abstract: In grain size analysis, the proportion of particles with a diameter of less than 63 µm is commonly referred to as the mud content of a sediment sample. The mud content is an important biophysical variable that often can be mapped with a quantifiable correspondence to organic matter, contaminants and the occurrence of benthic species and assemblages. Thismap conveys information on the percentage mud content of seabedsediments in the North Sea. It has been produced with multivariate geostatistics (external drift kriging) using water depth as a trend variable. The underlying data set is a compilation of over 30,000 sediment samples from many national and Europaen surveys conducted over a period of more than 50 years. Due to the vintage of some samples in the database, users are advised to consider the dynamic nature of the seafloor when using the data and when creating derived surrogate based habitatmaps. Also, due to the diversity of sources for the pointdata, users should be aware of the differing methods by which the grain size analyses were conducted. As a consequence, map confidence is not necessarily uniform and thus areas not always comparable, even though the interpolation surface may look continuous. purpose: The map shows the percentage mud content (silt + clay) of surface sediments in the North Sea predicted by interpolation of legacy grain size distribution data. It has been produced to aid in describing physical habitat characteristics and to supply consistent baseline data and boundary conditions for ecological and biophysical modelling.
observational data
: Level 3c data (products) usually take the form of a homogenous regularity gridded field and will be reserved for specialist, one-...
Description
observational data
: Level 3c data (products) usually take the form of a homogenous regularity gridded field and will be reserved for specialist, one-off products https://www.godae.org/Data-definition.html instruments: In Situ/Laboratory Instruments>>Samplers
platforms: In Situ Ocean-based Platforms>>SHIPS
Accuracy is described in Bockelmann (2018) https://doi.org/10.1016/j.margeo.2017.11.003
FAIR
F-UJI result: total 66 %
Description
Summary: Findable: 6 of 7 level; Accessible: 2 of 3 level; Interoperable: 3 of 4 level; Reusable: 5 of 10 level
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2017-12-12
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The temporal coverage description (metadata) is consistent to the data: passed; 6. The format is correct: passed; 7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1