Biogeochemical Model Research Articles

Multi-year three-dimensional simulation of seasonal variation in phytoplankton species composition in a large shallow lake

Lake Erie has been negatively impacted by multiple stressors, including nutrient enrichment and climate change, that have exacerbated eutrophication and harmful algal blooms. Management of these long-term water quality problems requires numerical models that can be run over years to decades. The three-dimensional hydrodynamics and biogeochemistry models applied to date, however, have not been tested for continuous runs longer than one year and have not been shown to accurately reproduce seasonal variation in phytoplankton species composition (e.g., the development of harmful algal blooms) over decadal timescales. We simulated the three-dimensional nutrient and phytoplankton concentrations in western Lake Erie continuously from 2002 to 2014. Using a single parameter set, we were able to reproduce both seasonal and inter-annual variation in phytoplankton species composition. The model qualitatively reproduced the observed seasonal succession (i.e., variation in phytoplankton species composition), including the spring diatom bloom and late summer cyanobacterial growth. This study demonstrates that three-dimensional models can be applied for multi-year simulations of nutrients and phytoplankton to inform large lake research and management.

Efficient spin-up of Earth System Models using sequence acceleration.

Marine and terrestrial biogeochemical models are key components of the Earth System Models (ESMs) used to project future environmental changes. However, their slow adjustment time also hinders effective use of ESMs because of the enormous computational resources required to integrate them to a pre-industrial equilibrium. Here, a solution to this "spin-up" problem based on "sequence acceleration", is shown to accelerate equilibration of state-of-the-art marine biogeochemical models by over an order of magnitude. The technique can be applied in a "black box" fashion to existing models. Even under the challenging spin-up protocols used for Intergovernmental Panel on Climate Change (IPCC) simulations, this algorithm is 5 times faster. Preliminary results suggest that terrestrial models can be similarly accelerated, enabling a quantification of major parametric uncertainties in ESMs, improved estimates of metrics such as climate sensitivity, and higher model resolution than currently feasible.

The carbonate pump feedback on alkalinity and the carbon cycle in the 21st century and beyond

Abstract. Ocean acidification is likely to impact all stages of the ocean carbonate pump, i.e. the production, export, dissolution and burial of biogenic CaCO3. However, the associated feedback on anthropogenic carbon uptake and ocean acidification has received little attention. It has previously been shown that Earth system model (ESM) carbonate pump parameterizations can affect and drive biases in the representation of ocean alkalinity, which is critical to the uptake of atmospheric carbon and provides buffering capacity towards associated acidification. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show divergent responses of CaCO3 export at 100 m this century, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. The greatest export declines are projected by ESMs that consider pelagic CaCO3 production to depend on the local calcite/aragonite saturation state. Despite the potential effects of other processes on alkalinity, there is a robust negative correlation between anomalies in CaCO3 export and salinity-normalized surface alkalinity across the CMIP6 ensemble. Motivated by this relationship and the uncertainty in CaCO3 export projections across ESMs, we perform idealized simulations with an ocean biogeochemical model and confirm a limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification. However, we highlight a potentially abrupt shift, between 2100 and 2300, in the dissolution of CaCO3 from deep to subsurface waters when the global-scale mean calcite saturation state reaches about 1.23 at 500 m (likely when atmospheric CO2 reaches 900–1100 ppm). During this shift, upper ocean acidification due to anthropogenic carbon uptake induces deep ocean acidification driven by a substantial reduction in CaCO3 deep dissolution following its decreased export at depth. Although the effect of a diminished carbonate pump on global ocean carbon uptake and surface ocean acidification remains limited until 2300, it can have a large impact on regional air–sea carbon fluxes, particularly in the Southern Ocean.

The Shelf‐To‐Basin Transport of Iron From the Northern U.S. West Coast to the Pacific Ocean

AbstractRelease of iron (Fe) from continental shelves is a major source of this limiting nutrient for phytoplankton in the open ocean, including productive Eastern Boundary Upwelling Systems. The mechanisms governing the transport and fate of Fe along continental margins remain poorly understood, reflecting interaction of physical and biogeochemical processes that are crudely represented by global ocean biogeochemical models. Here, we use a submesoscale‐permitting physical‐biogeochemical model to investigate processes governing the delivery of shelf‐derived Fe to the open ocean along the northern U.S. West Coast. We find that a significant fraction (∼20%) of the Fe released by sediments on the shelf is transported offshore, fertilizing the broader Northeast Pacific Ocean. This transport is governed by two main pathways that reflect interaction between the wind‐driven ocean circulation and Fe release by low‐oxygen sediments: the first in the surface boundary layer during upwelling events; the second in the bottom boundary layer, associated with pervasive interactions of the poleward California Undercurrent with bottom topography. In the water column interior, transient and standing eddies strengthen offshore transport, counteracting the onshore pull of the mean upwelling circulation. Several hot‐spots of intense Fe delivery to the open ocean are maintained by standing meanders in the mean current and enhanced by transient eddies and seasonal oxygen depletion. Our results highlight the importance of fine‐scale dynamics for the transport of Fe and shelf‐derived elements from continental margins to the open ocean, and the need to improve representation of these processes in biogeochemical models used for climate studies.

Impact of Dynamic Phytoplankton Stoichiometry on Global Scale Patterns of Nutrient Limitation, Nitrogen Fixation, and Carbon Export

AbstractPhytoplankton stoichiometry modulates the interaction between carbon, nitrogen and phosphorus cycles. Environmentally driven variations in phytoplankton C:N:P can alter biogeochemical cycling compared to expectations under fixed ratios. In fact, the assumption of fixed C:N:P has been linked to Earth System Model (ESM) biases and potential misrepresentation of responses to future change. Here we integrate key elements of the Adaptive Trait Optimization Model (ATOM) for phytoplankton stoichiometry with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) ocean biogeochemical model. Within a series of global ocean‐ice‐ecosystem retrospective simulations, ATOM‐COBALT reproduced observations of phytoplankton N:P, and compared to static ratios, exhibited reduced phytoplankton P‐limitation, enhanced N‐fixation, and increased low‐latitude export, improving consistency with observations and highlighting the biogeochemical implications of dynamic N:P. We applied ATOM‐COBALT to explore the impacts of different physiological mechanisms hypothesized to underlie N:P variation, finding that two mechanisms together drove the observed patterns: proportionality of P‐rich ribosomes in phytoplankton cells to growth rates and reductions in P‐storage during scarcity. A third mechanism which linked temperature with phytoplankton biomass allocations to non‐ribosomal proteins, led only to relatively modest impacts because this mechanism decreased the temperature dependence of phytoplankton growth rates, compensating for changes in N:P. We find that there are quantitative response differences that associate distinctive biogeochemical footprints with each mechanism, which are most apparent in highly productive low‐latitude regions. These results suggest that variable phytoplankton N:P makes phytoplankton productivity and export resilient to environmental changes, and support further research on the physiological and environmental drivers of phytoplankton stoichiometry and biogeochemical role.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation.

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis-Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

Modeling Interactive Effects of Manganese Bioavailability, Nitrogen Deposition, and Warming on Soil Carbon Storage

AbstractManganese (Mn) is a redox‐active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn‐promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn‐oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin‐oxidation products as mineral‐associated organic C. We also explored how Mn‐driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn‐dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.

Modelling sulfate concentrations in the global ocean through Phanerozoic time

Understanding the long-term variations in seawater sulfate concentrations ([SO 4 2− ] sw ) is crucial to our understanding of the dynamic relationships between the sulfur, carbon, calcium and oxygen cycles, and their influence on the habitability of the Earth. Here, we explore how [SO 4 2− ] sw has changed throughout the Phanerozoic and its impact on other elemental cycles. We do this by utilizing the biogeochemical box model GEOCARBSULFOR. The model suggests that [SO 4 2− ] sw increased throughout the Paleozoic, decreased during the Mesozoic and then increased once more in the Cenozoic, generally matching geochemical proxies. Atmospheric oxygen mirrors [SO 4 2− ] sw changes during the Paleozoic and Mesozoic, but, intriguingly, decouples during the Cenozoic. We further explored the controls on [SO 4 2− ] sw by modifying the modelled gypsum fluxes via the incorporation of evaporite data from the geological record. We found that forcing gypsum burial with the observed evaporite deposition data causes the model to better match proxy records at some times, but worsens predictions at others. We also investigated the reliance of the model on a prescribed record of marine calcium concentrations, finding that it is a dominant control on modelled Phanerozoic [SO 4 2− ] sw and that removing this control seriously degrades the model predictions. We conclude that no model can yet simulate a reasonable evolution of both the calcium and sulfur cycles. Supplementary material: Figures S1–S5 are available at https://doi.org/10.6084/m9.figshare.c.7164928 Thematic collection: This article is part of the Sulfur in the Earth system collection available at: https://www.lyellcollection.org/topic/collections/sulfur-in-the-earth-system

Multi-model comparison of trends and controls of near-bed oxygen concentration on the northwest European continental shelf under climate change

Abstract. We present an analysis of the evolution of near-bed oxygen in the next century in the northwest European continental shelf in a three-member ensemble of coupled physics–biogeochemistry models. The comparison between model results helps highlight the biogeochemical mechanisms responsible for the observed deoxygenation trends and their response to climate drivers. While all models predict a decrease in near-bed oxygen proportional to climate change intensity, the response is spatially heterogeneous, with hotspots of oxygen decline (up to −1 mg L−1) developing along the Norwegian trench in the members with the most intense change, as well as areas where compensating mechanisms mitigate change. We separate the components of oxygen change associated with the warming effect on oxygen solubility from those due to the effects of changes in transport and biological processes. We find that while warming is responsible for a mostly uniform decline throughout the shelf (−0.30 mg L−1 averaged across ensemble members), changes in transport and biological processes account for the detected heterogeneity. Hotspots of deoxygenation are associated with enhanced stratification that greatly reduces vertical transport. A major change in circulation in the North Sea is responsible for the onset of one such hotspot that develops along the Norwegian trench and adjacent areas in the members characterised by intense climate change. Conversely, relatively shallow and well-mixed coastal areas like the southern North Sea, Irish Sea and English Channel experience an increase in net primary production that partially mitigates oxygen decline in all members. This work represents the first multi-model comparison addressing deoxygenation in the northwest European shelf and contributes to characterising the possible trajectories of near-bed oxygen and the processes that drive deoxygenation in this region. As our downscaled members factor in riverine inputs and small- and medium-scale circulation, which are not usually well represented in earth system models, results are relevant for the understanding of deoxygenation in coastal and shelf systems.

National-scale mapping of soil-thickness probability in hilly and mountainous areas of Japan using legacy and modern soil survey

Soil thickness is a crucial parameter for local, regional and globalscale assessments, including those related to carbon cycles, water retention capacity, and landslide risk in the context of biogeochemical, soil physical, and slope stability models. This study had two primary objectives: 1) to predict maps depicting the probability of the A-horizon thickness exceeding 15 cm (AT15) and the A and B-horizon thickness exceeding 75 cm (soil thickness, ST75), across the expansive mountainous regions of Japan. 2) To evaluate the enhancement of model performance through the preselection of the maximum value and implementation of enhanced modeling using gridded modern soil survey data to utilize geographically clustered data. Initially, the study modeled the SOC, bulk density, and coarse fraction proportion using data from a modern soil survey of 0–30 cm. Subsequently, we employed a random forest model for AT15 and ST75 using a dataset of geographically clustered legacy soil profiles as training data, and topographic, vegetation, climatic, and volcanic attributes, and the predicted soil organic carbon and related properties as explanatory variables. We reduced the number of legacy soil profiles in the densely sampled areas by selecting the maximum soil thickness before modeling. The study assessed the final model performance at the national scale, with the accuracy and F1 scores reaching 0.691 and 0.754 for AT15 and 0.600 and 0.511 for ST75, respectively. Maximum value selection proved effective for modeling ST75 but not AT15. Although an enhanced model incorporating data from legacy and modern surveys did not improve accuracy at the national level, it did improve recall in sparsely sampled areas, for ST75. The resulting spatial pattern of the predicted ST75 effectively captured variations in soil thickness associated with topography, geology, and tephra deposition. However, ST75, representing pedological soil thickness, tended to be strongly underestimated compared to geotechnical soil thickness, including the C-horizon, especially in areas affected by tephra deposition. This study represents a significant contribution as it delivers Japan's first national-scale soil thickness map and an approach for utilizing clustered legacy data. It is expected to find practical applications in estimating water storage capacity for forest management and other relevant purposes.

Validation of the coupled physical–biogeochemical ocean model NEMO–SCOBI for the North Sea–Baltic Sea system

Abstract. The North Sea and the Baltic Sea still experience eutrophication and deoxygenation despite large international efforts to mitigate such environmental problems. Due to the highly different oceanographic frameworks of the two seas, existing modelling efforts have mainly focused on only one of the respective seas, making it difficult to study interbasin exchange of mass and energy. Here, we present NEMO–SCOBI, an ocean model (NEMO-Nordic) coupled to the Swedish Coastal and Ocean Biogeochemical model (SCOBI), that covers the North Sea, the Skagerrak–Kattegat transition zone and the Baltic Sea. We address its validity to further investigate biogeochemical changes in the North Sea–Baltic Sea system. The model reproduces the long-term temporal trends, the temporal variability, the yearly averages and the general spatial distribution of all of the assessed biogeochemical parameters. It is particularly suitable for use in future multi-stressor studies, such as the evaluation of combined climate and nutrient forcing scenarios. In particular, the model performance is best for oxygen and phosphate concentrations. However, there are important differences between model results and observations with respect to chlorophyll a and nitrate in coastal areas of the southeastern North Sea, the Skagerrak–Kattegat transition zone, the Gulf of Riga, the Gulf of Finland and the Gulf of Bothnia. These are partially linked to different local processes and biogeochemical forcing that lead to a general overestimation of nitrate. Our model results are validated for individual areas that are in agreement with policy management assessment areas, thereby providing added value with respect to better contributing to international programmes aiming to reduce eutrophication in the North Sea–Baltic Sea system.

An overview of the NEMO modelling for the BaySys project

This article is intended as an introduction to discuss the development of a modelling framework to examine simulated climate change and river discharge regulation and their combined impact on marine conditions in the Hudson Bay Complex as a contribution to BaySys, a collaborative project between Manitoba Hydro, Hydro-Quebec, the University of Manitoba, the University of Alberta, Université Laval and Ouranos. In support of this work, a sea ice and oceanographic model was improved and then used to further study the effects of freshwater loading and ice cover on the circulation of Hudson Bay. This modelling perspective is based on the Nucleus for European Modelling of the Ocean (NEMO) ocean general circulation model coupled to version 2 of the Louvain-la-Neuve sea ice model (LIM2). The goal of the modelling was to provide a framework and tool for simulating projected changes in marine state and dynamic variables, while also enabling an integration of observations and numerical analyses. A key aspect of this work was the climate-hydrologic-ocean model integration aspect. The inclusion of a biogeochemical model and explicit tidal forcing to examine the evolution of a Canadian marginal sea with century-long integrations was also a novel aspect of the work. Overall, this work examines the NEMO modelling configuration used in BaySys, how it is set up and the experiments carried out. A broader picture evaluation of the model output is made including the BaySys mooring observations, showing that the modelling framework is suitable to examine the posed questions on the role of climate change and river regulation.

Weakening Indian Ocean carbon uptake in 2015: The role of amplified basin‐wide warming and reduced Indonesian throughflow

AbstractIn 2015, the Indian Ocean exhibits an exceptionally weakened CO2 uptake, highlighting strong interannual variability of ocean carbon sink. By utilizing multiple ocean CO2 partial pressure (pCO2) data and a state‐of‐the‐art ocean biogeochemical model, we show that the 2015 ocean CO2 anomaly is characterized by a basin‐wide amplification of ocean pCO2, differing from ocean pCO2 responses to other Indian Ocean Dipole events (e.g., 1997 and 2019). The distinct ocean pCO2 anomaly is attributed to an amplified warming and an unprecedented weakening Indonesian Throughflow under the influence of co‐occurrence of positive IOD and extreme El Niño in 2015. The amplified warming drives higher ocean pCO2 in the western and central Indian Ocean, while the ITF transports anomalously high ocean pCO2 water from the Pacific Ocean to the southeastern Indian Ocean. This newly identified ocean carbon response provides deeper insights into the Indian Ocean carbon interannual variability.

Linking fine root lifespan to root chemical and morphological traits—A global analysis

Fine root lifespan is a critical trait associated with contrasting root strategies of resource acquisition and protection. Yet, its position within the multidimensional "root economics space" synthesizing global root economics strategies is largely uncertain, and it is rarely represented in frameworks integrating plant trait variations. Here, we compiled the most comprehensive dataset of absorptive median root lifespan (MRL) data including 98 observations from 79 woody species using (mini-)rhizotrons across 40 sites and linked MRL to other plant traits to address questions of the regulators of MRL at large spatial scales. We demonstrate that MRL not only decreases with plant investment in root nitrogen (associated with more metabolically active tissues) but also increases with construction of larger diameter roots which is often associated with greater plant reliance on mycorrhizal symbionts. Although theories linking organ structure and function suggest that root traits should play a role in modulating MRL, we found no correlation between root traits associated with structural defense (root tissue density and specific root length) and MRL. Moreover, fine root and leaf lifespan were globally unrelated, except among evergreen species, suggesting contrasting evolutionary selection between leaves and roots facing contrasting environmental influences above vs. belowground. At large geographic scales, MRL was typically longer at sites with lower mean annual temperature and higher mean annual precipitation. Overall, this synthesis uncovered several key ecophysiological covariates and environmental drivers of MRL, highlighting broad avenues for accurate parametrization of global biogeochemical models and the understanding of ecosystem response to global climate change.

The Global Distribution of Grazing Dynamics Estimated From Inverse Modeling

AbstractGrazing dynamics are one of the most poorly constrained components of the marine carbon cycle. We use inverse modeling to infer the distribution of community‐integrated zooplankton grazing dynamics based on the ability of different grazing formulations to recreate the satellite‐observed seasonal cycle in phytoplankton biomass after controlling for physical and bottom‐up controls. We find large spatial variability in the optimal community‐integrated half saturation concentration for grazing (K1/2), with lower (higher) values required in more oligotrophic (eutrophic) biomes. This leads to a strong sigmoidal relationship between observed mean‐annual phytoplankton biomass and the optimally inferred grazing parameterization. This relationship can be used to help constrain, validate and/or parameterize next‐generation biogeochemical models.

Maximizing carbon sequestration potential in Chinese forests through optimal management

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1–3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Soil Geobacteraceae are the key predictors of neurotoxic methylmercury bioaccumulation in rice.

Contamination of rice by the potent neurotoxin methylmercury (MeHg) originates from microbe-mediated Hg methylation in soils. However, the high diversity of Hg methylating microorganisms in soils hinders the prediction of MeHg formation and challenges the mitigation of MeHg bioaccumulation via regulating soil microbiomes. Here we explored the roles of various cropland microbial communities in MeHg formation in the potentials leading to MeHg accumulation in rice and reveal that Geobacteraceae are the key predictors of MeHg bioaccumulation in paddy soil systems. We characterized Hg methylating microorganisms from 67 cropland ecosystems across 3,600 latitudinal kilometres. The simulations of a rice-paddy biogeochemical model show that MeHg accumulation in rice is 1.3-1.7-fold more sensitive to changes in the relative abundance of Geobacteraceae compared to Hg input, which is recognized as the primary parameter in controlling MeHg exposure. These findings open up a window to predict MeHg formation and accumulation in human food webs, enabling more efficient mitigation of risks to human health through regulations of key soil microbiomes.

Biogeochemical modelling to assess the effect of bioclogging on multiple electron acceptor-mediated petroleum hydrocarbon bioremediation in vadose zone.

Bioremediation is an economically viable and sustainable clean-up strategy. Hydrodynamic, as well as transport characteristics of the porous medium, can evolve over the period as a result of biological clean-up activities. The present study proposes a 2-D numerical framework to simulate the effect of bioclogging on multiple electron acceptor-mediated petroleum hydrocarbon bioremediation in the vadose zone. For modelling, a spill of BTEX (benzene, toluene, ethylbenzene and xylene) is assumed near source zone. The developed model results are validated using three previously published datasets on flow, transport and biodegradation in the vadose zone. Simulations are performed for three types of soil, including clay, sand and loam. The analysis shows that sand has a maximum infiltration rate and clay has a minimum. Hydraulic conductivity and saturation profile peaks reach their minimal value at a shallower depth (around four times) when bioclogging is present compared to when it is absent. The migration depth and concentration of BTEX are observed to be restricted to a shallower depth in aquifers with the presence of microbial clogging. The outcome shows that electron acceptor consumption is more (around sevenfold for oxygen, fourfold for nitrate and threefold for sulphate) in the presence of bioclogging at the shallower zone. Zeroth order spatial moment and sensitivity analyses show that biological clogging, number of electron acceptors and inhibition constant substantially affect BTEX bioremediation in the vadose zone.

Marine Phosphate Level During the Archean Constrained by the Global Redox Budget

AbstractUnderstanding the oceanic phosphate concentration is critical for understanding marine productivity and oxygen evolution throughout Earth history. During the Archean, estimates of marine phosphate levels range from scarce to enriched conditions. However, biogeochemical conditions required for sustaining high phosphate concentrations while retaining an anoxic atmosphere during the Archean remain ambiguous. Here, we employ a biogeochemical model of the marine phosphate cycle to determine the conditions under which oceanic phosphate levels could have been higher than present‐day values during the Archean after the emergence of oxygenic photoautotrophs (OP). We show that, under the presence of OP, phosphate‐rich oceans require the limitation by factors other than phosphate, or a high outgassing rate of reducing gases. If these conditions were not met, the occurrence of oceanic phosphate levels higher than present‐day values during the Archean would require the absence of OP.

Storm-driven hydrological, seasonal, and land use/land cover impact on dissolved organic matter dynamics in a mid-Atlantic, USA coastal plain river system characterized by 21 T FT-ICR mass spectrometry

Introduction: Dissolved organic matter (DOM) as primary and secondary energy sources can be transported via rivers to estuaries and impact coastal biogeochemical cycles. Storm-induced high discharge events can alter the dominant river flow paths and enhance leaching of shallow organic-rich soil layers, leading to elevated terrestrial DOM export. Land use/land cover (LULC) and associated anthropogenic interventions (including artificial reservoirs and agricultural irrigation) can control sources and transformation processes of exported DOM along with hydrologic factors. The relative significance of LULC, hydrological factors, and temperature variations with seasons will differ depending on geographical locations and complicate their incorporation in biogeochemical models of DOM dynamics. This study investigates the role of LULC, seasonality, and storm events on DOM concentrations and molecular composition in the Murderkill River system.Method: Surface water samples were collected seasonally and before/after storm events from 6 sites representing forested, agricultural, and developed LULC units. The DOM was characterized via parallel factor analysis of excitation-emission matrix data and electrospray ionization 21 T Fourier-transform ion cyclotron resonance mass spectrometry to determine potential DOM sources and enable the development of a conceptual model for DOM dynamics in rivers impacted by anthropogenic reservoirs.Result and Discussion: Our results suggest that storm-induced shallow and overland flow paths can increase surface-vegetation/plant-litter derived DOM based on atomic ratios associated with specific biogenic precursors (i.e., lignin, tannins, and/or oxygenated aromatic DOM), particularly in winter when autochthonous production was suppressed due to reduced temperatures. We further demonstrate that the damming effects of artificial reservoirs enhance the role of seasonal patterns of autochthonous production, disrupting storm-shunt process and stimulating significantly more bio-produced DOM export during spring and summer (i.e., tryptophan/tyrosine-like. N- and S- containing, phytoplankton-derived compounds). Collectively, these results demonstrate how artificial reservoirs alter the characteristics of DOM exported from rivers with implications for understanding carbon export and fate at river-estuary interfaces.