Transcript Adapting to Nature in the New Normal Improving natural

ADAPTING TO NATURE IN
THE NEW NORMAL
IMPROVING NATURAL
RESOURCE DECISION
MAKING UNDER
UNCERTAINTY
Evan H. Campbell Grant
US Geological Survey
Amphibian Research and Monitoring Initiative
Patuxent Wildlife Research Center
SO Conte Anadromous Fish Research Laboratory
Turners Falls, MA
PROBLEM:
AMPHIBIAN POPULATIONS ARE DECLINING
WORLDWIDE
PROBLEMS ARE COMPLEX
AND INTERACTING
Matt Gray, UT
Huntington et al. 2009. Can J. For. Res.
Are amphibians in the USA declining?
http://armi.usgs.gov/index.php
IN THE
NORTHEAST…
HOTTER
IN THE
NORTHEAST…
DRIER
UNPREDICTABLE
PROBLEM: HABITAT PROTECTION
ALONE MIGHT NOT CUT IT
Number of droughts
PRESCRIPTION FOR RESOLVING 10,000
DECISIONS
Keeney 2004. Making better decision makers. Decision Analysis 1:193-204.
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PRESCRIPTION FOR RESOLVING 10,000
DECISIONS
Keeney 2004. Making better decision makers. Decision Analysis 1:193-204.
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WHAT IS DECISION ANALYSIS?
The structuring of a decision problem
 in terms of choices, outcomes, and values
 to identify the choice that is most likely to achieve
the values of the decision maker.
Decisions involve
 valuing the outcomes
 predicting outcomes from alternative choices
The first part is the (subjective) role of
society; the second part is the (objective) role
of science
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STRUCTURED DECISION
MAKING
Elements:
Clear Objectives
Creative management Alternatives
Models linking actions to objectives,
generate predictions
Optimization to determine best
approach, given observations and
objectives
Implement a decision
Monitor system state changes
STRUCTURED DECISION
MAKING
Clear Objectives
Creative management Alternatives
Models linking actions to objectives,
generate predictions
Optimization to determine best
approach, given observations and
objectives
Implement a decision
Monitor system state changes
Values
Science
Values
Science
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
SDM IS NOT A PANACEA
Disputed
Conflict
Resolution
OBJECTIVES
Structured DecisionMaking
Joint
Fact
Finding
Agreed
upon
Well
Understood
Uncertain
OUTCOMES
Disputed
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EXAMPLE FROM C&O CANAL NHP
‘Potomac Gorge’ area of
C&O
Threats (Allen and Flack 2001)
 Urbanization
 Invasive/alien species
 Isolation
Climate change (and
variability)
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
WHAT IS VALUED BY RESOURCE
MANAGEMENT: OBJECTIVES
Maintain average amphibian species richness
at C&O Canal NHP wetlands.
Minimize cost of doing management.
* Can include other competing objectives (e.g.,
visitor use and enjoyment, access to
recreation, other species-specific goals)
Monitoring data:
Since 2005
Observe a decline in
occupancy for all species
0
1000
2000
Wetland Area (m2)
3000
10
8
2
4
6
Relate occupancy to
measured variables
(*hydroperiod)
0
Temporary
Observed number of species (2005-2009)
8
6
2
4
Semi-permanent
0
Average projected richness
Permanent
0
2
4
6
8
Observed number of species (2010)
10
1000
2000
Wetland Area (m2)
3000
Average wetland richness
10
8
6
4
0
2
0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
0
2
Temporary
0
2
4
Semi-permanent
Observed number of species (2005-2009)
6
Permanent
0
Average projected richness
8
Make predictions
4
2005
6
8
2010
10
Observed number of species (2010)
Year
2015
2020
HOTTER
THINKING BACK TO
OUR FORECASTS
DRIER
UNPREDICTABLE
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
USING THE MODEL TO GUIDE
MANAGEMENT: OPTIMIZATION
Best Alternative: increase
hydroperiod of temporary wetlands
Optimization: Rank wetlands by the
expected increase in richness, to
choose most suitable sites for
management each year
NOW WHAT?
Typical response is to want to
understand what’s causing declines,
But there is a tradeoff in waiting for
more information (which may be
imperfect) and a need for action
Both have components of
uncertainty.
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Average wetland richness
When to initiate a decision?
Utility threshold
1
10
5
Year that management is implemented
Average wetland richness
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Manage
half
Manage a
quarter
Manage
none
1
5
10
Average wetland richness
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Marginal
benefit of
managing 50%
of sites in year
1, vs. no
management,
assuming poor
outcome.
1
5
10
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Average wetland richness
Marginal benefit
of implementing
management of
50% of sites in
year 1 vs. 5,
assuming best
outcome
1
5
10
Average wetland richness
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Marginal
benefit of
managing
50% vs. 25%
of sites in
year 1,
assuming
average
outcome.
1
5
10
Objectives – Alternatives – Models – Optimization – Implementation - Monitoring
Average wetland richness
Marginal
benefit of
managing
50% of sites
in year 1 vs.
25% of sites
in year 5,
assuming
learning
occurred
1
5
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IN SUMMARY
Amphibians are in trouble (or may be…)
Even amphibians in protected areas are at
risk under climate change
UNCERTAINTY IS SCARY,
BUT IF we value amphibians, where they are,
we need to make hard decisions about
active management
A proactive approach to
conservation
Designed to preempt (or respond to) climate
change effects – short term focus
Maintain community and prevent LOCAL
extinctions
A structured approach to decision making
[email protected]