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We utilize a coupled economy–agroecology–hydrology modeling framework to capture the cascading impacts of climate change mitigation policy on agriculture and the resulting water quality cobenefits. We analyze a policy that assigns a range of United States government’s social cost of carbon estimates ($51, $76, and $152/ton of CO2-equivalents) to fossil fuel–based CO2 emissions. This policy raises energy costs and, importantly for agriculture, boosts the price of nitrogen fertilizer production. At the highest carbon price, US carbon emissions are reduced by about 50%, and nitrogen fertilizer prices rise by about 90%, leading to an approximate 15% reduction in fertilizer applications for corn production across the Mississippi River Basin. Corn and soybean production declines by about 7%, increasing crop prices by 6%, while nitrate leaching declines by about 10%. Simulated nitrate export to the Gulf of Mexico decreases by 8%, ultimately shrinking the average midsummer area of the Gulf of Mexico hypoxic area by 3% and hypoxic volume by 4%. We also consider the additional benefits of restored wetlands to mitigate nitrogen loading to reduce hypoxia in the Gulf of Mexico and find a targeted wetland restoration scenario approximately doubles the effect of a low to moderate social cost of carbon. Wetland restoration alone exhibited spillover effects that increased nitrate leaching in other parts of the basin which were mitigated with the inclusion of the carbon policy. We conclude that a national climate policy aimed at reducing greenhouse gas emissions in the United States would have important water quality cobenefits. [ABSTRACT FROM AUTHOR]

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance. [ABSTRACT FROM AUTHOR]

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE Project (Spruce and Peatland Responses Under Climatic and Environmental Change, http: //mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Oce of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are: 1. Data acquisition and control system - set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components. 2. Data collection system - set of hardware and software to deliver data to a central depository for storage and further processing. 25 3. Data management plan - set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an eficient data system for managing high volume sources of in-situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data. [ABSTRACT FROM AUTHOR]

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global 5 scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper 10 provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics 15 (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving 20 the model performance. [ABSTRACT FROM AUTHOR]

Methane (CH4), an important greenhouse gas that affects radiation balance and consequently the earth's climate, still has uncertainties in its sinks and sources. The world's oceans are considered to be a source of CH4 to the atmosphere, although the biogeochemical processes involved in its formation are not fully understood. Several recent studies provided strong evidence of CH4 production in oxic marine and freshwaters but its source is still a topic of debate. Studies of CH4 dynamics in surface waters of oceans and large lakes have concluded that pelagic CH4 supersaturation cannot be sustained either by lateral inputs from littoral or benthic inputs alone. However, frequently regional and temporal oversaturation of surface waters occurs. This comprises the observation of a CH4 oversaturating state within the surface mixed layer, sometimes also termed the "oceanic methane paradox". In this study we considered marine algae as a possible direct source of CH4. Therefore, the coccolithophore Emiliania huxleyi was grown under controlled laboratory conditions and supplemented with two 13C-labelled carbon substrates, namely bicarbonate and a position-specific 13C-labelled methionine (R-S-13CH3). The CH4 production was 0.7 µg POC g-1 d-1, or 30 ng g-1 POC h-1. After supplementation of the cultures with the 13C labelled substrate, the isotope label was observed in headspace-CH4. Moreover, the absence of methanogenic archaea within the algal culture and the oxic conditions during CH4 formation suggest that marine algae such as Emiliania huxleyi contribute to the observed spatial and temporal restricted CH4 oversaturation in ocean surface waters. [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) is a developing technology that seeks to mitigate against the impact of increasing anthropogenic carbon dioxide (CO2) production by capturing CO2 from large point source emitters. After capture the CO2 is compressed and transported to a reservoir where it is stored for geological time scales. Potential leakages from CCS projects, where stored CO2 migrates through the overlaying sediments, are likely to have severe implications on benthic and marine ecosystems. Nonetheless, prokaryotic response to elevated CO2 concentrations has been suggested as one of the first detectable warnings if a CO2 leakage should occur. Applying properties of prokaryotic communities (i.e. community composition and metabolic status) as a novel CO2 monitoring application is highly reliable within a multidisciplinary framework, where deviations from the baseline can easily be identified. In this paper we review current knowledge about the impact of CO2 leakages on marine sediments from a multidisciplinary-based monitoring perspective. We focus on aspects from the fields of biology, geophysics, and chemistry, and discuss a case study example. We argue the importance of an integrative multidisciplinary approach, incorporating biogeochemistry, geophysics, microbial ecology and modelling, with a particular emphasis on metagenomic techniques and novel bioinformatics, for future CCS monitoring. Within this framework, we consider that an effective CCS monitoring programme will ensure that large-scale leakages with potentially devastating effects for the overlaying ecosystem are avoided. Furthermore, the multidisciplinary approach suggested here for CCS monitoring is generic, and can be adapted to other systems of interest. [ABSTRACT FROM AUTHOR]

This paper describes the sampling and analysis of biogeochemical parameters collected in the Rockall Trough in January/February of 2009, 2010, 2011 and 2012. Sampling was carried out across two transects, one southern and one northern transect each year. Samples for dissolved inorganic carbon (DIC) and total alkalinity (TA) were taken alongside salinity, dissolved oxygen and dissolved inorganic nutrients (total-oxidised nitrogen, nitrite, phosphate and silicate) to describe the chemical signatures of the various water masses in the region. These were taken at regular intervals through the water column. The 2009 and 2010 data are available on the CDIAC database. [ABSTRACT FROM AUTHOR]

The sea surface microlayer (SML) is an important biogeochemical system whose physico-chemical analysis often necessitates some degree of sample storage. However, many SML components degrade with time so the development of optimal storage protocols is paramount. Using freshwater and saline SML samples from a river-estuary, we interrogated temporal changes in surfactant activity (SA) and the absorbance and fluorescence of chromophoric dissolved organic matter (CDOM) over four weeks, following selected sample treatment and storage protocols. Some variability in the effectiveness of individual protocols most likely reflects sample provenance. None of the various protocols examined performed any better than dark storage at 4°C without pre-treatment. We thus recommend this as the optimal strategy, coupled with minimal storage times as far as practicable. Future studies of SML properties should validate their chosen storage protocols independently. [ABSTRACT FROM AUTHOR]

Dynamic Global Vegetation Models (DGVMs) typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semiempirical Plant Functional Types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity DGVM (JeDi-DGVM) as a new approach to global vegetation modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly-generated plant growth strategies (PGSs), each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional tradeoffs. These trade-offs ultimately determine whether a PGS is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other PGSs. The biogeochemical fluxes and land-surface properties of the individual PGSs are aggregated to the grid cell scale using a mass-based weighting scheme. Simulated global biogeochemical and biogeographical patterns are evaluated against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favorably with other state-of-the-art terrestrial biosphere models. This is despite the parameters describing the ecophysiological functioning and allometry of JeDi-DGVM plants evolving as a function of vegetation survival in a given climate, as opposed to typical approaches that fix land surface parameters derived from observational datasets for each PFT. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere. [ABSTRACT FROM AUTHOR]

Today, the routine assimilation of satellite data into operational models of the ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "re- analysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale threedimensional coupled physical-biogeochemical model of the North-Atlantic. The aim is on one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical-biogeochemical modelling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9 year-long period. In this frame, two experiences are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, the nitrate World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface chlorophyll concentrations analysis and forecast, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related litterature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentration deeper than 50 m. The assessement of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalysing the ocean biogeochemistry based on ocean color data. [ABSTRACT FROM AUTHOR]

An outstanding problem in biogeochemical modelling of the ocean is that many of the key processes occur intermittently at small scales, such as the sub-mesoscale, that are not well represented in global ocean models. As an example, state-of-the-art models give values of primary production approximately two orders of magnitude lower than those observed in the ocean's oligotrophic gyres, which cover a third of the Earth's surface. This is partly due to their failure to resolve sub-mesoscale phenomena, which play a significant role in nutrient supply. Simply increasing the resolution of the models may be an inefficient computational solution to this problem. An approach based on recent advances in adaptive mesh computational techniques may offer an alternative. Here the first steps in such an approach are described, using the example of a simple vertical column (quasi 1-D) ocean biogeochemical model. We present a novel method of simulating ocean biogeochemical behaviour on a vertically adaptive computational mesh, where the mesh changes in response to the bio geochemical and physical state of the system throughout the simulation. We show that the model reproduces the general physical and biological behaviour at three ocean stations (India, Papa and Bermuda) as compared to a high-resolution fixed mesh simulation and to observations. The simulations capture both the seasonal and inter-annual variations. The use of an adaptive mesh does not increase the computational error, but reduces the number of mesh elements by a factor of 2-3, so reducing computational overhead. We then show the potential of this method in two case studies where we change the metric used to determine the varying mesh sizes in order to capture the dynamics of chlorophyll at Bermuda and sinking detritus at Papa. We therefore demonstrate adaptive meshes may provide a suitable numerical technique for simu lating seasonal or transient biogeochemical behaviour at high spatial resolution whilst minimising computational cost. [ABSTRACT FROM AUTHOR]

Phenology is essential to our understanding of biogeochemical cycles and the climate system. We develop a global mechanistic model of leaf phenology based on the hypothesis that phenology is a strategy for optimal carbon gain at the canopy level so that trees adjust leaf gains and losses in response to environmental factors such as light, temperature and soil moisture, to achieve maximum carbon assimilation. We fit this model to five years of satellite observations of leaf area index (LAI) using a Bayesian fitting algorithm. We show that our model is able to reproduce phenological patterns for all vegetation types and use it to explore variations in growing season length and the climate factors that limit leaf growth for different biomes. Phenology in wet tropical areas is limited by leaf age physiological constraints while at higher latitude leaf seasonality is limited by low temperature and light availability. Leaf growth in grassland regions is limited by water availability but often in combination with other factors. This model will advance the current understanding of phenology for ecosystem carbon models and our ability to predict future phenological behaviour. [ABSTRACT FROM AUTHOR]

In situ observations showed phytoplankton blooms appear during winter in the Taiwan Strait (TWS), but the mechanism for bloom initiation was unclear. With the use of a coupled physical--biological numerical model, we find the winter bloom is triggered by the relaxation of the northeasterly monsoon. Thus, the aim of this study is to investigate the mechanism for bloom formation using the model. The model results show the weakening of the northeasterly wind generates a current that carries the fresh eutrophic Min-Zhe coastal water (MZCW) off the west coast of the TWS; then a stable stratification is formed in the upper ocean of the western strait, which significantly limits the turbulence. Via diagnostic analysis of the model output, we illustrate that the reduced turbulence allows the phytoplankton to accumulate within the upper layer of the western strait, which leads to an increase in chlorophyll. The analysis is further verified by the critical turbulence theory about the bloom. In addition to reduced turbulence, the lag between zooplankton and phytoplankton responses to the offshore extension of the MZCW is responsible for the formation of the bloom at the front. Therefore, we propose the observed offshore bloom in winter in the TWS is induced by the stable water stratification and the biological processes during the relaxation of the northeasterly wind. [ABSTRACT FROM AUTHOR]

We present a generic flux limiter to account for mass limitations from an arbitrary number of substrates in a biogeochemical reaction network. The flux limiter is based on the observation that substrate (e.g., nitrogen, phosphorus) limitation in biogeochemical models can be represented as to ensure mass conservative and non-negative numerical solutions to the governing ordinary differential equations. Application of the flux limiter includes two steps: (1) formulate the biogeochemical processes with a matrix of stoichiometric coefficients and (2) apply Liebig's law of the minimum using the dynamic stoichiometric relationship of the reactants. This approach contrasts with the ad hoc down-regulation approaches that are implemented in many existing models (such as CLM4.5 and the ACME (Accelerated Climate Modeling for Energy) Land Model (ALM)) of carbon and nutrient interactions, which are error prone when adding new processes, even for experienced modelers. Through an example implementation with a Centurylike decomposition model that includes carbon, nitrogen, and phosphorus, we show that our approach (1) produced almost identical results to that from the ad hoc downregulation approaches under non-limiting nutrient conditions; and (2) properly resolved the negative solutions under substrate-limited conditions where the simple clipping approach failed; and (3) successfully avoided the potential conceptual ambiguities that are implied by those ad hoc down-regulation approaches. We expect our approach will make future biogeochemical models easier to improve and more robust. [ABSTRACT FROM AUTHOR]

In the framework of the INDESO (Infrastructure evelopment of Space Oceanography) project, an operational ocean forecasting system was developed to monitor the state of the Indonesian seas in terms of circulation, biogeochemistry and fisheries. This fore-casting system combines a suite of numerical models connecting physical and biogeochemical variables to population dynamics of large marine predators (tunas). The physical/biogeochemical coupled component (INDO12BIO configuration) covers a large region extending from the western Pacific Ocean to the Eastern Indian Ocean at 1/12° resolution. The OPA/NEMO physical ocean model and the PISCES biogeochemical model are coupled in "on-line" mode without degradation in space and time. The operational global ocean forecasting system (1=4°) operated by Mercator Ocean provides the physical forcing while climatological open boundary conditions are prescribed for the biogeochemistry. This paper describes the skill assessment of the INDO12BIO configuration. Model skill is assessed by evaluating a reference hindcast simulation covering the last 8 years (2007-2014). Model results are compared to satellite, climatological and in situ observations. Diagnostics are performed on chlorophyll a, primary production, mesozooplankton, nutrients and oxygen. Model results reproduce the main characteristics of biogeochemical tracer distributions in space and time. The seasonal cycle of chlorophyll a is in phase with satellite observations. The northern and southern parts of the archipelago present a distinct seasonal cycle, with higher chlorophyll biomass in the southern (northern) part during SE (NW) monsoon. Nutrient and oxygen concentrations are correctly reproduced in terms of horizontal and vertical distributions. The biogeochemical content of water masses entering in the archipelago as well as the water mass transformation across the archipelago conserves realistic vertical distribution in Banda Sea and at the exit of the archipelago. [ABSTRACT FROM AUTHOR]

We applied a coupled, marine water column model to three sites in the North Sea. The three sites represent different hydrodynamic regimes and are thus representative of a wider area. The model consists of a hydro-biogeochemical model (GOTM-ERSEMBFM) coupled one way upwards to a size-structured model representing pelagic predators and detritivores (Blanchard et al., 2009). Thus, bottom-up pressures like changing abiotic environment (climate change, chemical cycling) impact on fish biomass across the size spectrum. Here, we studied three different impacts of future conditions on fish yield: climatic impacts (medium emission scenario), abiotic ocean acidification impacts (reduced pelagic nitrification) and biotic ocean acidification impacts (reduced detritivore growth rate). The three impacts were studied separately and combined, and showed that sites within different hydrodynamic regimes responded very differently. The seasonally stratified site showed an increase in fish yields (occuring in winter and spring), with acidification effects of the same order of magnitude as climatic effects. The permanently mixed site also showed an increase in fish yield (increase in summer, decrease in winter), due to climatic effects moderated by acidification impacts. The third site, which is characterised by large interannual variability in thermal stratification duration, showed a decline in fish yields (occuring in winter) due to decline of the benthic system which forms an important carbon pathway at this site. All sites displayed a shift towards a more pelagic oriented system. [ABSTRACT FROM AUTHOR]

We use an eddy-resolving, regional ocean biogeochemical model to investigate the main variables and processes responsible for the climatological spatio-temporal variability of pCO2 and the air--sea CO2 fluxes in the southwestern Atlantic Ocean. Overall, the region acts as sink of atmospheric CO2 south of 30° S, and is close to equilibrium with the atmospheric CO2 to the north. On the shelves, the ocean acts as a weak source of CO2, except for the mid/outer shelves of Patagonia, which act as sinks. In contrast, the inner shelves and the low latitude open ocean of the southwestern Atlantic represent source regions. Observed nearshore-to-offshore and meridional pCO2 gradients are well represented by our simulation. A sensitivity analysis shows the importance of the counteracting effects of temperature and dissolved inorganic carbon (DIC) in controlling the seasonal variability of pCO2. Biological production and solubility are the main processes regulating pCO2, with biological production being particularly important on the shelf regions. The role of mixing/stratification in modulating DIC, and therefore surface pCO2 is shown in a vertical profile at the location of the Ocean Observatories Initiative (OOI) site in the Argentine Basin (42° S, 42° W). [ABSTRACT FROM AUTHOR]

We present a numerical model of the ocean that couples a three-stream radiative transfer component with a marine biogeochemical-ecosystem in a dynamic threedimensional physical framework. The radiative transfer component resolves spectral irradiance as it is absorbed and scattered within the water column. We explicitly include the effect of several optically important water constituents (the phytoplankton community, detrital particles, and coloured dissolved organic matter, CDOM). The model is evaluated against in situ observed and satellite derived products. In particular we compare to concurrently measured biogeochemical, ecosystem and optical data along a north-south transect of the Atlantic Ocean. The simulation captures the patterns and magnitudes of these data, and estimates surface upwelling irradiance analogous to that observed by ocean colour satellite instruments. We conduct a series of sensitivity experiments to demonstrate, globally, the relative importance of each of the water constituents, and the crucial feedbacks between the light field and the relative fitness of phytoplankton types, and the biogeochemistry of the ocean. CDOM has proportionally more importance at short wavelengths and in more productive waters, phytoplankton absorption is especially important at the deep chlorophyll a (Chl a) maximum, and absorption by water molecules is relatively most important in the highly oligotrophic gyres. Sensitivity experiments in which absorption by any of the optical constituents was increased led to a decrease in the size of the oligotrophic regions of the subtropical gyres: lateral nutrient supplies were enhanced as a result of decreasing high latitude productivity. Scattering does not as strongly affect the ecosystem and biogeochemistry fields within the water column but is important for setting the surface upwelling irradiance, and hence sea surface reflectance. Having a model capable of capturing bio-optical feedbacks will be important for improving our understanding of the role of light and optical constituents on ocean biogeochemistry, especially in a changing environment. The potential benefits of capturing surface upwelling irradiance will be important for making closer connections to satellite derived products in the future. [ABSTRACT FROM AUTHOR]

The main goal of the project DUNE was to estimate the impact of atmospheric deposition on an oligotrophic ecosystem based on mesocosm experiments simulating strong atmospheric inputs of Aeolian dust. Atmospheric deposition is now recognized as a significant source of macro- and micro-nutrients for the surface ocean, but the quantification of its role on the biological carbon pump is still poorly determined. We proposed in DUNE to investigate the role of atmospheric inputs on the functioning of an oligotrophic system particularly well adapted to this kind of study: the Mediterranean Sea. The Mediterranean Sea - etymologically, sea surrounded by land - is submitted to atmospheric inputs that are very variable both in frequency and intensity. During the thermal stratification period, only atmospheric deposition is prone to fertilize Mediterranean surface waters which has become very oligotrophic due to the nutrient depletion (after the spring bloom). This paper describes the objectives of DUNE and the implementation plan of a series of mesocosms experiments during which either wet or dry and a succession of two wet deposition fluxes of 10 gm-2 of Saharan dust have been simulated. After the presentation of the main biogeochemical initial conditions of the site at the time of each experiment, a general overview of the papers published in this special issue is presented, including laboratory results on the solubility of trace elements in erodible soils in addition to results from the mesocosm experiments. Our mesocosm experiments aimed at being representative of real atmospheric deposition events onto the surface of oligotrophic marine waters and were an original attempt to consider the vertical dimension in the study of the fate of atmospheric deposition within surface waters. Results obtained can be more easily extrapolated to quantify budgets and parameterize processes such as particle migration through a "captured water column". The strong simulated dust deposition events were found to impact the dissolved concentrations of inorganic dissolved phosphorus, nitrogen, iron and other trace elements. In the case of Fe, adsorption on sinking particles yields a decrease in dissolved concentration unless binding ligands were produced following a former deposition input and associated fertilization. For the first time, a quantification of the C export induced by the aerosol addition was possible. Description and parameterization of biotic (heterotrophs and autotrophs, including diazotrophs) and abiotic processes (ballast effect due to lithogenic particles) after dust addition in sea surface water, result in a net particulate organic carbon export in part controlled by the "lithogenic carbon pump". [ABSTRACT FROM AUTHOR]

Soils are a crucial component of the Earth System; they comprise a large portion of terrestrial carbon stocks, mediate the supply and demand of nutrients, and influence the overall response of terrestrial ecosystems to perturbations. In this paper, we develop a new soil biogeochemistry model for the Community Land Model, version 4 (CLM4). The new model includes a vertical dimension to carbon (C) and nitrogen (N) pools and transformations, a more realistic treatment of mineral N pools, flexible treatment of the dynamics of decomposing carbon, and a radiocarbon (14C) tracer. We describe the model structure, comparison against site-level and global observations, and overall effect of the revised soil model on CLM carbon dynamics. Site-level comparisons to radiocarbon and bulk soil C observations support the idea that soil C turnover is reduced at depth beyond what is expected from environmental controls by temperature, moisture, and oxygen that are considered in the model. The revised soil model predicts substantially more and older soil C, particularly at high latitudes, where it resolves a permafrost soil C pool, in better agreement with observations. In addition the 20th century C dynamics of the model are more realistic than the baseline model, with more terrestrial C uptake over the 20th century due to reduced N downregulation and longer turnover times of decomposing C. [ABSTRACT FROM AUTHOR]

Ice melting in the Arctic Ocean exposes the surface water to more radiative energy with poorly understood effects on photo-biogeochemical processes and heat deposition in the upper ocean. In August 2009, we documented the vertical variability of light absorbing components at 37 stations located in the southeastern Beaufort Sea including both Mackenzie river-influenced waters and polar mixed layer waters. We found that melting multi-year ice released significant amount of non-algal particulates (NAP) near the sea surface relative to sub-surface waters. NAP absorption coefficients at 440nm (aNAP(440)) immediately below the sea surface (0-) were on average 3-fold (up to 10-fold) higher compared to sub-surface values measured at 2-3m depth. The impact of this unusual feature on the light transmission and remote sensing reflectance (Rrs) was further examined using a radiative transfer model. A 10-fold particle enrichment homogeneously distributed in the first meter of the water column slightly reduced photosynthetically available and usable radiation (PAR and PUR) by ~6% and ~8 %, respectively, relative to a fully homogenous water column with low particles concentration. In terms of Rrs, the particle enrichment significantly flattered the spectrum by reducing the Rrs by up to 20% in the blue-green spectral region (400–550 nm). These results highlight the impact of melt water on the concentration of particles at sea surface, and the need for considering nonuniform vertical distribution of particles in such systems when interpreting remotely sensed ocean color. Spectral slope of aNAP spectra calculated in the UV domain decreased with depth suggesting that this parameter is sensitive to detritus composition and/or diagenesis state (e.g., POM photobleaching). [ABSTRACT FROM AUTHOR]

Most future projections forecast significant and ongoing climate change during the 21st century, but with the severity of impacts dependent on efforts to restrain or reorganise human activity to limit carbon dioxide (CO2) emissions. A major sink for atmospheric CO2, and a key source of biological resources, the World Ocean is widely anticipated to undergo profound physical and -- via ocean acidification -- chemical changes as direct and indirect results of these emissions. Given strong biophysical coupling, the marine biota is also expected to experience strong changes in response to this anthropogenic forcing. Here we examine the large-scale response of ocean biogeochemistry to climate and acidification impacts during the 21st century for Representative Concentration Pathways (RCPs) 2.6 and 8.5 using an intermediate complexity global ecosystem model, Medusa--2.0. The primary impact of future change lies in stratification-led declines in the availability of key nutrients in surface waters, which in turn leads to a global decrease (1990s vs. 2090s) in ocean productivity (-6.3%). This impact has knock-on consequences for the abundances of the low trophic level biogeochemical actors modelled by Medusa--2.0 (-5.8%), and these would be expected to similarly impact higher trophic level elements such as fisheries. Related impacts are found in the flux of organic material to seafloor communities (-40.7% at 1000m), and in the volume of ocean suboxic zones (+12.5%). A sensitivity analysis removing an acidification feedback on calcification finds that change in this process significantly impacts benthic communities, suggesting that a better understanding of the OA-sensitivity of calcifying organisms, and their role in ballasting sinking organic carbon, may significantly improve forecasting of these ecosystems. For all processes, there is geographical variability in change, and changes are much more pronounced under RCP 8.5 than the RCP 2.6 scenario. [ABSTRACT FROM AUTHOR]

Based upon seven field surveys conducted between May 2011 and January 2012, we investigated pH, carbonate saturation state of aragonite (Ωarag), and ancillary parameters on the Chinese side of the North Yellow Sea, a western North Pacific continental margin of major economic importance. Subsurface waters were nearly in equilibrium with air in May and June. From July to October, the fugacity of CO2 (fCO2) of bottom water gradually increased to 697±103 µatm and pH decreased to 7.83±0.07 due to respiration/remineralization processes of primary production induced biogenic particles. In November and January, bottom water fCO2 decreased and pH gradually returned to an air-equilibrated level due to cooling enhanced vertical mixing. The corresponding bottom water Ωarag was 1.74±0.17 (May), 1.77±0.26 (June), 1.70±0.26 (July), 1.72±0.33 (August), 1.32±0.31 (October), 1.50±0.28 (November), and 1.41±0.12 (January). Critically low Ωarag values of 1.0 to 1.2 were mainly observed in subsurface waters in a salinity range of 31.5-32.5 psu in October and November, accounting for ~10% of the North Yellow Sea area. Water mass derived from the adjacent Bohai Sea had a typical water salinity of 30.5-31.5 psu, and bottom water Ωarag values ranged mostly between 1.6 and 2.4. This study showed that the carbonate system in the North Yellow Sea was substantially influenced by global atmospheric CO2 increase. The community respiration/remineralization rates in typical North Yellow Sea bottom water mass were estimated at 0.55-1.0 µmol O2 kg-1 d-1 in warm seasons, leading to seasonal drops in subsurface pH and Ωarag. Outflow of the Bohai Sea water mass counteracted the subsurface Ωarag reduction in the North Yellow Sea. [ABSTRACT FROM AUTHOR]

The Apparent Oxygen Utilization (AOU) is a classical measure of the amount of oxygen respired by biological processes in the ocean interior. We show that the AOU systematically overestimates the True Oxygen Utilization (TOU) in 6 coupled circulation- biogeochemical ocean models, due to atmosphere--ocean oxygen disequilibrium in the subduction regions, consistent with prior work. We develop a new approach that we call Evaluated Oxygen Utilization (EOU), which approximates the TOU at least twice as well as AOU in all 6 models, despite large differences in the physical and biological components of the models. Applying the EOU approach to a global observational dataset leads to an estimated biological oxygen consumption rate that is by 25 percent lower than that derived from AOU-based estimates. [ABSTRACT FROM AUTHOR]

The sea surface microlayer (SML) is at the very surface of the ocean, linking the hydrosphere with the atmosphere, and central to a range of global biogeochemical and climate-related processes. The presence and enrichment of organic compounds in the SML have been suggested to influence air-sea gas exchange processes as well as the emission of primary organic aerosols. Among these organic compounds, primarily of plankton origin, are dissolved exopolymers, specifically polysaccharides and proteins, and gel particles, such as Transparent Exopolymer Particles (TEP) and Coomassie Stainable Particles (CSP). These organic substances often accumulate in the surface ocean when plankton productivity is high. Here, we report results obtained in December 2012 during the SOPRAN Meteor 91 cruise to the highly productive, coastal upwelling regime off Peru. Samples were collected from the SML and from ~ 20 cm below, and were analyzed for polysaccharidic and proteinaceous compounds, gel particles, total and dissolved organic carbon, bacterial and phytoplankton abundance. Our study provides insight to the physical and biological control of organic matter enrichment in the SML, and discusses the potential role of organic matter in the SML for air-sea exchange processes. [ABSTRACT FROM AUTHOR]

Microbialites are a product of trapping and binding of sediment by microbial communities, and are considered to be some of the most ancient records of life on Earth. It is a commonly held belief that microbialites are limited to extreme, hypersaline settings. However, more recent studies report their occurrence in a wider range of environments. The goal of this study is to explore whether microbialite-bearing sites share common geochemical properties. We apply statistical techniques to distinguish any common traits in these environments. These techniques ultimately could be used to address questions of microbialite distribution: are microbialites restricted to environments with specific characteristics; or are they more broadly distributed? A dataset containing hydrographic characteristics of several microbialite sites with data on pH, conductivity, alkalinity, and concentrations of several major anions and cations was constructed from previously published studies. In order to group the water samples by their natural similarities and differences, a clustering approach was chosen for analysis. k means clustering with partial distances was applied to the dataset with missing values, and separated the data into two clusters. One of the clusters is formed by samples from atoll Kiritimati (central Pacific Ocean), and the second cluster contains all other observations. Using these two clusters, the missing values were imputed by k nearest neighbor method, producing a complete dataset that can be used for further multivariate analysis. Salinity is not found to be an important variable defining clustering, and although pH defines clustering in this dataset, it is not an important variable for microbialite formation. Clustering and imputation procedures outlined here can be applied to an expanded dataset on microbialite characteristics in order to determine properties associated with microbialite-containing environments. [ABSTRACT FROM AUTHOR]

The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the physical ocean model NEMO and the BFM biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach. [ABSTRACT FROM AUTHOR]

Mesoscale eddies play a major role in controlling ocean biogeochemistry. By impacting nutrient availability and water column ventilation, they are of critical importance for oceanic primary production. In the eastern tropical South Pacific Ocean off Peru, where a large and persistent oxygen deficient zone is present, mesoscale processes have been reported to occur frequently. However, investigations on their biological activity are mostly based on model simulations, and direct measurements of carbon and dinitrogen (N2) fixation are scarce. We examined an open ocean cyclonic eddy and two anticyclonic mode water eddies: a coastal one and an open ocean one in the waters off Peru along a section at 16° S in austral summer 2012. Molecular data and bioassay incubations point towards a difference between the active diazotrophic communities present in the cyclonic eddy and the anticyclonic mode water eddies. In the cyclonic eddy, highest rates of N2 fixation were measured in surface waters but no N2 fixation signal was detected at intermediate water depths. In contrast, both anticyclonic mode water eddies showed pronounced maxima in N2 fixation below the euphotic zone as evidenced by rate measurements and geochemical data. N2 fixation and carbon (C) fixation were higher in the young coastal mode water eddy compared to the older offshore mode water eddy. A co-occurrence between N2 fixation and biogenic N2, an indicator for N loss, indicated a link between N loss and N2 fixation in the mode water eddies, which was not observed for the cyclonic eddy. The comparison of two consecutive surveys of the coastal mode water eddy in November and December 2012 revealed also a reduction of N2 and C fixation at intermediate depths along with a reduction in chlorophyll by half, mirroring an aging effect in this eddy. Our data indicate an important role for anticyclonic mode water eddies in stimulating N2 fixation and thus supplying N offshore. [ABSTRACT FROM AUTHOR]

Biotic and abiotic factors influence the accumulation of organic carbon (Corg) in seagrass ecosystems. We surveyed Posidonia sinuosa meadows growing in different water depths to assess the variability in the sources, stocks and accumulation rates of Corg. We show that over the last 500 years, P. sinuosa meadows closer to the upper limit of distribution (at 2-4m depth) accumulated 3 to 4-fold higher Corg stocks (averaging 6.3 kgCorg m-2) at 3 to 4-fold higher rates (12.8 gCorg m-2 yr-1) compared to meadows closer to the deep limits of distribution (at 6-8m depth; 1.8 kgCorg m-2 and 3.6 gCorg m-2 yr-1). In shallower meadows, Corg stores were mostly derived from sea-grass detritus (88% in average) compared to meadows closer to the deep limit of distribution (45%on average). Also, sediment accumulation rates and fine-grained sediment content (< 0.125 mm) in shallower meadows (2.0mmyr-1 and 9%, respectively) were approximately 2-fold higher than in deeper meadows (1.2mmyr-1 and 5%, respectively). The Corg stocks and accumulation rates accumulated over the last 500 years in bare sediments (0.6 kgCorg m-2 and 1.2 gCorg m-2 yr-1) were 3 to 11-fold lower than in P. sinuosa meadows, while fine-grained sediment content (1%) and seagrass detritus contribution to the Corg pool (20%) were 8 and 3-fold lower than in Posidonia meadows, respectively. The patterns found support the hypotheses that Corg storage in seagrass soils is influenced by interactions of biological (e.g. meadow productivity, cover and density), chemical (e.g. recalcitrance of Corg stocks) and physical (e.g. hydrodynamic energy and sediment accumulation rates) factors within the meadow. We conclude that there is a need to improve global estimates of seagrass carbon storage accounting for biogeochemical factors driving variability within habitats. [ABSTRACT FROM AUTHOR]

We analysed mooring and ship-based hydrographic and biogeochemical data obtained from a Hope Valley biological hotspot in the southern Chukchi Sea. The moorings were deployed from 16 July 2012 to 19 July 2014, and data were captured during spring and fall blooms with high chlorophyll a concentrations. Turbidity increased and dissolved oxygen decreased in the bottom water at the mooring site before the fall bloom, suggesting an accumulation of particulate organic matter and its decomposition (nutrient regeneration) at the bottom. This event may have been a trigger for the fall bloom at this site. The bloom was maintained for 1 month in 2012 and for 2 months in 2013. The maintenance mechanism for the fall bloom was also studied by hydrographic and biogeochemical surveys in late summer to fall 2012 and 2013. Nutrient-rich water from the Bering Sea supplied nutrients to Hope Valley, although a reduction in nutrients may have occurred in 2012 by mixing of lower-nutrient water that would have remained on the Chukchi Sea shelf during the spring and fall blooms. In addition, nutrient regener ation at the bottom of Hope Valley could have increased nutrient concentrations and explained 60% of its nutrient content in fall 2012. The high nutrient content with the dome-like structure of the bottom water may have maintained the high primary productivity at this site during the fall bloom. Primary productivity was 0.3 in September 2012 and 1.6 gCm-2 d-1 in September 2013. The lower productivity in 2012 was related to strong stratification caused by the high fraction of surface sea ice meltwater. [ABSTRACT FROM AUTHOR]

Diagenetic processes are important drivers of water column biogeochemistry in coastal areas. For example, sediment oxygen consumption can be a significant contributor to oxygen depletion in hypoxic systems and sediment-water nutrient fluxes support primary productivity in the overlying water column. Moreover, non-linearities develop between bottom water conditions and sediment-water fluxes due to loss of oxygendependent processes in the sediment as oxygen becomes depleted in bottom waters. Yet, sediment-water fluxes of chemical species are often parameterized crudely in coupled physical-biogeochemical models, using simple linear parameterizations that are only poorly constrained by observations. Diagenetic models that represent sediment biogeochemistry are available, but rarely are coupled to water column biogeochemical models because they are computationally expensive. Here, we apply a method that efficiently parameterizes sediment-water fluxes by combining in situ measurements, a steady state diagenetic model and a parameter optimization method. We apply this method to the Louisiana Shelf where high primary production, stimulated by excessive nutrient loads from the Mississippi-Atchafalaya River system, promotes the development of hypoxic bottom waters in summer. The parameterized sediment-water fluxes represent non-linear feedbacks between water column and sediment processes at low bottom water oxygen concentrations, which may persist for long periods (weeks to months) in hypoxic systems such as the Louisiana Shelf. This method can be applied to other systems and is particularly relevant for shallow coastal and estuarine waters where the interaction between sediment and water column is strong and hypoxia is prone to occur due to land-based nutrient loads. [ABSTRACT FROM AUTHOR]

First results of a coupled modeling and forecasting system for the pelagic fisheries are being presented. The system consists currently of three mathematically fundamentally different model subsystems: POLCOMS-ERSEM providing the physical- biogeochemical environment implemented in the domain of the North-West European shelf and the SPAM model which describes sandeel stocks in the North Sea. The third component, the SLAM model, connects POLCOMS-ERSEM and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and lower trophic levels to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the base of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeels stocks are currently exploited close to the maximum sustainable yield, but large uncertainty is associated with de20 termining stock maximum sustainable yield due to stock eigen dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2-6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable. [ABSTRACT FROM AUTHOR]

Podzol-ferralsol soil systems cover great areas in Amazonia and in other equatorial regions, they are an end-member of old equatorial landscape evolution, are frequently associated with kaolin deposits and store and export large amounts of carbon. Their biogeochemistry was usually inferred from soil mineralogy and from spring or river water properties. This paper presents a database for groundwaters sampled in situ in a typical podzol-ferralsol soil catena from the Alto Rio Negro region, Brazil; the sampling periods allowed to sample under high- and low-level water-table conditions. The compositions of the groundwaters percolating the soil system are consistent with the currently observed mineral and organic paragenesis. The acidity and the site density of the dissolved organic matter (DOM) produced and circulating in the podzol white sand horizons are similar to what was observed in acid podzolic temperate zone. The aggressiveness of the white sand groundwater with regard to secondary minerals favours the podzol development at the expense of the ferralsolic or kaolin material. Some DOM is able to percolate in depth through clayey material with concentrations up to 9.7mgCl-1 (4.0 on average). This DOM is characterized by high site densities indicating a large proportion of small carboxylic acids. In the deep kaolin and in the ferralsolic horizons, the Si and Al content of the groundwater is controlled by gibbsite and kaolinite precipitation/dissolution and by quartz dissolution. The mobility of Fe, mainly transported as Fe2+, is sensitive to small variations in EH. The bleaching of the deep kaolin at the upper part of the slopes is favoured by the high content of small carboxylic compounds and by the redox conditions of the solutions issuing from the podzolic horizons. The transfer of Al and Fe result in the precipitation of Al-nodules in slope horizons and of Fe-oxides in the upper downslope horizon. It can be inferred that thick bleached kaolin are likely everywhere presently active giant podzols are close to a slope gradient sufficient to allow deep percolation of groundwater. [ABSTRACT FROM AUTHOR]

This paper is an attempt to generalize the nitrogen isotope information of the molecules that make up the cell from our point of view. Nitrogen in the cell exists as 20 proteinaceous amino acids, nucleobases, hemes, chlorophylls, and others, and their composition is similar among organisms. Based on a physiologically simple autonomous system that maintains a balance between inputs and outputs, it is theoretically predicted that 15N is distributed to each cellular compound with a certain regularity, and thus a specific relationship in nitrogen isotopic ratios among compounds. Previous studies essentially confirm this. The nitrogen isotopic ratio of compound i constituting the cell can be generalized as δ15Ni = δ15Nplant + Δi (TP − 1) + γi, where TP represents the trophic position, and Δi and γi are the trophic discrimination factor and the intracellular 15N distribution of compound i, respectively. Knowing reliable values of Δi and γi will help us to better understand nitrogen dynamics in the biosphere and advance our understanding of the picture of the Earth's environment through biogeochemistry. [ABSTRACT FROM AUTHOR]

Databases of 3D paleoclimate model simulations are increasingly used within global biogeochemical models for the Phanerozoic Eon. This improves the accuracy of the surface processes within the biogeochemical models, but the approach is limited by the availability of large numbers of paleoclimate simulations at different p CO 2 levels and for different continental configurations. In this paper we apply the Frame Interpolation for Large Motion (FILM) deep learning method to a set of Phanerozoic paleoclimate model simulations to upscale their time resolution from one model run every ∼25 million years to one model run every 1 million years (Myr). Testing the method on a 5 Myr time-resolution set of continental configurations and paleoclimates confirms the accuracy of our approach when reconstructing intermediate frames from configurations separated by up to 40 Myr. We then apply the method to upscale the paleoclimate data structure in the SCION climate-biogeochemical model. The interpolated surface temperature and runoff are reasonable and present a logical progression between the original key frames. When updated to use the high-time-resolution climate data structure, the SCION model predicts climate shifts that were not present in the original model outputs due to its previous use of widely spaced datasets and simple linear interpolation. We conclude that a time resolution of ∼10 Myr in Phanerozoic paleoclimate simulations is likely sufficient for investigating the long-term carbon cycle and that deep learning methods may be critical in attaining this time resolution at reasonable computational expense, as well as for developing new fully continuous methods in which 3D continental processes are able to translate over a moving continental surface in deep time. However, the efficacy of deep learning methods in interpolating runoff data, compared to that of paleogeography and temperature, is diminished by the heterogeneous distribution of runoff. Consequently, interpolated climates must be confirmed by running a paleoclimate model if scientific conclusions are to be based directly on them. [ABSTRACT FROM AUTHOR]

The paper provides a basin assessment of the spatial distribution of ocean alkalinity in the Mediterranean Sea. The assessment is made using a 3-D transport-biogeochemical-carbonate model to integrate the available experimental findings, which also constrains model output. The results indicate that the Mediterranean Sea shows alkalinity values that are much higher than those observed in the Atlantic Ocean on a basin-wide scale. A marked west-to-east surface gradient of alkalinity is reproduced as a response to the terrestrial discharges, the mixing effect with the Atlantic water entering from the Gibraltar Strait and the Black Sea water from Dardanelles, and the surface flux of evaporation minus precipitation. Dense water production in marginal seas (Adriatic and Aegean Seas), where alkaline inputs are relevant, and the Mediterranean thermohaline circulation sustains the west-to-east gradient along the entire water column. In the surface layers, alkalinity has a relevant seasonal cycle (up to 40 µmol kg-1) that is driven both by physical and biological processes. A comparison of alkalinity vs. salinity indicates that different regions present different relationships. In regions of freshwater influence, the two measures are negatively correlated due to riverine alkalinity input, whereas they are positively correlated in open seas. Alkalinity always is much higher than in the Atlantic waters, which might indicate a higher than usual buffering capacity towards ocean acidification, even at high concentrations of dissolved inorganic carbon. [ABSTRACT FROM AUTHOR]

The Michaelis-Menten kinetics and the reverse Michaelis-Menten kinetics are two popular mathematical formulations used in many land biogeochemical models to describe how microbes and plants would respond to changes in substrate abundance. However, the criteria of when to use which of the two are often ambiguous. Here I show that these two kinetics are special approximations to the Equilibrium Chemistry Approximation kinetics, which is the first order approximation to the quadratic kinetics that solves the equation of enzyme-substrate complex exactly for a single enzyme single substrate biogeochemical reaction with the law of mass action and the assumption of quasi-steady-state for the enzyme-substrate complex and that the product genesis from enzyme-substrate complex is much slower than the equilibration between enzyme-substrate complexes, substrates and enzymes. In particular, I showed that the derivation of the Michaelis-Menten kinetics does not consider the mass balance constraint of the substrate, and the reverse Michaelis-Menten kinetics does not consider the mass balance constraint of the enzyme, whereas both of these constraints are taken into account in the Equilibrium Chemistry Approximation kinetics. By benchmarking against predictions from the quadratic kinetics for a wide range of substrate and enzyme concentrations, the Michaelis-Menten kinetics was found to persistently under-predict the normalized sensitivity ∂ ln v / ∂ ln k2+ of the reaction velocity v with respect to the maximum product genesis rate k2+, persistently over-predict the normalized sensitivity ∂ ln v / ∂ ln k1+ of v with respect to the intrinsic substrate affinity k1+, persistently over-predict the normalized sensitivity ∂ ln v / ∂ ln [ E ]T of v with respect the total enzyme concentration [ E ]T and persistently under-predict the normalized sensitivity ∂ ln v / ∂ ln [ S ]T of v with respect to the total substrate concentration [ S ]T. Meanwhile, the reverse Michaelis-Menten kinetics persistently under-predicts ∂ ln v / ∂ ln k2+ and ∂ ln v / ∂ ln [ E ]T, and persistently over-predicts ∂ ln v / ∂ ln k1+ and ∂ ln v / ∂ ln [ S ]T. In contrast, the Equilibrium Chemistry Approximation kinetics always gives consistent predictions of ∂ ln v / ∂ ln k2+, ∂ ln v / ∂ ln k1+, ∂ ln v / ∂ ln [ E ]T and ∂ ln v / ∂ ln [ S ]T. Since the Equilibrium Chemistry Approximation kinetics includes the advantages from both the Michaelis-Menten kinetics and the reverse Michaelis-Menten kinetics and it is applicable for almost the whole range of substrate and enzyme abundances, soil biogeochemical modelers therefore no longer need to choose when to use the Michaelis-Menten kinetics or the reverse Michaelis-Menten kinetics. I expect removing this choice ambiguity will make it easier to formulate more robust and consistent land biogeochemical models. [ABSTRACT FROM AUTHOR]

Respiration in frozen soils is limited to thawed substrate within the thin water films surrounding soil particles. As temperatures decrease and the films become thinner, the available substrate also decreases, with respiration effectively ceasing at -8 °C. Traditional exponential scaling factors to model this effect do not account for substrate availability and do not work at the century to millennial time scales required to model the fate of the nearly 1700 Gt of carbon in permafrost regions. The exponential scaling factor produces a false, continuous loss of simulated permafrost carbon in the 20th century and biases in estimates of potential emissions as permafrost thaws in the future. Here we describe a new frozen biogeochemistry parameterization that separates the simulated carbon into frozen and thawed pools to represent the effects of substrate availability. We parameterized the liquid water fraction as a function of temperature based on observations and use this to transfer carbon between frozen pools and thawed carbon in the thin water films. The simulated volumetric water content (VWC) as a function of temperature is consistent with observed values and the simulated respiration fluxes as a function of temperature are consistent with results from incubation experiments. The amount of organic matter was the single largest influence on simulated VWC and respiration fluxes. Future versions of the parameterization should account for additional, non-linear effects of substrate diffusion in thin water films on simulated respiration. Controlling respiration in frozen soils based on substrate availability allows us to maintain a realistic permafrost carbon pool by eliminating the continuous loss caused by the original exponential scaling factors. The frozen biogeochemistry parameterization is a useful way to represent the effects of substrate availability on soil respiration in model applications that focus on century to millennial time scales in permafrost regions. [ABSTRACT FROM AUTHOR]

Microbial metabolism plays a key role in regulating the biogeochemical cycle of forest ecosystems, but the mechanisms driving microbial growth are not well understood. Here, we synthesized 689 measurements on soil microbial biomass carbon (Cmic) and nitrogen (Nmic) and related parameters from 207 independent studies published during the past 15 years across China's forest ecosystems. Our objectives were to (1) examine patterns in Cmic, Nmic, and microbial quotient (i.e., Cmic /Csoil and Nmic =Nsoil rates) by climate zones and management regimes for these forests; and (2) identify the factors driving the variability in the Cmic, Nmic, and microbial quotient. There was a large variability in Cmic (390.2mg kg-1), Nmic (60.1mg kg-1), Cmic :Nmic ratio (8.25), Cmic =Csoil rate (1.92%), and Nmic =Nsoil rate (3.43%) across China's forests, with coeffcients of variation varying from 61.2 to 95.6%. The natural forests had significantly greater Cmic and Nmic than the planted forests, but had less Cmic :Nmic ratio and Cmic =Csoil rate. Soil resources and climate together explained 24.4-40.7% of these variations. The Cmic :Nmic ratio declined slightly with the Csoil :Nsoil ratio, and changed with latitude, mean annual temperature and precipitation, suggesting a plastic homeostasis of microbial carbon-nitrogen stoichiometry. The Cmic =Csoil and Nmic =Nsoil rates were responsive to soil resources and climate differently, suggesting that soil microbial assimilation of carbon and nitrogen be regulated by different mechanisms. We conclude that soil resources and climate jointly drive microbial growth and metabolism, and also emphasize the necessity of appropriate procedures for data compilation and standardization in cross-study syntheses. [ABSTRACT FROM AUTHOR]

In a changing climate, marine pelagic biogeochemistry may modulate the atmospheric concentrations of climate-relevant species such as CO2 and N2O. To-date, projections rely on earth system models featuring simple pelagic biogeochemical model components, embedded into 3-D-ocean circulation models. Typically, the nucleus of these biogeochemical components are ecosystem models (i.e., a set of partial differential equations) which describe the interaction between nutrients, phytoplankton, zooplankton, and sinking detritus. Most of these models rely on the hyperbolic Michaelis-Menten (MM) formulation which specifies the limiting effect of light and nutrients on carbon assimilation by autotrophic phytoplankton. The respective MM constants, along with other model parameters, are usually tuned by trial-and-error exercises where the parameters are changed until a "reasonable" similarity with observed standing stocks is achieved. Here, we explore with twin experiments (or synthetic "observations") the demands on observations that allow for a more objective estimation of model parameters. We start with parameter retrieval experiments based on "perfect" (synthetic) observations which we, step by step, distort to approach realistic conditions and finally confirm our findings with real-world observations. In summary, we find that MM constants are especially hard to constrain because even modest noise (10%) inherent to observations may hinder the parameter retrieval already. This is of concern since the MM parameters are key to the model's sensitivity to anticipated changes of the external conditions. Further, we illustrate problems associated with parameter estimation based on sparse observations which reveals (additional) parameter dependencies. Somewhat counter to intuition we find, that more observational data can degrade the ability to constrain certain parameters. [ABSTRACT FROM AUTHOR]

Iron availability in the Southern Ocean controls phytoplankton growth, community composition and the uptake of atmospheric CO2 by the biological pump. The KEOPS-2 experiment took place around the Kerguelen plateau in the Indian sector of the Southern Ocean, a region naturally fertilised with iron at the scale of hundreds to thousands of square kilometres, producing a mosaic of spring blooms which showed distinct biological and biogeochemical responses to fertilisation. This paper presents biogeochemical iron budgets (incorporating vertical and lateral supply, internal cycling, and sinks) for three contrasting sites: an upstream high-nutrient low-chlorophyll reference, over the plateau, and in the offshore plume east of Kerguelen Island. These budgets show that distinct regional environments driven by complex circulation and transport pathways are responsible for differences in the mode and strength of iron supply, with vertical supply dominant on the plateau and lateral supply dominant in the plume. Iron supply from "new" sources to surface waters of the plume was double that above the plateau and 20 times greater than at the reference site, whilst iron demand (measured by cellular uptake) in the plume was similar to the plateau but 40 times greater than the reference. "Recycled" iron supply by bacterial regeneration and zooplankton grazing was a relative minor component at all sites (< 8% of "new" supply), in contrast to earlier findings from other biogeochemical iron budgets in the Southern Ocean. Over the plateau, a particulate iron dissolution term of 2.5% was invoked to balance the budget; this approximately doubled the standing stock of dissolved iron in the mixed layer. The exchange of iron between dissolved, biogenic and lithogenic particulate pools was highly dynamic in time and space, resulting in a decoupling of iron supply and carbon export and, importantly, controlling the efficiency of fertilisation. [ABSTRACT FROM AUTHOR]

The planktonic and biogeochemical dynamics of the Arctic shelves exhibit a strong variability in response to Arctic warming. In this study, in order to elucidate on the processes regulating the production of phytoplankton (PP) and bacterioplankton (BP) and their interactions, we employ a biogeochemical model coupled to a pan-Arctic ocean-sea ice model (MITgcm) to explicitly simulate and quantify the contribution of usable dissolved organic nitrogen (DON) drained by the major circum-Arctic rivers on PP and BP in a scenario of melting sea ice (1998-2011). Model simulations suggest that on average between 1998 and 2011, the removal of usable RDON by bacterioplankton is responsible of a ~ 26% increase of the annual BP for the whole Arctic Ocean. With respect to total PP, the model simulates an increase of ~ 8 % on an annual basis and of ~ 18% in summer. Recycled ammonium is responsible for the PP increase. The recycling of RDON by bacterioplankton promotes higher BP and PP but there is no significant temporal trend in the BP: PP ratio within the ice-free shelves over the 1998-2011 period. This suggests no significant evolution in the balance between autotrophy and heterotrophy in the last decade with a constant annual flux of RDON into the coastal ocean although changes in RDON supply and further reduction in sea ice cover could potentially alter this delicate balance. [ABSTRACT FROM AUTHOR]

Trends and seasonality analysis since 1980 and longitudinal distribution from headwaters to estuary of algal pigment, nitrate and phosphate were investigated in the eutrophic Loire River. The continuous decline of phosphate concentrations recorded since 1991 both in the main river and in the tributaries led to a significant reduction in algal biomass across the whole river system. While eutrophication remained lower in the main tributaries than in the Loire itself, they were found to contribute up to 45 % to the total nutrient load of the main river. The seasonality analysis revealed that the river has always been under P limitation, explaining why reducing P inputs led to decreasing eutrophication in the whole Loire basin. The decline of seasonal amplitudes of algal pigments reduced the seasonal amplitude of phosphate and of daily variations of dissolved oxygen and pH but did not significantly affect the seasonal amplitude of nitrate. Thus, algal uptake responsibility on the summer nitrate loss seemed to be declining, questioning the exact role played by denitrification, terrestrial vegetation and fixed aquatic vegetation on the nitrogen cycle. [ABSTRACT FROM AUTHOR]

This study aims to improve understanding of carbon cycling in the Buor-Khaya Bay (BKB) by studying the inter-annual, seasonal, and meso-scale variability of carbon stocks and related hydrological and biogeochemical parameters in the water, as well as factors controlling carbon dioxide (CO2) emission. Here we present data sets obtained on summer cruises and winter expeditions during 12 yr of investigation. Based on data analysis, we suggest that in the heterotrophic BKB area, coastal erosion and river discharge serve as predominant drivers of the organic carbon (OC) cycle, determining OC input and transformation, dynamics of nutrients, carbon stocks in the water column, and atmospheric emissions of CO2. [ABSTRACT FROM AUTHOR]

Recent advances in satellite retrieval methodology now allow estimation of particular organic carbon (POC) concentration in ocean surface waters directly from satellitebased optical data. Because of the good coverage these data reveal small-scale spatial and temporal concentration gradients and document the evolution of surface water POC as well as the underlying driving biogeochemical processes throughout the seasons. Water column nutrient data also reveal biogeochemical activity. However, because of the scarcity of data the deduction of temporal changes of particle production and export are not possible in most parts of the ocean. Here we present first results from a new study combining both data streams thereby exploiting the high spatiotemporal resolution of surface POC concentrations from satellite optical sensors with water column nutrient data having sparser coverage but providing information throughout the entire water column. We use a medium-resolution global model with steadystate 3-D circulation that has been optimized by fitting to a large number of hydro graphic parameters and tracers, including CFCs and natural radiocarbon. Production and export of POC is allowed to vary monthly, and the magnitudes of the monthly export fluxes are determined by fitting the model to satellite POC data as well as water column nutrient data using the adjoint method. Two cases have been investigated: (1) the production rate of POC is set to be proportional to export production EP and the seasonal changes are assumed sinusoidal (meridionally varying amplitude and phase) and (2) the POC production rate is linked to primary production rates (literature). Both cases were run with the same initial state and model settings, and show total cost function decreases of 12 and 95 %, respectively. The POC misfit term alone decreased by 75 and 99 %. The integrated annual global POC exports of the two cases are 9.9 GtCyr-1 and 12.3GtCyr-1, respectively. Overall, the remaining POC and phosphate misfits of both solutions are considered too large and the difference fields still exhibit significant systematic geographical patterns. This indicates that the present model runs are too simplistic and do not fully explain the data. Further, more refined model setups are needed. [ABSTRACT FROM AUTHOR]

Present and future levels of primary production (PP) in the Arctic Ocean (AO) depend on nutrient inputs to the photic zone via vertical mixing, upwelling and external sources. In this regard, the importance of horizontal river supply relative to oceanic processes is poorly constrained at the panarctic scale. We compiled extensive historical (1954-2012) data on discharge and nutrient concentrations to estimate fluxes of nitrate, soluble reactive phosphate (SRP), silicate, DOC, DON, PON and POC from 9 large Arctic rivers and assess their potential impact on the biogeochemistry of shelf waters. Several key points can be emphasized from this analysis. The contribution of riverine nitrate to new PP (PPnew) is very small at the regional scale (<1% to ca. 6.2 %) and negligible at the panarctic scale (ca. 0.73%), in agreement with recent studies. By consuming all this nitrate, oceanic phytoplankton would be able to use only ca. 13.5%and 6.6-17.5% of the river supply of silicate at the panarctic and regional scales, respectively. Corresponding figures for SRP are ca. 27.8% and 18.4-44.4 %. On the Beaufort and Bering shelves, riverine SRP cannot fulfil phytoplankton requirements. On a seasonal basis, the removal of riverine nitrate, silicate and SRP would be the highest in spring and not in summer when AO shelf waters are nitrogen-limited. Riverine DON is potentially an important nitrogen source for the planktonic ecosystem in summer, when ammonium supplied through the photoammonification of refractory DON (ca. 3.9x109 mol N) may exceed the combined riverine supply of nitrate and ammonium (ca. 2.9x109 mol N). Nevertheless, overall nitrogen limitation of AO phytoplankton is expected to persist even when projected increases of riverine DON and nitrate supply are taken into account. This analysis underscores the need to better contrast oceanic nutrient supply processes with the composition and fate of changing riverine nutrient deliveries in future scenarios of plankton community structure, function and production in the coastal AO. [ABSTRACT FROM AUTHOR]

In High-Nutrient-Low-Chlorophyll regions, phytoplankton growth is limited by the availability of water soluble iron. Volcanic ash can carry bio-available iron salts on its surface, which may be formed during volcanic eruptions by surface reactions between volcanic gases and ash. The eruption of Kasatochi volcano in August 2008 led to ash deposition into the iron-limited NE Pacific Ocean releasing iron upon contact of volcanic ash with seawater. Atmospheric and oceanic conditions were favourable to generate a massive phytoplankton bloom, which was observed by satellite instruments and in-situ measurements. Here we investigate this event with a regional scale ocean biogeochemical model system to illuminate the ocean response to iron fertilisation by volcanic ash. The results indicate that the added iron triggered an additional phytoplankton bloom in the summer of 2008, which produced a drawdown of carbon dioxide in surface seawater. The simulated development is in good agreement with the available observations. [ABSTRACT FROM AUTHOR]

The marine nitrogen (N) inventory is controlled by the interplay of nitrogen loss processes, here referred to as denitrification, and nitrogen source processes, primarily nitrogen fixation. The apparent stability of the marine N inventory on time scales longer than the estimated N residence time, suggests some intimate balance between N sinks and sources. Such a balance may be perceived easier to achieve when N sinks and sources occur in close spatial proximity, and some studies have interpreted observational evidence for such a proximity as indication for a stabilizing feedback processes. Using a biogeochemical ocean circulation model, we here show instead that a close spatial association of N2 fixation and denitrification can, in fact, trigger destabilizing feedbacks on the N inventory and, because of stoichiometric constrains, lead to net N losses. Contrary to current notion, a balanced N inventory requires a regional separation of N sources and sinks. This can be brought about by factors that reduce the growth of diazotrophs, such as iron, or by factors that affect the fate of the fixed nitrogen remineralization, such as dissolved organic matter dynamics. In light of our findings we suggest that spatial arrangements of N sinks and sources have to be accounted for in addition to individual rate estimates for reconstructing past, evaluating present and predicting future marine N inventory imbalances. [ABSTRACT FROM AUTHOR]