Decision Support Systems for Forest Biodiversity

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Decision Support Systems for Forest Biodiversity
NCSSF Project A10
Evaluation of Current Systems and Future Needs

• K. Norman Johnson
• Sean Gordon
• Oregon State University
• Oct. 14, 2003

http//ncseonline.org/NCSSF/DSS/
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Research Questions

• What problems and issues do decision support
  systems for forest biodiversity need to address?
• What decision support systems are available for
  forest biodiversity analysis?
• How well do they address problems and issues?
• What additional tools (or capabilities) are
  required to meet forest biodiversity management
  needs?

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Definitions DSS

• DSS are tools which
• are policy/management-oriented (decision)
• deal with complexity (support)
• have a clear, reproducible protocol (system)
• are computer-based
• Not
• HSIs alone
• research models
• forest certification standards
• informal expert systems (FEMAT)

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Definitions Biodiversity

• variety and variability among living organisms
  and the ecological complexes in which they
  occurnumber of different items and their
  relative frequency (OTA 1987)
• "Biodiversity is the totality of genes, species,
  and ecosystems in a region (UNEP 1992)
• Montreal Protocol Criterion 1
• ecosystems (1-5 coarse filter), species genetic
  (6-9 fine filter)
• composition, structure, and function (Franklin)

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Approach
ID most important biodiversity issues
Inventory of available DSS
Comparison Needs vs. Tools
Guidance for potential DSS users
Suggestions for future DSS development
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Results Priority Issues

• Nature of forest biodiversity problems
• Simple, complex, wicked
• Substance of forest biodiversity problems
• Characterizing biodiversity
• Influences on forest habitats
• Analytical methods

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Nature of Forest Biodiversity Problems
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Nature of Forest Biodiversity ProblemsPerspectiv
es on Forestry
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Nature of Forest Biodiversity Problems
Operational Measures

• Accommodate different kinds of perspectives
  information (biophysical, economic, social)
• Produce results for decision makers at multiple
  spatial scales(landowners to policymakers)
• Facilitate social negotiation and learning

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Substance of Forest Biodiversity
ProblemsAnalytical Methods Forest Influences

• Analytical Methods
• Risk assessment
• Trade-Offs (economic/ecological, species/species)
• Landscape Analysis
• Influences on Forest Habitats
• Silviculture timber harvest
• Biological (pests, pathogens, invasives)
• Fire
• Development
• Climate change

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Substance of Forest Biodiversity
ProblemsCharacterizing Biodiversity

• Montreal Process Criterion 1 Indicators
• Aggregate forest condition measures
• Area by forest type
• Area by forest age / successional stage
• Area by management class
• Fragmentation of forest types
• Species measures
• Diversity
• Viability
• Distribution
• Abundance

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Selection of Systems for Review

• Inventory identified 114 systems total
• Categorized screened by purpose
• FOR-BDV forest biodiversity DSS
• BDV biodiversity mgmt DSS
• FOR forest management DSS
• GEN general purpose DSS applied to forest
  biodiversity
• Other not reviewed
• 31 systems reviewed (screening additional 26)

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Substance of Forest Biodiversity
ProblemsCharacterizing Biodiversity
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Substance of Forest Biodiversity
ProblemsCharacterizing Biodiversity
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Substance of Forest Biodiversity
ProblemsCharacterizing Biodiversity
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Substance of Forest Biodiversity
ProblemsAnalysis Methods Forest Influences
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Substance of Forest Biodiversity
ProblemsAnalysis Methods Forest Influences
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Substance of Forest Biodiversity
ProblemsAnalysis Methods Forest Influences
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Nature of Forest Biodiversity ProblemsWicked
Problems
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Nature of Forest Biodiversity ProblemsWicked
Problems
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Nature of Forest Biodiversity ProblemsWicked
Problems
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Conclusions Given Substance of Problem

• Integration of forest biodiversity management
  DSS has potential to address majority of issues
• Sparse on biodiversity effects of climate,
  biologicals, fire
• Few options for small owners
• Diversity of approaches, but no widely accepted
  DSS for forest biodiversity

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Conclusions Given Nature of Problem

• Emergence of ecological as well as economic
  worldview
• DSS must accommodate fundamental assumptions of
  both
• Decisions no longer made by an elite group
• DSS must be understandable compelling to broad
  audiences
• No definitive solutions to wicked problems
• DSS should facilitate social learning (telling
  stories)

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Concluding Work

• Verification of results through developer user
  interviews
• Continue publishing results on project web site
• http//ncseonline.org/ncssf/dss/
• Add online tools to help users potential users
  choose appropriate DSS(web site search
  capabilities / DSS selection wizard)
• Final report