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Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington

Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

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Page 1: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Ecological Indicators: Software Development

Sergei RodionovJoint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington

Page 2: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Outline

Part I. Red noise problem. Upgrade to the regime shift detection method (STARS).

Part II. Knowledge management system for the Bering Sea.

Page 3: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

0 10 20 30 40

-2

0

2

-4

-2

0

2

4

a)

b)

R egim e 1

Regim e 2

AR (1) = 0.8

True and spurious regime shifts

Page 4: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Entry Form for STARS

www.BeringClimate.noaa.gov

Page 5: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Estimates of AR1 for PDO

0 10 20 30 40 50 60 70 80S u b sam p le s ize .

0

0.2

0.4

0.6

0.8

AR

1 co

effi

cien

t

M PK

IP4

O LS

Page 6: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

-1

0

1

-2

-1

0

1

2

-2

-1

0

1

2

a) PDO

b) A fter P rewhitening

c) R esiduals

1948 19761999

1948

PDO Index Before and After Prewhitening

Page 7: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Part II. Dealing with Information Overload

Dimensionality reduction (e.g., principal component analysis, singular value decomposition, multidimensional scaling)

Knowledge management system

Page 8: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Components of the KMS

Data Explorer Rule Explorer Inference Engine Graphical Interface Search Facility Reporting Facility

Page 9: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Data Explorer

Page 10: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

List of rules (partial) with the IF variables that affect walleye pollock recruitment

Page 11: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Part of the influence diagram for walleye pollock recruitment

Page 12: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Rule Explorer

Page 13: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Rule Edit Form

Page 14: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Example of a rule

IF ENSO event = El Niño,AND Aleutian low circulation type = W1,THEN SAT at St. Paul = above normal; CF = 10.

Page 15: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Running the project to find the value of the target variable

Page 16: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Questions about the variable in the terminal nodes

Page 17: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Search Form

Page 18: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Confidence Factors

CF = (P(C | e) − P(¬C | e)) * 100%,

CF = Degree of Belief – Degree of Disbelief

CFcomb = CFold + CFnew − (CFold * CFnew)/100.

Page 19: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Custom Property Window

Page 20: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

Report documenting the inference process

Page 21: Ecological Indicators: Software Development Sergei Rodionov Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle,

“A spoon is valuable at the lunch time.”

Russian proverb