ESSA Technologies Overview of Decision Analysis with examples - Jan 10, 2002 How ESSA has successfully used Decision Analysis to overcome challenges in multi-objective resource management problems General overview January 10 2002 Developed by ESSA Technologies Ltd. David Marmorek, Calvin Peters, Ian Parnell, Clint Alexander
How ESSA has successfully used Decision Analysis to overcome challenges in multi-objective resource management problems. Developed by ESSA Technologies Ltd. General overview January 10 2002. David Marmorek, Calvin Peters, Ian Parnell, Clint Alexander. - PowerPoint PPT Presentation
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
How ESSA has successfully used Decision Analysis to
overcome challenges in multi-objective resource management
problems
General overview
January 10 2002
Developed byESSA Technologies Ltd.
David Marmorek, Calvin Peters, Ian Parnell, Clint Alexander
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Common challenges in resource management
• Getting stakeholder groups to agree on a course of action, given multiple values and objectives
• Getting scientists to agree on which uncertainties most critically affect management decisions, and what decisions are most robust to these uncertainties
• Evaluating the costs and benefits of adaptive management - is it worth it?
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
How decision analysis can help with these challenges
• It provides a toolbox for handling multiple objectives / values, and analyzing tradeoffs among these objectives
• It systematically analyzes the impacts of uncertainties on decisions
• It can be used to evaluate the ability of Adaptive Management experiments to improve decisions
• It provides a helpful way to integrate many techniques employed by managers and scientists (i.e. models, interactive workshops, sensitivity analysis) into products that better clarify management decisions
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Three examples
• Getting scientists to agree: PATH
• Getting stakeholders to agree: Cheakamus
• Evaluating adaptive management: Keenleyside
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
PATH: Decision Context
• Multiple historical changes in Columbia and Snake River ecosystems and fisheries management practices
• Endangered species listings for Snake River salmon populations
• Multiple hypotheses and uncertainties held by different groups of scientists
• Duelling models representing these hypotheses and uncertainties
• Best management policies for species recovery?
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
PATH: Washington State, US
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
3. Uncertain states of nature (different hypotheses)
4. Probabilities of those states (to account for uncertainty);
5. Model to calculate outcomes of each combination of management action and hypothesised state of nature;
6. Decision tree;
7. Rank actions based on expected value of the performance measures; and,
8. Sensitivity analyses.
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Decision Analysis: Basic Elements
Module 3 -36MoF Adaptive Management Training Course
Action 1
Managementactions
Probabilities ofstates of nature
States of natureor hypotheses
Outcomes orconsequences
Action 2
P1
P2
P1
P2
Hypothesis 1
Hypothesis 2
Hypothesis 1
Hypothesis 2
C11
C12
C21
C22
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
PATH Decision Tree
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Benefits of decision analysis in PATH
• Allowed evaluation of multiple hypotheses for 14 uncertainties - scientists did not have to agree!
• Only 3 of these turned out to make a difference to the decision - created a common focus for AM, research
• Preferred actions were those which were most robust to the critical uncertainties (drawdown A3)
• Sensitivity analyses defined how much belief you would have to have in a given hypothesis to change decision
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Recent Publications on PATH
• Marmorek, David R. and Calvin Peters. 2001. Finding a PATH towards scientific collaboration: insights from the Columbia River Basin. Conservation Ecology 5(2): 8. [online] URL: <http://www.consecol.org/vol5/iss2/art8>
• Deriso, R.B., Marmorek, D.R., and Parnell, I.J. 2001. Retrospective Patterns of Differential Mortality and Common Year Effects Experienced by Spring Chinook of the Columbia River. Can. J. Fish. Aquat. Sci. 58(12) 2419-2430 http://www.nrc.ca/cgi-bin/cisti/journals/rp/rp2_tocs_e?cjfas_cjfas12-01_58
• Peters, C.N. and Marmorek, D.R. 2001. Application of decision analysis to evaluate recovery actions for threatened Snake River spring and summer chinook salmon (Oncorhynchus tshawytscha). Can. J. Fish. Aquat. Sci. 58(12):2431-2446. <same web site as above>
• Peters, C.N., Marmorek, D.R., and Deriso, R.B. 2001. Application of decision analysis to evaluate recovery actions for threatened Snake River fall chinook salmon (Oncorhynchus tshawytscha). Can. J. Fish. Aquat. Sci. 58(12):2447-2458. <same web site as above>
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Cheakamus WUP: Decision Context
• British Columbia Hydro, Water Use Planning: Stakeholder driven multi-objective consultation / decision process.
• No formal incorporation of uncertainty as for PATH
• Emphasis: values, objectives, performance measures, trade off analysis (DA steps 1, 2, 5 and 7).
• Used PrOACT approach (Smart Choices, Hammond et al 1999)
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Cheakamus WUP: ProcessPrOACT Approach
Problem
Objectives
Alternatives
Consequences
Tradeoffs
Clear choice
Many choices
WUP Steps
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Cheakamus WUP:Decision ProblemSelect operating alternatives for Daisy Lake Dam that:
1) recognize multiple water uses in the Cheakamus and Squamish Rivers, and
2) achieve a balance between competing interests and needs.
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Cheakamus WUP:Objectives and PMsFundamental
ObjectivesPerformance Measures
Average power revenue ($M/yr)
Power production (GWh)1. Maximize economicreturns from powergeneration. Greenhouse Gas emission reductions (Ktonnes/yr)
Active $0.6 (5.8) $0.6 (7.6) $0.2 (17.4) $0.6 (7.6)
$Cnd millionsNumbers in brackets = experimental pay-back interval in yearsBlue = things under AM practitioners controlRed = beyond AM practitioners control
I ncrease in annual power revenues from operating with experimental information (insensitive population only, 10-year experiments)
Low Nat Variability High Natural Variability
Natural Variability and Measurement Error
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Is AM and monitoring worth it?Is AM and monitoring worth it?
“Yes” IfNew information leads to choice of a
different management action that better satisfies a particular objective,
or rigorously confirms that current
management action is appropriate.
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
No definitive “yes/no”No definitive “yes/no”
Management objective(fish vs. power $)
Ability to do well designed experiments
Initial level of uncertainty in alternative hypotheses
Magnitude of natural variability in the system
What “truth” really is
Inherent sensitivity of best action to uncertainty
FactorUnder AM
practitioners controlCan evaluate implications using decision analysis?
Yes
Yes
Maybe
No
No (can’t know without doing the experiment)
No
Yes
Yes
Yes
Yes
Yes
Yes
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
General ConclusionsGeneral Conclusions• Value of AM potentially large
• Whether to proceed depends on “the kind” of system you are in (i.e. previous factors)
• Decision Analysis is very helpful for evaluating these benefits
– Determine which uncertainties have strongest effect on choice of “best” management decision
– Decisions more robust to uncertainties (reduces risk - integrates broader range of possible outcomes included)
– Include new information as revised probabilities on hypotheses
ESSA TechnologiesOverview of Decision Analysis with examples - Jan 10, 2002
Decision Analysis - SummaryDecision Analysis - SummaryElement of DecisionAnalysis