purpose:
The map shows the median grain size (or d50) 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.
abstract:
In grain size analysis, the median is the midpoint of the cumulative particles size distribution curve of a sediment sample. The median grain size is an important biophysical variable that relates to sediment stability and often can be mapped with a quantifiable correspondence to the occurrence of benthic species and assemblages. This map conveys information on the median grain size of seabed sediments in the North Sea. It has been produced with multivariate geostatistics (external drift kriging) using the percentage mud content as a trend variable. The underlying data set is a compilation of over 30,000 sediment samples from many national and European 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 habitat maps. 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 my look continuous.
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