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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. [ABSTRACT FROM AUTHOR]

Sulphate (SO4) abundance in the earth's crust contributes largely to industrial wastewater contamination lowering the pH, which exuberates the dissolution of metals forming acidic drainages. Biological sulphate reduction as a remediation process can be affected by factors such as pH, temperature and high sulphide concentrations. In this study, sulphate-reducing bacterial community enriched from mine wastewaters was applied in semi-automated bio-reactors to assess the effects of these factors on microbial sulphate reduction capacities. Low pH (3.5) and temperature (10°C) were observed to promote the toxicity of sulphur-reduced species on the consortium while mesophilic temperature (25°C) and near neutral pH (6.2) were observed to induce optimum SO4 reduction attaining a maximum of 95% SO4 reduction. Obtained SO4 reduction dynamics data was then applied in formulating a unique non-competitive inhibition equation that models biogeochemical events during SO4 reduction under varied pH and temperature conditions and predicts the efficacy of a bioremediation system. [ABSTRACT FROM AUTHOR]

The EU Habitat Directive adopted in 1992, requires member states of the European Union to protect species and habitats considered to be of 'Community Interest' and listed in annexes to the directive. The appropriate environmental assessment of "plans and projects" is an important part of the conservation process. Despite several amendments and guidelines supporting the implementation of the Habitat Directive, science based operational procedures, indicators, and impact criteria for assessing potential negative impacts on marine Natura 2000 areas are still lacking. The lack of a generic and operational methodology complicates the management of plans and projects with potential impact on marine Natura 2000 areas. In this study, generic methods for the assessment of marine aquaculture in the inner Danish waters in relation to Natura 2000 areas was developed and applied for assessment of nine existing marine fin fish farms, in accordance with the latest methodological guidance on the provisions of Article 6(3) and (4) of the Habitat Directive. The applied methodology is based on high resolution 3D hydrodynamic- and ecosystem modelling (MIKE by DHI), that describes the dynamical physical, chemical, and biogeochemical processes and changes of marine ecosystems in time and space. To our knowledge, this is the first study that formulates operational biological quality elements, key indicators, concrete and generic impact criteria, and assessment procedures for operational assessment across several distinct marine habitat types. The method represents a generic, operational, transparent, and science-based assessment tool, that simplifies management, and is widely applicable for quantification of environmental impacts from various marine activities and eutrophication related pressures across geographical zones and different marine habitat types in marine Natura 2000 areas. • Science-based method for assessment of impact on habitats in Natura (2000) areas. • The method is applicable for assessment of impacts from various pressures. • The method is applicable for assessment of impacts across geographical zones. • The study defines biological quality elements, indicators, and impact criteria. • The study defines procedures for assessment of several distinct marine habitats. [ABSTRACT FROM AUTHOR]

Rare earth elements (REEs) are used as powerful proxies for a variety of oceanic processes. The understanding of their biogeochemical behaviour in the marine environment is therefore essential. While the influence of OM-cycling on REE patterns in seawater is considered as insignificant, it has been shown that algae and bacteria provide good sorption surfaces for REEs and that components of the dissolved OM pool are able to complex REEs, thus potentially altering their behaviour. To investigate the impact of bio-associated processes on REEs in the bio-productive marine environment, we conducted an indoor mesocosm experiment that mimicked a phytoplankton spring bloom in the neritic coastal North Sea. The incubation period of 38 days covered two distinct phytoplankton bloom phases (diatoms followed by Phaeocystis sp.) and an interjacent bacterioplankton maximum. All dissolved REEs (dREEs) except samarium showed similar temporal concentration patterns, which were closely connected to the bloom succession. The concentration patterns were shaped by the ‘phytoplankton-shuttle’, which summarizes adsorption processes on phytoplankton-derived particulate OM (POM) and resulted in decreasing dREE concentrations alongside chlorophyll-a and POM maxima. The ‘heterotrophic-shuttle’ resulted in increasing dREE concentrations likely linked to heterotrophically mediated regeneration of POM and associated desorption processes. The effect of these processes on dREEs resulted in enhanced fractionation of light REEs (LREEs) relative to heavy REEs (HREEs) during adsorption processes and decreased fractionation as a result of desorption. At times of high dissolved organic carbon (DOC) concentrations, we observed a stabilization of especially dHREEs likely in organic complexes. To test the potential influence of DOC on dREEs, we used a PHREEQC model approach that revealed dREE complexation with components of the DOC pool and an increase in complexation with atomic mass of the REEs. That is, at high DOC concentrations OM-dREE complexation leads to an effective and preferential buffering of dHREE against adsorption. Our findings reveal that OM-cycling influences concentration patterns of dREEs via ad- and desorption processes as well as organic complexation with parts of the OM pool, suggesting these processes can have a significant impact on dREE concentrations in the natural marine environment under high OM conditions.

The Arctic is undergoing rapid changes in climate, altering the status and functioning of high-latitude soils and permafrost. The vast majority of studies on Arctic soils and permafrost are conducted during the summer period due to ease of accessibility, sampling, instrument operation, and making measurements, in comparison to during winter and transition seasons. However, there is increasing evidence that microbial activity continues in Arctic soils outside of the summer period. Moreover, it is becoming clear that understanding the seasonal dynamics of Arctic soils is of critical importance, especially considering that the under-studied winter is the period that is most sensitive to climate warming. Soil biogeochemical models have advanced our understanding of the functioning and fate of soils in the Arctic, however it is vital that seasonality in biotic and abiotic processes is accurately captured in these models. Here we synthesize recent investigations and observations of the year-round functioning of Arctic soils, review soil biogeochemical modelling frameworks, and highlight certain processes and behaviors that are shaped by seasonality and thus warrant particular consideration within these models. More attention to seasonal processes will be critical to improving datasets and soil biogeochemical models that can be used to understand the year-round functioning of soils and the fate of the soil carbon reservoir in the Arctic. [ABSTRACT FROM AUTHOR]

Hydrothermal iron supply contributes to the Southern Ocean carbon cycle via the regulation of regional export production. However, as hydrothermal iron input estimates are coupled to helium, which are uncertain depending on whether helium inputs are based on ridge spreading rates or inverse modelling, questions remain regarding the magnitude of the export production impacts. A particular challenge is the limited observations of dissolved iron (dFe) supply from the abyssal Southern Ocean ridge system to directly assess different hydrothermal iron supply scenarios. We combine ocean biogeochemical modelling with new observations of dFe from the abyssal Southern Ocean to assess the impact of hydrothermal iron supply estimated from either ridge spreading rate or inverse helium modelling on Southern Ocean export production. The hydrothermal contribution to dFe in the upper 250 m reduces 4–5 fold when supply is based on inverse modelling, relative to those based on spreading rate, translating into a 36–73% reduction in the impact of hydrothermal iron on export production. However, only the spreading rate input scheme reproduces observed dFe anomalies >1 nM around the circum-Antarctic ridge. The model correlation with observations drops 3 fold under the inverse modelling input scheme. The best dFe scenario has a residence time for hydrothermal iron that is between 21 and 34 years, highlighting the importance of rapid physical mixing to surface waters. Overall, because of its short residence time, hydrothermal Fe supplied locally by circum-Antarctic ridges is most important to the Southern Ocean carbon cycle and our results highlight decoupling between hydrothermal iron and helium supply.

Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia's GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC30) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC30 with no overall bias, and showed good performance at the LU level with no significant (p < 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC30 and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting. [ABSTRACT FROM AUTHOR]

Ocean Alkalinity Enhancement (OAE) simultaneously mitigates atmospheric concentrations of CO2 and ocean acidification; however, no previous studies have investigated the response of the non-linear marine carbonate system sensitivity to alkalinity enhancement on regional scales. We hypothesise that regional implementations of OAE can sequester more atmospheric CO2 than a global implementation. To address this, we investigate physical regimes and alkalinity sensitivity as drivers of the carbon-uptake potential response to global and different regional simulations of OAE. In this idealised ocean-only set-up, total alkalinity is enhanced at a rate of 0.25 Pmol a-1 in 75-year simulations using the Max Planck Institute Ocean Model coupled to the HAMburg Ocean Carbon Cycle model with pre-industrial atmospheric forcing. Alkalinity is enhanced globally and in eight regions: the Subpolar and Subtropical Atlantic and Pacific gyres, the Indian Ocean and the Southern Ocean. This study reveals that regional alkalinity enhancement has the capacity to exceed carbon uptake by global OAE. We find that 82–175 Pg more carbon is sequestered into the ocean when alkalinity is enhanced regionally and 156 PgC when enhanced globally, compared with the background-state. The Southern Ocean application is most efficient, sequestering 12% more carbon than the Global experiment despite OAE being applied across a surface area 40 times smaller. For the first time, we find that different carbon-uptake potentials are driven by the surface pattern of total alkalinity redistributed by physical regimes across areas of different carbon-uptake efficiencies. We also show that, while the marine carbonate system becomes less sensitive to alkalinity enhancement in all experiments globally, regional responses to enhanced alkalinity vary depending upon the background concentrations of dissolved inorganic carbon and total alkalinity. Furthermore, the Subpolar North Atlantic displays a previously unexpected alkalinity sensitivity increase in response to high total alkalinity concentrations.

The magnitude of the nitrogen (N) limitation of terrestrial carbon (C) storage over the 21st century is highly uncertain because of the complex interactions between the terrestrial C and N cycles. We use an ensemble approach to quantify and attribute process‐level uncertainty in C‐cycle projections by analysing a 30‐member ensemble representing published alternative representations of key N cycle processes (stoichiometry, biological nitrogen fixation (BNF) and ecosystem N losses) within the framework of one terrestrial biosphere model. Despite large differences in the simulated present‐day N cycle, primarily affecting simulated productivity north of 40°N, ensemble members generally conform with global C‐cycle benchmarks for present‐day conditions. Ensemble projections for two representative concentration pathways (RCP 2.6 and RCP 8.5) show that the increase in land C storage due to CO2 fertilization is reduced by 24 ± 15% due to N constraints, whereas terrestrial C losses associated with climate change are attenuated by 19 ± 20%. As a result, N cycling reduces projected land C uptake for the years 2006–2099 by 19% (37% decrease to 3% increase) for RCP 2.6, and by 21% (40% decrease to 9% increase) for RCP 8.5. Most of the ensemble spread results from uncertainty in temperate and boreal forests, and is dominated by uncertainty in BNF (10% decrease to 50% increase for RCP 2.6, 5% decrease to 100% increase for RCP 8.5). However, choices about the flexibility of ecosystem C:N ratios and processes controlling ecosystem N losses regionally also play important roles. The findings of this study demonstrate clearly the need for an ensemble approach to quantify likely future terrestrial C–N cycle trajectories. Present‐day C‐cycle observations only weakly constrain the future ensemble spread, highlighting the need for better observational constraints on large‐scale N cycling, and N cycle process responses to global change. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia’s GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC30) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC30 with no overall bias, and showed good performance at the LU level with no significant (p < 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC30 and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting.

The fate of microplastics (MP) in seawater is heavily influenced by the biota: the density of MP particles can be changed due to biofouling, which affects sinking, or MP can be digested by zooplankton and transferred into fecal pellets with increased sinking rate. We hypothesize that seasonal production and degradation of organic matter, and corresponding changes in the plankton ecosystem affect the MP capacity for transportation and burying in sediments in different seasons. This is simulated with a coupled hydrodynamical-biogeochemical model that provides a baseline scenario of the seasonal changes in the planktonic ecosystem and changes in the availability of particulate and dissolved organic matter. In this work, we use a biogeochemical model OxyDep that simulates seasonal changes of phytoplankton (PHY), zooplankton (HET), dissolved organic matter (DOM) and detritus (POM). A specifically designed MP module considers MP particles as free particles (MPfree), particles with biofouling (MPbiof), particles consumed by zooplankton (MPhet) and particles in detritus, including fecal pellets (MPdet). A 2D coupled benthic-pelagic vertical transport model 2DBP was applied to study the effect of seasonality on lateral transport of MP and its burying in the sediments. OxyDep and MP modules were coupled with 2DBP using Framework for Aquatic Biogeochemical Modelling (FABM). A depletion of MP from the surface water and acceleration of MP burying in summer period compared to the winter was simulated numerically. The calculations confirm the observations that the “biological pump” can be one of the important drivers controlling the quantity and the distribution of MP in the water column.

Assessments of the environmental impact of C-14 disposal often assume that C-14 is converted into gases that are able to migrate to the surface, where they pose a radiological risk. However, uncertainties, associated with the long-term release of C-14 from graphite and the evolution in the post-closure environment of a geological disposal facility (GDF), exist. In this paper, an integrated modelling framework has been developed to investigate these uncertainties. The modelling framework consists of a biogeochemical near field model which interfaces with a geosphere/biosphere model and it is verified by comparing the results to those obtained from other models. A sensitivity analysis discloses that a faster mid chain scission rate of stopped cellulose about four orders of magnitude assesses a twice higher effective dose. In another scenario, which is related to the control of microbial activity by pH and the availability of carbon dioxide to microbes, the effective dose is two orders of magnitude higher compared with a reference scenario. This modelling work illustrates also the importance of far field parameters, such as the rock permeability and the release area of gas pathway, to the assessment of effective dose. • A new integrated model was developed to assess the impact of C-14 release. • A biogeochemical near field code interfaces with a geo-biosphere far field model. • Microbial activity controlled by pH affects substantially the effective dose. • A faster mid chain scission rate of cellulose leads to a higher effective dose. • A higher effective dose is associated with a smaller release area in gas pathway. [ABSTRACT FROM AUTHOR]

Soil respiration is a crucial source of carbon dioxide (CO 2) in the atmosphere. The underlying processes involved are multifaceted, sequential chemical reactions associated with the conversion of soil organic carbon to CO 2. In this paper, we present a mechanistic, biogeochemical model to simulate soil CO 2 emissions considering the microbial and sequential chemical processes using the well-established hydrological model, Soil and Water Assessment Tool (SWAT) for the first time. The soil CO 2 emissions from multiple sequential soil chemical reactions were compared with the observed data at three sites in Canada. The results show that the modelled CO 2 emission rates are in good agreement with the observed data with performance statistics: PBIAS: 0.13%–23%; NSE: 0.27 to 0.62; RSR: 0.60 to 0.84; R2: 0.29 to 0.83. This approach could be used in future regional to global-scale models for simulating the soil CO 2 emission and hydrological processes. Image 1 • Modelling of soil organic matter (SOM) decomposition. • Soil chemical reactions modelling using microbial kinetics and thermodynamics. • Modelling of soil autotrophic respiration and soil heterotrophic respiration. • Modelling of soil CO 2 emissions using the soil and water assessment tool (SWAT). • Watershed-scale modelling of soil CO 2 emission using SWAT tool. [ABSTRACT FROM AUTHOR]

Biogeochemical models have the potential to provide insights into the key drivers of greenhouse gas (GHG) dynamics, and may be used in Tier 2 and 3 GHG emission reporting. Modelling nitrous oxide (N 2 O) emissions from agriculture, however, is still subject to large uncertainties. In the present study we analysed the performance of the three semi-mechanistic models, DailyDayCent (DayCent), DeNitrification-DeComposition (DNDC 9.4 and 9.5), and ECOSSE when simulating N 2 O fluxes from two different land uses (simulated grazing and spring barley) under a range of fertiliser types and application rates. Model performance was assessed using linear regression analysis, root mean square error (RMSE), and relative error. Monte Carlo analysis was carried out to assess the sensitivity of DayCent and ECOSSE to changes in the timing of management events. The results show high variability in model performance. The performance of each model was dependent on both site and treatment, with no model showing consistently good performance. When averaged across all sites and treatments DayCent simulations produced the lowest number of significant total and relative errors. When looking at the relationship between modelled and measured N 2 O fluxes, ECOSSE performed best with a significant relationship in 61.8% of all simulations and an average r 2 of 0.2. However, outputs from this model displayed the largest total and relative errors. Performance when simulating cumulative fluxes was generally poor. The Monte Carlo analysis showed that shifts in timing of management events by ±7 days lead to annual N 2 O fluxes varying by 5.6 ± 7.6% and 2.8 ± 4.2% for grassland and cropland, respectively. However the impact of the timing of single events can lead to much larger responses in N 2 O emissions. The large variation in model performance suggests that further development and calibration is required before using models in GHG reporting. [ABSTRACT FROM AUTHOR]

A nitrogen model was developed with the aim to trace nitrogen cycling in a cold climate-mining pond at the Aitik copper mine in northern Sweden. The model contains 10 state variables and 19 nitrogen cycling reactions. The model also includes sediment and physical properties of the pond, such as evaporation, freezing and thawing. The model was written in Mathworks MATLAB and was calibrated and validated using environmental monitoring data for the clarification pond at the Aitik mine. The data used comprised monthly values of nitrogen speciation, phosphorous and water flow. The model accurately predicts ammonium (r 2  = 0.84) and nitrate (r 2  = 0.82) concentrations in a time series from February 2012–August 2014. The model did not accurately predict nitrate concentrations (r 2  = 0.11), presumably due to high oxygen concentration in the pond water that prevented denitrification in the water column. The transport of organic material to the sediment was also limiting denitrification in the sediment. When allowing denitrification in the water column as well as increasing the rate of transport of organic material to the sediment the nitrate prediction capacity increased to a satisfactory level (r 2  = 0.54). A sensitivity analysis for the system showed that the most sensitive reactions for the water column were oxic mineralisation as well as the nitrification rate. [ABSTRACT FROM AUTHOR]

Globally, it is estimated that ~ 1500 Pg C of organic carbon is stored in the top meter of terrestrial soils. This represents the largest terrestrial pool of carbon. Appropriate management of soils, to maintain or increase the soil carbon pool, represents a significant climate change mitigation opportunity. To achieve this, appropriate tools and models are required in order to more accurately estimate soil carbon fluxes with a view to informing and developing more effective land use management strategies. Central to this is the evaluation of models currently in use to estimate soil carbon emissions. In the present study, we evaluate the ECOSSE (Estimating Carbon in Organic Soils – Sequestration and Emissions) model which has its origins in both SUNDIAL and RothC and has been widely used globally to model soil CO 2 fluxes across different locations and land-use types on both organic and mineral soils. In contrast to previous studies, the model was found to poorly represent observed soil respiration at the study site, an arable cropland on mineral soil located in south-east Ireland. To isolate potential sources of error, the model was decomposed into its component rate equations or modifiers. This investigation highlighted a deficiency in the model simulated soil water, resulting in significant inhibition of the model simulated CO 2 flux relative to the observed data. When measured values of soil water at the site were employed, the model simulated soil respiration improved significantly (r 2 of 0.775 vs 0.154). This highlighted model deficiency remains to be evaluated at other sites; however, the research highlights the need for a more comprehensive evaluation of soil carbon models prior to their use in informing policy, particularly models which are employed at larger scales and for climate change projections. [ABSTRACT FROM AUTHOR]

International regulation of the emission of acidic sulphur and nitrogen oxides from commercial shipping has focused on the risks to human health, with little attention paid to the consequences for the marine environment. The introduction of stricter regulations in northern Europe has led to substantial investment in scrubbers that absorb the sulphur oxides in a counterflow of seawater. This paper examines the consequences of smokestack and scrubber release of acidic oxides in the Baltic Sea according to a range of scenarios for the coming decades. While shipping is projected to become a major source of strong acid deposition to the Baltic Sea by 2050, the long-term effect on the pH and alkalinity is projected to be significantly smaller than estimated from previous scoping studies. A significant contribution to this difference is the efficient export of surface water acidification to the North Sea on a timescale of 15-20 years. [ABSTRACT FROM AUTHOR]

Marine particle fluxes from high productive coastal upwelling systems return upwelled CO 2 and nutrients to the deep ocean and sediments and have a substantial impact on the global carbon cycle. This study examines relations between production regimes on the shelf and over the continental margin of the Benguela Upwelling System (BUS) in the SE Atlantic Ocean. Data of composition and timing of vertical particle flux come from sediment trap time series (deployed intermittently between 1988 and 2014) in the regions Walvis Ridge, Walvis Bay, Luederitz and Orange River. We compare their seasonal variability to modelled patterns of chlorophyll concentrations in a 3-D ecosystem model. Both modelled seasonal chlorophyll a standing stocks and sampled particle flux patterns are highly correspondent with a bimodal seasonal cycle offshore the BUS. The material in the particle flux in offshore traps is dominantly carbonate (40–70%), and flux peaks in offshore particle flux originate from two independent events: in austral autumn thermocline shoaling and vertical mixing are decoupled from coastal upwelling, while fluxes in spring coincide with the upwelling season, indicated by slightly elevated biogenic opal values at some locations. Coastal particle fluxes are characterized by a trimodal pattern and are dominated by biogenic opal (22–35%) and organic matter (30–60%). The distinct seasonality in observed fluxes on the shelf is caused by high variability in production, sinking behaviour, wind stress, and hydrodynamic processes. We speculate that global warming will increase ocean stratification and alter coastal upwelling, so that consequences for primary production and particle flux in the BUS are inevitable. [ABSTRACT FROM AUTHOR]

Bubble-plume mixing systems are often deployed in eutrophic lakes and reservoirs to manage phytoplankton taxa. Unfortunately, inconsistent outcomes from bubble-plume (induced) mixing are often reported in the literature. The present study investigates the response of phytoplankton to induced mixing using a whole-reservoir field experiment and a three-dimensional hydrodynamic model (Si3D) coupled with the Aquatic EcoDynamics (AED) model through the framework for aquatic biogeochemical modelling (FABM). The coupled Si3D-AED model is validated against a 24-h field mixing experiment and subsequently used for a numerical parametric study to investigate phytoplankton responses to various induced mixing scenarios in which the phytoplankton settling rate, phytoplankton growth rate, reservoir depth, and mixing system diffuser depth were sequentially varied. Field observations during the mixing experiment suggest that the total phytoplankton concentration (measured in μ g / L ) across the reservoir was reduced by nearly 10% during the 24-h mixing period. The numerical modeling results show that phytoplankton concentration may be substantially affected by the functional traits of the phytoplankton and the deployment depth of the mixing diffuser. Interestingly, the numerical results indicate that the phytoplankton concentration is controlled by reduced growth rates due to light limitation in deep reservoirs (>20 m), whereas settling loss is a more important factor in shallow reservoirs during the mixing period. In addition, the coupled Si3D-AED model results suggest that deploying the mixing diffuser deeper in the water column to increase mixing depth may generally improve the successful management of cyanobacteria using bubble-plume mixing systems. Thus, the coupled Si3D-AED model introduced in the present study can assist with the design and operation of bubble-plume mixing systems. [ABSTRACT FROM AUTHOR]

By combining a crop model (STICS) and a geochemical model (PHREEQC), a new approach to assess the sustainability of agrosystems is proposed. It is based upon aqueous geochemistry and the stepwise modifications of soil solution during its transfer from the surface till aquifer. Meadows of Crau (SE France), irrigated since the 16th century, were field monitored (2012–2015) and modelled. Except for N, the mineral requirements of hay are largely covered by dissolved elements brought by irrigation water with only slight deficits in K and P, which are compensated by P-K fertilizers and the winter pasture by sheep. N cycle results in a very small nitrate leakage. The main determinants of the chemical composition changes of water are: concentration by evaporation, equilibration with soil pCO 2 , mineral nutrition of plants, input of fertilizers, sheep grazing, mineral-solution interactions in superficial formations till the aquifer, including ion exchange. Inverse modelling with PHREEQC allows for quantifying these processes. For groundwater, measured composition fit statistically very well with those computed, validating thus this approach. This long-term established agrosystem protects both soil and water resources: soil nutritional status remains constant with even some P and (minor) K fixation in soils; long-term decarbonatation occurs but it is greatly slowed by saturation of irrigation water by carbonate; P fixation in soil protects groundwater from eutrophication. [ABSTRACT FROM AUTHOR]

Secular decreases in dissolved oxygen concentration have been observed within the tropical oxygen minimum zones (OMZs) and at mid- to high latitudes over the last approximately 50 years. Earth system model projections indicate that a reduction in the oxygen inventory of the global ocean, termed ocean deoxygenation, is a likely consequence of on-going anthropogenic warming. Current models are, however, unable to consistently reproduce the observed trends and variability of recent decades, particularly within the established tropical OMZs. Here, we conduct a series of targeted hindcast model simulations using a state-of-the-art global ocean biogeochemistry model in order to explore and review biases in model distributions of oceanic oxygen. We show that the largest magnitude of uncertainty is entrained into ocean oxygen response patterns due to model parametrization of pCO2-sensitive C:N ratios in carbon fixation and imposed atmospheric forcing data. Inclusion of a pCO2-sensitive C:N ratio drives historical oxygen depletion within the ocean interior due to increased organic carbon export and subsequent remineralization. Atmospheric forcing is shown to influence simulated interannual variability in ocean oxygen, particularly due to differences in imposed variability of wind stress and heat fluxes. [ABSTRACT FROM AUTHOR]

This work presents a one-dimensional simulation of the seasonal changes in CO2 partial pressure (pCO2). The results of the model were constrained using data from observations, which improved the model's ability to estimate nitrogen fixation in the central Baltic Sea and allowed the impact of nitrogen fixation on the ecological state of the Baltic Sea to be studied. The model used here is the public domain water-column model GOTM (General Ocean Turbulence Model), which in this study was coupled with a modifed Baltic Sea ecosystem model, ERGOM (The Baltic Sea Research Institute's ecosystem model). To estimate nitrogen fixation rates in the Gotland Sea, the ERGOM model was modified by including an additional cyanobacteria group able to fix nitrogen from March to June. Furthermore, the model was extended by a simple CO2 cycle. Variable C:P and N:P ratios, controlled by phosphate concentrations in ambient water, were used to represent cyanobacteria, detritus and sediment detritus. This approach improved the model's ability to reproduce sea-surface phosphate and pCO2 dynamics. The resulting nitrogen fixation rates in 2005 for the two simulations, with and without the additional cyanobacteria group, were 259 and 278 mmol N m-2 year-1respectively.

For nearly a century, functional response curves, which describe how predation rates vary with prey density, have been a mainstay of ecological modelling. While originally derived to describe terrestrial interactions, they have been adopted to characterize aquatic systems in marine biogeochemical, size-spectrum, and population models. However, marine ecological modellers disagree over the qualitative shape of the curve (e.g. Type II vs. III), whether its parameters should be mechanistically or empirically defined (e.g. disk vs. Michaelis–Menten scheme), and the most representative value of those parameters. As a case study, we focus on marine biogeochemical models, providing a comprehensive theoretical, empirical, and numerical road-map for interpreting, formulating, and parameterizing the functional response when used to prescribe zooplankton specific grazing rates on a single prey source. After providing a detailed derivation of each of the canonical functional response types explicitly for aquatic systems, we review the literature describing their parameterization. Empirical estimates of each parameter vary by over three orders of magnitude across 10 orders of magnitude in zooplankton size. However, the strength and direction of the allometric relationship between each parameter and size differs depending on the range of sizes considered. In models, which must represent the mean state of different functional groups, size spectra or in many cases the entire zooplankton community, the range of parameter values is smaller, but still varies by two to three orders of magnitude. Next, we conduct a suite of 0-D NPZ simulations to isolate the sensitivity of phytoplankton population size and stability to the grazing formulation. We find that the disk parameterizations scheme is less sensitive to its parameterization than the Michaelis–Menten scheme, and quantify the range of parameters over which the Type II response, long known to have destabilizing properties, introduces dynamic instabilities. Finally, we use a simple theoretical model to show how the mean apparent functional response, averaged across sufficient sub-grid scale heterogeneity, diverges from the local response. Collectively, we recommend using a type II disk response for models with smaller scales and finer resolutions but suggest that a type III Michaelis–Menten response may do a better job of capturing the complexity of all processes being averaged across in larger-scale and coarser-resolution models, not just local consumption and capture rates. While we focus specifically on the grazing formulation in marine biogeochemical models, we believe these recommendations are robust across a much broader range of population and ecosystem models that use functional response curves. • A unified derivation of all common single-prey grazing formulations is provided. • Grazing parameters vary by 3–4 orders of magnitude with inconsistent allometric relationships. • Sub-grid scale heterogeneity alters the apparent shape of the mean functional response curve. • We recommend a type II disk response in smaller scale, finer resolution models. • We recommend a type III Michaelis–Menten response in larger scale, coarser resolution models. [ABSTRACT FROM AUTHOR]

Regulations pertaining to carbon dioxide capture with offshore storage (CCS) require an understanding of the potential localised environmental impacts and demonstrably suitable monitoring practices. This study uses a marine ecosystem model to examine a comprehensive range of hypothetical CO 2 leakage scenarios, quantifying both impact and recovery time within the benthic system. Whilst significant mortalities and long recovery times were projected for the larger and longer term scenarios, shorter-term or low level exposures lead to reduced projected impacts. This suggests that efficient monitoring and leak mitigation strategies, coupled with appropriate selection of storage sites can effectively limit concerns regarding localised environmental impacts from CCS. The feedbacks and interactions between physiological and ecological responses simulated reveal that benthic responses to CO 2 leakage could be complex. This type of modelling investigation can aid the understanding of impact potential, the role of benthic community recovery and inform the design of baseline and monitoring surveys. [ABSTRACT FROM AUTHOR]

We present the results from the RHOMA2011-LEG2 campaign that took place in the eastern Gulf of Lion from 7 to 17 Oct 2011 and combine them with remote sensing observations and results from a 3D coupled hydrodynamic-biogeochemical model to study an intrusion event of the Northern Current (NC) onto the continental shelf in the Gulf of Lion (NW Mediterranean). Our analysis shows that during the intrusion, the previously upwelled nutrient-rich water present on the shelf is replaced by warmer and mostly oligotrophic NC water within a matter of 2–3 days. This has a marked impact on the local biogeochemistry in the Gulf with pre-intrusion Chl- a concentrations in the surface layer of over 0.5 mg m −3 dropping to near the detection limit within less than 72 h. The intrusion event leads to a dramatic albeit short-lived regime shift in the limiting nutrient for primary production: prior to the intrusion most of production on the shelf is nitrogen limited while the intrusion induces a shift to phosphorous limitation. The relatively high frequency of occurrence of these intrusions in combination with their impact on the local ecosystem make them primary targets for future study. [ABSTRACT FROM AUTHOR]

The Western Baltic Sea is affected by eutrophication and receives nutrients from local land-based sources, atmospheric deposition and by advection from the neighbouring North Sea and Baltic Sea. In the present study, we evaluated the importance of local (Danish) versus external (Baltic Sea–North Sea) nutrient loads for surface Chl a- concentrations, total areal primary production and the vertical distributions of primary production in the W. Baltic Sea using the 3D coupled HBM-ERGOM model. This was assessed by improving descriptions of nutrient loads and primary production in the model and by conducting scenarios of different nutrient loads according to (i) the eutrophication level in 1990, (ii) the new Danish Water Plan (DWP) and iii) DWP+ the Baltic Sea Action Plan (BSAP2). The model results showed that local nutrient reductions have a profound effect on Chl a concentrations and primary production in the coastal areas of the Western Kattegat and the Belt Sea with the highest impact <10–25 km from the coast. However, on average for the study area, Danish reductions have a limited effect. The DWP complemented the BSAP2 reductions spatially, since they had the highest impact in different areas and both were important for improving the ecological status of the ecosystem. The model suggested a significant change in the vertical distribution of primary production with less deep primary production in response to increased nutrient load. We recommend using this redistribution as an ecological indicator of eutrophication in seasonally stratified seas. The new description of primary production takes into account that carbon fixation continue, even when phytoplankton is severely nutrient limited. This model improvement increases primary production by a factor of 2.6 and brings the model estimates in agreement with measurements and the physiology of phytoplankton. We recommend that other dynamic ecosystem models using Liebig's law for primary production consider a similar approach. [ABSTRACT FROM AUTHOR]

The complex biogeochemical SWAMCO-3 model has been used to assess the response of the ice-free Southern Ocean to the physical and biological mechanisms governing air–sea CO 2 exchanges. For this application, the model explicitly details the dynamics of three Phytoplankton Functional Types (PFTs) of importance for C, N, P, Si, Fe cycling and air–sea CO 2 exchange in this area. These are the diatoms, the pico–nanophytoplankton and the coccolithophores whose growth regulation by light, temperature and nutrients has been obtained from a literature review of phenomenological observations available for these PFTs. The performance of the SWAMCO-3 model coupled to a vertical one-dimensional physical model was first assessed at the location of the JGOFS time-series station KERFIX. The model was able to reproduce a mean seasonal cycle based on years where a maximum of chemical and biological observations are available at this location (1993–1994, 1994–1995, 1998–1999 and 2000–2001). Ocean fCO 2 in equilibrium with the atmosphere are simulated both in Austral winter associated with surface layer replenishment in DIC due to deep vertical mixing and in late summer as a consequence of the warming effect on the carbonate system. A clear under-saturation is found in spring/summer. Analysis of the modelled seasonal biogeochemical and physical features shows that thermodynamical conditions are driving the air–sea exchange of CO 2 in the region, while the biological activity under the control of light and iron availability, is responsible for the predicted relatively modest annual carbon sink (− 0.9 mol C m − 2 y − 1 ). [ABSTRACT FROM AUTHOR]

Nutrient limitation on phytoplankton growth plays a critical role in ocean productivity, the functioning of marine ecosystems, and the ocean carbon cycle. In the Celtic Sea, a temperate shelf sea, many studies have shown the importance of nitrate on phytoplankton growth focusing on the seasonal cycle of nitrate and feedbacks with the physical environment; but only recently has it been demonstrated, through discrete measurements, that dissolved iron also plays an important role in the ecosystem of the region. A well-established one-dimensional model has been developed to analyse the nutrient co-limitation between dissolved iron and dissolved inorganic nitrogen in the Celtic Sea. This model allows us to study the full seasonal cycle and inter-annual variability of these two nutrients. Simulations show that dissolved iron is an important nutrient for the development of the spring bloom, while nitrate plays a more important role during the summer season. Sensitivity analyses show that these results are robust when varying the nutrient-related parameters; the largest variability observed for primary production was observed when varying the nutrient sediment flux rates for dissolved iron and nitrate while less impact on phytoplankton production occurs when changing the half saturation constants. Here, we demonstrate that dissolved iron is an important nutrient for the development of the spring bloom and it should not be neglected as a state variable when modelling the Celtic Sea or other temperate shelf seas. • Investigation of nutrient co-limitation in the Central Celtic Sea. • Novel 1-D model approach to understand nutrient limitation on phytoplankton growth. • Dissolved iron shows limitation during the spring phytoplankton bloom. • Summer phytoplankton growth is mainly limited by nitrate concentrations. [ABSTRACT FROM AUTHOR]

In the recent past observational and modelling studies have shown that the vertical displacement of water parcels, and therefore, phytoplankton particles in regions of deep-reaching convection plays a key role in late winter/early spring primary production. The underlying mechanism describes how convection cells capture living phytoplankton cells and recurrently expose them to sunlight. This study presents a parameterisation called ‘phytoconvection’ which focusses on the influence of convection on primary production. This parameterisation was implemented into a three-dimensional physical–biogeochemical model and applied to the Northwestern European Continental Shelf and areas of the adjacent Northeast Atlantic. The simulation was compared to a ‘conventional’ parameterisation with respect to its influence on phytoplankton concentrations during the annual cycle and its effect on the carbon cycle. The simulation using the new parameterisation showed good agreement with observation data recorded during winter, whereas the reference simulation did not capture the observed phytoplankton concentrations. The new parameterisation had a strong influence on the carbon export through the sinking of particulate organic carbon. The carbon export during late winter/early spring significantly exceeded the export of the reference run. Furthermore, a non-hydrostatic convection model was used to evaluate the major assumption of the presented parameterisation which implies the matching of the mixed layer depth with the convective mixing depth. The applied mixed layer depth criterion principally overestimates the actual convective mixing depth. However, the results showed that this assumption is reasonable during late winter, while indicating a mismatch during spring. [ABSTRACT FROM AUTHOR]

Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions. [ABSTRACT FROM AUTHOR]

One of the most of challenging steps in the development of coupled hydrodynamic-biogeochemical models is the combination of multiple, often incompatible computer codes that describe individual physical, chemical, biological and geological processes. This “coupling” is time-consuming, error-prone, and demanding in terms of scientific and programming expertise. The open source, Fortran-based Framework for Aquatic Biogeochemical Models addresses these problems by providing a consistent set of programming interfaces through which hydrodynamic and biogeochemical models communicate. Models are coded once to connect to FABM, after which arbitrary combinations of hydrodynamic and biogeochemical models can be made. Thus, a biogeochemical model code works unmodified within models of a chemostat, a vertically structured water column, and a three-dimensional basin. Moreover, complex biogeochemistry can be distributed over many compact, self-contained modules, coupled at run-time. By enabling distributed development and user-controlled coupling of biogeochemical models, FABM enables optimal use of the expertise of scientists, programmers and end-users. [ABSTRACT FROM AUTHOR]

This article considers how aquatic systems modelling has changed since 1995 and how it must change in future if we are to continue to advance. A distinction is made between mechanistic and statistical models, and the relative merits of each are considered. The question of “when do aquatic systems models provide accurate and useful predictions?” is addressed, implying some guidelines for model development. It is proposed that, in general, ecological models only provide management-relevant predictions of the behaviour of real systems when there are strong physical (as opposed to chemical or ecological) drivers. Developments over the past 15 years have included changes in technology, changes in the modelling community and changes in the context in which modelling is conducted: the implications of each are briefly discussed. Current trends include increased uptake of best practice guidelines, increasing integration of models, operationalisation, data assimilation, development of improved tools for skill assessment, and application of models to new management questions and in new social contexts. Deeper merging of statistical and mechanistic modelling approaches through such techniques as Bayesian Melding, Bayesian Hierarchical Modelling and surrogate modelling is identified as a key emerging area. Finally, it is suggested that there is a need to systematically identify areas in which our current models are inadequate. We do not yet know for which categories of problems well-implemented aquatic systems models can (or cannot) be expected to accurately predict observational data and system behaviour. This can be addressed through better modelling and publishing practices. [ABSTRACT FROM AUTHOR]

Highlights: [•] A stand-level thinning model has been developed. [•] It is intended to be used within large-scale biogeochemical modelling applications. [•] It is based on the Austrian forest inventory data. [•] The model is based on logistic regression and empirical probability density maps. [•] Validation shows that the model is able to correctly mimic the thinning intensity. [ABSTRACT FROM AUTHOR]

A modelling tool was implemented in an Eastern Mediterranean Allocated Zone for Aquaculture (AZA) (Vourlias Bay, Greece) to examine the fate of seabass/seabream aquaculture wastes from multiple farms and assess their potential impacts on the surrounding ecosystem in terms of good environmental status. The model was validated against available satellite (Chl-a) and in situ data (PO4, NO3, NH4, Chl-a, Mesozooplankton), showing a reasonable skill in reproducing the observed range and horizontal variability. Environmental status was assessed by means of two environmental indicators (TRIX, E.I.), calculated using the simulated outputs. The environmental conditions in the AZA were "good" during the well mixed period in winter and "moderate" to "poor" during more stratified periods, particularly summer, when effluents from the fish farms were higher. In the vicinity of different fish farms, environmental conditions were found to be correlated to the fish farm production, as well as to the predominant current speed/orientation. Fish farms, where stronger prevailing currents induced a more efficient off-shore dispersion of wastes, showed relatively better conditions, despite their high fish production. Changes in the food web structure from the input of fish farm wastes were mainly characterized by an increase in dinoflagellates, an indicator for eutrophication, and also nanophytoplankton and microzooplankton. A series of scenario simulations (fish farms production and position) were performed to investigate the ecological carrying capacity of the AZA and demonstrate the utility of the modelling system, as a management tool for AZA spatial planning and licensing of fish farms. • A model was used to examine the impact of aquaculture waste on the marine environment. • The model was validated against satellite and insitu data, showing reasonable skill. • Environmental status was correlated to fish production and current speed/orientation. • Changes in the food web were mainly characterized by an increase in dinoflagellates. • A series of scenario simulations (fish farm production, position) were performed. [ABSTRACT FROM AUTHOR]