Global Biogeochemical Cycles最新文献

Plankton community structure influences biogeochemical and ecosystem processes, such as sequestration of atmospheric CO₂, carbon export to the ocean floor, and the productivity of higher trophic levels. One means of analyzing community structure is through the distribution of biovolume across size classes (the size spectrum), since size is a proxy for plankton functional traits. To understand how climate forcing affects plankton communities, we assessed the size spectra in the historical simulations of seven Earth System Models (ESMs) included in the 6th Coupled Model Intercomparison Project and analyzed projected changes under a high emissions scenario (SSP5-8.5). We compared historical estimates with the Pelagic Size Structure database (PSSdb), a novel size structure dataset from imaging systems. The median slope from models ranged from −1.66 to −1.07, with shallower slopes from this range approximating both the theoretical expectation and PSSdb observations (−1.05), with variations around the median representing differences in the total biovolume distribution across plankton functional groups. Consistent with the observations, most ESMs show steeper slopes and lower biovolume in oligotrophic subtropical gyres compared with productive ocean regions. Historical versus climate change simulations reveal increases in slope and biovolume at high latitudes, associated with greater biomass and productivity, and decreases at lower latitudes, consistent with nutrient limitation from stronger stratification. We emphasize the need for expanded observational data. Despite ESMs not being designed to simulate size, the plankton size spectra from models provide insights on large-scale ecological and biogeochemical processes, and how climate change could affect these dynamics in the future.

Early diagenetic forward and reverse weathering reactions play a significant role in controlling alkalinity fluxes and silica, alkali metal and alkaline earth metal cycling in coastal systems. In Kongsfjorden, Svalbard, the inputs of autochthonous biogenic debris (diatomaceous silica) and allochthonous lithogenic material of varying reactivity (dominated by clays, especially illite and chlorite, and primary aluminosilicates, mostly plagioclase) drive complex balances of diagenetic silicate reactions in sediments. The rapid dissolution of reactive silica results in the release of dissolved silica (Si_d) into pore-waters and sustains elevated benthic Si_d fluxes (−0.2 to −0.8 mmol m⁻² d⁻¹), which are on the upper end of values previously determined for Arctic environments. Increases with depth in pore-water lithium (Li⁺), potassium, magnesium, and barium concentrations within the top centimeters provided evidence for forward weathering of clays quickly upon burial. Due to the prevalent occurrence of forward weathering, the benthic net Li⁺ flux was associated with a light isotope signal. Decreases in pore-water rubidium concentrations with depth at the near-glacier station, elevated ratios of the authigenically altered silica to the biogenic silica pool at all sites, and small increases of pore-water δ⁷Li values with depth showed that reverse weathering also takes place. Anoxic incubation of diatom frustule probes provided further evidence for the neoformation of cation-rich clays. The superposition of reverse and forward weathering results in cryptic silica and cation cycling that muted net benthic fluxes. In deeper sediments, changes in pore-water solute patterns indicated an interconnected occurrence of reverse and forward weathering, potentially driven by reactive silica-limitation.

We analyzed the in situ diel variability in dissolved O₂ from a compilation of quality-controlled measurements collected with underwater gliders in the North Pacific Subtropical Gyre over a period spanning 14 years (2008−2021) and totaling >10,500 vertical profiles. We derived metabolic rates at different depths (0−110 m) from the diel oscillations in O₂ anomaly (ΔO₂), calculated here as the difference between instantaneous and 2-day mean O₂ concentrations, using all assembled measurements. Depth-integrated annual gross oxygen production and community respiration (CR) derived from this study (± standard deviation) were 87 ± 3 mmol O₂ m⁻² d⁻¹ and 89 ± 4 mmol O₂ m⁻² d⁻¹, respectively. Gross oxygen production and CR decreased with depth and were lower in winter and spring than in summer and fall. Hourly rates of O₂ change indicated relatively constant nighttime respiration, but enhanced net O₂ production in the morning compared with the afternoon. We found that when ΔO₂ was calculated by subtracting the O₂ concentration at equilibrium (ΔO₂-eq), as proposed in other studies, metabolic rates were overestimated by approximately 31%–36% in this oligotrophic oceanic region, due to diel variations in O₂ solubility driven by temperature oscillations. By demonstrating the reliability of depth-resolved characterization of ocean metabolism, we hope to pave the way for the use of autonomous underwater observations to characterize primary productivity and respiration in understudied ocean regions, improving the spatiotemporal resolution provided by conventional methods.

The ocean's biological pump, a critical component of the Earth's carbon cycle, transports organic matter from the surface ocean to depth and is dominated by sinking particles, often in the form of marine snow-sized (diameter ≥0.5 mm) aggregates. Controls of sinking particle carbon export are thought to be driven largely using ecological processes that create and transform sinking particles. We diagnose the importance of both biotic and abiotic processes in the dynamics of marine snow and other suspended particles using image-based determination of their size distribution. These observations were made during the demise of the North Atlantic spring bloom in May 2021 as part of the Export Processes in the Ocean from RemoTe Sensing-North Atlantic (EXPORTS-NA) field campaign. We show that intense storm events generated high turbulent mixing rates in the upper ocean that impacted the abundance, size distribution, porosity and sinking of marine snow. Mixed-layer turbulence levels both created and destroyed marine snow and the sequence of entrainment and detrainment of the mixed layer induced by repeated storm forcings enhanced the vertical transport of aggregates to depth. Evidence of biological transformations was also observed at mesopelagic depths, both for the consumption of particulate matter and in the creation of smaller particles from larger ones, likely due to interactions with zooplankton. Collectively, these results illustrate the complex interplay of physical and biological processes regulating the dynamics of marine snow and suggest their inclusion in predictive models of the ocean's biological pump.

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.