developing computational tools that are useful to decision makers

Ecosystem Management Project

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Developing Computational Tools that are Useful to Decision Makers

Virginia DaleEnvironmental 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

Academic audience: Environmental scientists Social scientists Economists Landscape architects Planners Risk communicators

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

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 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

Species-specifichabitat quality

Focal species

and communities

How RSim Models Stressor Effects on Focal Species & Communities

Stressors

Noise

ToxicitySmog

Air quality

Water quality

Land cover

RSim (Regional Simulation of Environmental Change)

Focal species and communities

Endangered Migratory species birds

Species-specifichabitat quality

Interactions of RSim with Environmental Laws and Regulations

Stressors

ToxicitySmog

RSim can be a scoping tool for the National Environmental Policy Act (NEPA)

Air quality

Water quality

Land cover

Compliance with Endangered Species Act

Compliance with Clean Air Standards

Compliance with Clean Water Standards

Compliance with Local and Federal Noise Standards

Wetland loss

Noise

Compliance with Migratory Bird Act


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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 HelmholtzAcademic discourse, Heidelberg, 1862

Relating Science to Decision Making


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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

Indicator ResearchProject 1

Indicator Research Project 2

Indicator Research Project 3

ThresholdResearch Project 1

ThresholdResearch project 2

Procedure for Including Indications in Decision Making Process= Research + Characterization + Management Needs

Suite of Indicators

Data repository

IntegratedPlanning Database

Monitoring And

Analysis Plan

Scie

nce

inte

grat

ion

scre

en

Management

needs scre

en


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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.

(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

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.

(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.

Are rewarded for novelty Often suggest and

sometimes test new ideas for management.

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.

(Schwartz, M.W, 1999. Annual Review of Ecology and Systematics 30: 83-108)

Scientists: Managers:


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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 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 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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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

Indicator criteria—relates to modeling criteria

developing computational tools that are useful to decision makers

Documents

decision makerscontinue

ecological models

use of models

environmental laws

rsim models stressor

resource plannersprivate

brief history of modeling

clean air standardscompliance