exploring the structure of the oceanic environment: a classification approach edward gregr karin...
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Exploring the structure of the oceanic environment:
A classification approach
Edward GregrEdward GregrKarin BodtkerKarin BodtkerAndrew TritesAndrew Trites
Marine Mammal Research UnitMarine Mammal Research UnitFisheries CentreFisheries CentreUniversity of British ColumbiaUniversity of British Columbia
October 2004October 2004
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Why classify oceanic structure?
• related to biological spatial distributions
• temporal changes (e.g. regime shifts)
• Steller sea lion in an ecosystem context
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Oceanic structure classified Dodimead et al. 1963
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Extending the classification approach
• biological perspective
• quantitative and repeatable
• adaptable– consider temporal variability
(seasons, years, regimes)
– different spatial scales (zooplankton vs. fish vs. sea lions)
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A quantitative approache.g. classifying landscapes
High densityResidentialIndustrialRoadsWaterPastureForestWetlandGrass
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Data for oceanic classification
Wind stress
Surface current speed
SSH
SSS
SST
1Yi Chao, Jet Propulsion Lab, California Institute of Technology
1 degree ROMS output1, interpolated to equal area grid.
Seasonal averages,1966-1975 and 1980-1989.
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Classification methodH - means clustering algorithm1
Sea surface salinity
Sea surface temperature
oC
31 32 33 34 350.0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
-0.8
+
+
+
+
+
Identify initial clusters
Assign pixels to ‘nearest’ cluster based on maximum likelihood
Iterate until stable
1Hartigan, J. A. 1975. Clustering Algorithms. John Wiley & Sons, New York.
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Results: summer, 1966-1975
130°140°150°160°170°180°170°
130°
140°
150°160°
30°
50°
40°
60°
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Results: correspond to domains
Summer, 1966-1975
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Results: seasonal variability
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Results: regime variability
Pre - winterPost - winter
130°140°150°160°170°180°170°
130°
140°
150°160°
30°
50°
40°
60°
- Alaska gyre: evidence of stronger flow post - 1976
- Transitional domain: boundary shift
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Results: map comparisonsPre-76 Post-76
• Seasons more similar between regimes than consecutive seasons within each regime
Winter
Spring
Summer
Fall
• Consistency between some seasons differs before and after regime shift
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Results: biological relevance
1.38 0.70
1.03
0.560.41
Chl-a, mg/L1
Summer, 1997-2003
1Andrew Thomas, School of Marine Sciences, University of Maine
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Summary
• quantitative and adaptable approach
• regions correspond to classic domains
• temporal differences mapped and quantified
• regions have biological relevance
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Thanks very much ...
Funding:NOAA, the North Pacific Marine Science Foundation, and the North Pacific Universities Marine Mammal Research Consortium.
Data:Yi Chao, Jet Propulsion Lab, California; Mike Foreman, Institute of Ocean Sciences, British Columbia; Al Hermann, PMEL, Washington; Wieslaw Maslowski, Naval Postgraduate School, California; Andy Thomas, University of Maine, Maine.
Intellectual:Ian Perry, Mike Foreman, Stephen Ban, the MMRU lab, and the attendees of numerous earlier presentations of this work.
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Map comparisons
Higher score, more similarSeasons more similar between regimes than
consecutive seasons within each regime.
Summer, 1980 - 1989 Fall, 1980 - 1989
KIA = 0.39AMI = 2.2
Spring, 1966 - 1975 Spring, 1980 - 1989
KIA = 0.49AMI = 2.4
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Classification algorithmSelecting the number of clusters to keep
Keep 6 or 8 clusters
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Biomes and provinces of Longhurst 1998
• variability within not evident
• boundaries may shift
Oceanic structure classified