CEFASc5111ddb-7772-4bd9-90dc-919dd9223989 English dataset Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk pointOfContact 2025-09-24T02:09:39 EPSG Geodetic Parameter Registry 2022-01-07 revision WGS 84 Biotope (macrofaunal assemblage) map and associated confidence layer based on grab and core data from 1976 to 2020 2022-02-11 publication 2025-09-24 revision 2022-02-11 creation CEFAS21416 https://data.cefas.co.uk Two vector (.shp) files are provided. The first, (*macro_assemblages.shp*) shows the modelled (random forest) macrofaunal assemblage type based on a clustering of abundance data from the OneBenthic database (see `https://sway.office.com/HM5VkWvBoZ86atYP?ref=Link`_). The second file, *(macro_assemblages_confidence.shp)* shows associated confidence in the modelled output, with darker shades (high values) indicating higher confidence and lighter shades (lower values) indicating lower confidence. Both layers can be viewed in the OneBenthic Layers tool *( `https://rconnect.cefas.co.uk/onebenthic_layers/`_)*, together with further details of the methodology used to produce them. .. _`https://sway.office.com/hm5vkwvboz86atyp?ref=link`: https://sway.office.com/HM5VkWvBoZ86atYP?ref=Link .. _`https://rconnect.cefas.co.uk/onebenthic_layers/`: https://rconnect.cefas.co.uk/onebenthic_layers/ Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk originator Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk custodian Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk distributor Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) data.manager@cefas.co.uk owner notPlanned Benthos Biodiversity Invertebrate Model GEMET, version 1.0 2008-06-01 publication Biota abundance, biomass and diversity SeaDataNet P03 parameter discovery vocabulary 2011-03-25 revision Habitat characterisation SeaDataNet P02 parameter discovery vocabulary 2011-03-25 revision Species distribution GEMET - INSPIRE themes, version 1.0 2008-06-01 publication Unknown SeaVoX Vertical Co-ordinate Coverages 2010-05-18 revision Marine Environmental Data and Information Network MEDIN metadata record availability 2012-01-11 publication data.gov.uk MEDIN metadata record availability 2012-01-11 publication otherRestrictions noLimitations otherRestrictions **Publicly available data licensed under the Open Government Licence v3.0 (`https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)`_ – Please note the applicable attribution statement is as follows: includes Crown copyright, Cefas 2022** .. _`https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)`: https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ 185 English biota 1.73881 1.74086 52.4581 52.4595 1976-11-16 2020-08-09 Delimited Geographic Information System Unknown https://data.cefas.co.uk/view/21416 Cefas Data Portal download The Cefas Data Portal contains metadata records and data sets available to download and connect to in support of our commitment to open science. Data is available in the following formats: CSV, ESRI Shapefile. The data can also be accessed via the WFS and WMS protocols. dataset INSPIRE Data Specification on Species Distribution – Technical Guidelines 2013-12-10 publication false See the referenced specification Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 publication true See the referenced specification The modelled layer for macrofaunal assemblage is based on a random forest modelling of point sample data from the OneBenthic *(OB, `https://rconnect.cefas.co.uk/onebenthic_dashboard`_/)* dataset, largely following the methodology in Cooper et al. (2019), but with an expanded dataset covering the Greater North Sea and including data from the EurOBI (`https://www.eurobis.org/`_) data repository. Of the 44,407 samples within OB, we selected a subset of 31,845 for which data were considered comparable (i.e. sample acquired using a 0.1 m2 grab or core, processed using a 1 mm sieve and not taken from a known impacted site). Colonial taxa were included and given a value of one. To take account of potential differences in taxonomic resolution between surveys, macrofaunal data were aggregated to family level using the taxonomic hierarchy provided by the World Register of Marine Species (`https://www.marinespecies.org/`_). This reduced the number of taxa from 3,659 to 750. To address spatial autocorrelation in the data, and in keeping with the previous approach, samples closer than 50 m were removed from the dataset, reducing the overall number to 18,348. A fourth-root transformation was then applied to the data to down weight the influence of highly abundant taxa. Data were then subjected to clustering using k-means. A species distribution modelling approach, based on random forest, was then used to model cluster group (i.e. macrofaunal assemblage or biotope) identity across the study area (Greater North Sea). Cross-validation via repeated sub-sampling was done to evaluate the robustness of the model estimate and predictions to data sub-setting and to extract additional information from the model outputs to produce maps of confidence in the predicted distribution, following the approach described in Mitchell et al. (2018). The cross-validation was done on 10 split sample data sets with 75% used to train and 25% to test models, randomly sampled within the levels of the response variable to maintain the class balance. The final model output was plotted as the cluster class with the majority vote of all 10 model runs. An associated confidence map was produced by multiplying map layers for 1) the frequency of the most common class and ii) the average probability of the most common class. Model outputs are used in the OneBenthic Layers Tool ( `https://rconnect.cefas.co.uk/onebenthic_layers/)`_. Cooper, K.M.; Bolam, S.G.; Downie, A.-L.; Barry, J. 2019. Biological-based habitat classification approaches promote cost-efficient monitoring: An example using seabed assemblages. J. Appl. Ecol. 56:1085–1098. `https://doi.org/10.1111/1365-2664.13381`_ Mitchell, P.J., Downie, A.-L., Diesing, M. How good is my map? 2018. A tool for semi-automated thematic mapping and spatially explicit confidence assessment. Env. Model. Softw. 108, 111–122. `https://doi.org/10.1016/j.envsoft.2018.07.014`_ .. _`https://rconnect.cefas.co.uk/onebenthic_dashboard`: https://rconnect.cefas.co.uk/onebenthic_dashboard .. _`https://www.eurobis.org/`: https://www.eurobis.org/ .. _`https://www.marinespecies.org/`: https://www.marinespecies.org/ .. _`https://rconnect.cefas.co.uk/onebenthic_layers/)`: https://rconnect.cefas.co.uk/onebenthic_layers/) .. _`https://doi.org/10.1111/1365-2664.13381`: https://doi.org/10.1111/1365-2664.13381 .. _`https://doi.org/10.1016/j.envsoft.2018.07.014`: https://doi.org/10.1016/j.envsoft.2018.07.014 MEDIN 3.1.1