Yes, We Can! Large-Scale Integrative Assessment of European Regional Seas, Using Open Access Databases

Substantial progress has been made in assessing marine health in an integrative way. However, managers are still reluctant in undertaking such assessments, because: (i) lack of indicators; (ii) absence of targets; (iii) difficulty of aggregating indicators from different ecosystem components, habitats, and areas; (iv) absence of criteria on the number of indicators to be used; (v) discussion on the use of “one-out, all-out” (OOAO) principle in aggregating; and (vi) lack of traceability when integrating data. Our objective was, using open access databases with indicators across all the European seas with agreed targets, to demonstrate if the Nested Environmental status Assessment Tool (NEAT), can be used at the European scale, serving to managers and policy-makers as a tool to assess the environmental status under the Marine Strategy Framework Directive (MSFD). We have used MSFD Descriptor D3 (commercial fish) from 341 stocks, 119 species and two indicators from each of them (years 2013–2015); D5 (eutrophication) with 90th percentile of Chlorophyll-a (years 2009–2014); and D8 (contaminants), with Anthracene, Fluoranthene, Naphthalene, Cadmium, Nickel, and Lead as indicators (years 2009–2013). We have calculated the environmental status for each European subdivision, subregion, and regional sea, nested at different levels. The analyses include weighting and no-weighting by each assessment area; for ecosystem component (water column, phytoplankton, fish, crustaceans, and molluscs); descriptor (three), and habitat (pelagic, demersal/benthic), with the confidence value of the status. A sensitivity analysis was undertaken to determine a minimum number of indicators to include for a robust assessment. We demonstrated that using NEAT in assessing the status of large marine areas, by aggregating indicators, ecosystem components and descriptors, at different spatial scales, can remove at least four out of the six barriers that managers and policy-makers confront when undertaking such assessments. This can be done by using open-access databases and already established targets. Aggregating indicators of different origin is possible. Around 40 indicators seem to be enough to obtain robust assessments. It is better to integrate the assessment items using an ecosystem-based approach, rather than using the OOAO principle. Using NEAT, this approach supports identifying the problematic environmental issues needing management attention and measures

Deliverable D4.4-5: Precision and behaviour of fish-based ecological quality metrics in relation to natural and anthropogenic pressure gradients in European estuaries and lagoons

This report summarises the work conducted in Work Package 4.4 – BQE fish in transitional (i.e. estuarine and lagoon) waters (TW) within the project WISER under the sponsorship of the European Commission. It omits most technical details of the analyses given in the four previous Work Package reports, but still provides the necessary information to understand the rationale, approach and underlying assumptions necessary to discuss the results. The focus is therefore to discuss and integrate the results obtained within Work Package 4.4 and with this, make recommendations to improve fish-based ecological assessments in TW, principally estuaries and lagoons. In addition, and to assist with the WFD implementation which is the overarching theme of WISER, the deliverable includes, where appropriate, case studies where we have used multi-metric fish indices currently under development, or already in use for WFD compliance monitoring across Europe. Furthermore, results of the work package have been shared with relevant Geographical Intercalibration Groups (GIGs) supporting the harmonization and equalization process across transitional fish indices in Europe. Development strategies for fish indices in TW vary but generally include: (1) the calibration of metrics to anthropogenic pressures, (2) the development of reference conditions, (3) the calculation of ecological quality ratios, and (4) the designation of thresholds for Ecological Status (ES) class. New fish indices are developed for a defined geographical area, using specific sampling method and under locally relevant pressure fields. The former two factors, area and sampling methods, define the relevant reference condition in the calculation of Ecological Quality Ratios (EQR) and the latter factor, human pressures, define the índex structure and especially the fish metric selection. To assess index relevance across areas, we calculated a suite of transitional fish indices on a standardized WISER dataset and then compared the agreement of the outcomes (using correlation analysis). The application of current indices to areas (or countries) different from the area in which it was originally developed leads to inconclusive or spurious results. The failure to accommodate the diferente indices to a standardized dataset in this work clearly demonstrates the fundamental reliance of current fish indices on the sampling methods and design of monitoring programmes used in the development of the index. Despite this, for some indices, correlations although weaker are statistically significant, also indicating the possible agreement in successful intercalibration between these indices. Harmonization of BQE fish methodologies across Europe (common metrics) is unlikely by adapting or creating new fish indices but inter-comparison assessments are possible and valid using a common pressure index to harmonise diferente indices on a common scale. We found a negative response of fish quality features to pressure gradients which make BQE fish in TW suitable for greater ecological integration than other BQEs. However, successful assessment of Ecological Status (ES) require a matching combination of fish index, reference values and local dataset gathered with compatible sampling methods. Whole indices provide more consistent overall ES assessments but fish metrics considered individually may be more useful as a means to focus restoration measures. Future work is needed to identify those specific pressures affecting fish assemblages providing targets for minimising the effects of stress in mitigation and restoration plans. In order to achieve this, and although the interpretation of outcomes is still difficult, more recent transitional fish indices are leading in the use of comprehensive appraisal and validation exercises to test the responsiveness of BQEs for the assessment of ES. Here we proposed for the first time a simple sensitivity exercise under realistic scenarios of metric change to explore the expected inertia (i.e. the tendency to buffer ES change after quality alterations), dynamic range (i.e. the ratio between the largest and smallest possible ES values) and most relevant metric components (i.e. the those driving the most likely scenarios leading to ES change) from a multi-metric fish índex under relevant human pressure gradients. Overall, the behaviour of multi-metric índices under manipulations of metric scores clearly indicated that metric type, number of metrics used and correlations between metrics are important in determining the index performance, with indices including more and/or uncorrelated metrics or metrics with skewed distribution being less affected by extreme metric manipulations. Results of this analysis may be used to set realistic management targets and also to identify the aspects of the indices that are more likely to affect the outcomes leading to more robust and responsive indices. Further improvements of fish indices may be attained by reducing the variability confounding biological quality metrics. This variability is undesirable noise in assessments and can be technical (i.e. linked to the method of assessment including sampling effort) or natural (physicochemical and biological). The implication for assessments is that different facts might then confound the metric-pressure correlation (the ‘signal’ in the signal-to-noise ratio in the assessments) increasing uncertainty in ES assignment. Models showed that salinity class, depth, season, time of fishing (day vs. night) and year of fishing may influence the values of the fish metrics. The modelling exercise also demonstrated that unexplained variance remains generally much higher within-systems than between-systems suggesting a higher importance of sources of variability acting at the WB level. Modelling and improved standardization in monitoring campaigns should reduce uncertainty in ES assignment. One important factor that was assessed further was the effect of sampling effort. The results suggest that richness-based metrics require larger sampling efforts although a similar effortrelated bias may be an issue for density-based metrics if fish distribution is very patchy (i.e. schooling fish or those aggregated in specific habitats) and insufficient replicates are taken to fully characterise the patchiness in their distribution. It is apparent that to overcome a potential large source of error, the Reference Conditions must be defined according to the level of effort used in the monitoring programme or, conversely, the monitoring must be carried out at the same level of effort used to derive the Reference Condition. The WP finally explored the use of a predictive linear modelling approach to define reference conditions for fish metrics in transitional waters. The fish response data was modelled together with Corine Land Cover (CLC)-derived pressure proxies (% agricultural, urban and natural land coverage). Based on the obtained models, the expected metric score was predicted by setting pressure levels either to the lowest observed pressure in the dataset or to zero in order to define the sample and theoretical reference condition, respectively. Even when significant, the effect of pressures on fish metrics was generally very weak, probably reflecting the use of too-generic pressure indicators (such as land cover data instead of more relevant estuarine proxies such as dredging, port development, waterborne pollutants, etc). The best explanatory models included sampling factors and natural characteristics considered important discriminant features in the definition of water body types. In particular, the present work argues for considering not only estuaries and lagoons as different typologies but also other natural and design characteristic such as the gear type, the sampling season and the salinity class. Furthermore, a relevant reference needs to account for survey design bias, including rare species contribution to assessment datasets, patchiness, choice of pressure proxies or sampling gear. The modelling approach of fish metrics against the physicochemical variables has proved useful to derive Reference Conditions. This is important for the computation of relevant EQRs in Europe where there is a general lack of pristine areas or historical data on fish BQE and it provides an alternative to best professional judgment. Taking all WP analysis and case studies together, the work conducted has highlighted the following key messages and linked research needs necessary to optimize BQE fish for the quality assessment of transitional waters: Key Message 01: Harmonization of BQE fish methodologies across Europe (common metrics) is unlikely by adapting or creating new fish indices but inter-comparison assessments are possible and valid using a common pressure index to harmonise diferente indices on a common scale. Research needs to be focused on more widely-applicable fish indices will require the formulation of completely new indices based on a more flexible use of fish metrics according to system typologies, relevance and, probably, an increased use of functional traits. For current indices, further research on a method of intercalibration is needed. Key Message 02: BQE Fish in TW respond consistently to human pressure gradients across transitional waters providing the means to assess Ecological Status (ES). Further work will be needed to identify those specific pressures affecting fish assemblages providing targets for minimising the effects of stress in mitigation and restoration plans. Key Message 03 Although the interpretation of outcomes is still difficult, more recente transitional fish indices are leading in the use of comprehensive appraisal and validation exercises to test the performance of BQEs in the assessment of Ecological Status (ES). Further appraisal of fish indices behaviour is needed to understand the meaning of the quality outcomes, to set realistic management targets and also to identify the aspects of the índices that are more likely to affect the outcomes leading to more robust and responsive indices Key Message 04 Uncertainty levels associated with metric variability in multi-metric fish indices can be managed to increase the confidence in Ecological Status (ES) class assignment. Further research is needed to include knowledge of habitat partition within systems, to understand metrics behaviour and precision, to test new combination rules allowing metric weighting by robustness and importantly to evaluate more robust sampling tools and methods. Key Message 05 Reference conditions for BQE fish-based quality assessments can be objectively estimated using predictive modelling. Further refinements will require the use of better pressure proxies, robust metrics amenable to modelling and to account for survey design bias (effort & choice of sampling gear) at the relevant scales used in monitoring programmes.info:eu-repo/semantics/publishedVersio

Distribution and Abundance of Fin whales and other baleen whales in the European Atlantic

The abundance of fin whales (Balaenoptera physalus) and other baleen whales was generated from data collected during shipboard sightings surveys as part of the Cetacean Offshore Distribution and Abundance in the European Atlantic project (CODA). The survey area covered offshore waters beyond the continental shelf of the UK, Ireland, France and Spain. The area was stratified into four blocks and was surveyed by five ships during July 2007. Double platform methods employing the trialconfiguration method (BT-method) were used. Fin, sei (B. borealis) and minke whales (B. acutorostrata) were positively identified, with possible sightings of blue whales (B. musculus). Abundance was estimated for these species and for “large baleen whales” which included fin, sei, fin/sei and blue whales. Abundance for the larger species was estimated using the Mark- Recapture Line Transect design-based method and also model-based methods using density surface modelling. Sample size limitations dictated that conventional line transect sampling methods were used to estimate the abundance of minke whales. Estimates from the two methods were comparable but model-based methods improved the precision and were considered best estimates. The density of large baleen whale species was greatest in the southern end of the survey area and water depth, temperature and distance to the 2000m contour were important predictors of their distribution. The total abundance estimated for the entire survey area was 9,019 (CV=0.11) fin whales and 9,619 (CV= 0.11) large baleen whales. The uncertainty around these estimates due to duplicate classification and species identification were explored. The fin whale estimate is likely to be underestimated because it excludes unidentified large whales, of which a large proportion was likely to have been fin whales. Notwithstanding this, these large baleen whale abundance estimates are the first robust estimates (corrected for responsive movement and g(0)) for this area. The estimated abundance of minke whales was 6,765 (CV=0.99) and sightings were restricted to the northern blocks of the survey area. The minke whale estimate, although imprecise and likely underestimated, does provide a baseline figure for this area and, when considered with results from the SCANS-II continental shelf surveys of July 2005, gives a more comprehensive picture of this species in the European Atlantic. These abundance estimates are important contributions to the conservation and management of these species in the Northeast Atlantic

Deliverable D4.4-3, Report detailing Multimetric fish-based indices sensitivity to anthropogenic and natural pressures, and to metrics’ variation range

The Water Framework Directive (WFD) aims at achieving good ecological status (GES) for surface water bodies throughout Europe, by 2015. Consequently European countries are currently developing and intercalibrating methods based on biological, hydromorphological and physico-chemical quality elements for the assessment of their transitional waters, including fishes. The present work focuses on the response of fish indicators and indices to anthropogenic pressures and natural factors. For doing that, datasets from the Basque and Portuguese estuaries, in the North East Atlantic, have been used. Hence, biological data from fish (and in some cases, crustaceans), together with different types of pressure (population, industry, ports, dredging, global pressures, pollution, channeling, etc.) and hydromorphological data (flow, estuary volume, depth, intertidal surface, residence time, etc.) have been analyzed. Together with fish assemblages composition and individual metrics (richness, trophic composition, etc.), two fish indices (Basque AFI and Portuguese EFAI) have been investigated. Additionally, the response of five fish indices (AFI, EFAI, ELFI, TFCI, Z-EBI) were tested on a common dataset, within Portuguese estuaries, to check the time lag in the metrics’ response to different human pressures and the variability in the strength of responses to those pressures. This work also focuses on the sensitivity analysis of two European fish-based indices (French ELFI and British TFCI) to changes in their respective metric scores through their observed dynamic range. Sensitivity analyses were run simulating different scenarios of metric score changes, taking into consideration the relationship between metrics. This allowed the metrics with stronger influence in the index score and the resulting water body classification to be highlighted. Importantly, the identification of the most influential metrics could help to guide management efforts in terms of achieving GES by 2015. In general, the fish metrics and indices tested responded to anthropogenic pressures in the Atlantic estuarine sites, yet at the individual metrics level environmental chemical quality was the main driver for observed differences. Also, some metrics did not respond to pressures as expected, which is most likely related to sampling gear efficiency, namely the low capture efficiency of diadromous species with beam trawl. The cause-effect relationship study emphasized that fish-based indices developed to assess the water quality of estuarine systems did not detect all the pressures with the same sensitivity in terms of strength and time-lag, and gave more importance to some pressures, namely chemical pollution. The fish-based indices developed to assess the water quality of estuarine systems do not allow the individualization of pressure effects, which may constitute a problem to put forward the correct specific measures for management and rehabilitation of estuaries. On the other hand, some indices also do not seem relevant, in a short time, to detect changes of the ecological quality which may constitute a handicap for management or an indication for their restructuring. The sensitivity analysis indicates that a number of estuarine resident taxa, a number of estuarine-dependent marine taxa, a number of benthic invertebrate feeding taxa and a number of piscivorous taxa have the greatest influence on the TFCI classification. For the French index ELFI, the most influential metrics are mainly DT (total density) and DB (density of benthic species), followed by RT (total richness). These results suggest a high sensitivity of the quality indication provided by these indices on richness related aspects of the fish assemblages. Management should therefore prioritize efforts to conserve or restore estuarine attributes underpinning abundance and ecological diversity, for example the diversity of fish habitats, food resources and shelter or the hydrological integration between coastal and transitional waters.info:eu-repo/semantics/publishedVersio

Abundance of baleen whales in the European Atlantic

The abundance of fin whales (Balaenoptera physalus), sei whales (B. borealis) and minke whales (B. acutorostrata) was estimated from data collected during shipboard sightings surveys conducted as part of CODA and TNASS (Faroese block) in July 2007 in offshore waters of the European Atlantic west of the UK, Ireland, France and Spain, combined with data collected from shipboard and aerial surveys of European Atlantic continental shelf waters conducted as part of SCANS-II in July 2005. Double platform methods employing the trial-configuration method (BT-method) were used in all shipboard surveys. Analysis used Mark-Recapture Distance Sampling to account for animals missed on the transect line. Density surface modelling was undertaken to generate model-based abundance estimates and maps of predicted density. Estimates are presented for the SCANS-II and CODA survey areas. Estimates for the Faroese block of TNASS have been presented elsewhere. The abundance of fin whales in the CODA and SCANS-II areas was estimated as 19,354 (CV 0.24) for identified sightings and 29,512 (CV 0.26) when adjusted to include a proportion of unidentified large whale abundance (which included large baleen and sperm whales), prorated by number of sightings, because there were a large number of such sightings in one of the CODA survey blocks. The model-based estimate of identified fin whales was 19,751 (CV 0.17), more precise than the design-based estimate. Fin whales were mainly found in the southern part of the CODA survey area. Estimates based on identified sightings were comparable to those from the Spanish survey conducted as part of 1989 NASS but were larger if adjusted for a proportion of unidentified large whales. Sei whales were rare except in the southwest of the survey area; the estimate of abundance was 619 (CV 0.34) for identified sightings and 765 (CV 0.43) adjusted for a proportion of unidentified large whales. Minke whale abundance was estimated for shelf and offshore European Atlantic waters as 30,410 (CV 0.34). The model-based estimate was less precise and considerably larger

Cross-basin and cross-taxa patterns of marine community tropicalization and deborealization in warming European seas.

Ocean warming and acidification, decreases in dissolved oxygen concentrations, and changes in primary production are causing an unprecedented global redistribution of marine life. The identification of underlying ecological processes underpinning marine species turnover, particularly the prevalence of increases of warm-water species or declines of cold-water species, has been recently debated in the context of ocean warming. Here, we track changes in the mean thermal affinity of marine communities across European seas by calculating the Community Temperature Index for 65 biodiversity time series collected over four decades and containing 1,817 species from different communities (zooplankton, coastal benthos, pelagic and demersal invertebrates and fish). We show that most communities and sites have clearly responded to ongoing ocean warming via abundance increases of warm-water species (tropicalization, 54%) and decreases of cold-water species (deborealization, 18%). Tropicalization dominated Atlantic sites compared to semi-enclosed basins such as the Mediterranean and Baltic Seas, probably due to physical barrier constraints to connectivity and species colonization. Semi-enclosed basins appeared to be particularly vulnerable to ocean warming, experiencing the fastest rates of warming and biodiversity loss through deborealization

Final report on the “Marine Resource-Environment Carrying Capacity and Spatial Development Suitability” approach application to Europe, showing the Bay of Biscay as an example

The EMODPACE project was approved by the European Commission, with the aim of promoting international ocean governance between EU and China, and support the implementation of global commitments, by making ocean marine data and data products more easily accessible and by providing better data and data products. In this context one of the objectives of EMODPACE is to compare European and Chinese models by analysing the applicability of each side models for ecosystem vulnerability. Hence, applying the Chinese Marine Resource-Environment Carrying Capacity and Spatial Development Suitability approach to a European sea (in this case, the Bay of Biscay) and looking for potential comparison with the Maritime Spatial Planning Directive (MSPD) and the Marine Strategy Framework Directive (MSFD) approaches in Europe, covers the abovementioned objective. The Bay of Biscay was selected because the abundance of data availability and previous transboundary management in the application of the MSPD and MSFD. China has carried out many years of research and application in the fields of carrying capacity, and the official methodology of ‘Marine Resource-Environment Carrying Capacity (MRECC) and Spatial Development Suitability’ developed and applied for MSP in coastal and marine area was adapted to the European context, in terms of the MSFD and the MSPD. The Chinese official methodology was applied to the Bay of Biscay. The methodology involves three different steps: (i) an evaluation of the marine ecological protection (MEP), which includes species and habitats (i.e., biodiversity protection); (ii) an evaluation of the Spatial Development Suitability, identifying the needs for marine activities development and the current use of the sea space; and (iii) an ecological risk identification and the evaluation of the MRECC, by intersecting results from (i) and (ii). After collating information for 31 species of interest (fish, reptiles, mammals and birds), seven habitats (seagrass, seaweeds, saltmarshes, fishery growing areas, tidal flats, estuaries and other unique habitats), marine protected areas and eight current human activities at sea (aquaculture, ports, ocean energy facilities, shipping, aggregate extraction and dredging, fisheries, military areas and tourism and recreation), they were aggregated and intersected (ecological data vs human activities), and the ecological risk was determined. Since the total area covered by Marine Protected Areas and Marine Ecological Protection importance areas is 135,372 km2, the available carrying capacity for marine development activities within the Bay of Biscay is 229,266 km2. Weighting the marine ecological protection and human activities, the importance areas increase and the available carrying capacity decreases 0.2%, being now 228,637 km2. Hence, it has been shown that this methodology is applicable to Europe, but more applications in different areas are needed, as well as improve the information for some species and habitats, in order to obtain more accurate results

Living under stressful conditions: Fish life history strategies across environmental gradients in estuaries

The life history strategies of fishes can be defined by specific combinations of demographic traits that influence species performances depending on environmental features. Hence, the constraints imposed by the local conditions restrict the range of successful strategies by excluding species poorly adapted. In the present study, we compared the demographic strategies of fish caught in 47 estuaries of the North East Atlantic coast, aiming to determine the specific attributes of resident species and test for changes in trait associations along the environmental gradients. Eight demographic traits were considered to project our findings within a conceptual triangular model, composed on three endpoint strategies: (i) periodic (large size, long generation time, high fecundity); (ii) opportunistic (small size, short generation time, high reproductive effort); and (iii) equilibrium (low fecundity, large egg size, parental care). We demonstrated that various life history strategies co-exist in estuaries, but equilibrium species were scarce and restricted to euhaline open-water. Resident species form a specialised assemblage adapted to high spatiotemporal variability of estuarine conditions, i.e. opportunistic attributes associated with parental care. Even with these singular attributes, our findings revealed changes in distribution of resident species across the estuarine gradients linked to their life history traits. Among other patterns, the diversity of life history strategies significantly decreased from euhaline to oligohaline areas and along gradient of human disturbances. These trends were associated with a convergence of species traits toward short generation times, suggesting that long-lived species with late maturation are more severely impacted by disturbance and environmental stress.info:eu-repo/semantics/publishedVersio

Applying the China’s marine resource-environment carrying capacity and spatial development suitability approach to the Bay of Biscay (North-East Atlantic)

The EMOD-PACE project, funded by the European Commission, aimed to promote international ocean governance between EU and China. One of the objectives of EMOD-PACE is to compare European and Chinese modelling approaches for ecosystem vulnerability assessment. In particular, our objective was to test the applicability of the Chinese evaluation approach of resource-environment carrying capacity (MRECC) and spatial development suitability (abbreviated as “double evaluation”) to a European sea (the Bay of Biscay), in the context of marine spatial planning. The methodology involves three different steps: (i) an evaluation of areas of ecological importance, which includes species and habitats (i.e., biodiversity protection) and coastal characteristics; (ii) assessment of current marine development and utilization; and (iii) an ecological risk identification and the evaluation of the MRECC, by intersecting results from (i) and (ii). After collating information for 31 species of interest (fish, reptiles, mammals and birds), seven habitats (seagrass, seaweeds, saltmarshes, fish spawning areas, tidal flats, estuaries and unique habitats), marine protected areas and eight current human activities performed at sea (aquaculture, ports, ocean energy facilities, shipping, aggregate extraction and dredging, fisheries, military areas and tourism and recreation), they were aggregated and intersected (ecological data vs. human activities), and the ecological risk was determined. Since the total area covered by Marine Protected Areas and areas of high ecological importance is 135,372 km2, the available carrying capacity for development of marine activities within the Bay of Biscay is 229,266 km2. When we apply weighting to the calculation of the ecological importance and human activities, the high importance areas increase and the available carrying capacity decreases by 0.2%, to 228,637 km2. In this work we demonstrate that the Chinese double evaluation approach can be adapted and applied to a European sea, but to obtain more accurate results, and more extensive application to different areas are needed. Also, we have identified essential improvements, including better information for a number of species and habitats; more robust methods to identify biodiversity priorities; additional fish life-story traits; include future human activities; risks posed by multiple activities; and use appropriate weights through a stakeholder consultation

Deliverable D4.4-2, part 1: Testing the adaptability and behaviour of 6 fish indices on a common dataset composed of multiple gears samplings from 8 estuaries and lagoons

The Water Framework Directive (WFD) aims at achieving good ecological status for surface waterbodies throughout Europe, by 2015. Consequently European countries are currently developing and intercalibrating methods based on biological, hydromorphological and physicochemical quality elements for the assessment and the monitoring of their rivers, lakes, coastal and transitional waters. In this context, the FP7 WISER project aims to support the implementation of the WFD by contributing (i) to making the existing assessment methods more comparable, and (ii) to estimating the uncertainty along each step of the assessment. The present work focuses on fish indicators for estuaries and lagoons (transitional waters in the WFD). Six fish indices (AFI, EFAI, ELFI, TFCI, BHI, Z-EBI) were tested on a common dataset, covering eight estuaries and lagoons throughout Europe. Fish sampling was carried out using several gears in 2009 and 2010. The objectives were twofold: (i) to test the adaptability of fish indices to different gears and different types of transitional waters; and (ii) to compare the behaviour of the indices with regard to their level of agreement. Five out of the six tested indices were gear-specific and all were specific to some type(s) of transitional waters and have particular data needs. Therefore calculating the indices on a common dataset raised many difficulties, especially regarding the determination of appropriate reference condition values. However, taking some reasonable assumptions it was possible to calculate most of the indices on the majority of the available data, thus showing their relative adaptability. The indication of extreme values for quality (high or bad) was relatively rare and the results of the indices often differed: when used outside of their initial framework, geographical limits or with different sampling methods, fish indices’ results are highly uncertain. This shows that the assessment of quality using fish indicators highly depends on the assessment tool, the sampling methodology and the type of transitional water. Despite these results, some statistically significant correlations between pairs of indices’ results were found, indicating the possibility of intercalibration between some of the tested indices. This work corresponds to the first step of WISER WP4.4 Deliverable 2. In a second step, some fish metrics in the indices tested here will be selected for a more in depth study: the effect of several natural sources of variability on these metrics will be studied and uncertainty will be quantified along the assessment process, from the sampling to final EQS formulation using WiserBugs software..info:eu-repo/semantics/publishedVersio