Natalie Coltman, JNCC, UK Progress meeting: 25 May 2010, Copenhagen

Outline Work done: work packages & progress Unexpected difficulties Feedback from potential users Information from other EMODNET projects Timetable for rest of project Prototype portal demonstration

Combination A Combination B Biologically relevant? Represented in EUNIS? e.g. Depth e.g. Seabed salinity e.g. Sediment type A reminder!

Work packages and progress WP1 – methodology WP2 – data preparation  finalising layers WP3 – validating thresholds  biological analysis WP4 – modelling & confidence  test runs; fuzzy classifiers WP5 – disseminating data  prototype portal online WP9 – reporting  interim report

Finalising layers Data typeBalticNorthCelticW Med Substrate Bathymetry Light Wave energy at seabed ** Tidal energy at seabed ** Salinity at seabed * Dissolved O 2 Stratification

Substrate Received draft EMODNET Geology substrate layer Continued data collation in W Mediterranean Standardising substrate layer for W Mediterranean

Substrate – N, Celtic & Baltic Sediment: EMODNET

Bathymetry Received draft EMODNET gridded bathymetry North & Celtic Seas: draft layer prepared in anticipation of EMODNET GEBCO & UK national data (SeaZone) W Med: gridded bathymetry prepared under EMODNET (IEO) Baltic: BALANCE bathymetry

Light reaching seabed Baltic based on Secchi disc measurements water depth/Secchi disc depth comparison to remote sensing data North & Celtic Seas, W Med MERIS satellite data 1km resolution  250m improved algorithm for coastal zones

Light – North, Celtic, W Med MERIS 1km  250m

Waves – North, Celtic & Baltic Baltic & North Seas DHI model  (extent only) Celtic & North Seas  DHI model within 6km of coast & POL model beyond

25m resolution Based on fetch Inshore wave model (Aquabiota SWM)

Tidal energy Baltic & North Seas – DHI model Celtic & North Seas – POL models CS20 CS3X NEA W Med North of 39 °N – 1km MENOR model South of 39 °N – 6km MFS model Increasingly coarse models

Energy – W Med 90% maximum bed shear stress for waves and currents combined: December 2008 (Nm -2 ) No tides but wind-driven currents and waves 6km resolution

Salinity, O 2 Baltic horizontal & vertical salinity O 2 to identify a permanent anoxic zone Celtic & North Seas salinity to identify estuarine areas W Med no salinity/O 2 data required

Thresholds: W Med Infralittoral Infralittoral zone defined by extent of Posidonia meadows Mapped extent of healthy meadows used to determine minimum light values Range of 0.84 – 1.08% surface light reaching the seabed to describe infralittoral zone

Lower limit of Posidonia

Thresholds: Baltic No existing Baltic-wide habitat classification Statistical analyses from dive transects & samples Habitats described in existing national habitat classification systems  List of preliminary EUNIS habitats for the Baltic Sea  Classified samples available for definition of thresholds e.g. for algal-dominated habitats: use dive transect data + Secchi disc data

Wave energy

Current energy

Combined wave & current energy

Producing the maps An example model for the Mediterranean: ArcGIS Model Builder

Producing the maps Successful test runs in Brittany, W Mediterranean, UK

UK seabed habitats: EUNIS classification

How good are the maps? Confidence in physical input data Qualitative, based on metadata Confidence in thresholds Fuzzy boundaries between habitats Confidence compared to maps from survey Local comparisons

Qualitative confidence: substrate

Confidence in thresholds ‘High’ ‘Low’ Parameter, e.g. salinity, x ALAL CL,AHCL,AH BLBL D L, B H CHCH DHDH Degree of membership, y 0 1 x2x2 x1x1 Point with salinity value x 1 : Membership of ‘Low’ class = 1 Membership of ‘High’ class = 0 Point with salinity value x 2 : Membership of ‘Low’ class = 0.7 Membership of ‘High’ class = 0.3

0 1 4 salinity classes Fully marine Brackish Freshwater- estuarine Kattegat

Boundaries clearly shown as lower confidence Associated fuzzy scores

Feedback from users HELCOM EUNIS development using EUSeaMap output OSPAR Presentation to a Working Group and paper to Biodiversity Committee EUSeaMap will support the MSFD assessment process ICES Discussions on confidence methodology CIESM Poster presented to CIESM in May PEGASO project interested in extending method to Eastern Mediterranean and Black Sea

Unexpected difficulties Energy Defining EUNIS energy classes numerically Standardising W Med substrate data Lack of raw data Unexpected habitats in W Med Fine-scale parameters driving habitat distribution

Information from other projects EMODNET Geology Date for next draft? Date for substrate confidence? Filling gaps in coverage Clarifications on classification – gravel!! Harmonising boundaries between EEZs

Information from other projects EMODNET Hydrography Update of gridded bathymetry this week Discussions on confidence methodology WMS registry details for online portals

Timetable for rest of project May-10 June-10 July-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 ……. Mar-12 Draft habitat maps Draft confidence maps Final habitat & confidence maps Draft final report Final maps on webGIS Final report Maintenance phase

Further information JNCC website Interim report on EC website  

Seazone 30m grid GEBCO 30 Arcsecond grid North & Celtic Seas – Depth

Light – Baltic

Substrate – W Med IBCM (above) & partner data: currently being harmonised Sediment data for other basins from EMODNET geological lot

Thresholds: N & Celtic Seas energy Peak seabed kinetic energy caused by waves Peak seabed kinetic energy caused by currents Thresholds tested using field data for habitats wave/current observations Current energy Kinetic Energy (Nm -2 ) High > 1.16 Moderate0.13 – 1.16 Low < 0.13 Wave energy Kinetic Energy (Nm -2 ) High > 1.2 Moderate0.21 – 1.2 Low < 0.21

Biological Zone Energy InfraCircaDeep Circa High Medium Low = C (Score of 0.9) = H (Score of 0.9)

Biological Zone Energy HHHLMH MHMLHM MMHHML LMMLHH LLHMHL LLMHLM Associated fuzzy scoresFuzzy classification output ICICDD IIICDD CICCCD ICCCCD CCIICC IIIICD These can be combined and equated to EUNIS codes These are measures of confidence in thresholds

‘Raw’ salinity layer Fuzzy class 1Fuzzy class 2Fuzzy class 3Fuzzy class 4 0 1