How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.

A global ocean observing system framework for sustainable development

Sustainable development depends on maintaining ecosystem services which are concentrated in coastal marine and estuarine ecosystems. Analyses of the science needed to manage human uses of ecosystem services have concentrated on terrestrial ecosystems. Our focus is on the provision of multidisciplinary data needed to inform adaptive, ecosystem-based approaches (EBAs) for maintaining coastal ecosystem services based on comparative ecosystem analyses. Key indicators of pressures on coastal ecosystems, ecosystem states and the impacts of changes in states on services are identified for monitoring and analysis at a global coastal network of sentinel sites nested in the ocean-climate observing system. Biodiversity is targeted as the “master” indicator because of its importance to a broad spectrum of services. Ultimately, successful implementation of EBAs will depend on establishing integrated, holistic approaches to ocean governance that oversee the development of integrated, operational ocean observing systems based on the data and information requirements specified by a broad spectrum of stakeholders for sustainable development. Sustained engagement of such a spectrum of stakeholders on a global scale is not feasible. The global coastal network will need to be customized locally and regionally based on priorities established by stakeholders in their respective regions. The E.U. Marine Strategy Framework Directive and the U.S. Recommendations of the Interagency Ocean Policy Task Force are important examples of emerging regional scale approaches. The effectiveness of these policies will depend on the co-evolution of ocean policy and the observing system under the auspices of integrated ocean governance.

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

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).

Enhancing the Global Ocean Observing System to meet evidence based needs for the ecosystem-based management of coastal ecosystem services

Ecosystem-based approaches (EBAs) to managing anthropogenic pressures on ecosystems, adapting to changes in ecosystem states (indicators of ecosystem health), and mitigating the impacts of state changes on ecosystem services are needed for sustainable development. EBAs are informed by integrated ecosystem assessments (IEAs) that must be compiled and updated frequently for EBAs to be effective. Frequently updated IEAs depend on the sustained provision of data and information on pressures, state changes, and impacts of state changes on services. Nowhere is this truer than in the coastal zone, where people and ecosystem services are concentrated and where anthropogenic pressures converge. This study identifies the essential indicator variables required for the sustained provision of frequently updated IEAs, and offers an approach to establishing a global network of coastal observations within the framework of the Global Ocean Observing System. The need for and challenges of capacity-building are highlighted, and examples are given of current programmes that could contribute to the implementation of a coastal ocean observing system of systems on a global scale. This illustrates the need for new approaches to ocean governance that can achieve coordinated integration of existing programmes and technologies as a first step towards this goal.

Altered Lipid Accumulation in Nannochlropsis Salina CCAP849/3 Following EMS and UV Induced Mutagenesis

Microalgae have potential as a chemical feed stock in a range of industrial applications. Nannochloropsis salina was subject to EMS mutagenesis and the highest lipid containing cells selected using fluorescence-activated cell sorting. Assessment of growth, lipid content and fatty acid composition identified mutant strains displaying a range of altered traits including changes in the PUFA content and a total FAME increase of up to 156% that of the wild type strain. Combined with a reduction in growth this demonstrated a productivity increase of up to 76%. Following UV mutagenesis, lipid accumulation of the mutant cultures was elevated to more than 3 fold that of the wild type strain, however reduced growth rates resulted in a reduction in overall productivity. Changes observed are indicative of alterations to the regulation of the omega 6 Kennedy pathway. The importance of these variations in physiology for industrial applications such as biofuel production is discussed.

On the Potential of Surfers to Monitor Environmental Indicators in the Coastal Zone

The social and economic benefits of the coastal zone make it one of the most treasured environments on our planet. Yet it is vulnerable to increasing anthropogenic pressure and climate change. Coastal management aims to mitigate these pressures while augmenting the socio-economic benefits the coastal region has to offer. However, coastal management is challenged by inadequate sampling of key environmental indicators, partly due to issues relating to cost of data collection. Here, we investigate the use of recreational surfers as platforms to improve sampling coverage of environmental indicators in the coastal zone. We equipped a recreational surfer, based in the south west United Kingdom (UK), with a temperature sensor and Global Positioning System (GPS) device that they used when surfing for a period of one year (85 surfing sessions). The temperature sensor was used to derive estimates of sea-surface temperature (SST), an important environmental indicator, and the GPS device used to provide sample location and to extract information on surfer performance. SST data acquired by the surfer were compared with data from an oceanographic station in the south west UK and with satellite observations. Our results demonstrate: (i) high-quality SST data can be acquired by surfers using low cost sensors; and (ii) GPS data can provide information on surfing performance that may help motivate data collection by surfers. Using recent estimates of the UK surfing population, and frequency of surfer participation, we speculate around 40 million measurements on environmental indicators per year could be acquired at the UK coastline by surfers. This quantity of data is likely to enhance coastal monitoring and aid UK coastal management. Considering surfing is a world-wide sport, our results have global implications and the approach could be expanded to other popular marine recreational activities for coastal monitoring of environmental indicators.

The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM

Ecosystem models are often assessed using quantitative metrics of absolute ecosystem state, but these model-data comparisons are disproportionately vulnerable to discrepancies in the location of important circulation features. An alternative method is to demonstrate the models capacity to represent ecosystem function; the emergence of a coherent natural relationship in a simulation indicates that the model may have an appropriate representation of the ecosystem functions that lead to the emergent relationship. Furthermore, as emergent properties are large-scale properties of the system, model validation with emergent properties is possible even when there is very little or no appropriate data for the region under study, or when the hydrodynamic component of the model differs significantly from that observed in nature at the same location and time. A selection of published meta-analyses are used to establish the validity of a complex marine ecosystem model and to demonstrate the power of validation with emergent properties. These relationships include the phytoplankton community structure, the ratio of carbon to chlorophyll in phytoplankton and particulate organic matter, the ratio of particulate organic carbon to particulate organic nitrogen and the stoichiometric balance of the ecosystem. These metrics can also inform aspects of the marine ecosystem model not available from traditional quantitative and qualitative methods. For instance, these emergent properties can be used to validate the design decisions of the model, such as the range of phytoplankton functional types and their behaviour, the stoichiometric flexibility with regards to each nutrient, and the choice of fixed or variable carbon to nitrogen ratios.

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The ERSEM model is one of the most established ecosystem models for the lower trophic levels of the marine food-web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North-Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic part of the marine ecosystem, including the microbial food-web, the carbonate system and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case-studies of mesocosm type simulations, water column implementations and a brief example of a full-scale application for the North-West European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

Marine regime shifts in ocean biogeochemical models: a case study in the Gulf of Alaska

Regime shifts have been reported in many marine ecosystems, and are often expressed as an abrupt change occurring in multiple physical and biological components of the system. In the Gulf of Alaska, a regime shift in the late 1970s was observed, indicated by an abrupt increase in sea surface temperature and major shifts in the catch of many fish species. This late 1970s regime shift in the Gulf of Alaska was followed by another shift in the late 1980s, not as pervasive as the 1977 shift, but which nevertheless did not return to the prior state. A thorough understanding of the extent and mechanisms leading to such regime shifts is challenged by data paucity in time and space. We investigate the ability of a suite of ocean biogeochemistry models of varying complexity to simulate regime shifts in the Gulf of Alaska by examining the presence of abrupt changes in time series of physical variables (sea surface temperature and mixed layer depth), nutrients and biological variables (chlorophyll, primary productivity and plankton biomass) using change-point analysis. Our study demonstrates that ocean biogeochemical models are capable of simulating the late 1970s shift, indicating an abrupt increase in sea surface temperature forcing followed by an abrupt decrease in nutrients and biological productivity. This predicted shift is consistent among all the models, although some of them exhibit an abrupt transition (i.e. a significant shift from one year to the next), whereas others simulate a smoother transition. Some models further suggest that the late 1980s shift was constrained by changes in mixed layer depth. Our study demonstrates that ocean biogeochemical can successfully simulate regime shifts in the Gulf of Alaska region, thereby providing better understanding of how changes in physical conditions are propagated from lower to upper trophic levels through bottom-up controls.

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient–phytoplankton–zooplankton–detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry–climate interactions.

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The European Regional Seas Ecosystem Model (ERSEM) is one of the most established ecosystem models for the lower trophic levels of the marine food web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic parts of the marine ecosystem, including the microbial food web, the carbonate system, and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case studies of mesocosm-type simulations, water column implementations, and a brief example of a full-scale application for the north-western European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.