The European regional seas ecosystem model, a complex marine ecosystem model

Anchovy and sardine condition and energy content in the North Aegean Sea (eastern Mediterranean) in relation to their contrasting reproductive strategies

Forage species with high biomass, such as anchovies and sardines, play a key role in pelagic ecosystems and make up a significant proportion of the world's capture fisheries production. In recent years, condition indices have gained interest as significant indicators for assessing the effects of environmental and human pressures on these species and the quality of their habitats. In the present study, we examined, for the first time in the North Aegean Sea (eastern Mediterranean), the year-round variation in somatic and gonadal condition, energy density, and percentage of lipid content of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus). Energy density was measured with bomb calorimetry and percentage lipid content with the fatmeter, a portable electronic device. Finally, the monthly changes in gonadal and energetic condition were examined in relation to the annual cycle of temperature and mesozooplankton biomass, simulated by the implementation of a coupled hydrodynamic-biogeochemical model (POM-ERSEM). There was a strong relationship between fish energy density (kJ g-1) and percentage dry weight. Furthermore, the mean monthly energy density and fatmeter measurements were strongly correlated, especially in sardine. Overall, the monthly changes in energetic condition were indicative of the species' different strategies for energy acquisition and allocation to reproduction (capital vs. income breeding): sardine exhibited low energy density and percentage lipid content during the winter spawning period (November-March) and markedly higher energetic condition from spring to autumn (April-October). Anchovy spawning period, as inferred from gonadal condition, lasted from April to September, i.e., during the warm period of the year but its energy density and percentage lipid content did not exhibit any seasonal changes and were markedly lower than in sardine from April to October. Finally, the simulated mesozooplankton biomass was higher from January to July, which corresponded to the second half of the spawning season for sardine, but first half of the spawning season for anchovy.

The impact of extreme precipitation on physical and biogeochemical processes regarding with nutrient dynamics in a semi-closed bay

An extreme precipitation event in August 2012 changed the ecosystem of Jiaozhou Bay (JZB), China. Biochemical variables in the sea, river mouths, and rainwater were monitored simultaneously during the event. The impact of the following excessive riverine input and wet atmospheric deposition on nutrient dynamics were studied before. However, regulatory processes of nutrient dynamics were not quantified and analyzed. Therefore, a coupled physical-biological model (FVCOM-ERSEM) was used to study the physical and biochemical mechanisms of the variation of the dissolved inorganic nitrogen (DIN), phosphorus (DIP), and silicon (DISi), as well as chlorophyll-a (Chl-a). The results indicate that physical processes increase nutrients, while biological processes reduce them. The exchange with the Yellow Sea, as an important physical process, exports DIN to the Yellow Sea, but imports DIP and DISi to the JZB. Only 20 % of the excessive DIN due to extreme precipitation event was reduced by water exchange with the Yellow Sea. The rest (80 %) was reduced and changed into organic nitrogen through biological processes. This paper also examines the variation of the pelagic and benthic cycles of biochemical processes. In these cycles, phytoplankton take up and use nutrients in the bay, while zooplankton excretion in the pelagic cycle and benthic releases resupply them. Precipitation enriched the surface nutrients, which boosted primary production and organic matter transport to the bottom water.

Decline in Size-at-Maturity of European Hake in Relation to Environmental Regimes: A Case in the Eastern Ionian Sea

European hake, Merluccius merluccius L. 1758, is a highly valuable demersal fish species exploited in both the east Atlantic and the Mediterranean Sea. Changes in the size-at-maturity of this species have been reported in various geographic areas. Size-at-maturity is a key parameter in fishery management. Our main goal was to study the trend of the size-at-maturity of European hake in the eastern Ionian Sea (Central Mediterranean) over the last five decades. Utilizing a multi-decadal series of data for various environmental variables, we employed multivariate analyses and non-additive modeling in an attempt to identify shifts in the climatic environment of the eastern Ionian Sea and whether the maturation of the hake population could be affected by these changes. The analyses used suggest a plausible environmental regime shift in the study area in the late 1990s/early 2000s. The decrease in size-at-maturity that was detected in the last two decades may, thus, be associated with environmental changes. However, as many fish stocks already experience fishery-induced evolution, further investigation is necessary to determine whether this environmental effect is an additional stressor on a possibly already fishery-impacted population. The outcomes of this study highlight the importance of investigating the relationship between fish reproductive traits and altered environmental conditions, as the latter are generally ignored during assessments, affecting the robustness of fishery management.

Neural closure models for dynamical systems

Complex dynamical systems are used for predictions in many domains. Because of computational costs, models are truncated, coarsened or aggregated. As the neglected and unresolved terms become important, the utility of model predictions diminishes. We develop a novel, versatile and rigorous methodology to learn non-Markovian closure parametrizations for known-physics/low-fidelity models using data from high-fidelity simulations. The new neural closure models augment low-fidelity models with neural delay differential equations (nDDEs), motivated by the Mori–Zwanzig formulation and the inherent delays in complex dynamical systems. We demonstrate that neural closures efficiently account for truncated modes in reduced-order-models, capture the effects of subgrid-scale processes in coarse models and augment the simplification of complex biological and physical–biogeochemical models. We find that using non-Markovian over Markovian closures improves long-term prediction accuracy and requires smaller networks. We derive adjoint equations and network architectures needed to efficiently implement the new discrete and distributed nDDEs, for any time-integration schemes and allowing non-uniformly spaced temporal training data. The performance of discrete over distributed delays in closure models is explained using information theory, and we find an optimal amount of past information for a specified architecture. Finally, we analyse computational complexity and explain the limited additional cost due to neural closure models.

Predator–Prey Models: A Review of Some Recent Advances

In recent years, predator–prey systems have increased their applications and have given rise to systems which represent more accurately different biological issues that appear in the context of interacting species. Our aim in this paper is to give a state-of-the-art review of recent predator–prey models which include some interesting characteristics such as Allee effect, fear effect, cannibalism, and immigration. We compare the qualitative results obtained for each of them, particularly regarding the equilibria, local and global stability, and the existence of limit cycles.

Spatial patterns of Posidonia oceanica structural and functional features in the Eastern Mediterranean (Aegean and E. Ionian Seas) in relation to large-scale environmental factors

In the context of general ecosystem monitoring of the Greek coastal marine environment, a total of 22 descriptors of Posidonia oceanica meadows were studied in 69 study sites. Spatial variation of P. oceanica meadows' features in relation to specific environmental factors (i.e., light, physical exposure, temperature, and nutrients) controlling their dynamics was assessed in three sub-ecoregions of the Hellenic seas (Eastern Ionian, North Aegean, and South Aegean). The studied meadows differentiated by exhibiting varying growth patterns at both the local and sub-ecoregional scale. Significant differences in morphological and demographic descriptors were observed for meadows of the N. Aegean Sea as compared to those of the S. Aegean and the Eastern Ionian Seas. Light limitation was determined as the main driver differentiating the P. oceanica meadows' distribution (i.e., lower limit depth), demography (i.e., shoot density, meadow cover) and shoots' biometry (i.e., shoot length, shoot leaf surface and leaf biomass) along the mainland coastal zone of the N. Aegean Sea. Considering the projected decline of P. oceanica in the face of increasing natural and human impacts, this study offers a crucial ecological baseline that can enhance our understanding of P. oceanica meadows' trends, against which the efficiency of conservation plans and management actions may be monitored.

Offshore multi-purpose platforms for a Blue Growth: A technological, environmental and socio-economic review

"Blue Growth" and "Blue Economy" is defined by the World Bank as: "the sustainable use of ocean resources for economic growth, improved livelihoods and jobs, while preserving the health of ocean ecosystem". Multi-purpose platforms (MPPs) can be defined as offshore platforms serving the needs of multiple offshore industries (energy and aquaculture), aim at exploiting the synergies and managing the tensions arising when closely co-locating systems from these industries. Despite a number of previous projects aimed at assessing, from a multidisciplinary point of view, the feasibility of multipurpose platforms, it is here shown that the state-of-the-art has focused mainly on single-purpose devices, and adopting a single discipline (either economic, or social, or technological, or environmental) approach. Therefore, the aim of the present study is to provide a multidisciplinary state of the art review on, whenever possible, multi-purpose platforms, complementing it with single-purpose and/or single discipline literature reviews when not possible. Synoptic tables are provided, giving an overview of the multi-purpose platform concepts investigated, the numerical approaches adopted, and a comprehensive snapshot classifying the references discussed by industry (offshore renewables, aquaculture, both) and by aspect (technological, environmental, socio-economic). The majority of the multi-purpose platform concepts proposed are integrating only multiple offshore renewable energy devices (e.g. hybrid wind-wave), with only few integrating also aquaculture systems. MPPs have significant potential in economizing CAPEX and operational costs for the offshore energy and aquaculture industry by means of concerted spatial planning and sharing of infrastructure.

Sensitivity of Modeled CO2 Air–Sea Flux in a Coastal Environment to Surface Temperature Gradients, Surfactants, and Satellite Data Assimilation

This work evaluates the sensitivity of CO2 air–sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic–ecosystem model GOTM–ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air–sea CO2 exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50°15.00’N, 4°13.02’W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008–2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air–sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with a p > 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air–sea flux of CO2 and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation > 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation > 0.43) and total biomass (correlation > 0.7) in a two year run for 2008–2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO2 (pCO2) with correlations between 0.4–0.5. The model result suggest that L4 is a weak net source of CO2 (0.3–1.8 molCm−2 year−1). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO2 air–sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.

A versatile marine modelling tool applied to arctic, temperate and tropical waters

The improved understanding of complex interactions of marine ecosystem components makes the use of fully coupled hydrodynamic, biogeochemical and individual based models more and more relevant. At the same time, the increasing complexity of the models and diverse user backgrounds calls for improved user friendliness and flexibility of the model systems. We present FlexSem, a versatile and user-friendly framework for 3D hydrodynamic, biogeochemical, individual based and sediment transport modelling. The purpose of the framework is to enable natural scientists to conduct advanced 3D simulations in the marine environment, including any relevant processes. This is made possible by providing a precompiled portable framework, which still enables the user to pick any combination of models and provide user defined equation systems to be solved during the simulation. We here present the ideas behind the framework design, the implementation and documentation of the numerical solution to the Navier-Stokes equations in the hydrodynamic module, the surface heat budget model, the pelagic and benthic equation solvers and the Lagrangian movement of the agents in the agent based model. Five examples of different applications of the system are shown: 1) Hydrodynamics in the Disko Bay in west Greenland, 2) A biogeochemical pelagic and benthic model in the inner Danish waters, 3) A generic mussel farm model featuring offline physics, food levels and mussel eco-physiology, 4) Sediment transport in Clarion-Clipperton zone at the bottom of the Pacific and 5) Hydrodynamics coupled with an agent based model around Zanzibar in Tanzania. Hence we demonstrate that the model can be set up for any area with enough forcing data and used to solve a wide range of applications.

The meagre future of benthic fauna in a coastal sea-Benthic responses to recovery from eutrophication in a changing climate

Nutrient loading and climate change affect coastal ecosystems worldwide. Unravelling the combined effects of these pressures on benthic macrofauna is essential for understanding the future functioning of coastal ecosystems, as it is an important component linking the benthic and pelagic realms. In this study, we extended an existing model of benthic macrofauna coupled with a physical-biogeochemical model of the Baltic Sea to study the combined effects of changing nutrient loads and climate on biomass and metabolism of benthic macrofauna historically and in scenarios for the future. Based on a statistical comparison with a large validation dataset of measured biomasses, the model showed good or reasonable performance across the different basins and depth strata in the model area. In scenarios with decreasing nutrient loads according to the Baltic Sea Action Plan but also with continued recent loads (mean loads 2012-2014), overall macrofaunal biomass and carbon processing were projected to decrease significantly by the end of the century despite improved oxygen conditions at the seafloor. Climate change led to intensified pelagic recycling of primary production and reduced export of particulate organic carbon to the seafloor with negative effects on macrofaunal biomass. In the high nutrient load scenario, representing the highest recorded historical loads, climate change counteracted the effects of increased productivity leading to a hyperbolic response: biomass and carbon processing increased up to mid-21st century but then decreased, giving almost no net change by the end of the 21st century compared to present. The study shows that benthic responses to environmental change are nonlinear and partly decoupled from pelagic responses and indicates that benthic-pelagic coupling might be weaker in a warmer and less eutrophic sea.

Development, application and evaluation of a 1-D full life cycle anchovy and sardine model for the North Aegean Sea (Eastern Mediterranean)

A 1-D full-life-cycle, Individual-based model (IBM), two-way coupled with a hydrodynamic/biogeochemical model, is demonstrated for anchovy and sardine in the N. Aegean Sea (Eastern Mediterranean). The model is stage-specific and includes a 'Wisconsin' type bioenergetics, a diel vertical migration and a population dynamics module, with the incorporation of known differences in biological attributes between the anchovy and sardine stocks. A new energy allocation/egg production algorithm was developed, allowing for breeding pattern to move along the capital-income breeding continuum. Fish growth was calibrated against available size-at-age data by tuning food consumption (the half saturation coefficients) using a genetic algorithm. After a ten-years spin up, the model reproduced well the magnitude of population biomasses and spawning periods of the two species in the N. Aegean Sea. Surprisingly, model simulations revealed that anchovy depends primarily on stored energy for egg production (mostly capital breeder) whereas sardine depends heavily on direct food intake (income breeder). This is related to the peculiar phenology of plankton production in the area, with mesozooplankton concentration exhibiting a sharp decrease from early summer to autumn and a subsequent increase from winter to early summer. Monthly changes in somatic condition of fish collected on board the commercial purse seine fleet followed closely the simulated mesozooplankton concentration. Finally, model simulations showed that, when both the anchovy and sardine stocks are overexploited, the mesozooplankton concentration increases, which may open up ecological space for competing species. The importance of protecting the recruit spawners was highlighted with model simulations testing the effect of changing the timing of the existing 2.5-months closed period. Optimum timing for fishery closure is different for anchovy and sardine because of their opposite spawning and recruitment periods.

A 1-Dimensional Sympagic–Pelagic–Benthic Transport Model (SPBM): Coupled Simulation of Ice, Water Column, and Sediment Biogeochemistry, Suitable for Arctic Applications

Marine biogeochemical processes can strongly interact with processes occurring in adjacent ice and sediments. This is especially likely in areas with shallow water and frequent ice cover, both of which are common in the Arctic. Modeling tools are therefore required to simulate coupled biogeochemical systems in ice, water, and sediment domains. We developed a 1D sympagic–pelagic–benthic transport model (SPBM) which uses input from physical model simulations to describe hydrodynamics and ice growth and modules from the Framework for Aquatic Biogeochemical Models (FABM) to construct a user-defined biogeochemical model. SPBM coupled with a biogeochemical model simulates the processes of vertical diffusion, sinking/burial, and biogeochemical transformations within and between the three domains. The potential utility of SPBM is demonstrated herein with two test runs using modules from the European regional seas ecosystem model (ERSEM) and the bottom-redox model biogeochemistry (BROM-biogeochemistry). The first run simulates multiple phytoplankton functional groups inhabiting the ice and water domains, while the second simulates detailed redox biogeochemistry in the ice, water, and sediments. SPBM is a flexible tool for integrated simulation of ice, water, and sediment biogeochemistry, and as such may help in producing well-parameterized biogeochemical models for regions with strong sympagic–pelagic–benthic interactions.

Application of the Spline Interpolation in Simulating the Distribution of Phytoplankton in a Marine NPZD Type Ecosystem Model

The available observations for the model are usually sparse and uneven. The application of interpolation methods help researchers obtain an approximate form of the original data. A marine nutrient, phytoplankton, zooplankton and detritus (NPZD) type ecosystem model is applied to simulate the distribution of phytoplankton combined with the spline interpolation (SI) and the Cressman interpolation (CI). In the idealized twin experiments, the performance of these two interpolation methods is validated through the analysis of several quantitative metrics, which show the minor error and high efficiency when using the SI. Namely, the given distributions can be better inverted with the SI. The actual distribution of phytoplankton in the Bohai Sea is interpolated in the practical experiment, where a satisfactory simulation result is obtained by the model with the SI. The model experiments and results verify the feasibility and effectiveness of SI.

Non-Redfieldian dynamics driven by phytoplankton phosphate frugality explain nutrient and chlorophyll patterns in model simulations for the Mediterranean Sea

The relative abundance of nitrate (N) over phosphate (P) measured as a molar ratio (N:P) is typically considered to determine the macronutrient limiting marine primary production. In low-complexity biogeochemical models, a simple threshold value is usually applied based on the canonical Redfield ratio (N:P = 16). However, the N:P ratio is not constant in many oceanic areas, especially marginal, semi-enclosed seas, such as the Mediterranean basin. In this work, a flexible definition of the N:P ratio based on the capacity of phytoplankton to modulate phosphate uptake according to its availability in seawater, the so-called Line of Frugality, is incorporated into the biogeochemical model MedERGOM. This modification allows the acquisition of a more realistic representation of the stoichiometry of nutrients in the Mediterranean basin and allows to better reproduce the observed phytoplankton biomass in productive areas such as the Gulf of Gabes and the Adriatic Sea. This approach is, thus, especially suitable for coastal areas in which basin-scale biogeochemical models fail to reproduce patterns observed by remote sensing or in situ measurements. Our results show that implementation of the stoichiometric flexibility of phytoplankton in a low-complexity biogeochemical model enhances the reproducibility of ecosystem dynamics without increasing the computational demand, representing a simple approximation easily implemented in models aiming to describe regions with a Non-Redfieldian stoichiometry.

Creating functional groups of marine fish from categorical traits

Background

Functional groups serve two important functions in ecology: they allow for simplification of ecosystem models and can aid in understanding diversity. Despite their important applications, there has not been a universally accepted method of how to define them. A common approach is to cluster species on a set of traits, validated through visual confirmation of resulting groups based primarily on expert opinion. The goal of this research is to determine a suitable procedure for creating and evaluating functional groups that arise from clustering nominal traits.

Methods

To do so, we produced a species by trait matrix of 22 traits from 116 fish species from Tasman Bay and Golden Bay, New Zealand. Data collected from photographs and published literature were predominantly nominal, and a small number of continuous traits were discretized. Some data were missing, so the benefit of imputing data was assessed using four approaches on data with known missing values. Hierarchical clustering is utilised to search for underlying data structure in the data that may represent functional groups. Within this clustering paradigm there are a number of distance matrices and linkage methods available, several combinations of which we test. The resulting clusters are evaluated using internal metrics developed specifically for nominal clustering. This revealed the choice of number of clusters, distance matrix and linkage method greatly affected the overall within- and between- cluster variability. We visualise the clustering in two dimensions and the stability of clusters is assessed through bootstrapping.

Results

Missing data imputation showed up to 90% accuracy using polytomous imputation, so was used to impute the real missing data. A division of the species information into three functional groups was the most separated, compact and stable result. Increasing the number of clusters increased the inconsistency of group membership, and selection of the appropriate distance matrix and linkage method improved the fit.

Discussion

We show that the commonly used methodologies used for the creation of functional groups are fraught with subjectivity, ultimately causing significant variation in the composition of resulting groups. Depending on the research goal dictates the appropriate strategy for selecting number of groups, distance matrix and clustering algorithm combination.

Connectivity of larval stages of sedentary marine communities between hard substrates and offshore structures in the North Sea

Man-made structures including rigs, pipelines, cables, renewable energy devices, and ship wrecks, offer hard substrate in the largely soft-sediment environment of the North Sea. These structures become colonised by sedentary organisms and non-migratory reef fish, and form local ecosystems that attract larger predators including seals, birds, and fish. It is possible that these structures form a system of interconnected reef environments through the planktonic dispersal of the pelagic stages of organisms by ocean currents. Changes to the overall arrangement of hard substrate areas through removal or addition of individual man-made structures will affect the interconnectivity and could impact on the ecosystem. Here, we assessed the connectivity of sectors with oil and gas structures, wind farms, wrecks, and natural hard substrate, using a model that simulates the drift of planktonic stages of seven organisms with sedentary adult stages associated with hard substrate, applied to the period 2001-2010. Connectivity was assessed using a classification system designed to address the function of sectors in the network. Results showed a relatively stable overall spatial distribution of sector function but with distinct variations between species and years. The results are discussed in the context of decommissioning of oil and gas infrastructure in the North Sea.

Spatial patterns in coastal lagoons related to the hydrodynamics of seawater intrusion

Marine intrusion was simulated in a choked and in a restricted coastal lagoon by using a 3D-hydrodynamic model. To study the spatiotemporal progression of seawater intrusion and its mixing efficiency with lagoon waters we define Marine Mixed Volume (V_MM) as a new hydrodynamic indicator. Spatial patterns in both lagoons were described by studying the time series and maps of V_MM taking into account the meteorological conditions encountered during a water year. The patterns comprised well-mixed zones (WMZ) and physical barrier zones (PBZ) that act as hydrodynamic boundaries. The choked Bages-Sigean lagoon comprises four sub-basins: a PBZ at the inlet, and two WMZ's separated by another PBZ corresponding to a constriction zone. The volumes of the PBZ were 2.1 and 5.4 millions m³ with characteristic mixing timescale of 68 and 84days, respectively. The WMZ were 12.3 and 43.3 millions m³ with characteristics mixing timescale of 70 and 39days, respectively.

Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-west European continental shelf

In 2006, a large and prolonged bloom of the dinoflagellate Karenia mikimotoi occurred in Scottish coastal waters, causing extensive mortalities of benthic organisms including annelids and molluscs and some species of fish (Davidson et al., 2009). A coupled hydrodynamic-algal transport model was developed to track the progression of the bloom around the Scottish coast during June-September 2006 and hence investigate the processes controlling the bloom dynamics. Within this individual-based model, cells were capable of growth, mortality and phototaxis and were transported by physical processes of advection and turbulent diffusion, using current velocities extracted from operational simulations of the MRCS ocean circulation model of the North-west European continental shelf. Vertical and horizontal turbulent diffusion of cells are treated using a random walk approach. Comparison of model output with remotely sensed chlorophyll concentrations and cell counts from coastal monitoring stations indicated that it was necessary to include multiple spatially distinct seed populations of K. mikimotoi at separate locations on the shelf edge to capture the qualitative pattern of bloom transport and development. We interpret this as indicating that the source population was being transported northwards by the Hebridean slope current from where colonies of K. mikimotoi were injected onto the continental shelf by eddies or other transient exchange processes. The model was used to investigate the effects on simulated K. mikimotoi transport and dispersal of: (1) the distribution of the initial seed population; (2) algal growth and mortality; (3) water temperature; (4) the vertical movement of particles by diurnal migration and eddy diffusion; (5) the relative role of the shelf edge and coastal currents; (6) the role of wind forcing. The numerical experiments emphasized the requirement for a physiologically based biological model and indicated that improved modelling of future blooms will potentially benefit from better parameterisation of temperature dependence of both growth and mortality and finer spatial and temporal hydrodynamic resolution.

Defining Planktonic Protist Functional Groups on Mechanisms for Energy and Nutrient Acquisition: Incorporation of Diverse Mixotrophic Strategies

Arranging organisms into functional groups aids ecological research by grouping organisms (irrespective of phylogenetic origin) that interact with environmental factors in similar ways. Planktonic protists traditionally have been split between photoautotrophic "phytoplankton" and phagotrophic "microzooplankton". However, there is a growing recognition of the importance of mixotrophy in euphotic aquatic systems, where many protists often combine photoautotrophic and phagotrophic modes of nutrition. Such organisms do not align with the traditional dichotomy of phytoplankton and microzooplankton. To reflect this understanding, we propose a new functional grouping of planktonic protists in an eco-physiological context: (i) phagoheterotrophs lacking phototrophic capacity, (ii) photoautotrophs lacking phagotrophic capacity, (iii) constitutive mixotrophs (CMs) as phagotrophs with an inherent capacity for phototrophy, and (iv) non-constitutive mixotrophs (NCMs) that acquire their phototrophic capacity by ingesting specific (SNCM) or general non-specific (GNCM) prey. For the first time, we incorporate these functional groups within a foodweb structure and show, using model outputs, that there is scope for significant changes in trophic dynamics depending on the protist functional type description. Accordingly, to better reflect the role of mixotrophy, we recommend that as important tools for explanatory and predictive research, aquatic food-web and biogeochemical models need to redefine the protist groups within their frameworks.

What can ecosystem models tell us about the risk of eutrophication in the North Sea?

Eutrophication is a process resulting from an increase in anthropogenic nutrient inputs from rivers and other sources, the consequences of which can include enhanced algal biomass, changes in plankton community composition and oxygen depletion near the seabed. Within the context of the Marine Strategy Framework Directive, indicators (and associated threshold) have been identified to assess the eutrophication status of an ecosystem. Large databases of observations (in situ) are required to properly assess the eutrophication status. Marine hydrodynamic/ecosystem models provide continuous fields of a wide range of ecosystem characteristics. Using such models in this context could help to overcome the lack of in situ data, and provide a powerful tool for ecosystem-based management and policy makers. Here we demonstrate a methodology that uses a combination of model outputs and in situ data to assess the risk of eutrophication in the coastal domain of the North Sea. The risk of eutrophication is computed for the past and present time as well as for different future scenarios. This allows us to assess both the current risk and its sensitivity to anthropogenic pressure and climate change. Model sensitivity studies suggest that the coastal waters of the North Sea may be more sensitive to anthropogenic rivers loads than climate change in the near future (to 2040).

Impacts of light shading and nutrient enrichment geo-engineering approaches on the productivity of a stratified, oligotrophic ocean ecosystem

Geo-engineering proposals to mitigate global warming have focused either on methods of carbon dioxide removal, particularly nutrient fertilization of plant growth, or on cooling the Earth's surface by reducing incoming solar radiation (shading). Marine phytoplankton contribute half the Earth's biological carbon fixation and carbon export in the ocean is modulated by the actions of microbes and grazing communities in recycling nutrients. Both nutrients and light are essential for photosynthesis, so understanding the relative influence of both these geo-engineering approaches on ocean ecosystem production and processes is critical to the evaluation of their effectiveness. In this paper, we investigate the relationship between light and nutrient availability on productivity in a stratified, oligotrophic subtropical ocean ecosystem using a one-dimensional water column model coupled to a multi-plankton ecosystem model, with the goal of elucidating potential impacts of these geo-engineering approaches on ecosystem production. We find that solar shading approaches can redistribute productivity in the water column but do not change total production. Macronutrient enrichment is able to enhance the export of carbon, although heterotrophic recycling reduces the efficiency of carbon export substantially over time. Our results highlight the requirement for a fuller consideration of marine ecosystem interactions and feedbacks, beyond simply the stimulation of surface blooms, in the evaluation of putative geo-engineering approaches.

A PHYLOGENETIC APPROACH TO THE ESTIMATION OF PHYTOPLANKTON TRAITS(1)

The quantitative characterization of the ecology of individual phytoplankton taxa is essential for model resolution of many aspects of aquatic ecosystems. Existing literature cannot directly parameterize all phytoplankton taxa of interest, as many traits and taxa have not been sampled. However, valuable clues on the value of traits are found in the evolutionary history of species and in common correlations between traits. These two resources were exploited with an existing, statistically consistent method built upon evolutionary concepts. From a new data set with >700 observations on freshwater phytoplankton traits and a qualitative phytoplankton phylogeny, estimates were derived for the size, growth rate, phosphate affinity, and susceptibility to predation of 277 phytoplankton types, from evolutionary ancestors to present-day species. These estimates account simultaneously for phylogenetic relationships between types, as imposed by the phylogeny, and approximate power-law relationships (e.g., allometric scaling laws) between traits, as reconstructed from the data set. Results suggest that most phytoplankton traits are to some extent conserved in evolution: cross-validation demonstrated that the use of phylogenetic information significantly improves trait value estimates. By providing trait value estimates as well as uncertainties, these results could benefit most quantitative studies involving phytoplankton.

An advanced modelling tool for simulating complex river systems

The present paper describes MOHID River Network (MRN), a 1D hydrodynamic model for river networks as part of MOHID Water Modelling System, which is a modular system for the simulation of water bodies (hydrodynamics and water constituents). MRN is capable of simulating water quality in the aquatic and benthic phase and its development was especially focused on the reproduction of processes occurring in temporary river networks (flush events, pools formation, and transmission losses). Further, unlike many other models, it allows the quantification of settled materials at the channel bed also over periods when the river falls dry. These features are very important to secure mass conservation in highly varying flows of temporary rivers. The water quality models existing in MOHID are base on well-known ecological models, such as WASP and ERSEM, the latter allowing explicit parameterization of C, N, P, Si, and O cycles. MRN can be coupled to the basin model, MOHID Land, with computes runoff and porous media transport, allowing for the dynamic exchange of water and materials between the river and surroundings, or it can be used as a standalone model, receiving discharges at any specified nodes (ASCII files of time series with arbitrary time step). These features account for spatial gradients in precipitation which can be significant in Mediterranean-like basins. An interface has been already developed for SWAT basin model.

Modelling the global coastal ocean

Shelf and coastal seas are regions of exceptionally high biological productivity, high rates of biogeochemical cycling and immense socio-economic importance. They are, however, poorly represented by the present generation of Earth system models, both in terms of resolution and process representation. Hence, these models cannot be used to elucidate the role of the coastal ocean in global biogeochemical cycles and the effects global change (both direct anthropogenic and climatic) are having on them. Here, we present a system for simulating all the coastal regions around the world (the Global Coastal Ocean Modelling System) in a systematic and practical fashion. It is based on automatically generating multiple nested model domains, using the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled to the European Regional Seas Ecosystem Model. Preliminary results from the system are presented. These demonstrate the viability of the concept, and we discuss the prospects for using the system to explore key areas of global change in shelf seas, such as their role in the carbon cycle and climate change effects on fisheries.

MODELING THE RELEASE OF DISSOLVED ORGANIC MATTER BY PHYTOPLANKTON(1)

Three models describing dissolved organic matter (DOM) flux and phytoplankton death, each of different levels of complexity, were constructed and tested against experimental data for a cyanobacterium, a chlorophyte, two diatoms, two dinoflagellates, and two prymnesiophytes. The simplest model described only bulk carbon (C) and nitrogen (N) forms of DOM (DOMC and DOMN ) and employed a fixed relationship between phytoplankton nutrient status and DOM release and death rate. The most complex model described fractions of DOM as low molecular weight dissolved organic carbon (DOC; saccharides, low molecular weight carbohydrates [DOCs]), low molecular weight nitrogenous material (comprising C and N as DOC associated with low molecular weight compounds containing amino acids and/or nucleic acids [DOCa] and N associated with DOCa [DONa], which included dissolved free amino acids [DFAA]), and more complex materials (DOC associated with high molecular weight compounds typically requiring extracellular degradation prior to uptake or use by microbes [DOCx] and N associated with DOCx [DONx]). It also employed descriptions of DOM flux and cell death related to nutrient status and growth rates. In all instances, material lysed from dead cells contributed to the DOM pool. All three models captured the gross dynamics of the primary data (dissolved inorganic C [DIC], dissolved inorganic N [DIN], particulate organic carbon [POC], particulate organic N [PON], DOC, dissolved organic N [DON]), but there was little or no improvement of the fit with increasing model complexity. However, the simplest models tended to employ excessively high growth rates to compensate for high fixed death rates. While the proportion of newly fixed C being liberated as DOMC (DOCs plus DOCa) increased as nutrient status declined, the actual rate of release typically did not do so and often declined. The most complex model gave predictions for changes in released saccharides and DFAA in keeping with expectations. The major obstacle to future progress is the lack of suitable, mass balanced data sets for further model testing.

Regional scale impacts of distinct CO(2) additions in the North Sea

A marine system model applied to the North West European shelf seas is used to simulate the consequences of distinct CO(2) additions such as those that could arise from a failure of geological sequestration schemes. The choice of leak scenario is guided by only a small number of available observations and requires several assumptions; hence the simulations reported on are engineered to be worse case scenarios. The simulations indicate that only the most extreme scenarios are capable of producing perturbations that are likely to have environmental consequences beyond the locality of a leak event. Tidally driven mixing rather than air-sea exchange is identified as the primary mechanism for dispersal of added CO(2). We show that, given the available evidence, the environmental impact of a sequestration leak is likely to be insignificant when compared to the expected impact from continued non-mitigated atmospheric CO(2) emissions and the subsequent acidification of the marine system. We also conclude that more research, including both leak simulations and assessment of ecological impacts is necessary to fully understand the impact of CO(2) additions to the marine system.