Marine Evidence-based Sensitivity Assessment (MarESA) – A Guide

The Marine Evidence-based Sensitivity Assessment (MarESA) methodology was developed by the Marine Life Information Network (MarLIN) team at the Marine Biological Association of the UK. The following guide details the approach, its assumptions, and its application to sensitivity assessment. The guide discusses: • key terms used in sensitivity assessment; • the definitions and terms used in the MarESA approach; • its assumptions; • the definition of resistance, resilience and sensitivity; • the definition of pressures and their benchmarks; • the step by step process by which the possible sensitivity of each feature (habitat, biotope or species) to each pressure is assessed; • the interpretation and application of evidence to sensitivity assessments on a pressure by pressure basis; and • limitations in the application of sensitivity assessments in management. The MarESA methodology provides a systematic process to compile and assess the best available scientific evidence to determine each sensitivity assessment. The evidence used is documented throughout the process to provide an audit trail to explain each sensitivity assessment. Unlike other expert-based approaches, this means that the MarESA assessments can be repeated and updated. The resultant 'evidence base' is the ultimate source of information for the application of the sensitivity assessments to management and planning decisions. The MarESA dataset and MarLIN website represent the largest review of the potential effects of human activities and natural events on the marine and coastal habitats of the North East Atlantic yet undertaken

Developing FeAST for mobile marine species.

Background The Feature Activity Sensitivity Tool (FeAST) is hosted on the Marine Scotland (MS) website and supported by Scottish Natural Heritage (SNH) and the Joint Nature Conservation Committee (JNCC). Its purpose is to enable high-level assessment of the sensitivity of features of conservation value, present in Scottish seas, to different pressures resulting from human activities. The overall aim of this project is to enable the FeAST methodology to be adapted for mobile marine species and to consider for which species sensitivity assessment at an individual level, as opposed to the population level, was more appropriate, and why. Main findings Existing approaches to Sensitivity Assessment, including FeAST, Marine Evidence-based Sensitivity Assessment (MarESA) and Highly Mobile Species Sensitivity (HMSS) methods, entail the estimation of changes in population expressed as a percentage of the existing population. They assess the sensitivity of a hypothetical population and are not site-specific. It was difficult to define, categorically, when it is most appropriate to use an individualbased rather than population-based approach to sensitivity assessment. Accordingly, two sets of indicators were identified which tended to favour such an approach. We suggest that Individual-based Sensitivity Assessment (IBSA) should be applied in species where the loss of a single individual (or small number of individuals) has the potential to affect the survival of the population adversely or where legislation protecting the species is implemented on an individual level. Such species are likely to be Kstrategists that are slow to reproduce with a long lifespan, slow growth rates, late reproduction, high parental investment in their young, low fecundity and, probably, small population sizes. We identified those species with legislative protection at an individual level, in Scotland, from criteria and species lists set out in the Wildlife and Countryside Act (W&C) 1981, the Habitats Directive and the Marine (Scotland) Act 2010. All the cetaceans, seals, marine reptiles, sharks and rays listed under W&C 1981 and as European Protected Species would be suitable for IBSA using this approach, together with the otter and notable fin-fish, i.e. the Atlantic sturgeon, Allis shad, Twaite shad and European river lamprey. RESEARCH REPORT Summary ii In addition, the sharks and rays listed as mobile PMFs are also suitable, together with the Atlantic halibut, blue ling, European eel, orange roughy, and round-nose grenadier. A list of another seven fin-fish requires further consideration. The remaining fin-fish listed as PMFs are probably not suitable under our suggested indicators. However, the life history characteristics examined represent a short review of the characteristics that influence population recovery and do not take into account larval/juvenile mortality, recruitment, population dynamics, or restricted breeding sites such as nursery areas in fish or rivers and estuaries in anadromous fish. In addition, the cut-off values for life history characteristics are subjective rather than definitive. Further study is required to expand and test the application of the above list of indicators and the IBSA approach to a wider range of species than considered here. An individual-based tolerance scale is suggested. We avoided a binary scale (dead/alive) and suggested a scale from ‘dead’ through different levels of impairments due to physical injury and behavioural changes. We slightly amended the existing FeAST recovery scale to emphasize its application to the recovery of individuals rather than that of populations. The FeAST sensitivity matrix was also amended slightly to highlight the fact that no recovery was possible from direct mortality. The existing FeAST scales for ‘confidence’ and ‘evidence’ were adopted. The suggested individual-based approach was tested on two pilot species: Risso’s dolphin and the harbour seal. Contrary to initial concerns, the suggested scales did not result in binary scores, that is, just mortality or no mortality. Both pilot assessments gave a range of scores for tolerance, recovery and, hence, sensitivity. Assessing on an individual level was found to simplify the assessment of tolerance. It was often very straightforward to assess whether an individual was likely to suffer injury or mortality from an impact. The suggested individual-based approach does not take the likelihood of the impact occurring or the extent of the impact into account at any point. Many of the pressures to which the assessed species are highly sensitive may be very unlikely to have a population level impact, due to their low likelihood of occurrence. It should also be noted that the revision of benchmarks and scales for highly mobile species in FeAST means that the resultant sensitivity assessment will differ from those generated under the MarESA and HMSS approaches, and that their sensitivity scores for the same species will not be directly comparable. Overall, the suggested Individual-based Sensitivity Assessment (IBSA) approach was used successfully to assess the sensitivity of two highly mobile species. More species need to be assessed to test the approach fully and to develop examples and guidance on the application of the individual-based tolerance scale to other highly mobile specie

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