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.

Influence of light in the mixed-layer on the parameters of a three-component model of phytoplankton size class

Phytoplankton size structure is an important indicator of the state of the pelagic ecosystem. Stimulated by the paucity of in situ observations on size structure, and by the sampling advantages of autonomous remote platforms, new efforts are being made to infer the size-structure of the phytoplankton from oceanographic variables that may be measured at high temporal and spatial resolution, such as total chlorophyll concentration. Large-scale analysis of in situ data has revealed coherent relationships between size-fractionated chlorophyll and total chlorophyll that can be quantified using the three-component model of Brewin et al. (2010). However, there are variations surrounding these general relationships. In this paper, we first revise the three-component model using a global dataset of surface phytoplankton pigment measurements. Then, using estimates of the average irradiance in the mixed-layer, we investigate the influence of ambient light on the parameters of the three-component model. We observe significant relationships between model parameters and the average irradiance in the mixed-layer, consistent with ecological knowledge. These relationships are incorporated explicitly into the three-component model to illustrate variations in the relationship between size-structure and total chlorophyll, ensuing from variations in light availability. The new model may be used as a tool to investigate modifications in size-structure in the context of a changing climate.

Conceptual Ecological Modelling of Sublittoral Rock Habitats to Inform Indicator Selection

The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.

The potential use of mapped extent and distribution of habitats as indicators of Good Environmental Status (GES)

The Healthy and Biologically Diverse Seas Evidence Group (HBDSEG) has been tasked with providing the technical advice for the implementation of the Marine Strategy Framework Directive (MSFD) with respect to descriptors linked to biodiversity. A workshop was held in London to address one of the Research and Development (R&D) proposals entitled: ‘Mapping the extent and distribution of habitats using acoustic and remote techniques, relevant to indicators for area/extent/habitat loss.’ The aim of the workshop was to identify, define and assess the feasibility of potential indicators of benthic habitat distribution and extent, and identify the R&D work which could be required to fully develop these indicators. The main points that came out of the workshop were: (i) There are many technical aspects of marine habitat mapping that still need to be resolved if cost-effective spatial indicators are to be developed. Many of the technical aspects that need addressing surround issues of consistency, confidence and repeatability. These areas should be tackled by the JNCC Habitat Mapping and Classification Working Group and the HBDSEG Seabed Mapping Working Group. (ii) There is a need for benthic ecologists (through the HBDSEG Benthic Habitats Subgroup and the JNCC Marine Indicators Group) to finalise the list of habitats for which extent and/or distribution indicators should be considered for development, building upon the recommendations from this report. When reviewing the list of indicators, benthic habitats could also be distinguished into those habitats that are defined/determined primarily by physical parameters (although including biological assemblages) (e.g. subtidal shallow sand) and those defined primarily by their biological assemblage (e.g. seagrass beds). This distinction is important as some anthropogenic pressures may influence the biological component of the ecosystem despite not having a quantifiable effect on the physical habitat distribution/extent. (iii) The scale and variety of UK benthic habitats makes any attempt to undertake comprehensive direct mapping exercises prohibitively expensive (especially where there is a need for repeat surveys for assessment). There is a clear need therefore to develop a risk-based approach that uses indirect indicators (e.g. modelling), such as habitats at risk from pressures caused by current human activities, to develop priorities for information gathering. The next steps that came out of the workshop were: (i) A combined approach should be developed by the JNCC Marine Indicators Group together with the HBDSEG Benthic Habitats Subgroup, which will compile and ultimately synthesise all the criteria used by the three different groups from the workshop. The agreed combined approach will be used to undertake a final review of the habitats considered during the workshop, and to evaluate any remaining habitats in order to produce a list of habitats for indicator development for which extent and/or distribution indicators could be appropriate. (ii) The points of advice raised at this workshop, alongside the combined approach aforementioned, and the final list of habitats for extent and/or distribution indicator development will be used to develop a prioritised list of actions to inform the next round of R&D proposals for benthic habitat indicator development in 2014. This will be done through technical discussions within JNCC and the relevant HBDSEG Subgroups. The preparation of recommendations by these groups should take into account existing work programmes, and consider the limited resources available to undertake any further R&D work.

An Objective Framework to Test the Quality of Candidate Indicators of Good Environmental Status

Large efforts are on-going within the EU to prepare the Marine Strategy Framework Directive’s (MSFD) assessment of the environmental status of the European seas. This assessment will only be as good as the indicators chosen to monitor the eleven descriptors of good environmental status (GEnS). An objective and transparent framework to determine whether chosen indicators actually support the aims of this policy is, however, not yet in place. Such frameworks are needed to ensure that the limited resources available to this assessment optimize the likelihood of achieving GEnS within collaborating states. Here, we developed a hypothesis-based protocol to evaluate whether candidate indicators meet quality criteria explicit to the MSFD, which the assessment community aspires to. Eight quality criteria are distilled from existing initiatives, and a testing and scoring protocol for each of them is presented. We exemplify its application in three worked examples, covering indicators for three GEnS descriptors (1, 5 and 6), various habitat components (seaweeds, seagrasses, benthic macrofauna and plankton), and assessment regions (Danish, Lithuanian and UK waters). We argue that this framework provides a necessary, transparent and standardized structure to support the comparison of candidate indicators, and the decision-making process leading to indicator selection. Its application could help identify potential limitations in currently available candidate metrics and, in such cases, help focus the development of more adequate indicators. Use of such standardized approaches will facilitate the sharing of knowledge gained across the MSFD parties despite context-specificity across assessment regions, and support the evidence-based management of European seas.

An Objective Framework to Test the Quality of Candidate Indicators of Good Environmental Status

Large efforts are on-going within the EU to prepare the Marine Strategy Framework Directive’s (MSFD) assessment of the environmental status of the European seas. This assessment will only be as good as the indicators chosen to monitor the eleven descriptors of good environmental status (GEnS). An objective and transparent framework to determine whether chosen indicators actually support the aims of this policy is, however, not yet in place. Such frameworks are needed to ensure that the limited resources available to this assessment optimize the likelihood of achieving GEnS within collaborating states. Here, we developed a hypothesis-based protocol to evaluate whether candidate indicators meet quality criteria explicit to the MSFD, which the assessment community aspires to. Eight quality criteria are distilled from existing initiatives, and a testing and scoring protocol for each of them is presented. We exemplify its application in three worked examples, covering indicators for three GEnS descriptors (1, 5 and 6), various habitat components (seaweeds, seagrasses, benthic macrofauna and plankton), and assessment regions (Danish, Lithuanian and UK waters). We argue that this framework provides a necessary, transparent and standardized structure to support the comparison of candidate indicators, and the decision-making process leading to indicator selection. Its application could help identify potential limitations in currently available candidate metrics and, in such cases, help focus the development of more adequate indicators. Use of such standardized approaches will facilitate the sharing of knowledge gained across the MSFD parties despite context-specificity across assessment regions, and support the evidence-based management of European seas.