Causal Analysis Using Stressor Identification &...
Transcript of Causal Analysis Using Stressor Identification &...
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Causal Analysis Using Stressor Identification & CADDIS
Glenn Suter, Susan Cormier & Sue NortonUSEPAOffice of Research & DevelopmentNational Center for Environmental Assessment
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Our Causal Strategy:Stressor Identification
Define the Case
List Candidate Causes
Evaluate Data from the Case
Evaluate Data from Elsewhere
Identify Probable Cause
Detect or Suspect Biological Effects
As Necessary: Acquire Data,
and Iterate Process
Identify and Apportion Sources
Management Action: Eliminate or Control Sources, Monitor Results
Biological Condition Restored or Protected
Decision-maker and
StakeholderInvolvement
Stressor Identification
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Define the Case
• Objectives and scope– Determine cause of failure to meet biocriteria– Determine whether a source is the cause– Determine cause of specific effect
• Specific Impairment to be analyzed• Location in space and time
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List Candidate Causes
• Make an initial list• Gather and map information on sources
Consult stakeholders and experts• Make conceptual model• Finalize the list
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Causal Analysis is the Hard Part
• Causation is one of the most difficult and controversial concepts in philosophy
• Epidemiologists do not agree on causal inference
• Epidemiologists do not agree that causation can be inferred for specific cases
• No standard formal method• But errors common without a method
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Why do smart people make mistakes?
1. Theory tenacity:– We form opinions rapidly based on non-
logical processes• Intuition• Heuristic biases
– Because we are smart, we can ably defend them.
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Why do smart people make mistakes?
2. We overweight meaningful chance events:
– Every time I wash my car it ______
Rain?No
Rain? Yes
Wash Car? No
WashCar? Yes
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Disproof
Popperian disproof– Based on crucial
experiment– Based on observation
• Cannot identify cause– No finite list
• But can shorten the list
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Diagnostics
• Koch’s Postulates (single chem. or pathogen)– Association of Cause and Effect– Isolation of Cause from Effect– Experimental Association of Cause and Effect– Experimental Isolation of Cause from Effect
• Can be applied where novel cause• Basis for diagnostic protocols
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Hill’s Criteria for Causation
• Causality based on weight of evidence• By applying criteria to the evidence
– Strength– Consistency– Specificity– Temporality– Biological Gradient– Plausibility– Coherence– Experiment– Analogy
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Statistical Methods
Fisherian Disproof / NHT– Only for experiments– Cannot identify cause
Probabilistic Association– Correlation ≠ Causation– One type of evidence– Frequentist– Bayesian
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Inference for Cases
• Abductive Inference -- C.S. Peirce– Reasoning to the best solution
• D is a set of data (facts, observations, etc.)• H, if true, would explain D• No other hypothesis explains D as well as H does• Then, H is probably true
– A rigorous logic for individual cases
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Our Causal Strategy
• Identify alternative candidate causes• Logically eliminate when you can• Diagnose when you can• Use strength of evidence for the rest• Do not claim proof of causation• Identify the most likely cause• Use a consistent process• Document the evidence and inferences
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We are Concerned with Cases
• Generic Causation– Does C cause E ?
• Case Causation– What C caused E ?– Equivalent to autopsies, forensics or cancer
clusters
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Our Solution
• Hill-like Analysis of the Strength of Evidence• Types of Evidence, not Criteria
– None are required• Redefined and Renamed to reduce Ambiguity• Three Categories of Evidence
– Evidence from the Site (9 types)• Did C cause E here?
– Evidence from Elsewhere (6 types)• Does C cause E in other circumstances?
– Characteristics of the Body of Evidence (2 types)
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Our Solution, 2
• Adapt Susser’s +/- Scoring Approach• Integrate Diagnostics and Elimination
– Diagnosis is extreme form of Symptomology– Elimination is extreme form of Case-specific
Absence of Association• Iterative and Adaptive Implementation
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• Spatial/Temporal Co-Occurrence• Causal Pathway• Stressor-Response Relationships from the Field• Evidence of Exposure or Biological Mechanism• Manipulation of Exposure• Laboratory Tests of Site Media• Temporal Sequence• Verified Predictions• Symptoms
Types of Evidence that Use Data from the Case
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Supports
Refutes
Spatial/Temporal Co-Occurrencewith positive reference sites
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Supports
Refutes
Spatial/Temporal Co-OccurrenceThrough Time
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Supports
Refutes
Spatial/Temporal Co-OccurrenceUpstream Downstream Comparison
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Algae
CO2Supports
Refutes
Causal Pathway
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Strengthens
Weakens
Stressor-Response Relationshipsfrom the Field
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Evidence of Exposure or Biological Mechanism
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Supports
Refutes
Manipulation of Exposure
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Supports
Refutes
Laboratory Tests of Site Media
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Supports
Refutes
Temporal Sequence
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Verified Predictions
Strengthens
Weakens
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Symptoms
Strengthens
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Types of Evidence that Use Data from Elsewhere
• Stressor-Response Relationships from Other Field Studies
• Stressor-Response Relationships from Laboratory Studies
• Stressor-Response Relationships from Ecological Simulation Models
• Mechanistically Plausible Cause• Manipulation of Exposure at Other Sites• Analogous Stressors
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Stressor-Response Relationships from Other Field Studies
StrengthensWeakens
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Stressor-Response Relationships from Laboratory Studies
Weakens Strengthens
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Stressor-Response Relationships from Ecological Simulation Models
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Mechanistically Plausible Cause
Weakens
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Strengthens
Weakens
Manipulation of Exposureat Other Sites
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Analogous Stressors
Strengthens
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Score Each Type of Evidence for Each Candidate Cause
R refutesD diagnoses+++ convincingly supports (or weakens)++ strongly supports (or weakens)+ somewhat supports (or weakens)0 neither supports nor weakens NE no evidence
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Scoring Example:Spatial/Temporal Co-occurrence
Refutes if negative evidence is indisputableR
Lack of co-occurrence convincingly negates, because exposure must occur- - -
Ambiguous evidence is neutral0
Weakly supports, because it could be a coincidence+
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Scoring Example:Laboratory Tests of Site Media
Laboratory tests cannot refute toxic effects in the field.no R
Lack of laboratory toxicity weakly negates, because the test species, responses or conditions may be inappropriate
-
Ambiguous evidence is neutral0
Laboratory toxic effects that are not clearly related to site effects weakly support+
Laboratory toxic effects similar to site effects are convincing support media toxicity as a cause+++
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Weigh the Evidence for Each Candidate Cause
• Evaluate the quantity and quality of evidence– Do not add the pluses and minuses
• Evaluate consistency and credibility• Summarize the compelling evidence
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Confidence in the argument for a candidate cause is increased when a post hoc mechanistic, conceptual, or mathematical model reasonably explains any inconsistent evidence.
Explanation of the Evidence
Confidence in the argument for or against a candidate cause is increased when many types of evidence consistently support or weaken it.
Consistency of Evidence
The ConceptType of Evidence
Evaluating Multiple Types of Evidence
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Consistency of Evidence
Strengthens
Weakens
Weakens
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Explanation of the Evidence
Strengthens
Weakens
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Scoring Explanation of Evidence
-A credible explanation for any positive inconsistencies in an otherwise negative case
0No explanation for inconsistencies
+A credible explanation exists for any negative inconsistencies in an otherwise positive case
Reasonable Explanation of the Evidence
ScoresPossible ResultsConsideration
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Connecticut Case StudyWillimantic River
– Identified source– Remediated– Biotic condition improved – Removed from 303d list– Residual impairment– Associated with upstream
dams• Temperature• Allocthonous trophic structure
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+ + +-+-----Consistency of EvidenceEvaluating Multiple Types of Evidence
+--+Stressor-Response Relationships from Laboratory Studies
- -Stressor-Response Relationships from Other Field Studies
Types of Evidence that Use Data from Elsewhere+ + +Verified Predictions+ + +Manipulation of Exposure
++--+Stressor-Response Relationships from the Field
+-++-+-Causal Pathway
+-++--+++Evidence of Exposure orBiological Mechanism
++- - -+--+Spatial/Temporal Co-OccurrenceTypes of Evidence that Use Data from the Case
Episodic Mix
Food TLow DOSiltFlowNH3MetalsWillimantic
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Possible Outcomes
Strong evidence for one causeCelebrate and remediate
Inconclusive evidence across causesRemediate as adaptive managementGather more data and reanalyzeRedefine the impairmentConsider more candidate causesConsider joint action of causes
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Causal Analysis/Diagnosis Decision Information System CADDIS
An online system that helps
• Organize• Use• Access, and• ShareInformationTo Identify
Causes of Biological Impairments
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CADDIS 1 Includes
• Step-by-Step Guide• Worksheets and Examples• Conceptual Models• Case Studies• External links• References• Search Glossarywww.epa.gov/caddis/
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• Stressor-Response relationships– Stressor syntheses
• Metals (Fall 2005)• Nutrients• Suspended and
Bedded Sediments• Dissolved oxygen• Temperature• Salinity
– Analytical methods• Stressor-specific
tolerance values • Regional stressor-
response curves
CADDIS 2 Technical Content
0 10 20 30 40 50 60MDEPTHFINE
0
10
20
30
EP
T
Unobserved EPT taxa
Effects due to additional stressors
EPT Taxa vs. Mean Depth Fines
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ORD Potomac / Shenandoah Team
Sue Norton Patricia Shaw-AllenGlenn Suter Sharon Taylor
Other CATs are standing by