This document discusses five obstacles to effective climate change decision making: 1) data used is often not meaningful or helpful, 2) stakeholder objectives and concerns are not sufficiently addressed, 3) attributes and measures used to characterize impacts are inadequate, 4) research is loosely tied to decisions that need to be made, and 5) there is little learning from past successes and mistakes. The document examines these obstacles in more detail and provides examples to illustrate challenges with using complex data, addressing stakeholder objectives, developing appropriate attributes and measures, and incorporating learning over time into the decision process.

1. ma ny)
(o f
Five Obstacles to Effective
Climate Decisions:
A Decision Science Perspective
Dr. Joseph Arvai
Environmental Science & Policy Program
Michigan State University
East Lansing, MI
Decision Research
Eugene, OR

2. Acknowledgements
National Science Foundation
SES 0350777
University of British Columbia
Natural Resources Canada
The Government of Nunavut

3. Introduction
• The following
discussion stems
from decision aiding
work carried out in
two contexts;
adaptation to
climate change in:
– Coastal British
Columbia
– Nunavut Territory

4. Introduction
• Though quite different
in terms of the levels of
development and
infrastructure, both
study sites shared a
common complaint:
– Despite years of
research (and millions of
dollars spent) people
were seeing very little in
the way of adaptation
action.
– “You can’t study our
problems away…”

5. Introduction
• Five common concerns:
1. The data used to describe the problems associated with
climate change are frequently not meaningful or helpful.
2. The objectives and concerns of affected stakeholders
are not receiving sufficient attention.
3. The attributes and measures used to characterize
climate change impacts, and the anticipated
consequences of alternative management plans, are
often inadequate.
4. Ongoing research is often only loosely tied to the
decisions that need to be made.
5. There seems to be very little learning from past success
stories as well as mistakes.

6. Data

7. Numeracy Issues
• Probabilistic information, even in the absence of
uncertainty, proves to be difficult for most people.

8. Dual Processing
• SYSTEM 1 is fast,
intuitive, highly
inductive, and based
heavily on our
instinctive emotional
(affective) responses to
stimuli.
• SYSTEM 2, is slower,
based on rules of logic
and rationality, highly
deductive, and based
heavily on effortful
calculation.

9. Numeracy Issues
9% Red Beans 10% Red Beans
A B
• 5% of high­numerate individuals select from Bowl B.
• 37% of low­numerate individuals select from Bowl A.
Peters, E., D. Vastfjall, P. Slovic, C.K. Mertz, K. Mazzocco, and S. Dickert. 2006.
Numeracy and decision making. Psychological Science, 17: 407­413.

10. Numbers and Nerves
15
13.6
12.9
11.7
10.9
10.4
10
5
0
150 98% 95% 90% 85%
Number and Percent of 150 Lives Saved
Slovic, P., M. Finucane, E. Peters, and D.G. MacGregor. 2004. Risk as analysis and risk as
feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24: 1­12.

11. Psychophysical Numbing

12. Psychophysical Numbing
“I am deeply moved if I see one man
suffering and would risk my life for him.
Then I talk impersonally about the possible
pulverization of our big cities, with a
hundred million dead. I am unable multiply
Value of Life Saving
one man’s suffering by a hundred million.”
­ Albert Szent Gyorgi
0 1 2 N
Number of Lives at Risk

13. Psychophysical Numbing

14. Objectives
• The objectives of stakeholders and decision
makers are the basis for considering any
decision.
• Therefore, the first step in any decision process
is for those involved to carefully consider their
objectives by clearly defining what it is they want
to achieve in a given decision context.
• This objectives­focus is in contrast to an
alternatives­focus, which involves analyzing the
available alternatives and selecting the ‘best’ one
from a set of implied, and often poorly defined,
criteria.

15. Objectives
• Despite their importance during decision making,
a thoughtful and thorough exploration of
objectives that will guide a decision is only
seldom undertaken.
• Decision makers and stakeholders seldom
differentiate between means and ends
objectives.
– This is important because decisions about climate
change are also linked to other areas of concern.

17. Attributes & Measures
• World Summit on Sustainable Development,
Johannesburg 2002
• Indicators in Integrated Coastal Management,
Ottawa 2002
• Much of the focus has been on the
identification of natural processes that require
further scientific study and/or should be
closely monitored in response to climate
drivers.
• Inventories with an emphasis on establishing
changes relative to some baseline.

18. Attributes & Measures
• Inventory data frequently does not provide
the kinds of insights that decision makers
desire (but they end up “using” it anyway):
– …because they often remove focus from what
matters to stakeholders and decision makers (i.e.,
their objectives).
– …because they are not presented at the
appropriate temporal or geographic scale.
– …because they fail to expose key tradeoffs that
will need to be addressed.

19. Attributes & Measures
Inventory Attribute Measure Option 1 Option 2 Option 3 Option 4
Sea level rise cm/100 yr. ­ ­ ­ ­
No. of flood
Flood frequency ­ ­ ­ ­
days
Degree of erosion Ha ­ ­ ­ ­
Fraser River freshet 1 Timing ­ ­ ­ ­
Fraser River freshet 2 Duration ­ ­ ­ ­
Inventory Data
Fraser River freshet 3 Volume ­ ­ ­ ­
Fraser River freshet 4 Max. Flow ­ ­ ­ ­
Water Quality Several ­ ­ ­ ­
No. of Surge
Storm Surge ­ ­ ­ ­
Days
Rate of
Subsidence ­ ­ ­ ­
Compaction

20. Attributes & Measures
Objective Attribute Measure Option 1 Option 2 Option 3 Option 4
Area of shorebird habitat Ha ­ ­ ­ ­
Biofilm exposure Ha ­ ­ ­ ­
% Change in key indicator
spp. (Dunlin, Western % ­ ­ ­ ­
Sandpiper)
Maintain/Improve
Environmental Health Extent of eelgrass beds Ha ­ ­ ­ ­
Constructed
Marsh stability ­ ­ ­ ­
Index
2
Benthic biomass gC/m ­ ­ ­ ­
TEK­based TEK ­ ­ ­ ­

21. Attributes & Measures
Objective Attribute Measure Option 1 Option 2 Option 3 Option 4
Flood damge (property
$ ­ ­ ­ ­
and structures) 1
Flood damge (property No. High
­ ­ ­ ­
and structures) 2 Water Days
Weighted User
Reacreational activities ­ ­ ­ ­
Days
Socioeconomic Dependability of BC % On­Time
­ ­ ­ ­
(Quality of Life) Ferries Sailings
Heritage and First Nation Constructed
­ ­ ­ ­
SItes Index
Citizen confidence in Constructed
­ ­ ­ ­
protection measures Index
Annual adaptation costs
$ ­ ­ ­ ­
(municipailties)

22. Attributes & Measures
Objective Attribute Measure Option 1 Option 2 Option 3 Option 4
Flood damge (property
$ A B C D
and structures) 1
Flood damge (property No. High
E F G H
and structures) 2 Water Days
Weighted User
Reacreational activities I J K L
Days
Socioeconomic Dependability of BC % On­Time
M N O P
(Quality of Life) Ferries Sailings
Heritage and First Nation Constructed
Q R S T
SItes Index
Citizen confidence in Constructed
U V W X
protection measures Index
Annual adaptation costs
$ $25 Mil. (CAD) $24 Mil. (CAD) $25 Mil. (CAD) $26 Mil. (CAD)
(municipailties)

23. Attributes & Measures
Objective Attribute Measure Option 1 Option 2 Option 3 Option 4
Flood damge (property
$ A B C D
and structures) 1
Flood damge (property No. High
E F G H
and structures) 2 Water Days
Weighted User
Reacreational activities I J K L
Days
Socioeconomic Dependability of BC % On­Time
85% 91% 78% 93%
(Quality of Life) Ferries Sailings
Heritage and First Nation Constructed
Q R S T
SItes Index
Citizen confidence in Constructed
U V W X
protection measures Index
Annual adaptation costs
$ $25 Mil. (CAD) $24 Mil. (CAD) $25 Mil. (CAD) $26 Mil. (CAD)
(municipailties)

24. Research & Monitoring Needs
• Analytic­Deliberative Process.
– Several successive rounds of deliberation by
stakeholders and analysis by technical experts
as part of a deliberate march towards a risk
management decision.
• Each successive round of analysis and
deliberation is meant to yield an improved
understanding on the part of both the
stakeholders and experts regarding the
various attributes that are “at risk” in an
ecological system.
• The analytic­deliberative process is not
simply a means for synthesizing the
information obtained through a set of
unrelated and predominantly expert­driven
risk assessments; it is an important shaper of
a long­range risk assessment and decision
making process.

25. Learning Over Time
• Climate decisions are questions
masquerading as answers.
• If we view decisions as
questions, then the outcomes of
these decisions become
treatments, in an experimental
sense.
• Adaptive management has two
key parts:
1. Implementing varied climate
“treatments” (e.g., across space and
time).
2. Monitoring, learning, and adjusting.

26. Learning Over Time
RESILIENCE
• Many would argue that,
globally speaking, we’ve
already done serious
damage to the climate.
• Decisions aimed at
reducing and responding
to the effects of climate
change should help (vs.
hurt).

27. Learning Over Time
SCALE
• There is often a need to
focus narrowly, in terms
of time and space, during
decision making.
• Spatially varied climate
management
“treatments” are already
in place.
– e.g., forestry projects in
India; energy projects in
Europe, fuel taxes in
Canada, Daylight Saving
Time in Australia (2000).

28. Learning Over Time
ETHICAL CONCERNS
• Sadly, the global
economy in concert with
regional variability in
climate already
inequitably distributes
costs and vulnerability
across communities and
places.

29. Learning Over Time
COMPLEXITY
• Overall, the basic
framework for carrying
out adaptive climate
management is already
in place.
• What’s missing is a
system for monitoring
and learning.

30. Recommendations
Time
Not (Necessarily) Software
Commitment
Expertise

31. Contact Information
Dr. Joe Arvai
E­Mail: arvai@msu.edu
Telephone: 517­353­0694
Facsimile: 517­353­8994
Web: http://www.msu.edu/~sknkwrks