Biocomplexity in the Environment (NSF) Stanley V. Gregory, David W. Hulse, John P. Bolte,

1. Social Experiments on Human Interactions with Ecosystems: Agents, Values, and Policies in the Willamette Valley, Oregon Biocomplexity in the Environment (NSF) Stanley V. Gregory, David W. Hulse, John P. Bolte, Courtland L. Smith, Michael Guzy, Chris Enright, Allan Branscomb, Linda Ashkenas, Randy Wildman Washington State University, Vancouver: April 11, 2006

2. Alternative Futuring Problem • Imagine yourself as a property owner, what would you do to restore salmon runs? • Situate yourself in the Puget-Willamette Lowland. • What is the role of policy (institutional structure) and values when choosing restoration actions?

3. Theory • Ecosystems – spatially-explicit, agent-based, multi-objective, scarcity-oriented, landscape futuring model • Evolutionary Ecology – landscape “evolution” (change) to reflect human values, evaluating alternative futures • Ethnoscientific/ideological/historical ecology – role of values in decision-making

6. Gallery Forests and Oak Savanna Willamette River Basin Planning Atlas, p. 82

7. McKenzie JCT Willamette River Basin Planning Atlas, p. 82

8. PNW-ERC change from 1990 initial conditions Willamette River Basin Planning Atlas, p. 128

9. Spatially-explicit McKenzie- Willamette Junction Springfield Eugene

10. Willamette Alternatives II – Study Areas

11. Urban growth boundary in the vicinity of Eugene, Oregon

12. Landscape

14. Agents Evaluative Models Inform Choose Outcomes Change Landscape Change Outcomes Autonomous Processes Policies

15. Evoland Framework Data Sources Evaluative Models Fish Abundance/Distributions Parcel Coverage Floodplain Habitat Policy Set(s) Small-Stream Macroinvertabrates Agent Descriptors Upslope Wildlife Habitat Evoland Parcel Market Values Autonomous Process Models Agricultural Land Supply Forest Land Supply Vegetative Succession Residential Land Supply Population Growth Conservation Set-Asides

16. EvoLand Agent Properties • Each agent makes decisions for an IDU (homogeneous tax lot and vegetation type) averaging 5000 m2. • Agents select policies that fit their values in adapting to scarcity. • Policies result in changes on the landscape to reduce scarcity regarding economic conditions and ecosystem health. • Scarcity metrics are updated with each iteration and agents make new decisions based on current scarcities and their values.

17. Evoland Agent Properties Adapted from Benenson and Torrens (2004:156)

18. Values Theory Integration • Theory of mind – developmental psychology, philosophy, sociology, linguistics(Malle et al. 2001; Conte and Castelfranchi 1995; Bratman 1987) • A general theory of action – sociology, developmental psychology, anthropology(Smelser 2001; Vaske et al. 2001; Rokeach 1973; Parsons and Shils 1951)

19. Theory of Mind

20. A general theory of action values  attitudes  action “… values are abstract concepts, but not so abstract that they cannot motivate behavior. Hence, an important theme of values research has been to assess how well one can predict specific behavior knowing something about a person’s values” (Karp 2001:3213).

21. A general theory of action (Parsons and Shils 1951) Systems Personality Social Cultural values  attitudes  action 

22. A synthetic theory of action Systems personality social cultural economic biophysical Actor values attitudes behavior beliefs  plan action norms desires goals intentions  I

23. Complex theory of action Drivers Context = difficulty, time, expense Systems personality social cultural economic biophysical Actor values attitudes behavior beliefs  plan action norms desires goals intentions  I information/matter/energy

24. Inferring Values from Actions: Votes on 1998 Environmental Ballot Measures

25. Definition of value categories including descriptive terms and text examples.

26. Value Frequencies in Ballot Measures

27. Scale of

28. EvoLand Policies River McMansion ? Court Smith photo Randy Wildman photo “Natural” River ? 

32. EvoLand Urban Growth Problem • Initial Conditions • Conservation Scenario with UGBs, 50 years • conservation policies, pop growth within UGB • Development Scenario without UGBs, 50 years • development policies, expansion anywhere • Conservation and Development, 50 years • which has the most impact

33. McKenzie Study Area 7,091 hectares 36% Urban 9% Rural 18% Agriculture 5% Other Vegetation 13% Forest 19% Roads&Water 40,000 people Evaluative Models scaled -3 to +3 Economic = -1.8 Ecosystem Health = -1.5 Initial Conditions

35. Initial Conditions 50-Yr Conservation Run

37. 36% Urban 9% Rural 18% Agriculture 5% Other Vegetation 13% Forest 19% Roads&Water 40,000 people Economic = -1.8 EcoHealth = -1.5 37% Urban 3% Rural 7% Agriculture 1% Other Vegetation 32% Forest 19% Roads&Water 82,300 (1.5%/yr inc) Economic = 0.3 EcoHealth = 2.1 Initial Conditions vs Conservation

39. 50-Yr Development Run Initial Conditions

41. Development 60% Urban 9% Rural 4% Agriculture <1% Other Veg 8% Forest 19% Roads/Water 82,500 people Economic = 2.5 EcoHealth = -2.0 Conservation 37% Urban 3% Rural 7% Agriculture 1% Other Veg 32% Forest 19% Roads/Water 82,500 people Economic = 0.3 EcoHealth = 2.1 Initial Conditions • 36% Urban • 9% Rural • 18% Agriculture • 5% Other Veg • 13% Forest • 19% Roads/Water • 82,500 people • Economic = -1.8 • EcoHealth = -1.5

42. PNW-ERC EvoLand

43. UGB Futuring Conclusions • UGBs cannot protect both farms and fish • Without UGBs development eliminates farms and fish • Ecological change is slow relative to economic change • Substantial conversion to forest required to achieve benefits for fish • Will forestry may produce more income and fish protection than agriculture? • What incentives will product more forests?

44. Modeling Conclusions • EvoLand provides a generalized modeling structure • Agent-based modeling allows for investigation of a broader set of future alternatives • Can we assume economic and ecological scarcity are major driving forces for future policy selection? • Are values important? What mechanisms change agents’ values? • Does institutional structure (policies) play a larger role than values? Institutional structure comes from values? • How should the results of alternative futuring be validated?

45. EvoLandA modeling framework for the analysis of complex, coupled ecological/human systems http://evoland.bioe.orst.edu/ http://oregonstate.edu/instruct/anth/smith/ Support from the National Science Foundation, Biocomplexity in the Environment