Ecosystem Management Project
Developing Computational Tools that
are Useful to Decision Makers
Virginia Dale
Environmental Sciences Division
Oak Ridge National Laboratory
February 2005
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Who is interested in ecological modeling for resource management?
A spectrum that runs between the
pure scholar and the decision maker
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Academic audience:
 Environmental scientists
 Social scientists
 Economists
 Landscape architects
 Planners
 Risk communicators
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Practitioner community:
 Resource planners
 Private and public land
owners
 Sociologists who deal with
goal and values
 Environmental engineers
 Applied ecologists
 Resource managers (e.g.,
foresters and fisheries
researchers and managers)
 Risk analysts
 Environmental lawyers.
 “Savvy” decision makers
 Training audience
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A brief history of modeling for
resource management
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Beginnings of ecological modeling: Lotka Voterra, etc.
Attempts to understand human population dynamics
Explanations of dynamics of laboratory animals
Fisheries management
Development of computers
Systems ecology
Risk assessment
Models of land-use change
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Overcoming barriers to the use of models
in decision making
 Generalized Barriers
 Communication
 Humans are risk averse
 Institutional
 Logistical
 Model capabilities
 Barriers specific to groups involved in
decision-making
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Overcoming barriers (continued)
 Solutions to barriers
 Collaborative decision making
 Improved technology transfer
 Outstanding issues
 modeling vs scientific questions
 modeling at different stages of decision process
• Scoping
• Analysis
• Decision making
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New Directions
 Trends
 Use of computers is growing
 More complex view of world
 Environmental pressures are increasing
 Awareness of environmental pressures increasing
 World is becoming networked
 Globalization of economy
 Stakeholders more educated and more actively
involved
 Philosophies of modeling
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A parsimonious approach
Assumptions are key
Generic modeling approaches
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New Directions (continued)
 Future directions of ongoing saga of using ecological
models for resource management
 Know problem
 Keep close communication between modeler and
decision makers
 Continue exploring diversity of modeling approaches
 Use models to direct data collection
 Explore alternative futures in a gaming mode
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RSim (Regional Simulation of Environmental Change)
Stressors
Air
quality
Water
quality
Land
cover
Noise
Species-specific
habitat quality
Focal
species
and
communities
How RSim Models Stressor Effects
on Focal Species & Communities
Interactions of RSim with Environmental Laws and Regulations
Stressors
Air
quality
Compliance with
Clean Air Standards
Water
quality
Compliance with Clean
Water Standards
Land
cover
Species-specific
habitat quality
Focal species
and communities
Endangered
species
Migratory
birds
Wetland loss
Noise
Compliance with Local and
Federal Noise Standards
Compliance
with
Endangered
Species Act
Compliance
with
Migratory
Bird Act
RSim can be a scoping tool for the National Environmental Policy Act (NEPA)
Relating Science to Decision Making
Whoever, in the pursuit of science, seeks after
immediate practical utility, may generally rest
assured that he will seek in vain. All that
science can achieve is a perfect knowledge
and a perfect understanding of the action of
natural and moral forces.
Hermann Ludwig Ferdinand van Helmholtz
Academic discourse, Heidelberg, 1862
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The scientific research uses several
methods to develop this knowledge:
 Observe nature
 Organize data
 Use logic
 Form a hypothesis
 Express findings mathematically
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Procedure for Including Indications in Decision Making Process
= Research + Characterization + Management Needs
Indicator
Research
Project 1
Indicator
Research
Project 2
Indicator
Research
Project 3
Threshold
Research
Project 1
Threshold
Research
project 2
Data
repository
Monitoring
And
Analysis
Plan
Suite of
Indicators
Integrated
Planning
Database
Scientists can discover
new options by:
 Exploring future options with computer
simulation models
 Examining past situations
 Determining causes of observed
phenomenon
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Most scientists are “introverted,
intuitive, thinking, judging” (INTJ)
 Are visionary and excel at creating systems
 Can understand complex and difficult subjects
 Enjoy creative and intellectual challenges
 Are good at theoretical and technical analysis and logical
problem solving
 Work well alone and are determined even in the face of
opposition.
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(Tieger, P.D. and Barron-Tieger, B. 1992.
Boston: Little, Brown and Company)
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However, INTJs can also
 Be less interested in projects after creative
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problem solving is completed
Drive others as hard as they drive themselves
Be too independent to adapt to corporate
culture
Have difficulty working with or for others they
consider less competent
Be inflexible and single-minded about their
ideas.
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Politicians are most often extraverted,
intuitive, feeling, judging (ENFJ)
 Tend to promote harmony and build
cooperation
 Respect a variety of opinions
 Are decisive and organized
 Are natural leaders.
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(Tieger, P.D. and Barron-Tieger, B.
1992. Boston: Little, Brown and
Company)
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However, ENFJs also
 May have trouble dealing with conflict
 Tend to sweep problems under the rug
 May not be attentive to factual accuracy
 May take criticism too personally
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Resource managers are both blessed and
cursed by the attention of biologists.
Scientists:
 Are rewarded for novelty
 Often suggest and
sometimes test new ideas
for management.
Managers:
 Are expected to employ the
latest scientific develops
 Find that application of
untried ideas can result in
failure
 Are often unsure as to what is
the most appropriate
technology.
New ideas should be tested with empirical data
before new methods are adopted.
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(Schwartz, M.W, 1999. Annual
Review of Ecology and Systematics
30: 83-108)
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Scientists and decision makers come
from different fields of endeavor
 Scientist who wish to contribute to policy are a subset of all
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scientists
Science only has value for decision-making when it can
influence a decision.
Neither scientists nor decision makers are a singular entity.
Scientists need to better understand the spectrum of
concerns in the policy process.
Decision makers typically accept a different level of
uncertainty than scientists.
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Communication between scientists and
decision makers is critical
 Scientific information is only useful to decision making when
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policy questions are addressed.
Decision makers often not aware that science can pertain to
a policy issue.
Regular discussions between scientists and decision makers
can enhance communications and build mutual respect.
Communication is a two-way street.
Scientific results are rarely expressed in terms that have
meaning or value to decision-makers.
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General questions about science and
decision making
 Does “better” science translate to “better” decision
making?
 How much does and should science influence decision
making (and vice versa)?
 How can we quantify the value of scientific
information to decision makers? How can we use this
information to make science more useful?
 How can the linkages between science and
environmental policy be facilitated?
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Questions dealing with communications
 How do decision makers receive scientific
information?
 What are the major barriers influencing effective
communication of science to decision makers?
 What aspects of the science should be communicated
to decision makers?
 What are the best ways to communicate science to
decision makers?
 Who are the decision makers?
 Do different decision makers want information in different
styles?
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How might resource managers use
indicators (or models)?
Their responses:
 Planning budgets
 Provide a “heads up” regarding compliance
 Heading toward non-compliance?
 Signal whether on right path toward
achieving longer term goals
 Signal whether on right path to achieve
shorter term objectives
 Suggest need for targeted research
 The “holy cow” scenario
Photo: Fort Bragg
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Indicator criteria—relates to
modeling criteria
Resource managers noted that
some criteria are conditional
 “Cheaper is better, but more expensive might
be ok”
If associated with
 Critical land use needs
 Red list (Endangered Species)
 Isolated populations (“lucrative targets”)
 Broad applicability is better, but narrow
applicability might be ok
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