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Sustainability in the 1980’s

Applying Fuzzy Logic to Assess Social, Economic, and Ecological Sustainability A Quantitative Approach Applied to the Tongass National Forest.

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Sustainability in the 1980’s

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  1. Applying Fuzzy Logic to AssessSocial, Economic, and Ecological SustainabilityA Quantitative Approach Applied to theTongass National Forest

  2. Title #2:Using Knowledge Base Architecture to Assess the Complexities of FMU SustainabilityA Quantitative Approach Applied to theTongass National Forest

  3. Sustainability in the 1980’s • Harvest <= Growth, NDY, LTSY, PNV • FORPLAN (LP) used to calculate Allowable Sale Quantities (ASQ) • ASQ was often a target, not a ceiling • Huge models on huge machines • No one could question the results • Difficult to analyze non-market resources

  4. 1990s • Clinton, environmental movement, politics • Recreation/tourism Use Explosion • Tongass Revision underway, Involvement of Science • Pulp Mills Close, Final Tongass Plan • GIS, Internal Demands for Accountability • Demands for Ecosystem Sustainability • Santiago Agreement, Montreal, Certification

  5. Bruntland Commission Report Defined sustainability as: ”the management of the human use of the biosphere so that it may yield the greatest sustainable benefit to present generations while maintaining the potential to meet the needs and aspirations of future generations.”

  6. Our take on Sustainability • 3 Equal Principles: Ecological, Economic, and Social • Based on Montreal Process Criteria and Indicators (a systems approach) • Evaluate at the Forest Management Unit (a very significant element) • We would go the distance (all the way to reference values)

  7. Criteria and Indicators • Principle – Ecological Sustainability, etc. (3-7) • Criteria – Maintain old growth dependent bird habitat (4-20) • Indicator – Average number of snags per harvested acre (1-many) • Measure (data) – Total snags/Total harvested acres • Reference Value – > 3 snags per acre is OK

  8. Bruntland Commission Market Forces Santiago Declaration National/International Reporting Initiatives Forest Management Unit Initiatives Certification Initiatives FSC, AFPA, Smartwood, SCS Montreal Process Helsinki Accord CIFOR National Scale C&I Set National Scale C&I Set Regional FMU Tests e.g., CIFOR-NA (Boise) Various Forest and Product Certification LUCID Sustainable Forest Monitoring Initiatives

  9. Bruntland Commission Market Forces Santiago Declaration National/International Reporting Initiatives Forest Management Unit Initiatives Certification Initiatives FSC, AFPA, Smartwood, SCS Montreal Process Helsinki Accord CIFOR National Scale C&I Set National Scale C&I Set Regional FMU Tests e.g., CIFOR-NA (Boise) Various Forest and Product Certification Tongass Sustainable Forest Monitoring Initiatives Field-level Realities

  10. Foundations of the C&I Approach • Despite geographic differences, efforts should be made to harmonize indicator measures and reporting. • The time dimension of indicators must be considered. Trends are essential in evaluating the status of ecosystem sustainability. • An acceptance of using qualitative and subjective measures for indicators. • Select indicators to build common understanding of what is meant by ecosystem sustainability.

  11. Foundations Simplified • Portable • Repeatable • Deal with Fuzziness • Sensible

  12. Our Approach • 3 Principles of Equal Weight: Ecological, Social, and Economic • Fuzzy Logic to deal with uncertainty, expert opinion, and traditional ecological knowledge • Spatially display results • Clear definitions backed by documented assumptions and references • No more smoke and mirrors

  13. The Fuzzy Logic Concept 1 Adult-ness (DM) 0 21 Age (Years)

  14. 1 Adult-ness (DM) 0 -1 21 Age (Years) Pseudo-Fuzzy Logic (redefined fuzzy parameters)

  15. Key Terms • Boolean vs. Fuzzy Logic • Knowledge Base • Inference Engine

  16. Technical Aspects • Easy to build a Netweaver Knowledge Base (KB) • KB’s are very portable • Use of Linguistic Variables • Incorporation of Risk and Uncertainty • Copes with Missing Data • Degree of Membership (DM) is not Probability

  17. 1)Legislatively removed: Boolean (YorN), no change 2)Forested: Boolean (YorN), no change 3)Regen/volume: Boolean (YorN), no change 1 -1 Tentatively Suitable Land Process Identification of Lands Suitable for Timber Harvest – This process is required in old and new regulations (219.28) Six attributes to evaluate: 4)Slope: Fuzzify 5)Site Index: Fuzzify 6)MM Haz: Fuzzify 1 1 -1 -1 35 72 35 40 60 2 4

  18. The Tongass Sustainability Model

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