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www.2010colombia.com<br />
An Alternative Futures Approach to Understanding Landscape Dynamics and Services<br />Kellie Vache, PhD. Biological & Ecol...
Today’s Discussion<br />Overview of alternative futures approach to socio-ecological modeling<br />Description of one appr...
Socio-Ecological Modeling<br />
To Start - A Definition of Biocomplexity<br />Term used to describe complex structures, interactions, adaptive capabilitie...
Challenge – How to make these operational?</li></li></ul><li>Alternative Futures Projects<br />Examine multiple scenarios ...
Software-based Alternative Futures<br />A mechanism to include biocomplexity in alternative Futures – to do so requires:<b...
Envision Components<br />Site Selection and Characterization<br />Aggregate Evaluation of Management Alternatives<br />Det...
Approach: Multi-Agent Modeling<br />Model the behavior and actions agents (actors)<br />represents land management decisio...
Envision – Conceptual Structure<br />Multiagent Decision-making<br />Ecosystem Service Models<br />Generating Landscape Me...
ENVISION – Triad of Relationships<br />Goals<br />Actors<br />Policies<br />Values<br />Intentions<br /><ul><li>Economic S...
Ecosystem Services
Socio-cultural Services</li></ul>Provide a common frame of reference<br />for actors, policies and landscape productions<b...
Policy Definition<br />Landscape policies are decisions or plans of action for accomplishing desired outcomes.<br /> from:...
Policies in ENVISION<br />Policies are a decision or plan of action for accomplishing a desired outcome; they are a fundam...
Models in ENVISION<br />Models are “plug-ins” of two types:<br />Autonomous Processes:  Represent processes causing landsc...
Some Examples From Northwestern  US<br />
Some Examples From Northwestern  US<br />Puget Sound<br />Andrews <br />Forest<br />
Example 1.  Andrews Forest<br />MACK (580 ha)<br />WS08 (21 ha)<br />WS03 (101 ha)<br />HI15<br />WS02 (60 ha)<br />HJ And...
Envision Andrews Forest<br />195 km2<br />25 year simulation<br />Population growth:<br />~10,000<br />~18,500<br />
Envision Andrews Forest - Scenarios<br />
Data Sources<br />Evaluative Models<br />Landscape Data <br />Mean Age at Harvest<br />Policy Set(s)<br />Carbon Sequestra...
Landcover Over 25 Yrs<br />Conservation Scenario<br />Development Scenario<br />
Scenario Results – Forest Carbon<br />
Scenario Results – Forest Product Extraction<br />
Scenario Results – Fish IBI<br />
Example 2. Puget Sound<br />42,800 km2<br />60 year simulation<br />Population growth:<br />~4.2 million to<br />~7.0 mill...
Envision Puget Sound- Scenarios<br />Three Different Scenarios<br />
Envision Puget Sound<br />Data Sources<br />Evaluative Models<br />Landscape Data<br />Impervious Surfaces<br />Policy Set...
Puget Sound<br />
Seattle Area<br />
SeattleArea<br />Mt Rainier<br />
Lessons Learned<br />Alternative future assessments are fundamentally place-based and client-dependent:  Each application ...
Thanks to Dr. John Bolte<br />and the Envision Development Team<br />
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ENVISION Y El Modelamiento Del Paisaje - En Ingles

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ENVISION Y El Modelamiento Del Paisaje - En Ingles

  1. 1. www.2010colombia.com<br />
  2. 2. An Alternative Futures Approach to Understanding Landscape Dynamics and Services<br />Kellie Vache, PhD. Biological & Ecological Engineering Oregon State University<br />
  3. 3. Today’s Discussion<br />Overview of alternative futures approach to socio-ecological modeling<br />Description of one approach using Envision<br />Example applications<br />Andrews Forest<br />Puget Sound<br />
  4. 4. Socio-Ecological Modeling<br />
  5. 5. To Start - A Definition of Biocomplexity<br />Term used to describe complex structures, interactions, adaptive capabilities and dynamics<br />diverse set of biological and ecological systems <br />multiple spatial and temporal scales<br /><ul><li>Many Approaches!!! Some focusing on capturing richness of system dynamics, some on complex adaptive systems approaches
  6. 6. Challenge – How to make these operational?</li></li></ul><li>Alternative Futures Projects<br />Examine multiple scenarios of trends and assumptions about future conditions, generally using one or more models of change, <br />Assist in incorporating stakeholder interactions to define goals, constraints, trajectories, drivers, outcomes<br />Allow visualization of the results <br />Ultimately are intended to assist in improving land management decision-making<br />
  7. 7. Software-based Alternative Futures<br />A mechanism to include biocomplexity in alternative Futures – to do so requires:<br />Easy to use interface<br />Present results in a format useful to end users<br />Spatially and temporally explicit<br />Extensible to incorporate evolving “best” science<br />Internal feedback<br />
  8. 8. Envision Components<br />Site Selection and Characterization<br />Aggregate Evaluation of Management Alternatives<br />Detailed Evaluation of Individual Services<br />Alternative Scenario Selection<br />Analysis Framework and Architecture<br />Alternatives<br />Datasets<br /> Landscape Production Evaluators<br />Visualizations<br />Goals<br />Water Quality<br />Policies<br />Stressors<br />Carbon<br />…<br />Other ESE’s<br />Drivers<br />
  9. 9. Approach: Multi-Agent Modeling<br />Model the behavior and actions agents (actors)<br />represents land management decisions of actors with authority over parcels of land<br />Actor decisions implemented through policies that guide & constrain potential actions<br />Ecosystem Services (e.g. forest succession, wetland function) can be simultaneously modeled<br />
  10. 10. Envision – Conceptual Structure<br />Multiagent Decision-making<br />Ecosystem Service Models<br />Generating Landscape Metrics Reflecting Landscape Productions<br />LandscapeFeedbacks<br />Select policies and generate land management decision affecting landscape pattern<br />Actors<br /> Decision-makers managing the landscape by selecting policies responsive to their objectives<br />Landscape<br /> Spatial Container in which landscape changes, ES Metrics are depicted<br />Scenario<br />Definition<br />Policies<br /> Fundamental Descriptors of constraints and actions defining land use management decisionmaking<br />Autonomous Change Processes<br />Models of Non-anthropogenic Landscape Change<br />
  11. 11. ENVISION – Triad of Relationships<br />Goals<br />Actors<br />Policies<br />Values<br />Intentions<br /><ul><li>Economic Services
  12. 12. Ecosystem Services
  13. 13. Socio-cultural Services</li></ul>Provide a common frame of reference<br />for actors, policies and landscape productions<br />Landscapes<br />Service Metrics<br />
  14. 14. Policy Definition<br />Landscape policies are decisions or plans of action for accomplishing desired outcomes.<br /> from:<br />Lackey, R.T. 2006. Axioms of ecological policy. Fisheries. 31(6): 286-290. <br />
  15. 15. Policies in ENVISION<br />Policies are a decision or plan of action for accomplishing a desired outcome; they are a fundamental unit of computation in Envision<br />Describe actions available to actors<br />Primary Characteristics:<br />Applicable Site Attributes (Spatial Query)<br />Effectiveness of the Policy at addressing goals<br />Outcomes (possible multiple) associated with the selection and application of the Policy<br />Example: [Purchase conservations easement to allow revegetation of degraded riparian areas] in [areas with no built structures and high channel migration capacity] when [native fish habitat becomes scarce]<br />
  16. 16. Models in ENVISION<br />Models are “plug-ins” of two types:<br />Autonomous Processes: Represent processes causing landscape changes independent of human decision-making – e.g. climate change, vegetative succession, fire, flooding, ??? <br />Evaluative Models – Generate production statistics and report back how well the landscape is doing a producing metrics of interest – e.g. carbon sequestration, habitat production, land availability, ???<br />
  17. 17. Some Examples From Northwestern US<br />
  18. 18. Some Examples From Northwestern US<br />Puget Sound<br />Andrews <br />Forest<br />
  19. 19. Example 1. Andrews Forest<br />MACK (580 ha)<br />WS08 (21 ha)<br />WS03 (101 ha)<br />HI15<br />WS02 (60 ha)<br />HJ Andrews<br />(LOOK – 6200 ha)<br />PRIMET<br />WS10 <br />(10 ha)<br />WS09<br />(9 ha)<br />Photographed by Al Levno Date: 7/91 <br />
  20. 20. Envision Andrews Forest<br />195 km2<br />25 year simulation<br />Population growth:<br />~10,000<br />~18,500<br />
  21. 21. Envision Andrews Forest - Scenarios<br />
  22. 22. Data Sources<br />Evaluative Models<br />Landscape Data <br />Mean Age at Harvest<br />Policy Set(s)<br />Carbon Sequestration<br />Agent Descriptors<br />Forest Products Extraction<br />ENVISION<br />Autonomous Process<br />Models<br />Harvested Acreage<br />Rural Residential <br />Expansion<br />Fish Habitat (IBI)<br />Vegetative Succession<br />Resource Lands Protection<br />Climate Change<br />Envision Andrews Forest<br />
  23. 23. Landcover Over 25 Yrs<br />Conservation Scenario<br />Development Scenario<br />
  24. 24. Scenario Results – Forest Carbon<br />
  25. 25. Scenario Results – Forest Product Extraction<br />
  26. 26. Scenario Results – Fish IBI<br />
  27. 27. Example 2. Puget Sound<br />42,800 km2<br />60 year simulation<br />Population growth:<br />~4.2 million to<br />~7.0 million in 2060<br />
  28. 28. Envision Puget Sound- Scenarios<br />Three Different Scenarios<br />
  29. 29. Envision Puget Sound<br />Data Sources<br />Evaluative Models<br />Landscape Data<br />Impervious Surfaces<br />Policy Set(s)<br />Water Quality/Loading (SPARROW)<br />Agent Descriptors<br />Nearshore Habitat (Controlling Factors Model)<br />ENVISION<br />Autonomous Process<br />Models<br />INVEST Tier 1 Carbon<br />Rural/Urban Development<br />Resource Lands Protection<br />Expansion of Nearshore Modifications<br />Residential Land Supply<br />Population Growth<br />
  30. 30. Puget Sound<br />
  31. 31. Seattle Area<br />
  32. 32.
  33. 33.
  34. 34. SeattleArea<br />Mt Rainier<br />
  35. 35.
  36. 36. Lessons Learned<br />Alternative future assessments are fundamentally place-based and client-dependent: Each application is different.<br />Commonalities do exist and should be exploited within an extensible, adaptable DSS framework<br />Interactions between population growth, landscape development and ecosystem services drive socio-ecological systems, and need to be accommodated<br />Engagement with stakeholders is critical to define decision processes, desired outcomes endpoints<br />
  37. 37. Thanks to Dr. John Bolte<br />and the Envision Development Team<br />
  38. 38. Muchas Gracias!more info at:http://envision.bioe.orst.edu<br />
  39. 39. www.2010colombia.com<br />

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