Impact of human activities on benthic biotopes and species

Executive Summary 1. The Marine Life Information Network (MarLIN) has been developed since 1998. Defra funding has supported a core part of its work, the Biology and Sensitivity Key Information Sub-programme. This report relates to Biology and Sensitivity work for the period 2001-2004. 2. MarLIN Biology and Sensitivity research takes information on the biology of species to identify the likely effects of changing environmental conditions linked to human activities on those species. In turn, species that are key functional, key structural, dominant, or characteristic in a biotope (the habitat and its associated species) are used to identify biotope sensitivity. Results are displayed over the World Wide Web and can be accessed via a range of search tools that make the information of relevance to environmental management. 3. The first Defra contract enabled the development of criteria and methods of research, database storage methods and the research of a wide range of species. A contract from English Nature and Scottish Natural Heritage enabled biotopes relevant to marine SACs to be researched. 4. Defra funding in 2001-2004 has especially enabled recent developments to be targeted for research. Those developments included the identification of threatened and declining species by the OSPAR Biodiversity Committee, the development of a new approach to defining sensitivity (part of the Review of Marine Nature Conservation), and the opportunity to use Geographical Information Systems (GIS) more effectively to link survey data to MarLIN assessments of sensitivity. 5. The MarLIN database has been developed to provide a resource to 'pick-and-mix' information depending on the questions being asked. Using GIS, survey data that provides locations for species and biotopes has been linked to information researched by MarLIN to map the likely sensitivity of an area to a specified factor. Projects undertaken for the Irish Sea pilot (marine landscapes), in collaboration with CEFAS (fishing impacts) and with the Countryside Council for Wales (oil spill response) have demonstrated the application of MarLIN information linked to survey data in answering, through maps, questions about likely impacts of human activities on seabed ecosystems. 6. GIS applications that use MarLIN sensitivity information give meaningful results when linked to localized and detailed survey information (lists of species and biotopes as point source or mapped extents). However, broad landscape units require further interpretation. 7. A new mapping tool (SEABED map) has been developed to display data on species distributions and survey data according to search terms that might be used by an environmental manager. 8. MarLIN outputs are best viewed on the Web site where the most up-to-date information from live databases is available. The MarLIN Web site receives about 1600 visits a day. 9. The MarLIN approach to assessing sensitivity and its application to environmental management were presented in papers at three international conferences during the current contract and a 'touchstone' paper is to be published in the peer-reviewed journal Hydrobiologia. The utility of MarLIN information for environmental managers, amongst other sorts of information, has been described in an article in Marine Pollution Bulletin. 10. MarLIN information is being used to inform the identification of potential indicator species for implementation of the Water Framework Directive including initiatives by ICES. 11. Non-Defra funding streams are supporting the updating of reviews and increasing the amount of peer review undertaken; both of which are important to the maintenance of the resource. However, whilst MarLIN information is sufficiently wide ranging to be used in an 'operational' way for marine environmental protection and management, new initiatives and the new biotopes classification have introduced additional species and biotopes that will need to be researched in the future. 12. By the end of the contract, the Biology and Sensitivity Key Information database contained full Key Information reviews on 152 priority species and 117 priority biotopes, together with basic information on 412 species; a total of 564 marine benthic species.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.

Light enhanced amino acid uptake by dominant bacterioplankton groups in surface waters of the Atlantic Ocean

35S-Methionine and 3H-leucine bioassay tracer experiments were conducted on two meridional transatlantic cruises to assess whether dominant planktonic microorganisms use visible sunlight to enhance uptake of these organic molecules at ambient concentrations. The two numerically dominant groups of oceanic bacterioplankton were Prochlorococcus cyanobacteria and bacteria with low nucleic acid (LNA) content, comprising 60% SAR11-related cells. The results of flow cytometric sorting of labelled bacterioplankton cells showed that when incubated in the light, Prochlorococcus and LNA bacteria increased their uptake of amino acids on average by 50% and 23%, respectively, compared with those incubated in the dark. Amino acid uptake of Synechococcus cyanobacteria was also enhanced by visible light, but bacteria with high nucleic acid content showed no light stimulation. Additionally, differential uptake of the two amino acids by the Prochlorococcus and LNA cells was observed. The populations of these two types of cells on average completely accounted for the determined 22% light enhancement of amino acid uptake by the total bacterioplankton community, suggesting a plausible way of harnessing light energy for selectively transporting scarce nutrients that could explain the numerical dominance of these groups in situ.

Late winter under ice pelagic microbial communities in the high Arctic Ocean and the impact of short-term exposure to elevated CO2 levels

Polar Oceans are natural CO2 sinks because of the enhanced solubility of CO2 in cold water. The Arctic Ocean is at additional risk of accelerated ocean acidification (OA) because of freshwater inputs from sea ice and rivers, which influence the carbonate system. Winter conditions in the Arctic are of interest because of both cold temperatures and limited CO2 venting to the atmosphere when sea ice is present. Earlier OA experiments on Arctic microbial communities conducted in the absence of ice cover, hinted at shifts in taxa dominance and diversity under lowered pH. The Catlin Arctic Survey provided an opportunity to conduct in situ, under-ice, OA experiments during late Arctic winter. Seawater was collected from under the sea ice off Ellef Ringnes Island, and communities were exposed to three CO2 levels for 6 days. Phylogenetic diversity was greater in the attached fraction compared to the free-living fraction in situ, in the controls and in the treatments. The dominant taxa in all cases were Gammaproteobacteria but acidification had little effect compared to the effects of containment. Phylogenetic net relatedness indices suggested that acidification may have decreased the diversity within some bacterial orders, but overall there was no clear trend. Within the experimental communities, alkalinity best explained the variance among samples and replicates, suggesting subtle changes in the carbonate system need to be considered in such experiments. We conclude that under ice communities have the capacity to respond either by selection or phenotypic plasticity to heightened CO2 levels over the short term.

Assessing the sensitivity of subtidal sedimentary habitats to pressures associated with marine activities. Phase 1 Report: Rationale and proposed ecological groupings for Level 5 biotopes against which sensitivity assessments would be best undertaken.

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.