal carbonate system, we applied multiple linear regression (MLR) to develop global empirical relationships for estimating river TA and DIC from watershed properties. We find that river TA values are primarily controlled by forest, carbonate rock coverage, and annual mean precipitation, explaining 74% of the spatial variability in TA. The variability explained improves to 77% with the inclusion of permafrost and glacial coverage, especially in high latitude and altitude regions. Additionally, nearly 30% of the spatial variability in the river DIC-to-TA ratio can be explained by terrestrial gross primary production and carbonate rock coverage. Applying these MLR-derived TA and DIC concentrations to a 1/4° resolution global ocean model reduces the high bias in model estimates of global coastal $��{\text{CO}}_{\text{2}}�$ uptake by 69% (equivalent to 0.11 Pg C yr⁻¹ less $��{\text{CO}}_{\text{2}}�$ uptake) compared to the case with zero river TA and DIC. This study elucidates key drivers of the river carbonate system and underscores the importance of accurately representing riverine inputs to improve predictions of global coastal carbon dynamics and ecosystem responses to environmental changes.

Precise measurements of ¹⁴C:C in atmospheric CO₂ (expressed as Δ¹⁴C) are increasingly used in contemporary carbon cycle studies as a tracer of various processes, including anthropogenic CO₂ emissions from combustion of fossil fuels and cement production. Here we develop a complete representation of the global atmospheric Δ¹⁴CO₂ budget and use a combination of economic inventories, geophysical observations and process models to create monthly 1° × 1° gridded estimates of ¹⁴C and associated CO₂ mass fluxes into the atmosphere for use in atmospheric transport models. The fluxes impacting Δ¹⁴C we include are (in order of impact on the global trend): fossil CO₂ emissions, cosmogenic production of ¹⁴CO₂, oceanic and terrestrial isotopic disequilibrium fluxes, ¹⁴C production from nuclear power generation, and the impact of net terrestrial and ocean CO₂ fluxes. The total impact of these fluxes from 2000 through 2012 underestimated the observed decline in global average Δ¹⁴C indicating that the sum of derived fluxes was too positive. We thus optimize two global and time-invariant scalars (for cosmogenic ¹⁴C production and terrestrial disequilibrium) that allow us to match observed atmospheric trends and close the global ¹⁴C budget. While our optimized scalars are not a unique combination, our optimized fluxes represent a geophysically plausible set that conforms with surface ocean ¹⁴C observations and newly convergent constraints on the magnitude of global cosmogenic ¹⁴C production. In Part 2 of this study, we implement this set of fluxes in a global atmospheric transport model and compare simulated Δ¹⁴CO₂ to a large array of global observations.

The ¹⁴C:C ratio in atmospheric CO₂ (expressed as Δ¹⁴C) is a powerful tracer of Earth system carbon cycle processes. In the 21st century, spatio-temporal variations of atmospheric Δ¹⁴C are mainly the result of anthropogenic fossil CO₂ emissions, but the oceans and terrestrial biosphere also exert significant influence on its variations. Here we present a complete three-dimensional representation of the impact of ¹⁴CO₂ and CO₂ fluxes on atmospheric CO₂ and Δ¹⁴C for 2000 through 2012. We compare simulated atmospheric Δ¹⁴C with approximately 5,000 measurements from both the remote atmosphere and continental areas strongly influenced by fossil CO₂ emissions. These comparisons demonstrate that the spatio-temporal characteristics of input surface fluxes developed in Part 1 of this study have high fidelity. Based on good model-observation agreement, we used the model's ability to determine the relative contributions of fossil, oceanic, and terrestrial fluxes to simulated Δ¹⁴C to help explain the origin of the observed variations. During our study period, the pole-to-pole difference in atmospheric Δ¹⁴C increased, which our analysis indicates results from changes in both fossil and oceanic fluxes. Over the continents, we show that most short-term variation of Δ¹⁴C in the PBL results from atmospheric mixing acting on fossil CO₂ fluxes. Overall, the validation of our simulations by comparison with observations demonstrates that we understand the processes affecting atmospheric Δ¹⁴C at a variety of spatial and temporal scales. This suggests that, especially with an expanded set of measurements, we can use Δ¹⁴C to better quantify and understand key carbon cycle processes, especially fossil CO₂ emissions.

Uncertainties in global ocean oxygen inventories are assessed by a coordinated intercomparison of dissolved oxygen inventories derived from two observational data sets with distinct quality control (QC) protocols and five different statistical interpolation methods. We investigate key sources of uncertainty including mapping interpolation schemes and data QC methods, which contribute more significantly than measurement or sampling errors. Local differences in mapped oxygen content can reach up to 10 μmol/kg (about 4% of the surface climatological mean), especially in the regions of high variability and poor sampling such as the eastern tropical Pacific and the coastal Antarctica. Globally integrated differences, however, are small (≤0.17% above 2,000 m depth). Mapping methods are likely the largest contributor of the uncertainty for the annual mean, but both mapping and QC methods are important for the seasonal cycle. These results are limited by only including two sets of QC methods and only statistical interpolation techniques. Future incorporation of machine learning-based methods and time-dependent oxygen maps will be critical for tracking deoxygenation trends and for providing observational constraints to validate Earth System Models.

Marine phytoplankton net primary productivity (PP) is vital in the global carbon cycle and varies significantly across different phytoplankton size classes. In this study, we investigated variations in the maximum carbon fixation rate within the water column (P^B_opt, mg C (mg Chl)⁻¹ hr⁻¹) among micro- (>20 μm), nano- (2–20 μm), and pico-phytoplankton (<2 μm). Our results demonstrated that P^B_opt values were markedly lower in samples dominated by micro-phytoplankton, while higher values were associated with increased fractions of nano- and pico-phytoplankton. Moreover, distinct patterns in P^B_opt with sea surface temperature (SST) were observed across three size classes. Building on these observations, we parameterized P^B_opt for each size class and developed a novel size-fractionated PP estimation model. Compared to the original Vertically Generalized Production Model (VGPM) proposed by Behrenfeld and Falkowski (1997), https://doi.org/10.4319/lo.1997.42.1.0001, our model achieved improved accuracy, exhibiting good agreement with in situ measurements, a reduced RMSE of 733.72 mg C m⁻² d⁻¹, and a lower bias of 112.78 mg C m⁻² d⁻¹. Application of this model to satellite data over the past two decades revealed that micro- and nano-phytoplankton primarily dominated PP in coastal and high-latitude regions, whereas pico-phytoplankton prevailed in oligotrophic open oceans. Notably, despite general dominance of pico-phytoplankton in total PP in most open oceans, episodic structural shifts in the fractional contribution of different phytoplankton size classes were observed, with increasing contributions of micro- and nano-phytoplankton. Our study proposes a simplified and innovative approach for estimating size-fractionated PP and enhances the understanding of global marine primary production dynamics linked to phytoplankton size structure.

Dissolved organic matter (DOM) is a key component of the lake biogeochemistry. Hydrology link variables influencing lake DOM at local and watershed scales, but its role at macroscales remains less understood. We studied the DOM concentration and composition from 548 lakes across the five major Canadian continental basins using absorption spectroscopy and parallel factor analysis, and ultra-high resolution mass spectroscopy, and linked this to deuterium excess (d-excess), derived from stable water isotopes as a proxy for evaporation, water residence time, and regional hydrology. DOM concentration and composition varied greatly within and across basins, with strong correlations between molecular and optical properties. At a continental scale, d-excess and TP concentration were the main drivers of DOM concentration and composition. TP positively influenced DOM concentration, and specific DOM components (e.g., Aliphatics), suggesting nutrient-driven effects on lake metabolism that varied regionally. DOM concentration declined with d-excess, but the relationships between individual DOM molecular composition classes and d-excess differed among components and basins, resulting in regional differences in DOM composition along hydrologic gradients. The inferred source composition DOM based on these patterns had subtle regional differences, with Aliphatics related to the average regional altitude and Aromatics related to the average regional soil organic content. We show that DOM processing along the hydrologic continuum is the key factor establishing differences in DOM composition in lakes at a continental scale. Overall, TP influenced DOM through effects on primary production and metabolism, whereas d-excess integrated the selective degradation and accumulation of DOM along the aquatic network.

The Tibetan Plateau (TP) has become warmer and wetter, which has led to permafrost degradation, increased soil erosion and higher CO₂ emissions from water bodies. There are ongoing debates on whether the TP will transition from a carbon sink to a source, but relevant analysis accounting for both terrestrial and aquatic carbon processes at the catchment scale remains lacking. Here, we develop a process-based distributed water-carbon coupling model applicable for the permafrost region GBEHM-Carbon, which integrates the vertical water-heat-carbon fluxes through the soil-vegetation-atmosphere continuum, the lateral water-carbon fluxes transported from hillslopes to river channels, as well as the water-sediment-carbon dynamics in river networks along the river routing process. The model is then applied in the Yellow River Source Region (YRSR) on the eastern TP. The results show that the ecosystem carbon budget of the YRSR is 3.3 Tg C/yr on average, with an increasing trend during 1960–2019. Lateral carbon fluxes played a substantial role, accounting for 30.1% of the net ecosystem production (NEP) on average, with their relative contribution rising to 37.8% during the 2010s. Regions undergoing permafrost degradation are identified as potential hotspots for carbon sink-to-source transitions, primarily driven by reduced vegetation productivity and enhanced heterotrophic soil respiration. In addition, riverine carbon fluxes show distinct spatial patterns associated with stream order and are strongly modulated by hydrological conditions. This study provides critical insights into the long-term variations of water and carbon fluxes in the TP headwater catchments, and offers valuable guidance for water resource and ecological management in alpine river systems.

The twilight zone plays a pivotal role in the oceanic carbon cycle because large amounts of organic carbon (OC) exported from the euphotic zone are degraded within this layer. However, the magnitude and variability of this remineralization flux remain incompletely understood, particularly across varying regional scales. Using a new particulate excess barium (PBa_xs)-oxygen utilization rate transfer function, this study examines spatial patterns of twilight zone OC remineralization fluxes (F_{OC_remineral}) in the western North Pacific (wNP) and the South China Sea (SCS). Results reveal a pronounced latitudinal gradient in wNP open waters, with PBa_xs concentrations and F_{OC_remineral} in the upper 150–600 m increasing from the oligotrophic western North Pacific Subtropical Gyre (NPSG) to the nutrient-rich North Pacific Transition Zone (NPTZ). Despite its subtropical location, the SCS basin shows values comparable to those of the NPTZ. Satellite-derived net primary production (NPP) and export production (EP) distributions generally align with F_{OC_remineral} patterns, indicating a strong association between upper and mesopelagic ocean carbon cycling. Using NPP, EP, and F_{OC_remineral} data, we estimated the twilight zone OC remineralization ratio (r-ratio) relative to the euphotic zone biological pump carbon export efficiency (e-ratio). The NPTZ shows enhanced carbon storage potential, with higher e-ratio and lower r-ratio values, while the western NPSG exhibits an opposite trend, indicating reduced carbon sequestration capacity. This spatial variability underscores the need for a comprehensive understanding of twilight zone OC remineralization and its connection to upper-ocean carbon cycling, in order to accurately assess the biological pump's role in the long-term pelagic carbon sink.

Microbial nitrogen (N) demand substantially influences soil N transformations during vegetation succession, its dynamics across contrasting successional pathways remain poorly understood yet. We used vector model, GeoChip 5.0, and ¹⁵N-tracer to investigate microbial N metabolism and gross N transformation across primary succession (20–130 years post-glacier retreat) and secondary succession (grassland to primary forest) in the eastern Tibetan Plateau. During primary succession, microbial N limitation was progressively alleviated, coincident with increasing plant biomass and richness, as well as the accumulation of soil labile carbon (C), total N, and phosphorus (P). Increases in soil C, N, and P pools enhanced both gross and net N mineralization rates directly and indirectly by elevating ureC abundance and 4-β-N-acetylglucosaminidase activity. Microbial N limitation emerged in the late coniferous stage of secondary succession. This pattern was associated with declines in plant richness, reductions in soil labile C and pH from early stage (grassland/shrubland) or mid-successional broadleaf stages to late coniferous stages, and concomitant decreases in leucine aminopeptidase activity. Such changes led to a lower gross N mineralization rate and reduced soil N availability in late secondary forests. Overall, our results indicate that microbial N limitation is gradually relieved during soil development following glacier retreat as plant communities and soil C and nutrients become more favorable, whereas late-stage secondary coniferous forests experience microbial N limitation driven by more homogeneous vegetation and reduced soil N mineralization rates. These findings imply that succession-specific management strategies are needed to conserve soil N cycling and ecosystem resilience in fragile subalpine ecosystems.

Particulate excess barium (pBa_xs), collected in situ, which is thought to exist as barite (BaSO₄), is potentially a powerful proxy of water column respiration. Here we use this proxy along the US GEOTRACES GA03 North Atlantic and GP16 East Pacific transects, comparing respiration rates derived from pBa_xs distributions, using previously proposed algorithms, and respiration rates calculated using ²³⁰Th-normalized particulate organic carbon (POC) fluxes in the water column. Both transects traversed upwelling regimes, oxygen deficient zones (ODZs), near-shore, and open-ocean gyre stations, providing a more robust evaluation of the methodology than previous work. Respiration rates were estimated over two different depth intervals in the mesopelagic zone (100–500 m and 100–1,000 m). Generally, respiration rates were different (p < 0.05) between biogeochemical provinces (i.e., gyre vs. Oxygen deficient zone stations) irrespective of method. Rates along GA03 were more difficult to establish using ²³⁰Th-normalized fluxes due to the absence of observed POC flux maxima in the top ∼0–100 m. Still, rate estimates using depth weighted average pBa_xs concentrations and Th-normalized POC fluxes in the 100–500 m interval agreed well within certain biogeochemical provinces: for example, at GP16 ODZ stations, average Th-normalized POC respiration rate estimates were 3.3 ± 1.6 whereas pBa_xs-based estimates were 2.9 ± 0.5 m mol C m⁻² day⁻¹. Excess particulate Ba appears to be a reasonable proxy for water column POC respiration. We suggest that average excess pBa_xs concentrations may be used as a method to calculate respiration rates in the 100–500 m depth interval if other methods are not available.