1. Decision-Making under Great
Uncertainty: Environmental
Management in an Era of Global
Change
Stephen Polasky
University of Minnesota

2. Introduction
 Two large related issues of ecosystem
management:
 Management of ecosystems to provide multiple
ecosystem services
 Spatially-explicit integrated ecological-economic
analysis
 Management under uncertainty in an era of
global change
 Global change clouds our ability to accurately predict
future conditions

3. Current state of affairs
 Ecosystems provide a wide array of goods and
services of value to people (“ecosystem
services”)
 Human actions affect ecosystems and the
services they provide
 The provision of ecosystem services often is not
factored into important decisions that affect
ecosystems
 As a result, we often do a poor job of ecosystem
management

4. The Millennium
Ecosystem
Assessment (2005)
Ecosystems and
biodiversity are
essential for human
well-being
Ecosystem services
as a central
organizing principle

5. Current state of affairs
 New global era – “anthropocene”
 Human actions driving global environmental
conditions (“global change”)

6. If humanity is driving –
where are we headed?

7. Introduction
 Global change issues are complex and
the consequences of decisions are often
highly uncertain
 Large spatial and temporal scales
 Large stakes involved
 Vitally important to try to take account of
present and potential future
consequences in decision-making
 But very difficult to do so

8. Introduction
 How can we best guide decision-making
to meet present and future human needs*
in an era of global change given pervasive
uncertainty?
 Note: could substitute alternative
objectives for human needs
 Biodiversity conservation
 Environmental health
 Evolutionary process

9. Outline
 An approach to ecosystem management taking
account of multiple ecosystem services at
landscape scales
 Examples from Minnesota and Oregon
 Approaches to decision-making under
uncertainty:
 Decision theory
 Scenario planning
 Thresholds approach
 Resilience thinking
 Thoughts on integrated assessment of
ecosystem management under great uncertainty

10. Assessing multiple ecosystem
services at landscape scales

11. A research agenda for ecosystem services
Policy (1) Incentives
Decisions by firms
decisions and individuals
(3) Non-
anthropocentric (2) Actions
approaches
Other (5) Biophysical
(7) Economic tradeoffs Ecosystems
considerations
efficiency
(4) Ecological
production
functions
Benefits Ecosystem
and costs services
(6) Valuation
Polasky & Segerson Annual Review of Resource Economics 1: 409-434.

12. The Natural Capital Project:
Mainstreaming ecosystem services

13. “InVEST”
Integrated Valuation of Ecosystem
Services and Tradeoffs
http://www.naturalcapitalproject.org/InVEST.html
Frontiers of Ecology
and Environment
Feb 2009

14. Modeling multiple ecosystem services and
tradeoffs at landscape scales
Nelson et al. 2009. Frontiers in Ecology and Environment 7(1): 4–11.

15. Modeling multiple services under
alternative scenarios
 Three scenarios of land use / land cover
change for the Willamette Basin
developed by the Willamette Partnership
for 1990 – 2050
• Plan trend
• Development
• Conservation

17. Modeling multiple services under
alternative scenarios
 Model outputs: service provision and biodiversity
 Water quality
 Storm peak mitigation
 Soil conservation (sediment retention)
 Climate stabilization (carbon sequestration)
 Biodiversity (species conservation)
 Market returns to landowners (agricultural crop
production, timber harvest and housing values)

18. Outputs through time

19. Ranking of scenarios depends on set of
ecosystem services considered

20. The Impact of Land Use Change on Ecosystem
Services, Biodiversity and Returns to Landowners:
A Case Study in the State of Minnesota
Photo by Raymond Gehman, National Geographic
Polasky et al. Environmental and Resource Economics 2011

21. Introduction
 Use InVEST to analyze how changes in
land use in Minnesota affect ecosystem
services and biodiversity conservation
 Compare the impact on ecosystem
services & biodiversity from:
 Actual land use change from 1992- 2001
 Alternative land use change scenarios

22. Land use scenarios
 Use National Land Cover Database (NCLD) for 1992 to
2001 for data on actual land use change in Minnesota
 Alternative land use scenarios:
 No agricultural expansion
 No urban expansion
 Agricultural expansion into highly productive soils
 Forestry expansion into highly productive forest parcels
 Conservation: low productivity ag land and ag land within a 100
m buffer of waterways in MN River watershed were converted to
pre-settlement vegetation

23. InVEST outputs
 Ecosystem services
 Carbon sequestration
 Water quality (phosphorus exports in the Minnesota River Basin)
 Biodiversity
 Grassland bird habitat
 Forest bird habitat
 Overall biodiversity (all natural habitat)
 Returns to landowners
 Value of agricultural production
 Value of timber production
 Value of urban/suburban development

24. Change from 1992 to 2001 by scenario:
carbon sequestration
Mg C

25. Change in phosphorus exports to mouth of
Minnesota River
Mg P/yr

26. Percentage change in habitat quality for
grassland breeding birds

27. Percentage change in habitat quality
for forest breeding birds

28. Change from 1992 to 2001 by scenario: market
returns to agriculture, forestry, urban
Agriculture
Forestry
Urban
Million 1992 US $

29. Annual value from land use change
scenarios 1992-2001
Actual land No ag No urban Ag Forest Conser-
use expansion expansion expansion expansion vation
Change in total value:
carbon, water quality, ag
& forest production,
$3,328 $3,407 $3,040 $2,742 $3,300 $3,380
urban using actual
prices (M1992 $)
Change in returns to
landowners: ag & forest
production, urban using $3,320 $3,343 $3,027 $3,418 $3,292 $3,221
actual prices (M1992 $)

30. Summary
 The failure to incorporate the value of ecosystem
services in land use planning can result in poor
outcomes
 Low level of ecosystem services
 Low value of total goods and services from landscape
 Agricultural land use change had a bigger effect on
ecosystem service value and biodiversity than
urbanization
 Result is largely due to the fact that there is far more agricultural land
than urban land
 Urban land: generates negative externalities but the direct value of
urban land use is high
 Agriculture: generates negative externalities but with lower direct land
use value

31. Challenge
 Analysis assumes we know the links between
 Action and ecosystem impact
 Ecosystem functions and ecosystem services
 Ecosystem services and human well-being
 Each link is subject to considerable uncertainty
 Global change means that future cause-effect
relationships may look quite different than
current relationships

32. Decision-making under uncertainty

33. Decision theory
 Standard approach for rational choice under uncertainty
 Specify objective function (e.g., maximize expected
human well-being)
 Define uncertainty: probability of alternative states
 Use best available information to specify how states and
actions combine to form outcomes (probability of
outcomes)
 Define the net benefits of different outcomes
 Choose action that maximizes the objective function

34. Example: guilty or not guilty?
Actual condition
Guilty Innocent
Guilty Correct False conviction
(Type I error)
Decision decision
Innocent False release Correct
(Type II error)
decision

35. Example: guilty or not guilty?
Version 1
Actual condition
(Unknown)
Guilty (p) Innocent
(1-p)
Guilty 20 -40
Decision
Innocent -5 10

36. Guilty or not guilty?
 How high does the probability of guilt need
to be before you issue a guilty verdict?
 Expected value of guilty verdict:
20P+(-40)(1-P) = -40+60P
 Expected value of innocent verdict:
-5P+10(1-P) = 10-15P
 As long as the probability of guilty is at
least 2/3, then issue a guilty verdict
(otherwise not)

37. Example: guilty or not guilty?
Version 2
Actual condition
(Unknown)
Guilty (p) Innocent
(1-p)
Guilty 20 -400
Decision
Innocent -5 10

38. Guilty or not guilty?
 As long as the probability of guilty is at
least 0.9425 then issue a guilty verdict
(otherwise not)
 If the cost of false imprisonment is high
then you must have a very high probability
of guilt before issuing a guilty verdict
 “Innocent until proven guilty” – high cost of
false imprisonment (US criminal law)

39. Application to climate change and
mitigation actions
Actual condition
(Unknown)
Low sensitivity High sensitivity
to climate to climate
change (p) change (1-p)
Business-as- 20 -400
usual
Decision
Reduce GHG -5 10
emissions

40. Decision theory
 Would only choose to continue on
business-as-usual path if you placed a
probability of 0.9425 of low sensitivity to
climate change

41. Decision theory
 Decision theory is NOT hypothesis testing
 Do not need to be 95% sure that climate
change is real before we act
 Decision theory applied here minimizes
expected losses
 Even if potential loss is uncertain, the optimal
action is often to avoid large potential losses

42. Risk versus uncertainty
 Critics of decision-theory say that you may not
know what the probabilities are
 “True uncertainty”
 Unknown probabilities (P)
 Unknown outcomes (don’t know possible states)
 Former Defense Secretary Donald Rumsfeld:
 “As we know, there are known knowns. There are
things we know we know. We also know there are
known unknowns. That is to say we know there are
some things we do not know. But there are also
unknown unknowns, the ones we don't know we don't
know.”

43. Typology of uncertainty

44. Risk versus uncertainty
 With known probabilities of all possible
events – maximizing expected utility is a
reasonable rule
 With “unknown unknowns” what do you
do?
 Almost all important global change issues
have some element of “unknown
unknowns”

45. Decision theory response to
uncertainty challenge
 Assign subjective probabilities then proceed to maximize
expected utility
 Subjective probabilities – combination of available
information and best guesses (or opinion)
 Predicting future mean global temperature in 100 years
with triple the greenhouse gas concentration from pre-
industrial times
• With some basic physics we can probably “narrow” the possible
range
• Could assign equal probability to every temperature in this range
• Or use best available information to assess probabilities, for
example, a normal distribution with a mean of +3C from today and
standard deviation of +/- 2C

46. Other approaches to decision-
making under uncertainty
 Social-ecological systems are complex systems
 The future trajectory of social-ecological systems
under global change is subject to considerable
uncertainty
 Hard to understand system behavior and harder
still to predict the likely impacts of decisions
 Complexity has led some to think the decision
theory approach is not well suited to provide
guidance for managing social-ecological
systems under global change

47. Scenario Planning
Natural Capital Project

48. Scenario planning
 Scenario planning is a method for thinking
creatively and systematically about complex
futures
 Scenarios: sets of plausible stories, supported
with data and simulations, about how the future
might unfold from current conditions under
alternative human choices
 Scenarios can address many important
uncertainties and contrasting beliefs about the
future of the system
 Example: IPCC scenarios of future emissions
and consequences

49. Scenario planning
 Scenarios were first used in the analysis of
global change during the 1970s
 More recent efforts:
 Global Environmental Outlook
 Special Report on Emissions Scenarios (SRES) of the
Intergovernmental Panel on Climate Change (IPCC)
 Millennium Ecosystem Assessment
 These studies explored widely contrasting
alternative visions using quantitative models and
a diverse set of quantitative indicators

50. Scenario planning
 Advantage of scenario planning is that it expands horizons (“blue
sky thinking”) that gets people thinking about potential outcomes
 Weakness: difficulty of assessing the likelihood of alternative
futures
 SRES presented six scenarios – all “equally sound”
 High uncertainty prevented realistic assessments of probabilities
 Criticism that the lack of probabilities limited the value of the scenarios
to decision-makers
 Scenario planning can be combined with more quantitative decision
theory analysis
 Scenario planning as first stage – get universe of potential outcomes
 Robust decision-making to analyze more and less desirable decisions in
light of potential outcomes

51. Thresholds approach
Rockstrom et al. Nature 2009

52. Thresholds Approach
 Social–ecological systems are complex
adaptive systems that can exhibit
nonlinear dynamics, historical
dependency, have multiple basins of
attraction and limited predictability
 When crossed, thresholds between
multiple basins of attraction can lead to
fundamental transformations in system
feedbacks and dynamics

53. Thresholds Approach
 Focus attention on critical boundaries that have major
consequences if crossed
 Examples of the application of thresholds in global
change:
 Planetary boundaries (Rockstrom et al. 2009)
 Limits on emissions to avoid dangerous climate change (e.g. cap
of 450 ppm CO2e)
 Thresholds are often used in regulatory or legal contexts to
distinguish permissible from impermissible activities
 Thresholds can be used as a screen to rule out actions
thought to have too high a risk of crossing a threshold or
to rank actions based on risk

54. Thresholds approach
 There is often uncertainty about the exact level
of a threshold
 Decision-making involves choices about what
risks are acceptable: putting more stress on the
system can increase current benefits but at a
cost of having a higher probability of crossing a
critical threshold
 Thresholds have been criticized as giving a false
impression that degradation below the threshold
level is ‘safe’ and improvements beyond a
threshold are of no value

55. Resilience thinking

Resilience Alliance

56. Resilience thinking
 Resilience thinking focuses on critical
thresholds for system performance
 If current situation is desirable then
manage in ways to increase resilience
 Resilience: ability to withstand shocks/perturbations
and remain within one basin of attraction (Hollings
resilience)
 Build capacity to recognize and respond to
emerging transformations before they occur
 Build capacity to adapt should transformation
occur

57. Resilience
 Multiple basins of attraction and hysteresis
Source: Scheffer et al. Nature 2001

58. Resilience
 Ways to shift between stable equilibria
Source: Scheffer et al. Nature 2001

59. Resilience thinking
 Resilience thinking:
 How can we remain within certain dynamic
limits to avoid crossing thresholds and remain
in a desirable state
 In addition, how can be build capacity to cope
with change should a change of regime occur
 Resilience thinking is more of a general
framework for thinking than specific
management prescriptions

60. Application to climate change and
ecosystem management

61. Application to climate change
 Question: how much and how fast should we
reduce GHG emissions?
 Dueling approaches to answering this question
 Nordhaus Dynamic Integrated Climate Economy
(DICE) Model
 Stern Review of Climate Change
 Framing climate change as minimizing risk of
crossing a threshold or maximizing expected
utility

62. Stern Review on the Economics of
Climate Change
 It is a “stern review” but in reality it is
named for Nicholas Stern, an economist,
who headed the study
 UK Treasury Department 2006
 Created a splash
 Proponents of strong action to address
climate change trumpet the report
 Critics say the report is fundamentally flawed
and the conclusions are unwarranted

63. Stern Review on the Economics of
Climate Change
 Main findings:
 “…the benefits of strong, early action considerably
outweigh the costs.”
 “…if we don’t act, the overall costs and risks of climate
change will be the equivalent to losing 5% of global GDP
each year, now and forever. If a wider range of risks and
impacts is taken into account, the estimates of damage
could rise to 20% of GDP or more…”
 “Resource cost estimates suggest that an upper bound
for the expected annual cost of emissions reductions
consistent with a trajectory leading to stabilization at
550ppm CO2e is likely to be around 1% of GDP by
2050.”

64. Nordhaus DICE Model
 Strong action at present is at odds with most prior
economic analyses of the climate change (e.g. Nordhaus
analysis)
 Nordhaus policy recommendations: “climate change
ramp” - low initial price of carbon that ramps up over
time
 Costs of moderate action are lower than rapid adjustment
 Technological change lower future costs
 Society will be richer in future and better able to afford costs
associated with climate change
 This approach will not result in stabilization at 550 ppm
CO2 – concentrations will continue to rise

65. Why do Nordhaus and Stern
disagree?
 Discounting
 Estimates of damages
 Uncertainty – and general approach to
climate change policy question

66. Uncertainty and general approach
to climate change policy question
 Nordhaus: question of balancing costs
and benefits
 Takes estimates of benefits of avoided
damages along with costs
 Use integrated assessment model and inter-
temporal optimization to find the efficient
climate change policy

67. Uncertainty and general approach
to climate change policy question
 Stern: risk assessment and cost
 First do an analysis of risk and find a target for atmospheric
concentrations (550 ppm of CO2e)
 Second figure out cost-effective way of achieving the target
 On the standard cost-benefit analysis approach:
 “As I have argued, it is very hard to believe that models where
radically different paths have to be compared, where time
periods of hundreds of years much be considered, where risk
and uncertainty are of the essence, and where many crucial
economic, social, and scientific features are poorly understood,
can be used as the main quantitative plan in a policy argument.”
 Modeling of costs and benefits to optimize emissions is “still less
credible”

68. Application to ecosystem
management
 Social-ecological systems: dynamic and interconnected
 Climate change problem is almost easy by comparison
 Single dimension – CO2 concentration
 Ecosystem management – multiple dimensions
 Water quality
 Water flow (flood protection, drought mitigation)
 Habitat and species
 Agriculture & timber productivity
 Livelihoods and jobs…
 Do we understand systems well enough to predict short-
term and long-term consequences of management
actions on services?

69. Application to ecosystem
management
 Path forward in ecosystem management
 Building systems models to improve understanding of
potential system dynamics
 Verification of models with data
 Sensitivity analysis to probe uncertainty
 Scenario thinking to broaden scope of analysis
(reduce blindspots)
 Focus on potential thresholds with dramatic
consequences for system performance
 Provide early warning to avoid thresholds and plan for
adaptation in case thresholds are crossed

70. Conclusions
 Paul Krugman writing about the financial
crisis (September 2009):
 “…an all-purpose punch line has become
‘nobody could have predicted. . . .’ It’s what
you say with regard to disasters that could
have been predicted…”

71. Conclusions
 Essential role for conservation
professionals
 Provide better understanding of social-
ecological systems
 Highlight potential large-scale changes that
could have detrimental impacts
 Provide early warning signs of danger
 Provide guide-rails to keep us from crossing
thresholds

72. Conclusions
 We do not know enough BUT…
 We know enough to improve on current
performance
 The long road rather than the quick fix:
 Better science to improve understanding
 Better institutions/policy that incorporates
science and reduces risks
 Adaptive process that learns through time