Select benthic invertebrate and sediment data collected between 1969 and 2023 for an Ecological Risk-Based Approach to Facilitate Licensing Offshore Wind Development

The OneBenthic dataset contains records of benthic invertebrate assemblages and associated sediment particle size analyses (PSA) collected between 1969 and 2023 across the UK continental shelf and wider North Sea. It brings together harmonised information on macrofaunal abundance, biomass, and sediment composition derived from more than 50,000 seabed grab and core samples. For this study, a quality-controlled subset of 18,348 samples was used to generate spatial models of three ecological risk elements: benthic sensitivity (based on biological traits), biodiversity, and assemblage rarity. The dataset supports the development of ecological risk maps and an online decision-support tool to inform offshore wind farm licensing and marine spatial planning. Users should note that the dataset represents sedimentary habitats sampled by grabs and cores; results may not accurately describe rocky or hard-substrate environments and are not intended for navigational use.

The dataset was compiled from publicly available benthic invertebrate and sediment particle size analysis (PSA) data stored within the OneBenthic database, a cloud-based PostgreSQL repository maintained by the Centre for Environment, Fisheries and Aquaculture Science (CEFAS). The database integrates over 50,000 grab and core samples collected between 1969 and 2023 from UK shelf waters and neighbouring areas of the northeast Atlantic. Sampling methods followed established methodology, with the subset used here restricted to samples collected using a 0.1 m² grab or core and processed on a 1 millimetre sieve. Colonial taxa were included and recorded with a value of one. Raw abundance data were fourth-root transformed to down-weight highly abundant taxa, and samples less than 50 metres apart were removed to mitigate spatial autocorrelation. Biological traits information for taxa was sourced primarily from Clare et al. (2022), with trait data inferred for missing taxa using closely related genera or families. Samples were subject to quality control checks to ensure consistency in taxonomic nomenclature (via the World Register of Marine Species, WoRMS) and comparability of sampling methods. Environmental predictor variables used for modelling were obtained from Bio-ORACLE, gridded bathymetry data (GEBCO), and sediment composition layers from Mitchell et al. (2019). Spatial modelling of sensitivity, biodiversity, and assemblage rarity was carried out using Random Forest approaches with cross-validation to assess model robustness. Overall, the dataset is considered of high quality for large-scale spatial analyses of benthic assemblages in sedimentary habitats. Users should note that the dataset does not include rocky or hard-substrate habitats and is therefore not comprehensive for all benthic environments.