GIS modelling for marine management Poland habitat mapping Oslo Workshop Martin Isæus
What drives the marine mapping in Sweden, Norway and the Baltic? EU National County management Industry – Marine Wind Power BALANCE Off-shore reefs survey Nature reserve survey WPD Finngrunden
The BALANCE project 19 partners & 10 countries 2½ year & € 4,7 mio. Main activities: Collation of marine environ- mental & anthropogenic data Baltic seafloor mapping Biodiversity assessment Marine spatial planning BSR INTERREG IIIB region from space, Source: SeaWiFS Project, NASA/Goddard Space Flight Centre and ORBIMAGE
The BALANCE approach Collate & analyse available geo- physical and hydrographical information within HELCOM region Define and agree on an unified data format Decide a common platform for data handling, processing and projection of marine landscape map, e.g. ArcGis, WGS84, UTM Define standards for classifying Baltic marine landscapes Validation & confidence scheme Applying an ecosystem-based approach, not the one nation – one approach
Benthic marine landscapes Basic layers: Seabed sediments Photic depth Bottom salinity Secondary layers: Temperature Wave exposure Ice cover Current velocity Bathymetry Word of caution!
Benthic marine landscapes Features 60 benthic landscapes identified Most common is non-photic mud at 7,5 – 11psu covering km 2 or 14,3% of total seabed 8 landscapes cover km 2 or 90,7% of total seabed 40 landscapes cover less than 1% of total seabed area Coverage data for each EEZ as well as entire HELCOM region is available
Linking the physical characterisation to socio-economic exploitation Illustrating the value of (transnational ?) marine landscape mapping Could be linked to implementation of various EU obligations, e.g WFD or pMSD (?) Could be linked to climatic change showing the consequences to marine environment Annual variation in the Cod Reproductive Volume, DIFRES Pelagic marine landscapes – an example
Habitat mapping Norway Denmark Sweden Lituania Estonia Finland
Nephrops in Skagerrak Martin Isæus, AquaBiota Hans C. Nilsson, NIVA Mattias sköld, Swedish board of Fishery
SPI – Sediment Profile Images
Ecological status
Study area Grids from multi-beam survey: Bathymetry (5 m res.) Hardness (4 classes) SPI (22) SPI + fauna (14) SPI + new fauna sample (2) New field data
Predictors importance for the model
Probalitity of Nephrops presence Spearman Corr 0.659
Random SPI + Nephrops burrow shape + Trawling frequency => density plot and population estimate
Kernel density mean yield per cage Radius 5 km, 100m-grid.
Kjell Magnus Norderhaug Martin Isæus Trine Bekkby Frithjof Moy Are Pedersen Spatial predictions of Laminaria hyperborea at the Norwegian Skagerrak coast
Probability of L. hyperborea Monitoring data vs All available data
Off-shore bank survey Natura 2000? Benthic biology Marine geology Hydrography
Nature values?
Utbredning av ”Död mans hand” Alcyonium digitatum
Nature values Fucus (+) Chara (+) Epithytes (-) Filamentous (-) Detritus (-) Sulphuric bacteria (-)
EUNIS in the Baltic
Wind Power FOTO: KNUT STRØM WPD
Bathymetry (multi-beam) Back-scatter Bentic biota Fish Birds Bats Seals
Presence of blue mussel Mytilus and Horse mussel Modiolus
Presence of fish Stensnultra cvROC=0,843 ROC=0,889 cvCOR=0,63 COR=0,682
Abundance of fish Stensnultra cvCOR=0,509 COR=0,619