Clustering Event I - Co-production of Policy Recommendations - Bridging Physics and Biology & Ecosystem Ocean Science - Deliverable 6.3

Funded by the European Union under Grant Agreement number 101136748. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Agency (REA). Neither the European Union nor the granting authority can be held responsible for them. Deliverable 6.3 Clustering Event I Co-production of Policy Recommendations - Bridging Physics and Biology & Ecosystem Ocean Science April 2025 Authors: Deniz Karaca, Said Hashim, Lisandro Benedetti-Checci, Patrick Lehodey, Nina Lepola, Florian Lüskow, Elizabeth Lawrence, Bianca Reis, Marja Koski, Monika Kedra, Dimitris Poursanidis, Ronan McAdam, Joana Soares, Lina Mtwana Nordlund Ref. Ares(2025)10648956 - 03/12/2025 Deliverable 6.3 Clustering Event I 2 Project Information Project full title: Co-Creating Transformative Pathways to Biological and Ecosystem Ocean Observations Project acronym: BioEcoOcean Grant agreement number: 101136748 Project start date and duration: 1st of February 2024, 48 months Project website: https://bioecoocean.org/ Project Coordinator: Lina Mtwana Nordlund, Uppsala University Deliverable information Deliverable number: 6.3 Deliverable title: Clustering Event I - Co-production of Policy Recommendations - Bridging Physics and Biology & Ecosystem Ocean Science Submission date: 30/04/2025 Level of dissemination: Public Work package and task: WP6, Task 6.4 Lead Beneficiary: EuroGOOS Authors: Deniz Karaca (EuroGOOS), Said Hashim (UU), Lisandro BenedettiChecci (UNIPI), Patrick Lehodey (MOi), Nina Lepola (UU), Florian Lüskow(UU), Elizabeth Lawrence (UNESCO-OBIS), Bianca Reis, Marja Koski (DTU), Monika Kedra (IO PAN), Dimitris Poursanidis (C-Blues), Ronan McAdam (ObsSea4Clim), Joana Soares (Air Centre), Lina Mtwana Nordlund (UU) Reviewers: Artur Palacz (IO PAN), Chiara Bearzotti (ObsSea4CLim) To be cited as: Karaca, Deniz; Hashim, Said; Benedetti-Checci, Lisandro; Lehodey, Patrick; Lüskow, Florian; Lepola, Nina; Lawrance, Elizabeth; Reis, Bianca; Koski, Marja; Kedra, Monika; Poursanidis, Dimitris; McAdam, Ronan; Soares, Joana; Nordlund, Lina Mtwana (2025). Clustering Event I - Co-production of Policy Recommendations - Bridging Physics and Biology & Ecosystem Ocean Science. BioEcoOcean Project Deliverable Report D6.3. https://10.5281/zenodo.17789946 Deliverable 6.3 Clustering Event I 3 Executive Summary This deliverable presents the outcomes of the first clustering event jointly organised by the Horizon Europe projects BioEcoOcean and ObsSea4Clim, aimed at advancing ocean observation strategies through the coproduction of policy recommendations. The report addresses critical challenges in current ocean observing systems and monitoring frameworks, emphasising the need for a more integrated, standardised, and interdisciplinary approach to observing physical, biogeochemical, and biological components of the ocean system. A core focus is the systematic implementation and operationalisation of Essential Ocean Variables (EOVs), managed by the Global Ocean Observing System (GOOS). EOVs provide a globally recognised framework for harmonising observations across disciplines and supporting evidence-based policy development. While EOVs for physical and biogeochemical variables are relatively mature, biological and ecosystem EOVs remain underrepresented, limiting the capacity to assess climate-driven changes in marine ecosystems and constraining biodiversity conservation strategies. The clustering event convened about 25 partner organizations across Europe, representing over 30 international initiatives and projects, to identify barriers and propose solutions to strengthen global ocean observing systems. Key issues addressed include fragmented observation efforts, data integration challenges across spatial and temporal scales, and the lack of standardised methodologies, particularly regarding biological observations. Bridging Land, Coastal, and Ocean Observing Systems was one focus during the event. Marine Heatwaves (MHWs) were used as a central case, both during the event and beyond to illustrate the complex interactions between physics and biology & ecosystem impacts, highlighting the need for coordinated and comprehensive observation strategies. In response to these challenges, the report advocates for an integrated suite of policy recommendations. It calls for expanding the application of EOVs, particularly by advancing the integration of biological and ecosystem variables alongside physical and biogeochemical data. It promotes upgrading and diversifying observation platforms, enhancing the linkage between satellite and in situ systems, and addressing scale mismatches, applying downscaling methodologies that can translate global datasets into regionally actionable insights. The report emphasises the need to harmonise data collection protocols under FAIR (Findable, Accessible, Interoperable, Reusable) principles to facilitate data sharing and meta-analyses, and highlights the potential of Artificial Intelligence (AI) and advanced data analytics to overcome current observational constraints and improve forecasting capabilities. Furthermore, it stresses the importance of enhancing interdisciplinary collaboration and capacity building, through regular workshops and stakeholder engagement, as essential mechanisms for ensuring that scientific insights are effectively translated into policy measures. Ultimately, the report underscores that by adopting an integrated, multidisciplinary, interdisciplinary, and transdisciplinary approach to ocean observation and data integration, policymakers can significantly improve marine conservation strategies, Deliverable 6.3 Clustering Event I 4 strengthen climate resilience, and contribute to the sustainable management of ocean resources. These actions directly align with key European policy objectives, including the EU Mission: Restore our Ocean and Waters, the European Green Deal, and the development of a Digital Twin of the Ocean (DTO), while supporting broader international environmental frameworks and global socio-economic stability. Deliverable 6.3 Clustering Event I 5 Table of Contents Executive Summary ......................................................................................................................................................... 3 Abbreviations .................................................................................................................................................................. 7 1. Introduction ............................................................................................................................................................ 8 1.1 EOVs and their role in policy development .......................................................................................................... 9 1.2 The Need for a Co-Design and Co-Production Approach.................................................................................... 10 2. Bridging Physics and Biology & Ecosystem Ocean Science - Exemplified by marine heatwaves and their impacts on marine life ................................................................................................................................................................ 11 2.1 Socio-economic impact of MHWs in relation to biology & ecosystems ............................................................. 12 2.2 Case studies of effects of MHWs on biology & ecosystems ............................................................................... 13 2.2.1 Seagrass Under Siege: MHWs, Algal Blooms, and Coastal Decline .............................................................. 14 2.2.2 Biodiverse macroalgal forests at risk ........................................................................................................... 14 2.2.3 MHW induced compositional shift in Iberian Kelp Forests .......................................................................... 15 2.2.4 The Blob and the Rise of Pyrosomes: Disrupting the Northeast Pacific Food Web ..................................... 16 2.2.5 MHWs and their role in the Arctic ecosystems............................................................................................ 17 2.2.6 Effects of MHWs on Arctic Zooplankton ...................................................................................................... 17 2.2.7 Understanding Zooplankton and MHWs in the Mediterranean .................................................................. 18 2.3 Identification of critical EOV Sub-variables ......................................................................................................... 19 2.4 Current state of links between MHWs and OBIS ................................................................................................ 20 3. Clustering Event I - Deep Dive into the Blue Frontier .............................................................................................. 21 3.1 Objectives and Structure of Clustering Event I ................................................................................................... 21 3.2 Introducing the sister projects ............................................................................................................................ 22 3.3 Essential Ocean Variables: Physics and Biology & Ecosystems (the EOV speed dating) .................................... 23 3.4 Bridging Land, Coastal, and Ocean Observing Systems – Integrating Physical, Biogeochemical, and Biological Data for Comprehensive Data Products ................................................................................................................... 26 3.5 MHWs in space and time: understanding thermal anomalies at ecologically relevant scale ............................ 28 3.6 Identification of key issues and barriers in ocean observing .............................................................................. 29 3.6.1. Key Challenges in Ocean Observations ....................................................................................................... 29 3.6.2. Potential Solutions for Improved Ocean Observations .............................................................................. 30 4. Co-production of Policy Recommendations ............................................................................................................. 31 4.1 Policy recommendations brought forward from this process ............................................................................ 31 4.1.1 Support and encourage the use of EOVs ..................................................................................................... 31 4.1.2 Upgrade and Diversify Observation Platforms ............................................................................................ 32 4.1.3 Addressing Scale Mismatch ......................................................................................................................... 32 Deliverable 6.3 Clustering Event I 6 4.1.4 Implement Downscaling and Targeted Observation Strategies .................................................................. 32 4.1.5 Support for Integrated Ocean Observing Systems ...................................................................................... 33 4.1.6 Standardisation of Data Collection Protocols .............................................................................................. 33 4.1.7 Investment in AI and Data Analytics ............................................................................................................ 33 4.1.8 Adopt FAIR Data Principles and Enhance Dataset Integration .................................................................... 33 4.1.9 Promote Low-Cost Sensor Development and Citizen Science Initiatives .................................................... 34 4.1.10 Encourage Cross-Sectoral Collaboration .................................................................................................... 34 4.1.11 Regular interdisciplinary workshops and trainings .................................................................................... 34 4.1.12 Incorporate Biogeochemical and Biological Data ...................................................................................... 35 4.1.13 Integrate biological responses to exceptional warm periods .................................................................... 35 4.1.14 Identification of indicator species for MHWs ............................................................................................ 35 4.2 Summary of policy recommendations ................................................................................................................ 36 5. The way forward ....................................................................................................................................................... 37 6. Acknowledgements ................................................................................................................................................... 37 7. References ................................................................................................................................................................ 38 Deliverable 6.3 Clustering Event I 7 Abbreviations Abbreviation Definition AI Artificial Intelligence AMOC Atlantic Meridional Overturning Circulation DTO Digital Twin of the Ocean EMODnet Copernicus Marine Service and European Marine Observation and Data Network EMSO European Multidisciplinary Seafloor and water-column Observatory EOV Essential Ocean Variable FAIR Findable, Accessible, Interoperable, Reusable GOOS Global Ocean Observing System MHWs Marine Heatwaves OBIS Ocean Biodiversity Information System SDGs UN Sustainable Development Goals SST Sea surface temperature WoRMS World Register of Marine Species Deliverable 6.3 Clustering Event I 8 1. Introduction The global ocean plays a fundamental role in climate regulation, biodiversity maintenance and global socioeconomic stability (Muller-Karger et al., 2024; Visbeck, 2018). However, anthropogenic pressures, including climate change, pollution, and habitat degradation, have significantly altered oceanic processes and states. Therefore, stronger collaboration across disciplines and robust multidisciplinary monitoring frameworks to assess changes in marine systems are required (e.g., Levin et al., 2019; Miloslavish et al., 2024). To meet this challenge, ocean research must be increasingly multi-, interand transdisciplinary, combining expertise across domains to develop and advance our understanding of the ocean. Furthermore, there is a need to develop and operationalise Essential Ocean Variables (EOVs) which provide a standardised framework for observing and understanding the ocean system, encompassing physical variables (e.g., temperature, salinity), biogeochemical variables (e.g., Dissolved Oxygen, Particulate Organic Matter), and biology & ecosystems variables (e.g., species composition, biomass, habitat areal extent). EOVs span physics, biogeochemistry and biology & ecosystems and are managed by the Global Ocean Observing System (GOOS) programme (Figure 1). Each EOV has a specification sheet, basically a recipe with recommendations on what and how to measure and how to ensure the data follows Findable, Accessible, Interoperable, and Reusable (FAIR) data principles. GOOS EOVs are developed to deliver ocean forecasts and early warnings, climate projections and assessments to protect ocean health and its benefits. Despite advancements in ocean observing networks, gaps remain, particularly regarding biology & ecosystem EOVs which are currently largely absent from global ocean observation frameworks (Miloslavich et al., 2018; Sloyan et al., 2019; Tanhua et al., 2019a). This knowledge gap limits our capacity to evaluate the effects of climate change on marine ecosystems and constrains the formulation of effective biodiversity conservation strategies. It underscores the urgent need to integrate biological and ecological insights into global ocean observation systems, especially as policymakers strive to develop comprehensive frameworks that account for both environmental shifts and their ecological implications (Gissi et al., 2019). Standardized global ocean variables and a standardised ocean indicator framework that incorporates biological insights could enhance decision-making processes for marine conservation and climate mitigation strategies (Miloslavich et al., 2024). To improve collaboration and address the critical gap in physics and biology & ecosystem integration, ObsSea4Clim and BioEcoOcean held a joint clustering event. This timely initiative responded to the growing need for cross-sectoral coordination, promoting collaboration across disciplines in ocean science and policy. The goal was to co-develop solutions to improve EOV-based global ocean monitoring, with an emphasis on linking physical and biology & ecosystem data. By driving interdisciplinary cooperation, this effort aims to deliver practical recommendations for policymakers and support more effective and integrated ocean governance. Deliverable 6.3 Clustering Event I 9 Figure 1. Essential Ocean Variables (EOVs) span physics, biogeochemistry and biology & and ecosystems and are managed by the Global Ocean Observing System (GOOS) programme, and three expert panels respectively. The majority of EOVs are also Essential Climate Variables (ECVs) defined by the Global Climate Observing System. Figure source: Global Ocean Observing System (GOOS). 1.1 EOVs and their role in policy development By enabling systematic data collection and integration, EOVs form the scientific backbone for evidencebased decision-making in marine governance. They contribute to international environmental agreements (e.g., SDG 14, the Paris Agreement, Kunming-Montreal Global Biodiversity Framework), regional strategies such as the EU Biodiversity Strategy for 2030, and operational programs including Copernicus Marine Service and European Marine Observation and Data Network (EMODnet). Furthermore, EOVs allow the harmonisation of observations across disciplines, enabling multidisciplinary data assimilation into climate, ecosystem and socio-economic models (Sloyan et al., 2019). These models can then feed into marine spatial planning, risk assessment, early warning systems, and policy performance evaluation. Despite the established utility of EOVs, challenges persist due to the lack of standardised methodologies across projects and regions, fragmented data collection among disciplines, and limited integration of biological and ecosystem variables into forecasting systems. Despite the importance of biodiversity monitoring, there is a gap in the development and implementation of biological EOV indicators. Studies highlight that EOVs enhance predictive modelling and improve early warning systems by integrating remote sensing and in situ observations (Rolle et al., 2023). EOVs are also essential for detecting anomalies linked to marine heatwaves (MHWs) (Brando et al., 2024). The integration of these datasets enables Deliverable 6.3 Clustering Event I 16 productive, and less biodiverse than their predecessors (Ellison et al., 2005; Pessarrodona et al., 2019; Stuart, King and Smale, 2025). Moreover, the change in community structure directly affects critical ecological functions such as productivity, carbon uptake, habitat complexity, and the maintenance of other ecosystem services. Therefore, a decline in the resilience of coastal ecosystems can occur, which in turn has negative implications for economic activities that depend on these systems, notably local fisheries (Smale et al., 2013). Given the challenges, there is an urgent need for proactive policy responses (Bonebrake et al., 2018; Wilson et al., 2020; Eger et al., 2022; Smith et al., 2024). The identification and protection of climate refugia - areas that offer a buffer against the effects of climate change by providing a more stable climate and maintaining biodiversity (Keppel et al., 2012)- must be prioritized to safeguard vulnerable habitats. In parallel, active restoration efforts involving the re-establishment of kelp populations can and are starting to be implemented. Additionally, integrating MHW metrics into conservation planning is critical, as it provides a more robust framework for predicting and mitigating the impacts of future warming events. Long-term monitoring programs using different technologies and techniques are equally essential. These programs should emphasise the development of early-warning systems capable of detecting shifts in forest composition and ecosystem function before they reach a critical threshold. By combining continuous monitoring with comprehensive ecological data collection, changes can be anticipated timely, thereby increasing the effectiveness of adaptive management strategies. 2.2.4 The Blob and the Rise of Pyrosomes: Disrupting the Northeast Pacific Food Web The Blob, an unusually warm water period in the Northeast Pacific in 2013 and the following years, led to substantial changes in the structure and function of regional marine ecosystems (Miller et al., 2019). This event disrupted established ecological connections and had far-reaching consequences for various trophic levels. One of the most notable ecological changes was the dramatic increase in biomass and spread of pyrosomes (Pyrosoma atlanticum). These pelagic gelatinous animals (considered tropical to subtropical species) were rarely found in the northeastern Pacific, i.e., north of California, before this event. Pyrosomes were increasingly observed from 2014 until the summer of 2019 when they took unprecedented roles along the entire west coast of North America (Sutherland et al., 2018). The sudden and massive increase in the pyrosome population substantially impacted energy and nutrient flows in the food web. Ecosystem models that compare periods before and after the start of The Blob indicate that P. atlanticum consumed a considerable amount of energy previously available to other low-trophic groups, including amphipods, krill, and pteropods (Gomes et al., 2024). The pyrosome blooms likely contributed to a reduction in the biomass of these groups. Most of pyrosome biomass (> 90%) ended up as detritus, which implies that their enormous biomass was only available for higher trophic levels as a food source to a limited extent. Although there are reports that some predators and scavengers are eating pyrosomes (Henschke et al., 2013; Brodeur et al., 2021), they are of lower energetic value compared to traditional prey. Modelling of pelagic food webs that reflect conditions before and after The Blob further showcased cascading (indirect) effects Deliverable 6.3 Clustering Event I 17 on various trophic levels. Ecosystem changes (even if temporary) because of MHWs show the potentially complex impacts of extreme warming events on oceanographic conditions and food web functioning. To learn more, please see Lüskow 2025. 2.2.5 MHWs and their role in the Arctic ecosystems MHWs in the Arctic have increased in number over the past decades (Huang et al., 2021). Factors triggering MHWs differ depending on the sea ice cover type, and include abrupt sea ice retreat, precipitation, freshwater dilution processes and elevated air temperature (Barkhordarian et al., 2024; Zhang et al., 2024). MHWs are predicted to have particularly severe impact on the cold-adopted and sensitive Arctic species while benefiting boreal ones (Frölicher et al., 2018; Pecuchet et al., 2025). MHWs have been shown to cause shifts in phytoplankton species abundance and composition (e.g., in the North Atlantic (Mills et al., 2013)) and have the potential to increase and intensify primary production in comparably nutrient-rich Arctic waters (Wolf et al., 2024). Since metabolic rates and respiration are temperature-sensitive, elevated temperatures may increase heterotrophic processes and net community respiration altering productivity patterns (Gou et al., 2025; Latorre et al., 2023). Elevated temperatures may surpass physiological boundaries of organisms as well as impact reproduction success and growth rates. For example, in the northern Bering and Chukchi seas during 2017–2019 MHW, lower densities of zooplankton and benthic communities were observed along with an increase in small, low-lipid copepods and a decrease in large, high-lipid copepods (Duffy-Anderson et al., 2019). Accompanied by toxic algal blooms (Huntington et al., 2020; Walsh et al., 2018) these shifts further propagated into the food web and upper trophic levels, including fish and sea birds (Huntington et al., 2020; Pecuchet et al., 2025). 2.2.6 Effects of MHWs on Arctic Zooplankton The potential effects of MHWs on Arctic marine zooplankton include changes in species composition with increasing abundance of boreal and non-indigenous species, changes in biomass and productivity, and changes in phenology. These types of effects were, to some degree, observed in Gulf of Alaska as a response to a prolonged North Pacific MHW in 2014-2016 (Suryan et al., 2021; Batten et al., 2022; McKinstry et al., 2022). In general, the MHW tended to result in an increase of warm-water associated species, whereas there were no consistent trends for cold-water associated species (Suryan et al., 2021; Batten et al., 2022), including the important large lipid-rich copepods (McKinstry et al., 2022). However, there were indications for changes in diversity of zooplankton, with a lower taxonomic richness after the MHW than before it, and a successful overwintering of a warm-water predatory copepod Corycaeus anglicus (Batten et al., 2022), which could change the functioning of the zooplankton community. Also, the phenology of warm-water associated meroplankton and copepods appeared to have shifted, with earlier appearance and longer persistence in the area (Batten et al., 2022). The changes observed in the Arctic were therefore relatively similar to temperate areas, with observations of promoted warm-water species with high temperature tolerance (Gubanova et al., 2022 Winans et al., 2023). In conclusion, the studies on the effects of Arctic Deliverable 6.3 Clustering Event I 18 MHWs on zooplankton are scarce, pointing towards modest effects mainly consisting of increased biomass and occurrence of sub-Arctic and boreal species, but little effect on the cold-water species. However, further research is urgently needed. 2.2.7 Understanding Zooplankton and MHWs in the Mediterranean The zooplankton is a pivotal group in the oceanic ecosystem to understand and model key processes in fish population dynamics, e.g., early life history and recruitment mechanisms in the population (e.g., Menu et al., 2023), as well as the distribution of species, from small pelagic species (sardine, anchovy, mackerel) to baleen whales (Romagosa et al., 2021). The modelling of zooplankton is still limited by the availability of detailed data and the complexity of biogeochemical models. In the meantime, the uncertainty on the impact of climate change on zooplankton is high. It is linked to changes in primary production and a diversity of responses from phytoplankton species, under the effects of changes in temperature, thermal stratification and mixing driven by wind and convection. Gelatinous zooplankton could also benefit from ocean warming and shifts in phytoplankton abundance and diversity towards smaller-sized species. Large pelagic tunicates (gelatinous zooplankton species), for example, are likely to be favoured due to their filterfeeding mode, which gives them access to small preys. A recent study by Li et al., (2024) took advantage of satellite data and autonomous observations from BioGeoChemical-Argo floats to show that a MHW occurring in the Mediterranean Sea during the 2020 winter drastically inhibited phytoplankton carbon biomass in spring by up to 70%. This was attributed to enhanced stratification limiting the renewal of nutrients from deeper layers, causing an earlier shift of phytoplankton phenology. While zooplankton was not observed with the other variables, simulation outputs from the model SEAPODYM (cf. Pelagic lab 1) showed a coherent similar time shift in the peak of zooplankton biomass, occurring ~1.5 month earlier than on average (Figure 4). The area impacted by the 2020 MHW was located east of the Balearic waters. The western and southern Balearic waters are well known to be a favourable seasonal spawning ground of the Atlantic and Mediterranean bluefin tuna from May to June (Alemany et al. 2010), coinciding with warm waters (> 24 °C) and just following the peak of zooplankton biomass (Figure 4). Deliverable 6.3 Clustering Event I 19 Figure 4. Top: Phytoplankton biomass measured by a BGC-ARGO float within the mixed layer in the western Mediterranean Sea (blue continuous line), and regional non‐MHW average (blue envelope and dotted line) along the track of the ARGO float. Bottom: Model‐derived zooplankton biomass within epipelagic layer (iZooc) and non‐ MHW average. Redrawn from Li et al., (2024). It can be assumed that a winter MHW affecting the south and west of the Balearic Islands could result in a mismatch between the bluefin tuna spawning season and the presence of prey for larvae and juvenile tuna. There are regular sampling studies of bluefin tuna larvae around the Balearic Islands, and one study (Reglero et al., 2025) indicates that 2020 was effectively a year of low larvae density compared to 2022, i.e.: 0.27 (±0.52) m-3 vs 1.16 (±3.7) m-3, respectively. However, the trends were opposite for zooplankton sampled at the same stations, highlighting the difficulty of establishing a direct correlation between environmental factors and bluefin tuna recruitment success despite a regular sampling effort. 2.3 Identification of critical EOV Sub-variables To better understand the effects of MHWs on marine life, we need to understand what to measure, when to measure and how to do it. For example, in-situ physical, biogeochemical and biology & ecosystem observations (e.g., temperature, phytoplankton and zooplankton abundances and species diversity) located in areas and time periods where MHWs occurred need to be identified to conduct impact studies. MHW indicators based on SST satellite data exhibit a strong potential for detecting offshore MHWs due to the high spatio-temporal resolution and coverage of these datasets. In addition, to get a measure of how the MHW extends vertically, the mixed-layer depth, thermocline depth or heat content integrated over a certain depth constitute critical data products which are derived from physical observations, in particular the Sea Surface Temperature and the Subsurface Temperature EOVs. Other physical EOVs which are important for understanding drivers and predictors of MHW occurrence and displacement include: Surface Currents EOV, Subsurface Currents EOV (needed to provide information on heat advection), Ocean Surface Deliverable 6.3 Clustering Event I 20 Heat Flux EOV (since MHWs are typically driven by heat gain from the atmosphere or lack of latent heat loss to the atmosphere), and Sea State EOV (low winds being strongly linked to MHW occurrence). Similar approaches can be used to identify MHW indicators of associated extreme events in biological and biogeochemical phenomena. These could include the use of: • data on primary production and/or chlorophyll a concentration to inform on primary production decrease/increase; • data on dissolved oxygen concentration to inform on deoxygenation; or • data on pH or aragonite saturation (Ω_aragonite) to inform on ocean acidification For instance, when Ω_aragonite falls below 1, the ocean becomes undersaturated with respect to aragonite, making it difficult for some marine organisms to build and maintain their shells and skeletons. This can have significant ecological impacts, particularly on species like corals, molluscs, and some plankton. To explore the change in species/size community structures due to the impact of MHWs, one needs to consider At the biological level, sub-variables that identify measuring changes in functional type distribution of phytoplankton, zooplankton and micronekton - sub-variables or derived products of the Phytoplankton Biomass and Diversity EOV, and the Zooplankton Biomass and Diversity EOV. Harmonization, not to mention standardisation, of the sampling methods related to these measurements remains an issue and requires a large effort at the global research community level. Currently, we lack adequate datasets and data products which would enable consistent model evaluation of the impact of MHWs on these structural and functional ecosystem properties at regional and global levels. A first step would be to consider each existing sampling program separately before combining them together in a single dataset that can be used to calibrate and validate models. However, there are established ecosystem sampling programs worldwide which have the potential to investigate the impact of MHW and associated extreme events by providing time series datasets as a basis for adequate indicator development and testing. These include but are not limited to the regions of the eastern Pacific (CALCOFI), the North-East Pacific (Line P), the North Pacific (ECOFOCI), the subtropical north Pacific (HOT) and Atlantic (BATS) regions, as well as the Barents Sea (IMR). 2.4 Current state of links between MHWs and OBIS The Ocean Biodiversity Information System (OBIS) has not yet produced outputs specifically addressing MHWs or their impacts on marine biodiversity. This gap highlights an opportunity to better integrate biodiversity data with MHWs monitoring to improve understanding and response strategies. However, GOOS has established a MHWs Exemplar under the Co-Design program. This initiative aims to identify pilot areas for studying MHWs and lay the groundwork for broader monitoring efforts. Members of this Exemplar are already involved in both BioEcoOcean and ObsSea4Clim. OBIS is currently exploring a project proposal to investigate MHWs that would leverage tools already under development that focus on species’ physiological limits and thermal traits, using its own data and from Deliverable 6.3 Clustering Event I 21 other databases like WoRMS (World Register of Marine Species). These tools can be used to predict how species and ecosystems respond to MHW events. The proposal is looking to include innovative approaches to strengthen and improve models to implement early warning systems that would help communities prepare for MHWs. Innovative approaches could include, for example, using eDNA to conduct preand postMHW assessments to provide insights on species-specific impacts and community shifts. These models could be refined using real-world data from observed MHW events, fostering a feedback loop to enhance accuracy. 3. Clustering Event I - Deep Dive into the Blue Frontier 3.1 Objectives and Structure of Clustering Event I Recognising the need for collective action, the BioEcoOcean and ObsSea4Clim projects organised a clustering event (March 2025) aimed at advancing ocean observation methodologies and strategies. More than 30 relevant European and international initiatives and projects were represented, such as SEAQuester, BioBoost+, IMDOS, Ocean Best Practice, and the European Polar Board. The event focused on identifying challenges in integrating physics, biogeochemistry, and biology & ecosystems EOVs, exploring solutions for EOV indicators (combination of variables), enhancing interdisciplinary collaboration in ocean observation and policy development, and developing policy recommendations to strengthen global ocean observing and monitoring efforts. The primary objectives of the clustering event were: 1. To strengthen the implementation and integration of EOV-based global observing systems. EOVs, managed by GOOS, are critical for assessing ocean health and its interactions with Earth systems. The objective is to advance interdisciplinary collaboration to refine methodologies for monitoring and forecasting ocean changes, thereby supporting future contributions to global climate and biodiversity assessments and early warning systems. 2. To promote integration across physical, biogeochemical, and biological & ecosystem domains. The aim is to foster a holistic approach to ocean data collection that captures the interconnectedness of oceanic processes. This integration is intended to improve understanding of the ocean’s role in climate regulation and ecosystem dynamics, while addressing existing gaps in coordinated biological and ecosystem observations. 3. To advance the development of a standardised ocean observing framework that informs policy and economic decision-making. The objective is to ensure that ocean data is accessible, comparable, and interoperable to support evidence-based policymaking and sustainable economic practices related to ocean resources. This includes generating actionable recommendations to guide future policy applications and strengthen links between observation systems and decisionmaking processes. Deliverable 6.3 Clustering Event I 22 To achieve these objectives, the event was organised into the following four focused sessions: EOV Speed Dating: This interactive session facilitated exchanges among participants to discuss advancements, challenges, and collaborative opportunities related to specific EOVs. The format encouraged cross-disciplinary discussion, understanding, and the formulation of EOV partnerships aimed at refining observation methodologies and data utilization. Bridging the Land-Coast-Ocean Nexus: Addressing the continuum of terrestrial environments to the open ocean, this session explored methodologies for integrating observations across these domains, emphasising the importance of cohesive monitoring strategies that encompass land-sea interactions, which are vital for understanding, for example, nutrient fluxes, pollutant pathways, and sediment transport. MHWs: Given the increasing frequency and impact of MHWs on marine ecosystems and coastal communities, the session focused on identifying observation requirements, and understanding the implications of these extreme events on marine ecosystems. Identifying Issues and Barriers in Ocean Observing: This session aimed to pinpoint existing challenges in ocean observation systems, including technological limitations, data accessibility, and coordination gaps and to propose actionable solutions to overcome these barriers. By uniting expertise from both projects, the clustering event served as a catalyst for advancing ocean observing practices toward a more comprehensive, cost-effective, and coordinated approach to ocean monitoring and sustainable management. The recommendations developed during these sessions are instrumental in informing policymakers, guiding sustainable ocean management and enhancing the coherence of the global ocean observation and assessment community. 3.2 Introducing the sister projects BioEcoOcean - Co-Creating Transformative Pathways to Biological and Ecosystem Ocean Observations - and ObsSea4Clim - Ocean observations and indicators for climate and assessments - aim to advance ocean observation methodologies and enhance our understanding and management of ocean systems to support climate and biodiversity assessments. The ultimate goal of BioEcoOcean is to enhance the biology & ecosystem ocean observing capacity for advancing scientific understanding of the ocean and increasing the utility of ocean observations. One important component is to transform biological and ecosystem ocean observations through the development of the Blueprint for Integrated Ocean Science. This comprehensive tool is designed to guide ocean observing programs at all stages, from planning to policy application, promoting a holistic and collaborative approach across the ocean observing value chain. The project engages stakeholders in cocreating the Blueprint to enhance communication and cooperation among various sectors involved in ocean observation. BioEcoOcean also focuses on accelerating the implementation of biology & ecosystems EOVs to improve global biodiversity and ecosystem assessments while strengthening common approaches and standards through the development of standardised methodologies for observations. Furthermore, a Deliverable 6.3 Clustering Event I 23 key focus of BioEcoOcean is improving the understanding of the links between ocean biodiversity, biogeochemistry, and climate using interdisciplinary approaches and advanced technologies. BioEcoOcean prioritises capacity building and collaboration with global ocean observation initiatives to promote widespread adoption of its co-produced standards. ObsSea4Clim aims to enhance the framework for European nations' contributions to ocean observations, with a strong focus on physical EOVs and Essential Climate Variables (ECVs) and their use for the implementation of the Rolling review of requirements (RRR), as defined in the Manual on the World Meteorological Organization (WMO) Integrated Global Observing System. The RRR process compiles information about requirements for observations, about observing system capabilities, their costeffectiveness, and draws on experts and impact studies to provide guidance on the most important priorities for addressing the gaps between requirements and capabilities. These efforts support both regional and global climate assessments, refine projections, and develop actionable indicators for sustainable development. The project seeks to create new ocean indicators that inform sustainable practices, advance Earth System Models (ESMs) by integrating EOVs and ECVs to reduce uncertainties in climate projections and establish an interoperable data ecosystem that serves multidisciplinary needs across oceanic and climatic studies. Additionally, ObsSea4Clim prioritises the development of standardized methods for both in situ and satellite observations to ensure data consistency and reliability. Both ObsSea4Clim and BioEcoOcean highlight the significance of collaborative efforts and standardised practices in ocean observation. By working across disciplines and engaging with a broad range of stakeholders, projects contribute to strengthening climate resilience and fostering sustainable ocean management. 3.3 Essential Ocean Variables: Physics and Biology & Ecosystems (the EOV speed dating) The EOV Speed Dating workshop session marked one of the first instances where experts from the fields of biology & ecosystems, and physics were brought together in a collaborative setting. This was a significant milestone in fostering interdisciplinary dialogue and cooperation. It was an achievement in its own right that lays the groundwork for future innovations in ocean observation and climate solutions. The EOV Speed Dating workshop was designed with multiple objectives in mind (please see Nordlund et al., 2025 for more information). First, it served as an icebreaker, allowing participants to build understanding across different scientific fields. Participants from the BioEcoOcean and ObsSea4Clim projects, which respectively focus on biology & ecosystem EOVs and physics and climate EOVs, were introduced to one another and encouraged to collaborate. The workshop sought to enhance understanding of EOVs by facilitating discussions on their characteristics, sub-variables, and relevance to ocean observing. Through these interactions, the participants were expected to identify potential synergies that could contribute to more comprehensive ocean observing, ultimately addressing challenges related to climate and ecosystem changes. Deliverable 6.3 Clustering Event I 24 The workshop was structured into three rounds followed by an open-floor discussion. In the first round, participants were grouped with colleagues from different fields to familiarise themselves with EOVs across disciplines. The discussions in this phase revolved around understanding the attributes, sub-variables, and importance of these variables to different fields. In the second round, participants were tasked with exploring potential collaborations by discussing how biology & ecosystem EOVs could pair with physical EOVs. This phase focused on identifying synergies and collaborations that could improve ocean observing. The third round encouraged participants to translate these relationships into practical collaborations, discussing potential joint research opportunities, product development ideas, and other innovative concepts. Finally, the open-floor discussion allowed groups to share their key findings and propose further steps for collaboration. The workshop resulted in several key discussion points. Participants explored the interconnectedness of EOVs across biology & ecosystem and physics (Table 1), noting variables such as subsurface temperature and ocean colour. Notably, subsurface temperature was identified as a crucial parameter, as it influences various biological variables, including phytoplankton biomass, species composition, fish abundance, and benthic invertebrates (Figure 5). The importance of considering how living habitats can affect physical parameters (like temperature or currents) was also highlighted. Other discussions highlighted the relationship between ocean colour and biological sub-variables like phytoplankton biomass and macroalgae coverage. For example, changes in ocean colour could indicate shifts in phytoplankton composition, affecting the downward flux of organic matter and the benthic ecosystems that rely on it. Figure 5: Subsurface temperature, a key physical EOV, affects several biology & ecosystem EOVs. While multiple physical EOVs interact with biological processes, temperature plays a significant role in shaping the distribution, abundance, and diversity of organisms such as fish, zooplankton, phytoplankton, seagrass, and macroalgae. This simplified diagram focuses on subsurface temperature's influence within the scope of this document, acknowledging that other physical EOVs also impact biological and ecosystem dynamics (biology & ecosystems EOVs from top left: Fish abundance and distribution; Phytoplankton biomass and diversity; Zooplankton biomass and diversity; Seagrass cover and composition; Macroalgal canopy cover and composition; Hard Coral cover and composition, and Invertebrate abundance and distribution). Deliverable 6.3 Clustering Event I 25 Table 1. Examples of EOV relationships identified during the workshop. Biology & ecosystem EOVs Physics EOVs Example of identified Relationships Phytoplankton biomass and diversity & Benthic invertebrate abundance and distribution Subsurface temperature Subsurface temperature influences growth, with potential effects on species composition and distribution. Fish abundance and distribution Subsurface temperature Subsurface temperature changes affect habitat suitability for fish, influencing their abundance, species composition and distribution. Many biology & ecosystem EOVs are also affected. Macroalgal canopy cover and composition & Phytoplankton biomass and diversity Sea ice Sea ice coverage affects light penetration, which in turn influences macroalgal and phytoplankton growth and distribution. Phytoplankton biomass and diversity & Benthic invertebrate abundance and distribution Ocean colour A change in ocean colour may indicate a change in phytoplankton composition and thus "health" of the openocean primary producer population (also influenced by sub surface temperature). This is then connected to a potentially increasing rate of downward flux of dying/dead phytoplankton feeding the benthic invertebrates (filter feeders). Hence, a change in water colour could be linked to the biomass, present/absence, percent coverage of benthic invertebrates. Several challenges and knowledge gaps were also identified during the session. Participants found it difficult to understand and integrate technical terms and acronyms across the different EOV sub-variables from distinct fields. Additionally, there were gaps in understanding how certain physics EOVs, such as ocean pressure, impact biological variables. A key challenge was the development of EOVs in silos (Figure 1), which complicates interdisciplinary collaboration. A recognition of the need for more explicit connections between EOVs was identified. There were also issues related to the measurement of certain variables, such as biomass and percent cover, and how these variables relate to physical parameters like currents and temperature. Scale mismatches between physical and biological variables were another challenge, as different scales (cm to 1000s of kilometres) can lead to inconsistencies when integrating data. Potential solutions emerged from these discussions. Participants proposed involving a broader range of EOV experts to provide comprehensive feedback on the EOV specification sheets, and in the future, consider sub-variables to cover all relevant biological/ecosystems, physical, and biogeochemical functions. Fostering interdisciplinary research to explore how physical variables, such as ocean pressure, impact biological EOVs through additional studies and model development was also suggested. Integrated models that include both biology &ecosystem and physics variables could be developed to create cross-field data products and reduce uncertainties. For example, linking phytoplankton biomass to changes in sea surface temperature, currents, and sea ice cover could enhance understanding of how physical changes influence biological processes. The use of AI tools and integrated data products, combining satellite and in-situ sensor data, were proposed as potential methods to address the issue of scale mismatches. Looking ahead, several next steps were identified. The participants agreed to continue building connections between biology & ecosystem and physics EOVs, particularly by focusing on the relationships between phytoplankton biomass and ocean colour, with the aim to develop data products that integrate these Deliverable 6.3 Clustering Event I 32 4.1.2 Upgrade and Diversify Observation Platforms We recommend that national and regional policy frameworks prioritise investment in a broader range of advanced ocean observation platforms to improve data quality and coverage across physical, biogeochemical, and biology & ecosystem domains. Investing in various advanced ocean observation tools such as autonomous vehicles, multi-sensor Argo floats, and high-resolution satellites has been shown to greatly improve the collection of detailed physical, biogeochemical, and biological data (Chai et al., 2020; Saad et al., 2020). This investment should be supported by funding programmes at the national and regional levels to encourage innovation and ensure the interoperability among different observation systems. 4.1.3 Addressing Scale Mismatch We recommend that policy frameworks actively support and address scale mismatch by promoting the integration of observations and data systems across spatial and temporal scales. This is particularly important because ecosystem changes are driven by processes operating at multiple, and often mismatched, spatial and temporal scales, from fine-scale species interactions to broad-scale environmental shifts (Trifonova et al., 2022). Furthermore, the temporal scale at which shifts in biological systems can be detected will vary depending on the specific EOVs, the properties being monitored, and the length of the existing time-series (Miloslavich et al., 2018). To address this scale mismatch, policy frameworks should promote collaboration between projects, organisations and agencies managing satellite data and those operating localised sensor networks (Howe et al., 2020) and conducting in situ investigations for a consistent integration of broad satellite observations with detailed in situ measurements across global and local contexts. 4.1.4 Implement Downscaling and Targeted Observation Strategies We recommend that policy frameworks support the development and integration of downscaling methodologies and targeted observation strategies to improve the relevance and usability of global ocean data at regional and local levels. Development of downscaling methodologies that convert global oceanic data into actionable, regional insights is particularly important in areas such as AMOC hotspots and vulnerable coastal zones. Evidence from region-specific case studies shows that downscaling techniques are effective in improving local forecasts, including predictions of coastal erosion and habitat loss (see e.g. Antolínez et al., 2018). Policy actions should integrate these methods into existing programs and support pilot projects in diverse environmental contexts. Deliverable 6.3 Clustering Event I 33 4.1.5 Support for Integrated Ocean Observing Systems We recommend that policy frameworks prioritise sustained funding and coordination for the development of integrated ocean observing systems that bring together biological, biogeochemical, and physical Essential Ocean Variables (EOVs). Allocate funding toward initiatives that foster interdisciplinary research and combine biological, biogeochemical, and physical EOVs into unified observing systems. Evidence confirms that integrated systems deliver more reliable and comprehensive assessments of ecosystem dynamics and enhance the accuracy of climate predictions (Thurston et al., 2021). Policy development should establish international funding programmes that support and encourage cross-disciplinary projects and build integrated ocean observing networks at national, regional and global levels. 4.1.6 Standardisation of Data Collection Protocols We recommend that policy frameworks support the harmonisation of data collection protocols across institutions and borders to ensure data interoperability and comparability. Harmonise data collection protocols across national and international organizations. Comparative research demonstrates that standardised methodologies significantly improve data interoperability and facilitate meta-analyses critical for global environmental assessments (Tanhua et al., 2019b). Policies should leverage the coordinating role of international organisations and regional alliances to standardise guidelines for enabling interoperability of data sharing and integration. 4.1.7 Investment in AI and Data Analytics We recommend that policy frameworks prioritise sustained investment in AI technologies and advanced modelling tools to improve the processing, interpretation, and application of ocean observation data. Promoting and investing in advanced AI tools and modelling techniques enhances the synthesis of ocean observation data and reduces uncertainty in predictive analyses. Studies have shown that AI-driven analytics greatly increases the speed and accuracy of trend detection within complex datasets (Saad et al., 2020), thereby overcoming limitations of traditional methods. Policy frameworks should encourage public– private partnerships that fund research in trustworthy AI applications for ocean science while mandating the integration of these tools across governmental and research institutions acting in compliance with the European AI Strategy and supporting the AI Continent Action Plan. 4.1.8 Adopt FAIR Data Principles and Enhance Dataset Integration We recommend truly mandating adherence to Open Science, FAIR and Directive 2007/2/EC (INSPIRE) principles for all marine datasets to enhance their utility in research and policy-making. Integrated data platforms, such as the UNESCO-IOC Ocean Biodiversity and Information System (OBIS), provide excellent examples of how FAIR principles can be applied in practice to enhance data accessibility, interoperability, and reusability. Such initiatives accelerate scientific discovery, improve research reproducibility, and Deliverable 6.3 Clustering Event I 34 ultimately lead to better-informed policy outcomes. Policies should require adherence to Open Science and FAIR principles in research funding and research project evaluations, along with promoting international data-sharing agreements. 4.1.9 Promote Low-Cost Sensor Development and Citizen Science Initiatives We recommend promoting the development of low-cost, high-precision sensors and supporting citizen science initiatives to expand spatial and temporal coverage of marine data. This includes fostering the development of low-cost, high-precision sensors and actively engaging local communities, such as fishers and coastal inhabitants, in citizen science projects to expand spatial and temporal data coverage. Evidence from various coastal studies indicates that when standardised low-cost monitoring technologies are combined with citizen science, data networks can be substantially expanded and enriched with localized insights (Marcelli et al., 2021). Policy measures should support programs that provide funding, training, and equipment for local monitoring efforts. 4.1.10 Encourage Cross-Sectoral Collaboration We recommend developing policy frameworks that incentivise cross-sectoral collaboration to ensure ocean observation data is effectively translated into actionable policy insights. Such frameworks should promote and incentivise cooperation among scientists, data managers, industry and decision-makers. Given that scientific evaluation is inherently connected to political, cultural, and social dynamics, investing in effective communication and fostering engagement across interdisciplinary networks is essential. Interdisciplinary collaboration that align ocean observations with societal needs—such as food security, human health, and ecosystem services—enhance the adoption of best practices in environmental monitoring and support the practical application of research findings (Mackenzie et al., 2019; Satterthwaite et al. 2021). Policies should incorporate research grants and establish interagency working groups to foster regular communication among stakeholders. 4.1.11 Regular interdisciplinary workshops and trainings We recommend securing funding for regular interdisciplinary workshops and training sessions to facilitate knowledge exchange and build capacity among experts in ocean monitoring and management. Allocate and secure funding for regular interdisciplinary workshops and training sessions that facilitate knowledge exchange among experts in ocean monitoring and management. Interdisciplinary knowledge exchange is essential to develop methods that integrate insights across scales, enabling a more effective understanding, quantification, and prediction of climate impacts on marine ecosystem services (McDonald et al., 2018). Policy frameworks should integrate interdisciplinary capacity-building components into existing educational and vocational training programs and support regular trainings at both the national and international levels. Deliverable 6.3 Clustering Event I 35 4.1.12 Incorporate Biogeochemical and Biological Data We recommend mandating the systematic integration of biogeochemical and biological indicators into ocean observation programs to provide a more comprehensive assessment of ecosystem health and marine biodiversity. Mandate the systematic integration of biogeochemical and biological indicators within ocean observation programs to provide a comprehensive assessment of ecosystem health and marine biodiversity. Research demonstrates that inclusion of biological metrics alongside physical data not only improves early detection of ecological disturbances but also enhances adaptive management responses (Miloslavich et al. 2018; 2024; Muller-Karger et al 2024). Policies should update existing monitoring guidelines to require biological data collection and analysis, and support research to develop new biological indicators. 4.1.13 Integrate biological responses to exceptional warm periods We recommend allocating funding to investigate the impacts of exceptional warm periods on marine life by systematically analysing existing time-series data. This should include examination of ecological responses regardless of whether the effects are strong or subtle. A literature review highlights a regional bias in studies of MHWs, with significantly fewer investigations conducted in European countries, underscoring the need for broader geographic representation to achieve a more balanced scientific understanding (Joyce et al., 2024). Policy measures should design funding programs that encourage reporting both strong and weak effects to capture the full spectrum of ecological responses. 4.1.14 Identification of indicator species for MHWs We recommend supporting research to identify and validate indicator species for monitoring the effects of marine heatwaves (MHWs), particularly in sensitive regions such as the Arctic. This includes investigating species such as non-indigenous organisms with wide temperature tolerances. Empirical studies, including those by Gubanova et al., (2022) in the Black Sea, provide evidence that such indicators can serve as earlywarning proxies for detecting environmental stress, thus facilitating timely management interventions. Policies should integrate these research findings into marine management guidelines and encourage further interdisciplinary research to validate these indicators across diverse marine environments. Deliverable 6.3 Clustering Event I 36 4.2 Summary of policy recommendations In summary, striving to implement these policy recommendations will significantly contribute to the European Green Deal by promoting climate resilience, protecting marine biodiversity, and promoting the sustainable use of ocean resources. Enhanced ocean observing and monitoring systems will support the development of adaptive management strategies that address both global and local environmental challenges, thus reinforcing the ocean–climate–biodiversity nexus. This integrated approach not only aligns with the European environmental and sustainability goals but also creates socio-economic benefits by empowering coastal communities, stimulating innovation in ocean technologies, and preserving the marine ecosystems. The development of an interdisciplinary ocean observing system would benefit from interdisciplinary collaborations and coordination of ongoing activities in alignment with regional and global efforts (e.g., All Atlantic Ocean Research and Innovation Alliance (AAORIA), GOOS Biology & ecosystem Panel (2022), the Marine Biodiversity Observation Network (MBON)). Enhancing coordination among national and international observation networks, adopting best practices, fostering the implementation of EOVs, standardising data formats, promoting interoperability and open access publication, and promoting knowledge sharing will minimize redundancy, boost efficiency and improve more effective ocean observation. Deliverable 6.3 Clustering Event I 37 5. The way forward The challenges facing our ocean, from the increasing frequency of MHWs to the underrepresentation of biodiversity in observation systems, demand a shift in how we design, operate, and apply ocean monitoring frameworks. The work of BioEcoOcean and ObsSea4Clim marks an important step towards this transformation. Through joint efforts and the forthcoming Blueprint for Integrated Ocean Science, we are building the tools and relationships needed to turn fragmented data into actionable knowledge. A critical component of this shift will be the systematic implementation and operationalisation of Essential Ocean Variables (EOVs), which offer a standardised framework for observing the ocean system across physical, biogeochemical, and biology & ecosystem domains. Strengthening EOV-based observations and enhance their integration will help close persistent knowledge gaps and provide the foundation for more effective marine conservation and climate mitigation strategies. Continued collaboration across disciplines, sectors, and scales will be essential. As this work progresses, it will create new pathways for more inclusive, standardised, and policy-relevant ocean observations. This is not just an opportunity; it is the call to action for securing a sustainable and climate-resilient future for our oceans and the communities that rely on them. 6. Acknowledgements We would like to express our sincere gratitude to Inga Lips (EuroGOOS), Alicia Blanco (EuroGOOS), Steffen M. Olsen (DMI), Justyna Agata Bekier (DMI), Stefano Ciavatta (MOi), Toste Tanhua (GEOMAR), Gerard McCarthy (NUIM), Catherine O’Beirne (NUIM), and Dominik Krzymiński (IO PAN) for their invaluable contributions to the organisation of the meeting, as well as for serving as session leads and rapporteurs. We also extend our thanks to IO PAN for hosting the meeting and providing excellent organisational support in Sopot, Poland. Deliverable 6.3 Clustering Event I 38 7. References Alemany, F., Quintanilla, L., Vélez-Belchí, P., García, A., Cortés, D., Rodríguez, J. M., ... & López-Jurado, J. L. 2010. 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