OneBenthic brings together disparate benthic datasets from grab/core, trawl, imagery and eDNA surveys in a cloud-based platform.
The resulting high-quality, standardised dataset is used to generate new science, and innovative and collaborative ways of working.
This big data approach creates an opportunity to do things differently, realising the concept of 'collect once, use many times' by finding ways to add
value to marine data.
This is important given the increasing use of the marine environment and the challenges associated with delivering sustainable development.
Outputs are shared via open-access publications and a suite of interactive web apps.
OneBenthic brings together four Postgres databases (grab/core, trawl, imagery, and eDNA), providing access to more than 60,000 samples.
While the imagery and eDNA databases are recent additions and still under development, data from the grab/core and trawl databases can be accessed via web app (see Apps tab) or API (grab/core only).
We continue to collate data from a variety of sources, but get in touch if you'd like to share your data. They'll immediately appear within the apps (putting them into a broader context), and will also support new scientific endeavours, generating insights and promoting more sustainable marine practices.
Explore the data holdings in the map opposite.
Explore the faunal assemblage composition of grab and core samples (see Cooper and Barry, 2017).
The Survey Array Tool provides a record of survey arrays and associated protocols.
Match new faunal data to existing cluster groups identified using machine learning.
This tool allows users to see locations where such species have been encountered and to track their spread over time.
Use this tool to identify ecologically significant changes in sediment composition in support of the delivery of licence compliance requirements.
Identify statistically significant changes in sediment composition between baseline and monitoring surveys. Use it for monitoring of licensed areas, MPAs and research sites.
Identify statistically significant changes in faunal composition between baseline and monitoring surveys. Use it for monitoring of licensed areas, MPAs and research sites.
Use this tool to identify and download macrofaunal and sediment particle size data from the OneBenthic grab/core sample database.
Use this tool to identify and download macrofaunal and sediment particle size data from the OneBenthic trawl sample database.
Use this tool to obtain distribution records for selected taxa from the OneBenthic grab/core sample database.
YouTube video explanation of how app works.
YouTube video explanation of how to use OneBenthicAPI-9 to access spatial data layers in raster .tif format.
YouTube video explanation of how to use OneBenthicAPI-10 to access to Primary and Secondary Impact Zone (PIZ/SIZ) polygons for UK marine aggregate extraction licenses.
Cooper, K.M., Thompson, M.S.A., Bolam, S.G., Peach, C.M., Webb, T.J., Downie, A-L. (2026). Mapping benthic biodiversity to facilitate future sustainable development. Ecosphere 17(1), e70494. https://doi.org/10.1002/ecs2.70494
Bolam, S.G., Cooper, K.M., Downie, A-L. 2026. Developing an ecological risk-based approach to facilitate licensing offshore wind development. Ecosphere 17(1), e70520. https://doi.org/10.1002/ecs2.70520
Cooper, K.M., Curtis, M., Downie, A‑L. & Bolam, S.G. (2026). Big data approaches reveal large‑scale spatial patterns in marine epifauna. ICES Journal of Marine Science, 83(1), fsaf227. https://doi.org/10.1093/icesjms/fsaf227
Couce, E., Pinnegar, J.K., & Townhill, B.L. (2025). Climate change resilience of vulnerable marine species in northwest Europe. Marine Biology, 172(116), 1-12. https://doi.org/10.1007/s00227-025-04672-x
Bolam, S.G., Cooper, K., Downie, A.-L. (2023). Mapping marine benthic biological traits to facilitate future sustainable development. Ecological Applications e2905. https://doi.org/10.1002/eap.2905
Cooper, K.M, Barry, J. (2017). A big data approach to macrofaunal baseline assessment, monitoring and sustainable exploitation of the seabed. Scientific Reports, 7:12431 doi:10.1038/s41598-017-11377-9
Cooper, K.M., Bolam, S. G., Downie, A. L. and Barry, J. (2019). Biological‐based habitat classification approaches promote cost‐efficient monitoring: an example using seabed assemblages. J Appl Ecol. 56:1085–1098. doi:10.1111/1365-2664.13381
Cooper K.M., Barry, J. (2020). A new machine learning approach to seabed biotope classification. Ocean and Coastal Management 198, 105361. https://doi.org/10.1016/j.ocecoaman.2020.105361
Barrio Froján, C.R.S., Cooper, K.M., Bolam, S.G. (2016). Progress towards a unified approach to marine benthic monitoring. Mar. Pollut. Bull. 104, 20-28.
Thompson, M.S.A., Couce, E., Webb, T., Grace, M., Cooper, K.M., Schratzberger, M. (2020). What’s hot and what’s not: Making sense of biodiversity ‘hotspots’. Global Change Biology 27, 3: 521-535.
Cooper, K. M., Downie, A.-L. and Curtis, M. (2022). North Sea Net Gain (NSNG). Cefas Project Report for The Crown Estate, 57 pp.
Gray, P., Garcia, C., Robinson, C., Bremner, J. (2022). A method for Identifying sensitivity of marine benthic invertebrates to ocean acidification through a biological traits approach. ICES Journal of Marine Science 79, 7: 2117–2125. https://doi.org/10.1093/icesjms/fsac146
McIlwaine, P.S.O., Barry, P.J., Curtis, M., & Cooper, K.M. (2025). Tracking long-term benthic recovery at a disused marine aggregate extraction site using monitoring tools developed for the marine aggregate industry. Estuarine, Coastal and Shelf Science, 319, 109278. https://doi.org/10.1016/j.ecss.2025.109278
Putuhena, H., Williams, T.J., Sturt, F., White, D., Solan, M., Godbold, J.A., & Gourvenec, S. (2025). Integrated geospatial datasets to inform marine spatial planning and impact assessment in waters surrounding the United Kingdom. Scientific Data, 12, 1845. https://doi.org/10.1038/s41597-025-05950-5
Dove, D., Marchant, B., Mowat, M., Paice, M. 2025. User Guide for Predictive Seabed Sediments - UK (v1). British Geological Survey Open Report, OR/25/040. 50pp
Bakir, A., Porter, A., Lewis, C., Barry, J., Brookes, R., Procter, W., Silburn, B., McGoran, A. R., Garcia, C., Mason, C., Bolam, S., Clare, D. S., Cooper, K., Downie, A., Ellis, J., Wood, D., Phillips, C., & Galloway, T. S. (2025). A step towards microlitter risk assessment: Modelling microlitter storage potential of the UK seabed. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 383(2307), 20240428. https://doi.org/10.1098/rsta.2024.0428
From Cooper, K.M., Bolam, S. G., Downie, A. L. and Barry, J. (2019), Biological-based habitat classification approaches promote cost-efficient monitoring: an example using seabed assemblages. J Appl Ecol. 56:1085-1098. doi:10.1111/1365-2664.13381
From Cooper, K. M., Downie, A.-L. and Curtis, M. (2022). North Sea Net Gain (NSNG). Cefas Project Report for The Crown Estate, 57 pp.
Fully interactive 3D model based on work in Cooper, K. M., Downie, A.-L. and Curtis, M. (2022). North Sea Net Gain (NSNG). Cefas Project Report for The Crown Estate, 57 pp.
DEM data source: GEBCO Compilation Group (2022) GEBCO 2022 Grid (doi:10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c).
In addition to the data extraction tools (see Apps tab), OneBenthic data are also available via API (Application Programming Interface).
APIs allow you either to download data (e.g. in JSON format, raster .tif files), or to access them directly within an R session.
The OneBenthic APIs provide access both to:
- raw data (e.g. API-1),
- data formatted for OneBenthic apps (e.g. API-6), and
- spatial raster outputs (e.g. API-9).
To download data, simply open the relevant API interface and follow the instructions. JSON data can be converted to .csv format using the instructions
here.
Use this
script
to access data directly in an
R
session. Further APIs will be released in due course.
Returns publicly available macrofaunal abundance and biomass (where available) data from the OneBenthic grab/core database. Filter data by parameters: year and sieve size. Use the OneBenthic dashboard (grab/core) (see Apps) to identify available values for filtering parameters.
Returns publicly available occurance records for selected taxa from the OneBenthic (grab/core) database. Select using a valid AphiaID code (see https://www.marinespecies.org/).
Returns publicly available sediment particle size data (PSA) from samples in the OneBenthic (grab/core) database. Filter data by parameters: year. Use the OneBenthic dashboard (grab/core) (see Apps) to identify available values for filtering parameter.
Returns macrofaunal abundance and biomass (where available) data from Marine Conservation Zones (MCZ). Filter data by parameters: year. Use the OneBenthic dashboard (grab/core) (see Apps) to identify available values for filtering parameter.
Returns family level macrofaunal abundance data for use with the OneBenthic Faunal Cluster ID Tool (see Apps). Filter data by parameter: Survey Name. Use the OneBenthic Data Extraction Tool (grab/core) (see Apps) to identify available values for filtering parameter.
Returns sediment data (% Wentworth class), from aggregate industry RSMP surveys, for use with the OneBenthic M-test Tool (see Apps). Filter data by parameter: Survey Name. Use the OneBenthic Data Extraction Tool (grab/core) (see Apps) to identify available values for filtering parameter.
Returns UK priority non-native taxa. Filter by parameter: year.
Identify and download modelled benthic biodiversity layers in .tif format. File names are prefaced with the relevant publication (see Publications tab). Watch a demo video from the Demo Videos tab.
Identify and download Primary and Secondary Impact Zone (PIZ/SIZ) polygons for UK marine aggregate extraction licenses IN GeoJSON format. Watch a demo video from the Demo Videos tab.
Your data will be visible in the apps
You'll be contributing to research and decision making
Turn your data into useful information
Improved understanding leads to better decisions
Stay up-to-date with developments
Help shape future direction
Work with stakeholders and other sectors on issues of common interest