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Ecological Indicators: Software Development

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

Outline

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

Part II. Knowledge management system for the Bering Sea.

0 10 20 30 40

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a)

b)

R egim e 1

Regim e 2

AR (1) = 0.8

True and spurious regime shifts

Entry Form for STARS

www.BeringClimate.noaa.gov

Estimates of AR1 for PDO

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

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AR

1 co

effi

cien

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M PK

IP4

O LS

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

-1

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a) PDO

b) A fter P rewhitening

c) R esiduals

1948 19761999

1948

PDO Index Before and After Prewhitening

Part II. Dealing with Information Overload

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

Knowledge management system

Components of the KMS

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

Data Explorer

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

Part of the influence diagram for walleye pollock recruitment

Rule Explorer

Rule Edit Form

Example of a rule

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

Running the project to find the value of the target variable

Questions about the variable in the terminal nodes

Search Form

Confidence Factors

CF = (P(C | e) − P(¬C | e)) * 100%,

CF = Degree of Belief – Degree of Disbelief

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

Custom Property Window

Report documenting the inference process

“A spoon is valuable at the lunch time.”

Russian proverb

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