Determining the Spatial Distribution of Benthos in the Western Arctic Ocean Jon Goodall Environmental and Water Resources Engineering December 6, 2001 CE 394K.3 GIS in Water Resources Term Project Presentation

Overview Background –Identify Study Region –Introduce Benthic Biomass Data Sets –Explain Ordinary Kriging Benthic Biomass in the Western Arctic Ocean –Account for Global Trends –Present Biomass Interpolated Surface –Discuss Results Conclusions

What is Benthic Biomass? Measurement of amount of living material on the ocean floor (g/m 2 )

Study Region Projection: Lamberts Azimuthal Equal-Area Alaska Canada Siberia Bering Strait Western Arctic Ocean Pacific Ocean

Data Sets Stoker (1970 – 1974)Wacasey (1971 –1975)Carey ( )Broad (1975 – 1981)Feder (1979 – 1986)Grebmier (1984 – 1995) Complete Data Set (1970 – 1995) Stoker (1970 – 1974)Wacasey (1971 –1975)Carey ( )Broad (1975 – 1981)Feder (1979 – 1986)Grebmier (1984 – 1995)

Benthic Biomass at Each Location Image created in ArcScene with 3D Analyst Alaska Canada Siberia

Why Use Geostatistics? Point dataContinuous Surface “The Geostatistical Analyst uses sample points taken at different locations in a landscape and creates (interpolates) a continuous surface.” -ArcGIS Help Menu

Source: aqd.nps.gov/ard/figure3.html

How Ordinary Kriging Works h = Separation Distance Z(i) = Attribute value at i N = # samples separated by distance h You can find value at any location based on known values at neighboring locations

“One of the main issues concerning Ordinary Kriging is whether the assumption of a constant mean is reasonable.” - ArcGIS Help Menu

68.5 º N

Location of Data Split 68.5 º N

(-43 for overall data set)

Benthic Biomass Spatial Distribution (Northern Data Set) Legend Prediction Standard Contours Biomass (g/m 2 ) 0 – – – –

Benthic Biomass Spatial Distribution (Southern Data Set) Legend Prediction Standard Contours Biomass (g/m 2 ) 0 – – – –

Semivariograms NorthSouth

Small-Scale Variation a Problem in Southern Data Set Biomass (g/m 2 ) Biomass (g/m2) = 1216 = 720 = 405 = 254 Which is it?

Small-Scale Variation in Northern Data Set Biomass (g/m2) = 840 = 270 = 269 Biomass (g/m 2 )

Conclusions It was possible to interpolate the biomass on a continuous scale with relatively high certainty for the northern region This method was not capable of accurately predicting biomass in the southern region due to small-scale variability of biomass measurements Future work: Is small-scale variability a result of measuring errors or is it an inherent property of the benthic biomass?

Acknowledgements Dr. Maidment Center for Research in Water Resources Dr. Barrett Center for Research in Water Resources Dr. Dunton Marine Science Institute UT-Austin Susan Schonberg Marine Science Institute UT-Austin Jóna Finndís Jonsdottír Previous M.S. Student Center for Research in Water Resources

Questions?