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Worldwide reduction of carbon emissions is needed to help reduce the effects of climate change. Twenty-seven member states of the European Union have committed to reduce emissions by 55% of 1990 levels by 20301. To achieve this, an unprecedented installation of offshore marine renewable energy devices (wind, wave, tidal, solar) and cable networks is required2. To date, offshore wind energy is the largest marine renewable energy provider, currently producing globally 35 GW with an increase to 70 GW expected by 20253 and a potential increase worldwide to 1000 GW expected by 20504. Europe has the majority of offshore wind farms (OWFs) with a capacity of 28 GW5, which corresponds to 5,795 grid-connected wind turbines across 123 OWFs and 12 countries5. Marine biodiversity and their associated ecosystems are increasingly being affected by anthropogenic pressures, such as the growing number of artificial structures6,7, eutrophication, fisheries and climate change8–10. The introduction of man-made structures can potentially have both positive and negative effects on marine ecosystems11– 14. Soft-bottom communities are altered close to artificial structures15–17, while a significant amount of marine growth colonises the artificial hard structures18,19. To assess the effects of man-made structures on the benthic community, most environmental impact assessment data collection studies have been conducted over small spatial and temporal scales20 such as single turbines or single OWFs and associated infrastructure15,21,22. Some countries have coordinated programmes to standardise data collection methods on soft sediments (e.g., Germany23, Belgium24, the Baltic Sea25), and there are existing methods to study macrofauna on natural hard substrates such as rocky bottoms26. However, there are no internationally agreed methods, metrics or databases for the data collection, which is critical for understanding the effects of artificial structures on marine ecosystems. Data are disparate owing to differences in data diversity, regarding (i) sampling devices and methods, (ii) sample analysis (e.g., variables, taxonomic resolution), (iii) data storage and management, as well as (iv) continuously changing taxonomy. This results in a lack of consistent data with regards to offshore artificial structures and benthos. Thus, investigation of large-scale benthic effects requires merging data from different sources, which is challenging (time consuming, costly, difficult) or even not possible19. Taken together, the available data are underutilised. A few attempts have been made to collect and analyse biodiversity data from different substrates (wind turbines, oil and gas platforms, surrounding soft sediments and rocky reefs) in a single region19,27,28. Ecosystem-based management requires a deep understanding of the effects of artificial structures over large spatial and temporal scales that exceed budgets, timeframes and jurisdictional borders. Data sharing through the creation of an integrated database can provide multiple benefits for science, industry, and policy. It could be used for large-scale research studies examining the aforementioned effects and facilitate ecosystem-based management. Furthermore, the creation of a centralised dataset could enable answering scientific questions regarding stepping stone effects beyond the scale of individual OWFs, platforms or countries29,30. Industry could exploit this dataset for environment-friendly planning, predicting effects of new activities at offshore locations. Finally, sharing such data is crucial in developing fact-based scientific advice for decommissioning decisions for various stakeholders. This paper presents the first data collection ‘Biodiversity Information of benthic Species at ARtificial structures’ (BISAR). BISAR contains data on benthic macrofauna collected in environmental impact studies, scientific projects and species inventories conducted at 17 artificial offshore structures in the North Sea between 2003 and 2019. The structures include OWFs, oil and gas platforms, a research platform and a geogenic reef to compare natural and artificial reef communities. BISAR includes data from soft and hard substrate studies (34 artificial structures), allowing comparisons of changes in both habitat types. This data collection currently contains data from a total of 3864 samples with 890 taxa. BISAR is the first data product containing harmonised and quality-checked international data on benthos from substrates influenced by artificial structures in the North Sea. Various stakeholders (e.g., industry, public authorities, research) will profit from the BISAR data collection as the greatest challenge in an era of blue growth is to get access to data from various sources

Given the global offshore wind farm (OWF) proliferation, we investigated the impact of OWFs on the marine food web. Using linear inverse modelling (LIM), we compared theOWF food web with two softsediment food webs nearby. Novel in situ data on species biomass and their isotopic composition were combined with literature data to construct food webs.Our findings highlight the prominent role of hard-substrate species on turbine foundations as organic material inputs for the food web. Hard substrate species account for approximately 26% of food source uptake from the water column and increase carbon deposition on the surrounding seafloor by ~10%. OWFs facilitate a novel food web with a higher productivity than expected based on standing biomass alone, as a result of numerous interactions between a diverse species community. Our study underscores profound effects of OWFs on marine ecosystems, suggesting the need for further research into their ecological impacts.

Motivation: Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included: The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain: Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain: The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement: The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format: csv and. SQL.

The development of offshore wind farms (OWFs) in the North Sea is a crucial component for the transition to renewable energy. However, local hydrodynamics in the vicinity of OWF turbine foundations may be affected due to their interaction with tidal currents. This study investigates the impact of offshore wind turbine foundations on local hydrodynamics and stratification in the southern North Sea. We conducted a series of measurements around a single monopile in the Belgian part of the North Sea, focusing on hydrodynamics, salinity and temperature both near the surface and over the water column, and turbulent kinetic energy (TKE). Our results indicate that the foundation-induced wake significantly affects local hydrodynamics, leading to a well-defined band of colder, more saline water at the surface and warmer, less saline water near the seabed. This is quantified through the Potential Energy Anomaly (PEA), which shows a marked decrease in the wake-affected area. The wake is spatially confined, with a width of approximately 70 meters and a length of less than 400 meters downstream of the monopile. Additionally, our measurements reveal an increase in TKE within the wake, indicating enhanced turbulent mixing. This mixing reduces vertical gradients in salinity and temperature, leading to a more homogeneous water column. The findings highlight the importance of considering monopile-induced mixing in large-scale hydrodynamic and ecosystem models, as these effects can influence nutrient transport, primary production, and overall ecosystem dynamics. Furthermore, our research provides valuable data for validating and improving the models used to predict the ecological impact of OWFs.

In recent years, research into the occurrence of bats at the Dutch North Sea has shown that there is regular seasonal migration over sea. However, so far, little is known about their migration ecology, the fatality risks at offshore wind turbines, and the number of individuals migrating over sea. Since the Dutch government wants to boost the further development of wind energy production in the southern North Sea, the Ministry of Economic Affairs commissioned to Rijkswaterstaat a Wind at Sea Ecological Programme (in Dutch: Wozep). This study, as part of the Wozep-project Behaviour and Collision Risk of Bats (Bats_2), investigates how telemetry can be applied to gain insight into migratory movements of bats over land and over sea and individual bat behaviour near and in offshore wind farms. To find out whether it is wise to continue and further develop telemetry research in the context of the Wozep programme, we first identified potential telemetry methods for small bats based on a desk study and selected the most promising method for the application of telemetry. Members of the team attended an international workshop on telemetry in Lund (Sweden) to gather practical technical knowledge, gain insight in data-management standards, and increase their international network. Several field tests were conducted to test the equipment and explore the possibilities of tracking. Finally, suitable locations for bat trapping in bat boxes and for the use of a Heligoland trap were identified. There are several options to track bats with radio telemetry during their migration at the coast and over sea. However, for long-term monitoring of multiple individuals, establishing a grid of stationary receivers is the only feasible option. Eight field tests were carried out to test the performance of the technical infrastructure. Each of the tests was unique and set up to test the signal strength/detection range for a certain type of antenna or a certain transmitter/receiver constellation. We showed that detections over at least 6 km are possible, and likely more than 10 km can be achieved. Precondition is that the receiving stations must be installed at high structures (lighthouses, buildings, masts) or hills, installing them a few meters off ground level will lead to detection ranges just over one km. Furthermore we explored the possibilities of calculating movement tracks with a setup of several receivers using different estimation methods. These experiments indicated that a relatively high accuracy (of c. 100 m) can be reached estimating the location when signals of different receiving stations are combined. It is likely that the accuracy can be improved by estimating the bearings of the received signals based on the signal strength of different antennas. Even further improvement seems possible by assessing the (likely) flight route with a state-space model. There are plenty of locations with bat boxes, especially in the province of Noord-Holland, where potentially hundreds of bats can be captured during migration stopovers, though it is not known how many of these are likely to be migrants. In addition, we identified four locations where actively migrating bats can potentially be captured with an Heligoland trap. In conclusion, we are confident that telemetry can be successfully applied to study migratory movements of bats over land and over sea and individual bat behaviour near and in offshore wind farms. Joining a wildlife tracking system like Motus (Canada) in order to enlarge the data collection, is highly recommended. Motus-members can get detections from both

Sub-Antarctic islands are expected to show a high degree of endemicity due to their remoteness. However, biogeographic affinities in the sub-Antarctic remain poorly understood, especially in the marine realm. Sub-Antarctic islands being at the crossroads between Antarctic and cold temperate regions, biodiversity characterization and biogeographic analyses are a priority for monitoring and rapidly assessing variations associated with environmental changes. One underexplored sub-Antarctic area is Crozet, a protected archipelago located halfway between Antarctica and South Africa. In this study, we investigated the shallow-water Crozet macrofaunal diversity, distribution patterns and biogeographic affinities based on the examination of fieldwork specimens via a thorough morphological identification and a genetic characterisation. The resulting dataset provides an important baseline for further studies and conservation strategies, compiling the first genetic and taxonomic database for the Crozet archipelago. In total, 100 morphotypes were found, belonging to nine different phyla, among whicharthropods(32), molluscs (18)and echinoderms (17) were the richest. Forty-seven morphotypes were identified to the species level, among which 20 were reported in Crozet for the first time. This confirms that Crozet is a poorly known region, even compared to other sub-Antarctic areas. A large proportion of species (62%) had circum Southern Ocean or circum sub Antarctic distributions. These species were mostly shared with Kerguelen (72%), the Magellan Province (64%), and Prince Edward Islands (64%), confirming the patterns found in macroalgae and specific macrofaunal groups. However, this large-distribution statement needs to be counterbalanced by the detection (genetic data) of more restricted distributions than expected in four study cases (the tanaid Apseudes spectabilis, the nudibranch Doris kerguelenensis, the polychaete Neanthes kerguelensis and the chiton Hemiarthrum setulosum). Considering that most morphotypes had no genetic data available from other regions, the proportion of morphotypes with restricted distribution is likely to increase alongside future investigations. In addition, we also found a few cases of unrecognized diversity that might lead to the descriptions of new species, some likely to be endemic to Crozet (e.g., within the polychaete genus Harmothoe and the bryozoan genus Antarctothoa). Altogether, this stresses the need to maintain conservation efforts in Crozet and pursue integrative investigations in order to highlight and protect its unusual diversity

RÉSUMÉ Les observations pétrographiques en lames-minces et les analyses au microscope électronique à balayage complètent les observations macroscopiques et mésoscopiques faites sur des tessons appartenant à deux espaces d’occupation rubanée situés à Velroux (Grâce-Hollogne, Province de liège, Belgique). Quatre groupes et plusieurs sous-groupes de pâtes céramiques ont été identifiés et caractérisés. Les sources locales et régionales des matières premières utilisées par les potiers rubanés sont discutées et ouvrent des perspectives sur les utilisations des matières premières sur la grande aire rubanée. MOTS-CLÉS : Rubané, pétrographie en lames-minces, microscope électronique à balayage, EDS, sources des matières premières, Hesbaye, Belgique. SUMMARY/ABSTRACT Petrographic observations in thin sections and scanning electron microscopic analyses complete the macroscopic and mesoscopic observations made on pottery sherds belonging to two occupation area belonging to the Linear Pottery culture and located at Velroux (Grâce-Hollogne, Province of Liege, Belgium). Four groups of ceramic pastes and some sub-groups were identified and characterized. Local and regional sources of raw materials used by the LBK potters are discussed and open perspectives on the uses of raw materials in the large Linear Pottery Culture area. KEYWORDS: Linear Pottery Culture, thin-section petrography, scanning electron microscope, EDS, raw material sourcing, Hesbaye, Belgium.

One of the greatest challenges of the last decades in the fight against climate change has been to achieve net-zero emissions by mid-century. According to the US EPA (2016), in 2014, global anthropogenic emissions of carbon dioxide (CO2) accounted for ~64% of the greenhouse effect. Carbon dioxide capture and storage (CCS) plays an irreplaceable part as a mitigation technology that avoids CO2 emissions at their source and bridges the transition into a non-carbon-based energy future. The International Energy Agency (IEA) estimates that the need to store CO2 will grow from 40 Mt/y at present to more than 5000 Mt/y by 2050. Additionally, in the IEA’s Sustainable Development Scenario, which aims for global net-zero CO2 emissions from the energy sector by 2070, CCS needs to become a global industry supporting emissions reductions across the overall energy system. CCS technologies essentially consist of capturing and compressing the CO2 at the source and then transport it towards deep suitable rock formations where it is injected to be permanently stored. The key to successful and permanent CO2 storage is the proper analysis and characterization of the reservoir and seal formation. Among the types of reservoir suitable for CO2 storage are unmined coal beds, depleted oil and gas fields, EOR/EGR, saline aquifers, man-made caverns, and basaltic formations (IPCC, 2005). The storage capacity of any of these reservoirs is the subsurface commodity whose quantities and properties are assessed when existing data is provided. Capacity estimations bring their own level of uncertainty and complexity according to the scale at which they are addressed and the nature of the geological conditions of the reservoir. This degree of uncertainty should be accounted for in every estimation (Bradshaw et al., 2007) Resource classification systems (RCS) are frameworks that establish the principles and boundaries for each level of capacity assessment. By making use of these frameworks, it is possible to properly allocate the stage of development of a resource (United Nations, 2020). For every level of assessment, the principles of the estimation change and so do the scale and purpose. As the analysis moves forward, a prospective site develops and exhaustive information is acquired, initial estimations are adjusted, and uncertainty is likely to reduce. Additionally, different economic, technical, regulatory, environmental and societal factors are integrated into the assessment to bring the estimations under present conditions. For instance, if the storage capacity is to be matched with a CO2 source, detailed simulations and analyses regarding injectivity, supply rate, potential routes and economic distances must be performed to achieve a realistic estimation. However, an assessment where the main goal is to merely quantify the space available to store CO2 in a reservoir, does not consider the aforementioned limitations and will carry higher risk and uncertainty in its estimation (Bradshaw et al., 2007). Even though resource classification systems provide a solid foundation for CCS projects, they do not provide the input parameters and analyses needed to reach every level of assessment. This is why storage capacity estimation methodologies go hand in hand with RCS given that the former can give information related to the parameters and constraints considered in the estimation. No standard process has been proposed that can be followed from the starting level of a CO2 storage capacity assessment until a fully developed carbon storage resource; that is, a CO2 storage site ready to become fully operational. This paper aims to develop a methodology where the fundamental steps needed to go through every level of the resource classification systems are standardized. This methodology intends to serve as a general baseline that, regardless of the geological settings and techno-socio-economic conditions, can be adopted for any CCS assessment. The proposed methodology is built by reviewing the available capacity estimation methods for every level of assessment and identifying social, technical and economic aspects that come into play as the resource is being developed. Considering that capacity estimation methodologies can vary their approach even for the same level of assessment, the rationales behind them are expected to be determined. Such rationales can be related to in-place policy restrictions, geographical economic behavior, or the nature of the parameters contemplated. Additionally, PSS, an in-house developed tool that can assess CO2 storage reservoirs at different levels, will be proposed within the methodology. This tool is a bottom-up geotechnical and economic forecasting simulator that can generate source-sink matching for CCS projects, where technical, economic, and geological uncertainties are handled through a Monte Carlo approach for limited foresight (Welkenhuysen et al., 2016). Acknowledgements This research is carried out under the LEILAC2 project, which receives funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 884170. The LEILAC2 consortium consists of: Calix Europe SARL, HeidelbergCement AG, Ingenieurbüro Kühlerbau Neustad GmbH (IKN), Centre for Research and Technology Hellas (CERTH), Bundesanstalt für Geowissenschaften und Rohstoffe (BGR), Politecnico di Milano (POLIMI), Geological Survey of Belgium (RBINS-GSB), ENGIE Laborelec, Port of Rotterdam, Calix Limited, CIMPOR-Indústria de Cimentos SA and Lhoist Recherche et Development SA. References Bradshaw, J., Bachu, S., Bonijoly, D., Burruss, R., Holloway, S., Christensen, N. P., & Mathiassen, O. M. (2007). CO2 storage capacity estimation: Issues and development of standards. International Journal of Greenhouse Gas Control, 1(1), 62–68. https://doi.org/10.1016/S1750-5836(07)00027-8 IPCC. (2005). Carbon Dioxide Capture and Storage. https://www.ipcc.ch/report/carbon-dioxide-capture-and-storage/ United Nations. (2020). United Nations Framework Classification for Resources: Update 2019. UN. https://doi.org/10.18356/44105e2b-en US EPA. (2016). Global Greenhouse Gas Emissions Data. US EPA. https://www.epa.gov/ghgemissions/global-greenhouse-gas-emissions-data Welkenhuysen, K., Brüstle, A.-K., Bottig, M., Ramírez, A., Swennen, R., & Piessens, K. (2016). A techno-economic approach for capacity assessment and ranking of potential options for geological storage of CO2 in Austria. Geologica Belgica. http://dx.doi.org/10.20341/gb.2016.012