# Presentation: 011072

## Suzette Kimball
USGS Eastern Regional Director

**Suzette Kimball**
***USGS Eastern Regional Director***

**Department of the Interior**
***April 24, 2007***

**Notes:**
Ione:  Could combine this with next slide giving outline

Multiple methods/models exist for Informed Decision Making

Today present two examples, one from science perspective and another from management perspective

(But 1 of our themes will be that these perspectives should merge, or at least become much more similar, in the conduct of Informed Decision Processes.) 

Our distinguished panel members from MMS, BLM, FWS will discuss current bureau applications of informed decision processes

## Decisions, Decisions...Making Choices

**Notes:**
Ione:  Decisions are often no longer between good and bad but are becoming increasingly complex choices between better and best – if you can figure out which is which

## The Evolving Nature of Decision-making

- Interface of information providers and decision-makers
- Broader applications
- More collaborative
- Increasing coordination to leverage capabilities

**Notes:**
Ione:  Suzette’s key points 
Also alerts audience as to expectations for them for this session

## Current Efforts Use              Different Language 

**Current Efforts Use              Different Language **

***Decision   Analysis***

***Stakeholder       Analysis***

***Others??***

***Community-based Collaboration***

***Decision                                     Support                                     Systems***

***Joint Fact-finding***

***Adaptive Management***

***Decision Science***

***Structured Decision-      making***

**Notes:**
Ione:  What other terms to add so everyone feels included? 

## Elements of a Structured Decision

-   Identify management _*objectives*_
-   Develop management _*alternatives*_
-   Create _*models*_ of potential outcomes
-   Populate models with appropriate
-      scientific data and information
-   Test model _*credibility*_* *
-   _*Monitor*_ program to assess
-      effectiveness

**Notes:**
Ione: added the populate models with data bullet

5 basic elements of informed decision making
First 2: based on societal values, law, politics, stakeholders
Last 3: fall under purview of science 

JDN – OK, but these are stated more as steps to take (they begin with verbs) rather than as elements that you must have before embarking on SDP. I would list similarly as: management objectives, management alternatives, models predicting potential outcomes, measures of model credibility (if more than 1 model), and monitoring program

What do you want to accomplish?
What can actually be done?
Develop scenarios based on potential  courses of action

JDN- The models provide means of predicting the outcomes of the potential courses of action. This is slightly different from modeling the outcomes, perhaps? 

4. Does this do what we need it to do? 

JDN- The testing is part of the process itself. If there are multiple models, then we must have measures of model credibility. In the usual listing of elements, the testing itself is not listed. However, the testing does provide the basis for the measures of credibility. 

5. Ongoing learning and reintegration of knowledge 

JDN- Statement above is probably fine as a summary. We monitor because knowledge of system state is needed for the next decision, and because comparison of what really happened with our model-based predictions leads to changes in our measures of credibility.

## Complex decisions 
Framework to integrate
Use of scientific data 
Policy-relevant
Increased involvement
Requires transparency 
Addresses uncertainty 
Improves planning and utilization of limited resources: Time, Money, People

- Framework to integrate
- Use of scientific data
- Policy-relevant
- Increased involvement
- Requires transparency
- Addresses uncertainty
- Improves planning and utilization of limited resources: Time, Money, People

**Why Structured Decision Making? **

**Notes:**
Ione:  Critical to note the data integration and calibration of scale role that structured decision-making brings, added bullet to address Jim’s point about science- management interface

JDN- OK, but it also integrates science into management, because as you learn from current management actions and their outcomes, you are better able to make smart decisions in the future. This insures that the science is maximally useful to managers.

JDN- It is also easily defended (might be an important point to folks who deal with legal issues). You can demonstrate that, conditional on your objectives , available acitons, and state of knowledge, you are taking the smartest decision.  

## For use as standard operating procedure
To facilitate interactions between information providers and decision-makers
In training and developing our people in the pertinent competencies
Other ideas?

- For use as standard operating procedure
- To facilitate interactions between information providers and decision-makers
- In training and developing our people in the pertinent competencies
- Other ideas?

**Notes:**
Ione:  Might want to get thoughts from audience at end of talk

JDN- might consider switching this slide and next one. 

JDN- OK, but we may want to emphasize that very few scientists and managers are trained in this stuff, so capacity building will present a real challenge)

JDN- The final tidal wave was intended to reflect our perception of a substantial increase in the need for expertise in application of SDP, and our current relative lack of trained folks to carry out these processes. 

Structured decision making is currently being used throughout DOI by- FWS, USGS, MMS, BLM, XXX, XYZ, 

Centers of excellence: build on core groups for natural resources, leasing, litigation, and appeals, OTHER EXAMPLES to create centers of excellence

Build via investment in postdoctoral investigators attached to these groups

Share knowledge and experiences 

## Suzette Kimball, USGS - Moderator

Jim Nichols, USGS
Teresa Woods, FWS
Robyn Thorson, FWS
John Goll, MMS
Henri Bisson, BLM

Plenary Discussion

*Jim Nichols, USGS*
*Teresa Woods, FWS*
*Robyn Thorson, FWS*
*John Goll, MMS*
*Henri Bisson, BLM*
- Plenary Discussion

**Panelists**

**Notes:**
Ione:  Gets everyone introduced up front to minimize shuffling and lets audience know they will have a chance to participate

## Structured Decisions: An  Approach to a Nuisance 

**James D. Nichols**
***USGS Patuxent Wildlife Research Center***

- Department of the Interior
*April 24, 2007*

**Notes:**
State of Virginia, FWS, USGS, OTHER STAKEHOLDERS?

JDN- My preference is not to view adaptive management as including scientific and (perhaps by implication) nonscientific examples. I might have used: “Adaptive Management: Integrating Science and Management”.

## Conservation/Management: A Common Approach 

- Information is collected and provided to managers
- Managers make decisions based on information

**Notes:**
Normally would have done this

Problems with this approach:
	Primarily a transfer of data, limited interaction 
	Can be inefficient
	Focus on getting more information rather than the information needed to address the issue/solve problem

## Conservation/Management: A Structured Decision Approach

- Collaborative
- Focused on objectives
- Science based predictions
- Transparent
- Deals with uncertainty
- Broad base of support

**Notes:**
Information gatherer--scientist, financial analyst, lawyer or other professional works with manager 
Information collected is specific to the management decision
Proposed options are based on how the system may respond to management actions
Involves the stakeholders—may be municipal, state, federal, tribal, NGO, interest groups

## Sources of Uncertainty

- Management
- Predictive uncertainty
- Environmental (weather)
- Indirect actions
- Observation uncertainty
- Policy
- Financial constraints and unknowns
- Shifting societal preferences and opinions
- Linguistic imprecision

**Notes:**
Every DOI bureau deals with uncertainty in various forms

Uncertainty then has to be part of the equation in identifying management decisions

JDN- I would probably recommend redoing slide to capture 2 flavors of uncertainty: scientific and policy. I usually list a few other scientific courses. The policy sources can be dealt with via so-called double-loop learning, and I can emphasize this here and later in the slide dealing with the ARM process.

## Structured Decision Making: Iterative Process

**Notes:**
JDN- I think that we tentatively agreed to knock out this slide, but the rationale seemed to concern a desire to not emphasize “adaptive management”. However, our original title (I recommended change above to try to deal with this concern) for this entire part of presentation and another slide or so later on include the terms “adaptive management”. Adaptive management is actually a form of SDM that can be used when decisions are iterated across time or space. Anyway, I thought about this, and I concluded that if it were up to me, I would like to describe the process in general before launching into example. So my vote would be to retain the diagram on p.38 here. Note that I have given it a different name in effort to emphasize that it is simply 1 flavor of the broader SDM. One point to note; this diagram emphasizes the role of policy folks, etc., an emphasis that may appeal to audience?

## Damage
		- Roosting colonies: damage to property
		- Individual birds: predation of livestock, pets
Control
		- Range of methods, including lethal take
Relevant laws
		- Migratory Bird Treaty Act (“take” permits required) 	- Enabling legislation for USDA
		- NEPA (EA or EIS related to ‘take”)

- Damage
- 		- Roosting colonies: damage to property
- 		- Individual birds: predation of livestock, pets
- Control
- 		- Range of methods, including lethal take
- Relevant laws
- 		- Migratory Bird Treaty Act (“take” permits required) 	- Enabling legislation for USDA
- 		- NEPA (EA or EIS related to ‘take”)

**Notes:**
Where: State of Virginia
When: 
Why: Issues of property damage, management methods and legal framework

## USDA & USFWS issue:
Focus on population estimate to determine vulture “take” permits

USGS proposal: 
-a strategy for setting “take” based on management objectives
- iterated nature of action leads to reduction in uncertainty

- USDA & USFWS issue:
- Focus on population estimate to determine vulture “take” permits
- USGS proposal:
- -a strategy for setting “take” based on management objectives
- - iterated nature of action leads to reduction in uncertainty

**Notes:**
Roles of  DOI bureaus in the process

## Management ObjectiveScientific Model 

- Annual take

- Legal constraints:
- MBTA requires only that take be sustainable
- “Significant effect” under NEPA

**Notes:**
Determine population size parameters that remains in the bounds of MBTA- Migratory Bird Treaty Act requires population sustainability  . . .. 
And National Environmental Policy Act.

## Uncertainty in the example decision of annual black vulture take
- Population size
- Population demographics
- Actual take 
Risk management 
- Flexibility of the decision-maker 
- Resiliency in the population

- Uncertainty in the example decision of annual black vulture take
- - Population size
- - Population demographics
- - Actual take
- Risk management
- - Flexibility of the decision-maker
- - Resiliency in the population

**Notes:**
In this example population size and projected growth- but also pertains to oil, coal, trees, financial resources

## Iterated decision process
Annual monitoring of population size
Annual lethal take permit  
Learning (reducing uncertainty)
Compare observed/predicted population size following each action
Better estimates – 
Population size
Sustainable harvest

- Iterated decision process
- Annual monitoring of population size
- Annual lethal take permit
- Learning (reducing uncertainty)
- Compare observed/predicted population size following each action
- Better estimates –
- Population size
- Sustainable harvest

**Notes:**

Learning
Monitor population size
Conduct auxiliary studies to refine the estimate of the population size.
Use demographic studies to refine estimate of sustainable annual harvest.
Compare observed and predicted population size to verify whether the framework is working.

## Black Vulture Nuisance Control: Decision Process Benefits

- Focused decision-maker efforts on objectives
- Focused scientific efforts on needed models and estimates
- Products:
- Defensible decisions
- Optimal use of scientist and manager efforts

## Structured Decision Making:  An Emerging Practice

**Teresa Woods**
***USFWS Midwest Region***

**Department of the Interior**
**April 24, 2007**

## Further develop concepts 
Example:  Cerulean Warbler conservation
Building capacity for this emerging practice

- Further develop concepts
- Example:  Cerulean Warbler conservation
- Building capacity for this emerging practice

## Features
Diagnose problem
Transparency
Boundaries
Address uncertainty
Break down problems

- Diagnose problem
- Transparency
- Boundaries
- Address uncertainty
- Break down problems

**Structured Decision Processes**

## Cerulean Warbler

- Neotropical migratory bird
- Breeds in North America
- Winters in South America
- Trans-Gulf migrant
- Declining at 2% - 4% annually
- ~500,000 individuals
- Habitat loss and degradation

## How do we conserve this species?
What are desired population goals?
What are limiting factors?
How do we control what is limiting? 
Should the species be listed under the Endangered Species Act?

- What are desired population goals?
- What are limiting factors?
- How do we control what is limiting?
- Should the species be listed under the Endangered Species Act?

**Management Questions**

## ESA

- Extinction risk
- Population size and trend
- Expert Workshop
- North and South America
- USGS, FWS, FS, academia, industry, NGO
- Explore uncertainty
- Make projections

## Workshop Conclusions

- Conclusions
- ~500,000, more likely underestimated
- Decline likely to continue at historical rate
- Little risk of extinction for foreseeable future
- FWS decided:
- ESA listing not warranted at this time
- Keep going with structured decision making!

## Original Issues

- Need to know
- Desired population goals
- Limiting factors
- Conservation recommendations
- Workshop participants
- 6 nations
- Industry & conservation groups
- Government scientists & managers
- Conclusions
- Information gaps
- Habitat loss and degradation

## Habitat Conservation

- Making conservation recommendations for winter habitat

- Question:  How can we conserve shade-grown coffee plantations in South America when our responsibility is limited to the birds?

## Winter Habitat

- Non-traditional partners
*Technical group & el Grupo Ceruleo*
- Cerulean Warbler habitat preserve in Colombia
- Cerulean Warbler coffee
- Stay tuned for other creative solutions

## Capacity:  Skills 

- Subject matter experts
- Modeling & other quantitative analyses
- Risk assessment
- Risk attitudes
- Decision making under uncertainty
- Creation of forums
- Communication

## Capacity Building

- Interaction with academic institutions
- Sharing expertise
- Training, education, learning
- Cross-discipline interaction
- Willingness to learn by doing

## Increased communication
Many benefits
Leadership

- Increased communication
- Many benefits
- Leadership