Social Experiments on Human Interactions with Ecosystems: Agents, Values, and Policies in the Willamette Valley, Oregon

Transcription

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, agentbased, 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 decisionmaking

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

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

8 PNW-ERC change from 1990 initial conditions Dev Percent Plan Cons Conifer Riparian 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

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

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

16 EvoLand Agent Properties Each agent makes decisions for an IDU (homogeneous tax lot and vegetation type) averaging 5000 m 2. 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 Property Meaning Evoland Reactive Responds to environment Yes Autonomous Controls own actions Yes Social Interact with other actors No Goal-oriented More than responsive to environment Yes Temporally continuous Agent behavior continuous Once/step Communicative Communicates with other agents No Mobile Can transport self to other locations No Flexible Actions not scripted Yes Learning Changes based on experience No Character Believable personality or emotions No 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 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).

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 Drivers Complex theory of action Systems personality social cultural economic biophysical Context = difficulty, time, expense 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 Ballot Measure Yes Votes Statewide No Votes Statewide Percent Yes Lane County Percent Yes 56 (notification) (timber) (parks & salmon )

25 Definition of value categories including descriptive terms and text examples. Value Category Descriptive Terms Economic Property Rights Ecosystem Health Nonmarket Fairness Credibility Safety Recreation reflecting economic production of the landscape, job activity, productivity, opportunities for capital production and revenue generation concern is with the freedom to own and use private property as a landowner desires ecological health, diversity of the landscape, environmental protection and restoration reflecting aesthetics, scenic integrity, beauty, spiritual, future generations, right thing to do, undiscovered utility, learning about and gaining connection with the environment refers to actor perceptions about economic justice, winners and losers, fears about litigation and its costs; unfair policies force an actor to do something she does not want to do refers to policies are justified by scientific or other expertise, or to policies that lack scientific or support by other expertise concerned with human safety in jobs and activites, from chemicals, from natural hazards emphasis on any type of recreational activity that could be helped or hurt by passage of the ballot measure.

26 Value Frequencies in Ballot Measures % MEASURE No Economic Private property rights Ecosystem health % % % % % Nonmarket Fairness Credibility Safety Recreation Notification % Timber - Pro Timber - Con Salmon & Parks

27 Scale of Economics Values cell ACTORWT_

28 EvoLand Policies River McMansion? Randy Wildman photo Natural River?

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31 Policy Name Tax credits for fish Riparian Conservation Easement on Rural Lands River McMansions Persistance (yrs) Mandatory? Site Attributes no In_Flood = 1 and In_UGB = 0 and (Lulc_C = 67 or Lulc_C = 71 or Lulc_C = 79 or Lulc_C = 83 or Lulc_C = 85 or Lulc_C = 86 or Lulc_C = 88 or Lulc_C = 90) no Dist_Str < 100 and In_UGB = 0 {Outside Urban Growth Boundary} and (Lulc_C = 24 {Rural non-vegetated} or Lulc_A = 3 {Agriculture}) Outcomes Lulc_C = 87 {shrubland} Lulc_C = 87 {shrubland} no Dist_Str < 100 Lulc_C = 1 {Residential 0-4 DU/ac}

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 LULC_A Roads (8) Water (7) Other Vegetation (6) Wetlands (5) Forest (4) Agriculture (3) Rural (2) Urban (1) No Data Range: 1-8 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 Initial Conditions Economic = -1.8 Ecosystem Health = -1.5

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35 LULC_A Roads (8) Water (7) Other Vegetation (6) Wetlands (5) Forest (4) Agriculture (3) Rural (2) Urban (1) No Data Range: 1-8 LULC_A Roads (8) Water (7) Other Vegetation (6) Wetlands (5) Forest (4) Agriculture (3) Rural (2) Urban (1) No Data Range: 1-8 Initial Conditions 50-Yr Conservation Run

36 Conservation Scenario Ecosystem Health Measures Score Time _Ecosystem_Health _HabScore _Small_Streams _Willamette_Fish

37 Initial Conditions vs Conservation 36% Urban 9% Rural 18% Agriculture 5% Other Vegetation 13% Forest 19% Roads & Water 40,000 people Economic = -1.8 EcoHealth = % 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

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39 LULC_A Roads (8) Water (7) Other Vegetation (6) Wetlands (5) Forest (4) Agriculture (3) Rural (2) Urban (1) No Data Range: 1-8 LULC_A Roads (8) Water (7) Other Vegetation (6) Wetlands (5) Forest (4) Agriculture (3) Rural (2) Urban (1) No Data Range: 1-8 Initial Conditions 50-Yr Development Run

40 Development Scenario EcoHealth Measures Score _Ecosystem_Health _HabScore _Small_Streams _Willamette_Fish Time

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 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 Conservation 37% Urban 3% Rural 7% Agriculture 1% Other Veg 32% Forest 19% Roads/Water 82,500 people Economic = 0.3 EcoHealth = 2.1

42 forest Land Use rural Initial Conserve Develop PNW-ERC urban Percent forest Land Use rural Initial Conserve Develop EvoLand urban Percent

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 EvoLand A modeling framework for the analysis of complex, coupled ecological/human systems Support from the National Science Foundation, Biocomplexity in the Environment