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Envisioning Skagit Alternative Futures

Envisioning Skagit Alternative Futures. John Bolte Biological and Ecological Engineering Department Oregon State University. Alternative Futures Projects. Examine multiple scenarios of trends and assumptions about future conditions, generally using one or more models of change,

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Envisioning Skagit Alternative Futures

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  1. Envisioning Skagit Alternative Futures John Bolte Biological and Ecological Engineering Department Oregon State University

  2. Alternative Futures Projects • Examine multiple scenarios of trends and assumptions about future conditions, generally using one or more models of change, • Assist in incorporating stakeholder interactions to define goals, constraints, trajectories, drivers, outcomes • Allow visualization of the results in a variety of types and formats • Ultimately are intended to assist in improving land management decision-making and informing choices

  3. An Approach to Projecting Alternative Future Landscapes • Based on modeling behavior and actions of individual land owners/land managers (actors) • Our approach: spatially explicit, represents land management decisions of those with authority over parcels of land • Actor decisions implemented through policies that guide & constrain potential actions • Autonomous processes (e.g. succession) simultaneously modeled

  4. Envision – Conceptual Structure Actors Decision-makers managing the landscape by selecting policies responsive to their objectives Landscape Production Models Generating Landscape Metrics Reflecting Ecosystem Service Productions LandscapeFeedbacks Landscape Spatial Container in which landscape changes, ES Metrics are depicted Multiagent Decision-making Select policies and generate land management decision affecting landscape pattern Scenario Definition LandscapeFeedbacks Policies Fundamental Descriptors of constraints and actions defining land use management decisionmaking Autonomous Change Processes Models of Non-anthropogenic Landscape Change

  5. ENVISION – Triad of Relationships Goals Actors Policies Values Intentions • Economic Services • Ecosystem Services • Socio-cultural Services Provide a common frame of reference for actors, policies and landscape productions Landscapes Metrics of Production

  6. Policy Definition Landscape policies are decisions or plans of action for accomplishing desired outcomes. from: Lackey, R.T. 2006. Axioms of ecological policy. Fisheries. 31(6): 286-290.

  7. Policies in ENVISION • Policies are a decision or plan of action for accomplishing a desired outcome; they are a fundamental unit of computation in Evoland • Describe actions available to actors • Primary Characteristics: • Applicable Site Attributes (Spatial Query) • Effectiveness of the Policy (determined by evaluative models) • Outcomes (possible multiple) associated with the selection and application of the Policy • 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]

  8. Models in ENVISION • Models are “plug-ins” of two types: • Autonomous Processes: Represent processes causing landscape changes independent of human decision-making – e.g. climate change, vegetative succession, forest growth, fire, flooding, ??? • 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, risk, ???

  9. Models in ENVISION • A well-defined, relatively simple, yet robust interface specification is defined for both Autonomous Processes and Evaluative Models. • Models can expose input and output variables • Models have full access to the underlying spatial representation, policy sets, exposed variables, actor representation, and spatial engine • Models can make changes to the underlying landscape representation • Envision automatically manages all exposed model data

  10. ENVISION FrameworkAndrews Application Data Sources Evaluative Models Parcels (IDU’s) Mean Age at Harvest Policy Set(s) Carbon Sequestration Agent Descriptors Forest Products Extraction ENVISION Autonomous Process Models Harvested Acreage Rural Residential Expansion Fish Habitat (IBI) Vegetative Succession Resource Lands Protection Climate Change

  11. Envision Andrews Study Area

  12. Envision Andrews - Scenarios Conservation - no Climate Change Development - no Climate Change Conservation - with Climate Change Development - with Climate Change

  13. Envision Demonstration

  14. Scenario Results – Forest Carbon

  15. Scenario Results – Forest Product Extraction

  16. Scenario Results – Fish IBI

  17. A possible approach for the Skagit Use a mixture of parcel-level data, land use/land cover, and zoning to establish decision units (IDU coverage) Develop sets of policy alternatives, focusing on those landscape areas of primary interest to the project, and addressing land management alternatives that represents a range of possible management approaches Define several scenarios reflecting 1) plan trend , and 2) scenarios addressing key stakeholder alternatives in terms of alternative policy sets Evaluate the resulting landscape trajectories with defensible models of key metrics relevant to stakeholder goals.

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