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North Aleutian Basin Energy-Fisheries Workshop Anchorage Marriott Downtown Hotel Anchorage, Alaska, USA March 18–19, 2008 Graham Long

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Presentation on theme: "North Aleutian Basin Energy-Fisheries Workshop Anchorage Marriott Downtown Hotel Anchorage, Alaska, USA March 18–19, 2008 Graham Long"— Presentation transcript:

1 North Aleutian Basin Energy-Fisheries Workshop Anchorage Marriott Downtown Hotel Anchorage, Alaska, USA March 18–19, 2008 Graham Long Application of Structured Decision Making to the Consideration of Multiple Objectives in Fishery Resource Management

2 Overview  Why Structured Decision Making?  Example of SDM applied to Fishery Resource Management: Cultus Lake Sockeye  Lessons Learned  Initial Thoughts on Possible Application to North Aleutian Basin Energy-Fisheries Issues 2

3 Why Use Structured Decision Making?  Resource management decisions are almost always multi-attribute problems  That is, they have implications for a wide variety of end-points  Impacts to various environmental endpoints  Economic impacts  Social and cultural impacts  Any particular management alternative will affect each of these in different ways 3

4 Why Use Structured Decision Making?  Structured Decision Making can be defined as the formal study of trade-offs – the important differences between alternatives, and what they mean to people  Structured Decision Making and Decision Analysis are largely synonymous  The term ‘SDM’ is preferred in the BC government and in the US Fish & Wildlife Service / Dept of Interior 4

5 What is Structured Decision Making?  Based on principles of Decision Analysis and Multi-attribute Utility Theory (MAUT)  well developed axiomatic structure for how decisions (individual and group) should be made  “The formal use of common sense for decision problems that are too complex for the informal use of common sense” (R. Keeney, 1982)  Incorporates insights from Behavioral Decision Theory  how humans process information and evaluate options  importance of the decision context 5

6 Why Use Structured Decision Making?  Think you don’t make trade-offs? Common decisions we have to make:  What time to leave home for a meeting?  Small house or long commute?  Cheap car or safe car?  Burger or salad?  All of these decisions involve making trade- offs  We usually evaluate these trade-offs implicitly  How might we evaluate them explicitly? 6

7 Steps in Good Decision Making Define the decision Set objectives and evaluation criteria Create alternatives Assess consequences Analyze Trade- Offs and Decide Graham Long, 18 March 2008, Anchorage, Alaska7

8 A Simple SDM Example  You need to purchase a flight ticket next week for a personal trip from Anchorage to Vancouver. Graham Long, 18 March 2008, Anchorage, Alaska8

9 A Simple SDM Example  What’s important to you?  I don’t want to spend much money  I don’t want hidden fees  I don’t want to spend an extra day in Vancouver  I want a direct flight  I want easy check-ins  I want decent leg room  I want an aisle seat  I want friendly service  I am concerned about all the airline crashes recently  I am not comfortable flying with a new airline Graham Long, 18 March 2008, Anchorage, Alaska9

10 10 A Simple SDM Example I don’t want to spend much money I don’t want hidden fees I don’t want to spend an extra day in Vancouver I want a direct flight I want easy check-ins I want decent leg room I want an aisle seat I want friendly service I am concerned about all the airline crashes recently I am not comfortable flying with a new airline Graham Long, 18 March 2008, Anchorage, Alaska10  Minimize Cost  Minimize Travel Time  Maximize Comfort  Maximize Safety $ Total Hours Scale (5 = best, 0 = Worst) # Accidents / 1 million take-offs (5 yr ave) IssuesObjectivesEvaluation Criteria

11 11 A Simple SDM Example Objective Indicator Units Preferred Direction A Air Canada B Transat C Vintage Air Minimize Cost $ Lower is better $2,000$1,500$400 Minimize Travel Time Hours Lower is better Maximize Comfort (5 = best, 0 = worst) Higher is better 44? 0-5 Maximize Safety # Accidents / 1 million take- offs (5 yr ave) Lower is Better ? 0 – 40(?) Graham Long, 18 March 2008, Anchorage, Alaska11

12 12 A Simple SDM Example Objective Indicator Units Preferred Direction A Air Canada B Transat C Vintage Air Minimize Cost $ Lower is better $2,000$1,500$400 Minimize Travel Time Hours Lower is better Maximize Comfort (5 = best, 0 = worst) Higher is better 44? 0-5 Maximize Safety # Accidents / 1 million take- offs (5 yr ave) Lower is Better ? 0 – 40(?) Graham Long, 18 March 2008, Anchorage, Alaska12

13 13 A Simple SDM Example Objective Indicator Units Preferred Direction A Air Canada B Transat C Vintage Air Minimize Cost $ Lower is better $2,000$1,500$400 Minimize Travel Time Hours Lower is better Maximize Comfort (5 = best, 0 = worst) Higher is better 44? 0-5 Maximize Safety # Accidents / 1 million take- offs (5 yr ave) Lower is Better ? 0 – 40(?) Graham Long, 18 March 2008, Anchorage, Alaska13 Which flight would YOU choose?

14 14 Why Use Structured Decision Making?  This is simply a more formalized version of what we all do implicitly  “formal use of common sense…”  But what happens when decisions are too complex and too important for the informal use of common sense? Graham Long, 18 March 2008, Anchorage, Alaska14

15 15 Why Use Structured Decision Making?  An explicit approach to understanding trade-offs can help:  When there is not just ONE decision maker, but a panel of people with different viewpoints  When we desire to explore a problem transparently and accountably  When we want to set up a framework that can be updated on an ongoing basis  When we want to separate FACTS about expected outcomes from VALUES about which would be better 15

16 Undertaken in partnership with: Robin Gregory (Decision Research, Value Scope Research) Example of SDM applied to Fishery Resource Management: Cultus Lake Sockeye

17 17 Steps in Good Decision Making Define the decision Set objectives and evaluation criteria Create alternatives Assess consequences Analyze Trade- Offs and Decide Graham Long, 18 March 2008, Anchorage, Alaska17 Scientific Assessments Social & Economic Assessments Multi-party Input

18 18 Cultus Lake Sockeye 18

19 19 Cultus Lake Sockeye  Client: Fisheries and Oceans Canada  Multiple interests:  High visibility species, high importance to Conservation, commercial fishers, and First Nations  Worked with multi-stakeholder committee (approx. 20 people) over 1 month period in 2006  Key trade-off:  Environmental protection – of a listed species  Economic impacts – to commercial fishing 19

20 20 Cultus Lake Sockeye  Data quality variable (and controversial)  Multiple management options  commercial fleet exploitation rate  captive breeding options  freshwater programs  What Cultus Lake management alternative represents the 'best balance' across multiple objectives for 2006 season? 20

21 21 Steps in Good Decision Making Define the decision Set objectives and evaluation criteria Create alternatives Assess consequences Analyze Trade- Offs and Decide Graham Long, 18 March 2008, Anchorage, Alaska21 Scientific Assessments Social & Economic Assessments Multi-party Input

22 22 Cultus Lake Sockeye  OBJECTIVES (Slide 1 of 2)  Sockeye conservation  Probability of meeting Recovery Plan objectives 1 and 2  Returns in years 2010 and average of  Probability of extirpation by 2036  % Enhanced in 2010 and average of  Costs  Total costs over 12 years, levelized  No cost allocation attempted 22

23 23 Cultus Lake Sockeye  OBJECTIVES (Slide 2 of 2)  Catch  Traditional commercial catch  Commercial TAC available upstream of Vedder  Total First Nations Food, Social and Ceremonial Catch  Jobs  Employment opportunities directly related to enhancement and freshwater projects 23

24 24 Steps in Good Decision Making Define the decision Set objectives and evaluation criteria Create alternatives Assess consequences Analyze Trade- Offs and Decide Graham Long, 18 March 2008, Anchorage, Alaska24 Scientific Assessments Social & Economic Assessments Multi-party Input

25 25 Cultus Lake Sockeye  ALTERNATIVES  Alternatives created by assembling ‘blocks’ of options:  Cultus Exploitation Rate %  Enhancement options  Freshwater projects options  Make use of strategy tables to encourage creative thinking.Two examples: 25

26 26 Cultus Lake Sockeye Cultus Exploitation Rate % EnhancementFreshwater projects options 5None 10Current Captive BroodCurrent Milfoil Removal 20Double Current Capacity Current Pikeminnow 30Maximum Enhancement Large Milfoil Removal 40Large Pikeminnow Removal Alternative 1: “Status Quo” 26

27 27 Cultus Lake Sockeye Cultus Exploitation Rate % EnhancementFreshwater projects options 5None 10Current Captive BroodCurrent Milfoil Removal 20Double Current Capacity Current Pikeminnow 30Maximum Enhancement Large Milfoil Removal 40Large Pikeminnow Removal Alternative 2: “Spread the Pain 2” 27

28 28 Cultus Lake Sockeye  Exploration of alternatives through iterative SDM process: creation, analysis, elimination  Iteration 1  Created 6 alternatives  Iteration 2  Reviewed these 6 and created 3 more  Iteration 3  Reviewed all 9, eliminated 6 because they were dominated (others the same or better on objectives)  Agreed on several key components for all alternatives 28

29 29 Cultus Lake Sockeye 29

30 30 Cultus Lake Sockeye  Recognition of need to simplify the decision problem through elimination of relevant objectives and alternatives.  Do this via exploration of  Redundancy: where performance measures do not vary across alternatives  Dominance: where one alternative is better than or equal to all (or, by collective agreement, nearly all) aspects of another 30

31 31 Cultus Lake Sockeye  Three alternatives remained at the end of this process 31

32 32 Cultus Lake Sockeye  One alternative favoured by group (8)  Though disagreement on some factors remained  Agreement on many common features  Detailed agreements and disagreements at end of process  Remaining issues settled outside the process with other parties who had chosen not to participate 32

33 33 Cultus Lake Sockeye  Key Messages  Although an endangered species problem, SDM examined trade-offs across ALL significantly affected objectives  Considered a large number of alternatives  Best available science used to populate the consequence matrix  People agreed on the matrix, disagreed on some aspects of what was important  Transparent process 33

34 Lessons Learned

35 35 Lessons learned  We have applied this approach to a large number of multi-attribute resource management problems, including:  Hydro-electric facility operations  Including Columbia and Peace Rivers  Long range energy planning  Fisheries planning  Fish habitat management planning  Various wildlife management issues  Initiating a major project concerning the use of the Athabasca River in Alberta by oil companies Graham Long, 18 March 2008, Anchorage, Alaska35

36 36 Lessons learned  Factors that tend to favour the success of an SDM approach to a multi-objective resource management problem… Graham Long, 18 March 2008, Anchorage, Alaska36

37 37 Success Factors  1) There is Agreement from All Sides to Commit to the Process  Can be many reasons and/or preconditions for this:  Goodwill has previously been established between participants OR  Not so much goodwill but SDM is seen as the ‘least worst’ process option!  High level champions in organizations  Clearly understood role of process committee and its findings Graham Long, 18 March 2008, Anchorage, Alaska37

38 38 Success Factors  2) Participants are willing to trust, or at least to suspend scepticism, of the process  An independent person (Decision Analyst?) leads the process:  Is appointed as the ‘guardian of the process’  Reports to committee, not funders  Leads an analytical team that is ‘firewalled’ from participants  Has capacity to ensure ALL participants can understand materials and participate effectively Graham Long, 18 March 2008, Anchorage, Alaska38

39 39 Success Factors  3) The process is given sufficient time and resources  The process helps build relationships through face to face contact OVER TIME  Understanding complex issues takes time and effort  Short changing the process can be counter- productive  Consider how long any process might take without a structured approach! Graham Long, 18 March 2008, Anchorage, Alaska39

40 Thoughts on North Aleutian Basin Energy-Fisheries Issues

41 41 Thoughts on North Aleutian Basin Energy- Fisheries Issues  If you choose to undertake any kind of analytical approach, some suggestions are: Graham Long, 18 March 2008, Anchorage, Alaska41

42 42 Thoughts on North Aleutian Basin Energy- Fisheries Issues  Think hard (and collaboratively) about defining the problem  There are many forms the problem could take  All parties must buy into the wording of the problem Graham Long, 18 March 2008, Anchorage, Alaska42

43 43 Thoughts on North Aleutian Basin Energy- Fisheries Issues  If you adopt a ‘precautionary’ approach remember:  Being precautionary with one endpoint usually means being profligate with another!  This may (or may not be) OK  The point is:  Make trade-offs clear! Graham Long, 18 March 2008, Anchorage, Alaska43

44 44 Thoughts on North Aleutian Basin Energy- Fisheries Issues  Uncertainty plays a central role in all management approaches  Not all uncertainties are significant to the decision at hand  “Don’t count the hairs in the horse’s tail”  SDM has many techniques for identifying, characterizing and communicating key uncertainties to decision makers Graham Long, 18 March 2008, Anchorage, Alaska44

45 Closing Remarks

46 46 Structured Decision Making  Focuses on what matters  Improves the quality & transparency of judgments  Generates creative alternatives  Explores trade-offs and uncertainties  Ensures a decision-relevant information base  Provides insight: does not “make” the decision  Provides a framework for planning and consultation Graham Long, 18 March 2008, Anchorage, Alaska46

47 47 Contact Graham Long Partner, Compass Resource Management Ltd Hamilton St. Vancouver, B.C. V6B 2S8 Canada Phone: Fax: Graham Long, 18 March 2008, Anchorage, Alaska47


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