Decision Support Systems for Forest Biodiversity

1. Decision Support Systems for Forest Biodiversity Evaluation of Current Systems and Future Needs K. Norman Johnson Sean Gordon Oregon State University

2. Project Questions • What types of decision support systems exist for use in sustainable forestry and biodiversity management? • How they are being applied? • How can existing tools could be adapted and applied elsewhere? • What additional tools (or capabilities) are required to meet forest management needs?

3. What are Decision Support Systems? • “… situations where human judgment is important but where limitations in human information processing impede decision making.” • “…bring together the intellectual flexibility and imagination of humans with the speed, accuracy, and tirelessness of the computer.” • Our definition – DSS help: • evaluate alternative decision options (decision) • deal with complexity (support) • have a clear, reproducible protocol (system)

4. What is Biodiversity? • …variety and variability among living organisms and the ecological complexes in which they occur…number 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)

5. Approach • “Top down” identification of priority needs for forest biodiversity decisions • review of literature and interviews with experts & decision makers • “Bottom-up” inventory of available systems • previous surveys, literature, interview system designers • Comparison • to what extent are existing DSS able to assist with priority needs? • Suggestions for improvement

6. Literature Review : Decision Needs Smythe, K.D.; Bernabo, J.C.; Carter, T.B.; Jutro, P.R. 1996. Focusing Biodiversity Research on the Needs of Decision Makers. Environmental Management 20(6): 865-872. • 100+ decision makers: government, environmental, industry • 5 types of decision areas • protection/ conservation, management, organizational authority and responsibility, siting, and laws and regulations. • 4 levels of decision making • operational, tactical, strategic, policy • 4 categories of info needed • (l) significance of biodiversity, (2) status and trends of biodiversity, (3) management for biodiversity, and (4) linkage of social and biological objectives.

7. Interviews with Forestry and Conservation Leaders • Tony Melchoirs, Weyerhaeuser • Rick Brown, Defenders of Wildlife • Dennis Grossman, Nature Serve • Jerry Franklin, Univ. of Washington • Sally Duncan, Consultant • Carlton Owen, Consultant • Barry Noon, Colorado State Univ.

8. Problems in Assessing Biodiversity from Literature and Interviews • Need for credible measures & tools for assessing biodiversity • Need for standardization in ways to characterize and assess biodiversity across a region (currently many different ways)

9. Major Forest Biodiversity Influences From Interviews and Literature • Development • Climate change • Invasive species • Uncharacteristic disturbance • Timber harvest

10. Typical Decisions that Involve Biodiversity Evaluations from Interviews and Literature • Recovery Plans, HCPs, and Safe Harbor Agreements • Conservation easements • Certification • Adoption of state forest practice laws • Federal and state plans • Private forest plans • Development choices • Restoration opportunities • Land exchanges

11. Important “Framing Issues” for Decisionsfrom Interviews and Literature • Consideration of the entire relevant landscape, such as whole watersheds for riparian issues • Consideration of short-term and long-term risk, especially relative to the relative risks of action and inaction

12. Important “Institutional Issues” from Interviews and Literature • Commitment to assess and organize information on biodiversity, set trigger points, identify cause-effect relationships • Trust among agencies responsible for biodiversity protection • Acceptance of, and ownership in, landscape-level (cross-ownership) evaluation tools • Existence of landscape-level institutions

13. Literature Review : DSS Mowrer, H.T. et al. 1997. Decision support systems for ecosystem management: an evaluation of existing systems. General Technical Report RM-GTR-296. Rauscher, H.M. 1999. Ecosystem management decision support for federal forests in the United States: a review. Forest Ecology and Management 114: 173-197. Johnson, P.; Lachman, B. 2001. Rapid scan of decision support system tools for land-use related decision making. Unpublished draft. Arlington, VA : NatureServe.

14. Some Conclusions from DSS Literature Review • Successful tool kits address the process of decision-making (social negotiation), rather than just putting information in front of decision-makers • Consideration of T&E species a common thread in decisions at different levels • At county level, rarely deal with individual species unless legally required • Federal forest planning focused on individual species, but tools lacking

15. Inventory of Systems86 systems in current inventory

16. Prioritization of Systems24 systems currently ranked priority 1-2

17. System Description Template • purpose, core outputs, major components • simulation, evaluation, optimization • capabilities for evaluating biodiversity concerns • coarse vs. fine filter approaches • examples of use • brief description + contact info • transferability • development status, cost, technical resources required • future development plans

18. System Description : NED Purpose • help managers develop goals, assess current and future conditions, and produce management plans for forests in the eastern United States Core Outputs • evaluation of goals, for any or all of five resources: visual quality, wildlife, water, wood production, and health

19. System Example : NED management options forest growth model (simulation) stand conditions habitat suitability indices (evaluation – fine filter)non-spatial other factors:visual quality, water, wood production, and general ecological objectives management goals (evaluation)

20. System Description : NED Major Components • NED/SIPS: stand inventory analysis, treatments, 4 integrated growth models • NEWILD: evaluates the habitat suitability of stand inventory • NED-Health: estimates effects of numerous insects and diseases, along with detrimental aspects of adverse weather, logging damage, animal grazing, and air pollution. • NED-1: evaluates how a management unit as a whole, or an individual stand, may provide conditions required for specific goals (aesthetics, ecology, forest health, timber, water and wildlife)

21. System Description : NED Capabilities for evaluating biodiversity concerns • Includes Habitat Suitability Indices for 338 New England vertebrate species • Fine filter approach • Analyst’s choice of which to include • Analyze existing or work towards desired habitat • Non-spatial • Species richness but not abundance or interaction • Coarse filter interaction between invasives/pathogens and biodiversity

22. System Description : NED Examples of use 1. Numerous (in hundreds) East Coast federal, state and private foresters use NED to prepare forest stewardship plans. 2. Mike Rauscher of the Forest Service (828-667-5261) has adapted and used it on private lands in South Carolina. 3. It is being used on Ft. Campbell's 70,000 acres (contact: Steve Forry 270-956-3376). 4. Maryland DNR is working to adapt and use NED to analyze different properties in terms of water quality, wildlife, recreation and biodiversity (contact: Rob Northrop 410-287-2918).

23. System Description : NED Transferability (development status, cost, technical resources required) • “Production” system prepared for use by others • Growth models operate with species and diameter • Wildlife, health, aesthetics require understory conditions and additional data beyond traditional, timber-oriented, forestry stand exams.

24. Ability of NED to address Montreal Process Criterion 1 indicators

25. Indicators 338 species Timeframe User determined Measure Habitat Suitability Index Reference optimum habitat conditions Sus. Check none Projection management & forest growth simulators Monitoring Other Evaluation Criteria? 7 Elements of sustainability (Davis, et. al. 2001)

26. System example: EMDS Ecosystem Management Decision Support is primarily designed to help users conduct ecological assessments. It provides a framework for users to integrate spatial information (using ArcGIS) with models of how to evaluate this information (using the Netweaver knowledge-base builder).

27. EMDS: Knowledge bases • A form of meta database • A formal logical representation of how to evaluate information • Networks of interrelated topics • Mental map • Advantages • Interactive, graphic design (modularity) • Numerous & diverse topics can be analyzed within a single integrated analysis

28. EMDS Applied to the Montreal C& I.

29. Willamette Basin Alternative Futures Analysis • Purpose: Help diverse stakeholders understand the ecological consequences of possible societal decisions related to changes in human populations and ecosystems in the Pacific Northwest. Simulates the effects of 3 possible development scenarios on regional measures of biodiversity over the next 50 years.

36. Interim Conclusions onSystem Capabilities • Diversity of approaches, but relatively few fully developed and accepted DSS for forest biodiversity • Many systems link a variety of independent components • Traditional systems (e.g. NED) fit well within our description template, but many do not • generic systems like EMDS • prototypical systems like Willamette Futures • Often difficult to evaluate transferability

37. DSS for Commercial Timber Supplies and Forest Biodiversity—A Comparison The 1970s—the golden age of DSS for commercial timber supplies. For this work, we had: • A widely-accepted, integrated mathematical theory of the decision problem • Agreement on a limited number of forest types of interest • Existence of quantitative models of growth and yield for most major forest types • General agreement among landowners/agencies about how to formulate the problem

38. DSS for Commercial Timber Supplies and Forest Biodiversity—A Comparison Is now the golden age for forest biodiversity DSS? • A widely-accepted, integrated mathematical theory of the decision problem? NO • Agreement on the major species of interest? NO • Published models of how species of interest react to changes in forest conditions? NO • General agreement among landowners/agencies about how to formulate the problem? NO

39. DSS for Commercial Timber Supplies and Forest Biodiversity—A Comparison • DSS for forest biodiversity often must develop all this information on the fly—theoretical model, species of interest, relation of species to habitat, agreement among affected parties • It should not be surprising that relatively few DSS exist for forest biodiversity or that they are often so difficult and expensive to create.

40. Interim Conclusions Comparison of Major Issues to DSS Capabilities • Most focus on timber harvest as the central issue • Some now allow consideration of the hazard of fuel build-up • Very few deal with pests, pathogens, climate change, or development (esp. effects on biodiversity)

41. What is a DSS? • Many important decisions include biodiversity evaluations not covered by the traditional computer-based definition • forest certification standards • Expert committee approaches (e.g. FEMAT) used in bioregional assessment and planning

42. Communication of Results • Report & presentation for NCSSF • Electronic distribution of report • Web-linked database of DSS (searchable by items in our template) • Publication in forestry and conservation journals

43. Questions for NCSSF Group • What uses might you have for decision support systems (DSS) to assist you with decisions that affect forest biodiversity? • If you haven’t used them much for this purpose, why not? 3. What would you need to know to help you select appropriate tools? a. What attributes of systems are likely to make them most useful? b. What aspects of DSS cause you to have reservations about their use? 4. How would biodiversity implications from these systems need to be expressed to make them comparable to other major factors that typically influence your decisions?