CADDIS Workshop [Causal Analysis/Diagnosis Decision Information System]

New Jersey Water Restoration, Protection, and Planning Working Group

Rutgers University, New JerseyMay 7, 2008

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Your guides…

Susan Cormiercormier.susan@epa.gov

Kate Schofieldschofield.kate@epa.gov

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Time Topic Facilitator

10:00 Introduction Host

10:10 Philosophy and Framework of Causal Analysis Cormier

10:50 Analysis and Interpretation of Evidence Schofield

11:30 Identifying the Probable Cause Cormier

12:00 CADDIS Tour— resources for causal analysis Schofield

12:30 Lunch

1:00 CADStat•Enter data•Make a Scatter Plot

Cormier

1:30 Analysis and Interpretation of Evidence•Scatter Plot•Box Plot•Conditional Probability Analysis •Regression and Quantile Regression

Schofield/Cormier

2:30 Screening Assessment Schofield

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Why Stressor Identification?• All states and several

tribes use biological assessments to identify whether streams and small rivers are impaired.

• In many cases, causes of impairment are unknown.

• To set a TMDL (or otherwise address the problem), you must identify a cause.

• It’s defensible & reproducible.

Causes of Impairment

NOTE: Click on the underlined "Causes of Impairment Reported" value to see a listing of those waters with that cause of impairment. Click on the underlined "General Impairment Name" to see the detailed state-reported impairment names.

General Impairment Name Causes of Impairment Reported Percent of Reported

MERCURY 8555 13.45

PATHOGENS 8526 13.41

SEDIMENT 6689 10.52

METALS (OTHER THAN MERCURY)

6389 10.05

NUTRIENTS 5654 8.89

OXYGEN DEPLETION 4568 7.18

PH 3389 5.33

CAUSE UNKNOWN - BIOLOGICAL INTEGRITY

2866 4.51

TEMPERATURE 2854 4.49

HABITAT ALTERATION 2220 3.49

PCBS 2081 3.27

TURBIDITY 2050 3.22

CAUSE UNKNOWN 1356 2.13

PESTICIDES 1322 2.08

SALINITY/TDS/CHLORIDES 996 1.57

FLOW ALTERATION 591 .93

ALGAL GROWTH 510 .80

AMMONIA 415 .65

OTHER TOXIC ORGANICS 339 .53

TOTAL TOXICITY 292 .46

DIOXINS 290 .46

TOXIC INORGANICS 270 .42

FISH CONSUMPTION ADVISORY - POLLUTANT UNSPECIFIED

260 .41

SULFATES 259 .41

NOXIOUS AQUATIC PLANTS

229 .36

OIL AND GREASE 138 .22

OTHER CAUSE 127 .20

TASTE, COLOR AND ODOR

83 .13

CHLORINE 78 .12

FLOATABLES 73 .11

NUISANCE EXOTIC SPECIES

50 .08

NUISANCE NATIVE SPECIES

30 .05

RADIATION 23 .04

CAUSE UNKNOWN - FISH KILLS

19 .03

HARMFUL ALGAL BLOOMS

4 .01

CAUSE UNKNOWN - BIOTOXINS

4 .01

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Success stories

SITE RESULT

Bogue Homo, MS

Identified low DO, high sediment as probable causes of impairment; developed template to expedite TMDLs

Touchet River, WARecommended sediment reduction & restoration of canopy cover

Groundhouse River, MNIdentified data needs & secured funding for data collection

Long Creek, MEDeveloped report examining non-point source TMDLs for urban streams

Naugatuck River, CTUsed applied toxicity tests & modeling to identify toxic effluent as probable cause; TMDL recently approved

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CADDIS is based on a formal method

2005, 2007…2010

http://www.epa.gov/caddisSI Guidance

2002

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General and Specific Causation

• General– Does C cause E?

– Does smoking cause lung cancer?– Does dissolved oxygen reduce mayflies in rivers?

• Case and Cause Specific– Did C cause E?

– Did smoking cause lung cancer in Ronald Fisher?– Did low dissolved oxygen reduce mayflies in my river?

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• Case Specific —Which C caused E?– What exposure and/or genetic predisposition caused

cancer in Ronald Fisher– What stressor(s) are causing reduced mayflies in my river

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Physical Interaction

Causal agents change affected agents by physical interaction.

Directionality The cause precedes its effect

SufficiencyIntensity or frequency of contact with the cause is adequate to produce the observed effect

Sequential Dependence

All effects result from a prior sequence of cause-effect events

Coherence of Characteristics

Specific causal relationships are consistent with scientific theory

Characteristics of Causal Relationships

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Inference of Causal Characteristics

Inference from Definition

Observation The effect is observed to occur with the cause.

Manipulation Changing the cause changes its effect.

PredictionKnowledge from empirical observations or mechanistic studies permits reliable prediction of events.

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Inference from

Observation/ Consistency

Manipulation Prediction

Physical Interaction

Directionality

Sufficiency

Sequential Dependence

Coherence of CharacteristicsC

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Inference of Causal Characteristics Provides Evidence of Causal Relationships

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Inference from

Observation/ Consistency

Manipulation Predictability

Physical Interaction

Spatial/Temporal Co-occurrence

Manipulation of co-occurrence; e.g., caging experiment

Evidence of exposure or biological mechanismVerified Prediction

DirectionalityTemporal Sequence

Manipulation of time order

Verified prediction of time order

Sufficiency

Stressor-Response in the Field

Manipulation of duration, concentration, frequency, other factors Laboratory tests of site media

Stressor response from ecological simulation or physiological models

Sequential Dependence

Causal pathway (before and after)

Manipulation of circumstances or pathways leading to the proximate cause

Verified prediction of source, precursor, or subsequent effectAnalogous situations

Coherence of Characteristics

Mechanistically plausibleSymptomology

Verified Prediction of Symptom Analogous stressors

Ch

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sInference of Causal Characteristics Provides

Evidence of Causal Relationships

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Types of Evidence used in CADDIS Characteristic

Spatial/Temporal Co-occurrence with positive reference sites

Physical InteractionSpatial/Temporal Co-occurrence through Time

Spatial/Temporal Co-occurrence Upstream Downstream Comparison

Evidence of Exposure or Biological Mechanism

Temporal Sequence Directionality

Stressor-Response Relationship in the Field

SufficiencyStressor-Response from Laboratory Studies

Stressor-Response from Ecological Simulation Models

Causal Pathway Causal Dependence

SymptomsCoherence

Mechanistically plausible

Laboratory Tests of Site Media (Manipulation)

Verified Predictions

Manipulation of Exposure

Analogous stressors (Prediction)

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General and Specific Causation

•General– Does C cause E?

– Ecological knowledge and theory, regional assessment

• Case and Cause Specific– Did C cause E?

– Good for permits, damage assessment costs, reregistration of chemicals

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• Case Specific —Which C caused E?

– Identifying an unknown cause

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Planning

Analysis

Synthesis

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Planning

Analysis

Synthesis

Decision/Action

Initiator

Common Assessment Process

Define the Case

List Candidate Causes

Evaluate Data from the Case

Evaluate Data from Elsewhere

Identify Probable Cause

Detect or Suspect Biological Impairment

Identify and Apportion Sources

Management Action: Eliminate or Control Sources, Monitor Results

Biological Condition Restored or Protected

Stressor Identification

CADDIS Stressor Identification Process

Problem Resolution

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Our causal strategy (& some notes)

• Identify alternative candidate causes

• Logically eliminate when you can

• Diagnose when you can

• Use strength of evidence for the rest

• Identify most likely cause

– Do not claim proof of causation

– Use a consistent process

– Document evidence & inferences

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Why use a formal method?

• To provide a defensible & reproducible evaluation

• To convince stakeholders

• To increase confidence that remedial or restoration efforts can improve biological condition

• To identify causal relationships that are not immediately apparent

• To prevent biases and other lapses of logic

“Science is a way of trying not to fool yourself. The first principle is that you must not fool yourself – and you are the easiest person to fool.” [Feynman 1964]

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Philosophers of causation

David Hume: Causality as associations between events

Galileo: Causes of effects are knowable

John Stuart Mill:Manipulating cause will change effect

Charles Peirce: Inference to the best explanation

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Philosophers of causation

Ronald Fisher: Controlled experiments with replication and randomization

Karl Pearson: Need to quantify association between variables

Austin Bradford Hill: Causality based on strength of evidence

Robert Koch: Postulates for demonstrating causes of diseases

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• Gives you tools & information to make your causal assessment easier

• You can’t just push a button on CADDIS to determine cause of impairment…

–Will need to use your head–Will need data to generate evidence

What does CADDIS do?