Determining the Spatial Distribution of Benthos

in the Western Arctic Ocean

Jon GoodallEnvironmental and Water Resources Engineering

December 6, 2001

CE 394K.3 GIS in Water ResourcesTerm 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 materialon the ocean floor (g/m2)

Study Region

Projection: Lamberts Azimuthal Equal-Area

Alaska

CanadaSiberia

Bering Strait

Western Arctic Ocean

Pacific Ocean

Data Sets

Stoker (1970 – 1974) Wacasey (1971 –1975) Carey (1971-1976) Broad (1975 – 1981) Feder (1979 – 1986) Grebmier (1984 – 1995)

Complete Data Set (1970 – 1995)

Stoker (1970 – 1974) Wacasey (1971 –1975) Carey (1971-1976) Broad (1975 – 1981) Feder (1979 – 1986) Grebmier (1984 – 1995)

Benthic Biomass at Each Location

Image created in ArcScene with 3D Analyst

AlaskaCanada

Siberia

Why Use Geostatistics?

Point data Continuous Surface

“The Geostatistical Analyst uses sample points taken at different locations in a landscape and creates (interpolates) a continuous surface.”

-ArcGIS Help Menu

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

How Ordinary Kriging Works

2

1

)()(2

1)(

n

iii hXZXZ

nh

h = Separation Distance Z(i) = Attribute value at iN = # samples separated by distance h

Separation Distance

Square difference of attribute Values

100 m 225

150 m 64

100 m 200

75 m 50… …

You can find value atany 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

All Data

y = -43.331x + 3138.2

R2 = 0.2004

0

500

1000

1500

2000

2500

3000

3500

61 63 65 67 69 71 73 75

Latitude

Bio

mas

s (g

/m2 )

68.5 º N

Location of Data Split

68.5 º N

North Data ( > 68.4 N )

y = 3.1665x + 174.43

0

500

1000

1500

2000

2500

3000

3500

61.0 62.0 63.0 64.0 65.0 66.0 67.0 68.0 69.0

Latitude

Bio

mas

s (g

/m2 )

(-43 for overall data set)

South Data ( < 68.4 N)

y = 13.602x - 902.29

0

100

200

300

400

500

600

700

800

900

68.0 69.0 70.0 71.0 72.0 73.0 74.0

Latitude

Bio

mas

s (g

/m2 )

(-43 for overall data set)

Benthic Biomass Spatial Distribution(Northern Data Set)

Legend

Prediction Standard Contours53

71

89

107

Biomass (g/m2)

0 – 2.32.3 – 11.611.6 – 49.7

49.7 – 204.9204.9 - 838

Benthic Biomass Spatial Distribution(Southern Data Set)

Legend

Prediction Standard Contours432

457

482

507

Biomass (g/m2)

0 – 3737 – 106106 – 233

233 – 469469 - 3222

Semivariograms

North South

Small-Scale Variation a Problem in Southern Data Set

Biomass (g/m2)

Biomass (g/m2) = 1216 = 720 = 405 = 254

Which is it?

0 - 105

105- 300

300 - 560

560 - 1000

1000 - 1832

1832 - 3200

Small-Scale Variation in Northern Data Set

Biomass (g/m2) = 840 = 270

= 269

Biomass (g/m2)

0 - 105

105- 300

300 - 560

560 - 1000

1000 - 1832

1832 - 3200

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. MaidmentCenter for Research in Water Resources

Dr. BarrettCenter for Research in Water Resources

Dr. DuntonMarine Science Institute

UT-Austin

Susan SchonbergMarine Science Institute

UT-Austin

Jóna Finndís JonsdottírPrevious M.S. StudentCenter for Research in Water Resources

Questions?