Developing Computational Tools that are Useful to Decision Makers

1. Ecosystem Management Project Developing Computational Tools that are Useful to Decision Makers Virginia Dale Environmental Sciences Division Oak Ridge National Laboratory February 2005

2. 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 Who is interested in ecological modeling for resource management? A spectrum that runs between the pure scholar and the decision maker

3. 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

4. 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

5. 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

6. 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

7. 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

8. RSim (Regional Simulation of Environmental Change) Stressors Air quality Toxicity Smog Water quality Focal species and communities Species-specific habitat quality Land cover Noise How RSim Models Stressor Effects on Focal Species & Communities

9. Interactions of RSim with Environmental Laws and Regulations Stressors Compliance with Clean Air Standards Air quality Smog Toxicity Water quality Focal species and communities Endangered Migratory species birds Species-specific habitat quality Land cover Compliance with Clean Water Standards Wetland loss Noise Compliance with Endangered Species Act Compliance with Migratory Bird Act Compliance with Local and Federal Noise Standards RSim can be a scoping tool for the National Environmental Policy Act (NEPA)

10. 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

11. The scientific research uses several methods to develop this knowledge: • Observe nature • Organize data • Use logic • Form a hypothesis • Express findings mathematically

12. Procedure for Including Indications in Decision Making Process = Research + Characterization+ Management Needs Indicator ResearchProject 1 Management needs screen Data repository Indicator Research Project 2 Monitoring And Analysis Plan Indicator Research Project 3 Suite of Indicators Threshold Research Project 1 Integrated Planning Database Science integration screen ThresholdResearch project 2

13. Scientists can discover new options by: • Exploring future options with computer simulation models • Examining past situations • Determining causes of observed phenomenon

14. 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. Most scientists are “introverted, intuitive, thinking, judging” (INTJ) (Tieger, P.D. and Barron-Tieger, B. 1992. Boston: Little, Brown and Company)

15. 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.

16. 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)

17. 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

18. 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. Resource managers are both blessed and cursed by the attention of biologists. Scientists: Managers: 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)

19. 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.

20. 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.

21. 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?

22. 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?

23. 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

24. 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