GIS based tools for marine habitat determination and marine spatial

planning Tiffany C. Vance

NOAA/NMFS/Alaska Fisheries Science Center

C.J. Beegle-Krause, David Steube

ASA / Applied Science Associates

Sharon M. MesickNOAA National Oceanographic Data Center / Coastal Data Development

Center

Why look at habitat?

• Climate studies look at societal impacts – habitat loss/gain/change is analogous for organisms

• Legislative mandate to identify critical habitat• As ecosystem forecasting develops, need for

tools to integrate climate impacts• Element of marine spatial planning –

identifying critical areas and activities that can occur there

• Ecosystem forecasting

Defining Habitat

• Habitat crucial to survival of organisms

• Habitat can be 2.5 or 3D

• Determining habitat parameters for organisms, e.g. temperature ranges, altitudes or substrate types

• Data gathering vs habitat modeling

Using GIS to Delineate Marine Habitat

• Seagrass is a typical 2D habitat

• Species interact with the surface

• Bottom type, slope and currents define

‘best’ habitat

• GIS provides many tools to delineate and

model benthic habitats

• Open ocean fish experience a

multidimensional environment

• Species interact with water column

• Optimal pelagic habitat varies by life stage

and is multivariate

• Traditional GIS tools inadequate to

integrate diverse time series data

• Walleye Pollock produce the largest catch of any single species inhabiting the 200-mile U.S. Exclusive Economic Zone.

• Key forage fish in the ecosystem• One spawning aggregation is in Shelikof Strait.

- Larvae transported down the Strait. - Favorable nursery areas assumed to be inshore- Larval dispersal studied using sampling, drifters and models

Walleye Pollock in Shelikof Strait

EcoFOCI Forecast Horizon

Years: 1 50

INPUT: Indices ROMS/NPZ IPCC Scenario

OUTPUT : Qualitative Quantitative Quantitative Scenario Prediction Prediction

EXAMPLES : Ecosystems FOCI Recruitment Work in Process Considerations Predictions (Recruitment, Chapter Dominant Stabeno et al., Species (2008) Energy Flow)

EcoFOCI = Ecosystems and Fisheries Oceanography Coordinated Investigations

NPCREP = North Pacific Climate Regimes and Ecosystem Productivity

HabitatSpace• Pelagic habitat – 3D

• Using in situ data, ocean models and biological data to define habitats

• Interactive not static display

• User can define parameter ranges for organism, iterative

• Statistics to compare habitats

Software Elements• ArcGIS – extension and standalone tool

• IDV - for analysis and visualization

• netCDF files in a THREDDS server

• EDC - Environmental Data Connector

• ASA COASTMAP

• Statistics toolbox – Python

System Architecture

Data Sources Data Server Clients

• Ocean Models

- NCOM, ROMS

• Physical data

- temperature, salinity

• Meteorological data

- Wind speed, insolation

• Biological data

-Fish catch abundance

• Larval track

-Modeled using ROMS currents data

Northern Gulf Institute

Ecosystem Data Assembly Center

• Visualization:-Integrate data to define habitats

• ESRI ArcGIS ext or standalone tool

• IDV client

• Statistical Analysis- Hot spot analysis

- Kriging

- Mean center

-User defined, iterative

parameter ranges

-Path of organism through

habitat

• Data Ingest

- ASCII

- NetCDF

- Shapefiles

• Transformation

-From source to standard formats

• Data Service

- THREDDS

- ESRI FGDB

ASA-IDV Data Connector

• Ocean Model Data (ROMS)• Curvilinear grid• Single file• netCDF CF

compliant • Works ‘out of the

box’

ESRI Data ConnectionsPhysical

Meteorological

Biological

Particle (Larval) Track

Ancillary (grid)

• Feature data readily ingested

• Point, line & poly

• Raster data readily ingested

• Users specify data rendering with customized menus

• Select and name variables

• Name and save

project files

Analysis Capabilities• Shape

characterization• Statistics

– Landscape metrics

– Fractal dimension

– Mean center

• Path of organism through habitat

Conclusions

• Habitat determination is important for marine spatial planning and in determining climate impacts

• GIS can provide tools to describe and model habitats in 3-D

• IDV can be modified to provide visualization and analysis of habitats

• Statistical tools for landscape metrics in 3-D still under development

For additional information contact:

Tiffany.C.Vance@noaa.gov

Guide to the ASA IDV plugin available in the back.

Plugin available at www.asascience.com

Terrestrial Habitat for Ducklings

http://www.ducks.ca/aboutduc/news/archives/2004/040531.html