Alternate title

GB400007

Date (Creation)

2015-03-30

Date (Publication)

2018-04-26

Citation identifier

EMODnetSeabedHabitats / GB400007

Point of contact

Organisation name	Individual name	Electronic mail address	Role
Defra		open@defra.gsi.gov.uk	Owner
JNCC		habitatmapping@jncc.gov.uk	Custodian

GEMET - INSPIRE themes, version 1.0

• Habitats and biotopes

http://inspire.ec.europa.eu/codelist/ReferenceHabitatTypeSchemeValue

• Eunis

Use limitation

┬® Defra. Data may be re-used under the terms of the Open Government Licence.

Use limitation

geossAttribution

Access constraints

Other restrictions

Other constraints

no limitation

Spatial representation type

Vector

Denominator

100000

Language

English

Topic category

• Biota
• Oceans

Begin date

2012-01-01

End date

2012-12-31

Supplemental Information

Lark, R.M.. 2015 Mapping seabed sediments of the Fulmar rMCZ. Nottingham, UK, British Geological Survey, 12pp. (OR/15/015) (Unpublished) Available from: http://nora.nerc.ac.uk/id/eprint/510587/

Reference system identifier

EPSG / WGS 84 (EPSG:4326) / 7.9

Topology level

Geometry only

Distribution format

Name	Version
ESRI Shapefile	1.0

OnLine resource

Protocol	Linkage	Name
WWW:LINK-1.0-http--link	https://www.emodnet-seabedhabitats.eu/access-data/launch-map-viewer/?zoom=10&center=2.17705,56.35055&layerIds=501&baseLayerId=1&activeFilters=NobwRANghgngpgJwJIBMwC4CsAGAjAGjADMBLCAF0VQwBYB2Q0ixAGQHs2BrAVwAdUAzhmABdRmUoIAKnAAe5DGADiAIRrYN2OmAC+IoA	EMODnet Seabed Habitats Map Viewer
OGC:WMS	https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_view_maplibrary/wms?	gb400007
OGC:WFS	https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_open_maplibrary/wfs?	gb400007
WWW:LINK-1.0-http--link	https://files.emodnet-seabedhabitats.eu/data/EMODnetSBHsurvey_GB400007.zip	EMODnet Seabed Habitats download

Hierarchy level

Dataset

Statement

The data used in this work were obtained by Cefas in 2012 (Ware & Meadows, 2013). A total of 65 stations were sampled by 0.1 m2 Hamon grab on a pre-planned survey grid. JNCC required that only PSA data supplied by JNCC specifically for this work should be used to produce the outputs. This is to remove compatibility issues arising from the use of PSA data originating from differing grab techniques. The data provided are percent by mass of gravel (particles diameter > 2mm), mud (particles diameter < 0.063 mm) and sand (particles 2mm > diameter > 0.063 mm).

Before modelling the linear coregionalization, exploratory spatial analysis was undertaken. There is a pronounced cluster of observations in the south west corner of the rMCZ, and the exploratory analysis indicated that this clustering was a potential source of artefacts for spatial modelling. Whilst some close-spaced observations are desirable for the estimation of spatial models, this pronounced clustering can cause problems because of over-representation of one part of the region (e.g. Marchant et al., 2013). For this reason the cluster of points was removed leaving 52 data for spatial modelling. All 65 data were used subsequently for mapping, as described in section 2.3. Auto-variograms and cross-variograms of the alr-transformed data were estimated from the data. The same method-of-moments estimator (MoM) was used as described by Lark et al. (2012). The linear model of coregionalization (LMCR) was fitted to the MoM estimates of the auto- and cross-variograms by weighted least squares, as described by Lark et al. (2012).

Lark et al. (2012) describe the cokriging procedure used to obtain conditional expectations of the transformed variables and covariance matrices for these at target points. This procedure was undertaken to form predictions at nodes of a 250-m grid. At this stage all 65 observations in the data set were used. The simulation method used by Lark et al. (2012) was then used to generate 5000 independent realizations from the joint prediction distribution at each node. For each realization a back-transformation was undertaken to give values of gravel, mud and sand. Over all realizations the mean value of gravel, mud and sand were computed as the conditional expectation of these variables, and the 0.025 and 0.975 quantiles of the realizations were computed as confidence intervals for the predictions. It should be noted that these predictions and confidence intervals should be considered for each variable in turn. For each realization, the EUNIS level 3 sediment texture classes (Long, 2006) were identified. At each grid node the proportion of realizations that occurred in each class is an estimate of the conditional probability of finding that class at the location. One may report the probability for each class, one may also report the class of maximum probability. The uncertainty attached to treating a site as if the class of maximum probability were the true class, can be evaluated by examining that maximum probability value, which may range from just over 1/k (where k is the number of classes) to 1.0.

Metadata

File identifier

5e247290-6076-48d4-9fe3-93a097f4ae83 XML

Metadata language

English

Character set

MD_CharacterSetCode_utf8

Hierarchy level

Dataset

Date stamp

2020-01-15T12:07:36

Metadata standard name

ISO19115

Metadata standard version

2003/Cor.1:2006

Metadata author

Organisation name	Individual name	Electronic mail address	Role
JNCC		HabitatMapping@jncc.gov.uk	Point of contact