gis modelling for marine management poland habitat mapping oslo workshop 2007-05-29

GIS modelling for marine

management

Poland habitat mapping Oslo Workshop

2007-05-29

Martin Isæus

08-16 10 11martin.isaeus@aquabiota.se

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 mappingBiodiversity assessmentMarine 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 schemeApplying an ecosystem-based

approach, not the one nation – one approach

Benthic marine landscapesBasic layers:

Seabed sediments

Photic depth

Bottom salinity

Secondary layers:TemperatureWave exposureIce coverCurrent velocity

Bathymetry

Word of caution!

Benthic marine landscapesFeatures 60 benthic landscapes

identifiedMost common is non-photic

mud at 7,5 – 11psu covering 58.640 km2 or 14,3% of total seabed

8 landscapes cover 371.000 km2 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, AquaBiotaHans C. Nilsson, NIVAMattias 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 2002-2006 mean yield per cage

Radius 5 km, 100m-grid.

Kjell Magnus NorderhaugMartin IsæusTrine BekkbyFrithjof 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

2003-06Natura 2000?

Benthic biologyMarine geologyHydrography

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 biotaFishBirdsBatsSeals

Presence of blue mussel Mytilus and Horse mussel Modiolus

0 6,400 12,8003,200 Kilometers

4

Vågexponering0 - 590,000

590,001 - 708,224

Djup-129.49 - -22

-21.99 - 0

Stensnultra sannolikhet0 - 0.05

0.06 - 0.25

0.26 - 0.5

0.51 - 0.75

0.76 - 1

Presence of fish StensnultracvROC=0,843ROC=0,889cvCOR=0,63COR=0,682

Abundance of fish StensnultracvCOR=0,509COR=0,619