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
Why classify oceanic structure?
• related to biological spatial distributions
• temporal changes (e.g. regime shifts)
• Steller sea lion in an ecosystem context
Oceanic structure classified Dodimead et al. 1963
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)
A quantitative approache.g. classifying landscapes
High densityResidentialIndustrialRoadsWaterPastureForestWetlandGrass
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.
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.
Results: summer, 1966-1975
130°140°150°160°170°180°170°
130°
140°
150°160°
30°
50°
40°
60°
Results: correspond to domains
Summer, 1966-1975
Results: seasonal variability
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
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
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
Summary
• quantitative and adaptable approach
• regions correspond to classic domains
• temporal differences mapped and quantified
• regions have biological relevance
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.
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
Classification algorithmSelecting the number of clusters to keep
Keep 6 or 8 clusters
Biomes and provinces of Longhurst 1998
• variability within not evident
• boundaries may shift
Oceanic structure classified
