Logic‑based Evaluation of Forest Ecosystem Sustainability

1. Logic‑based Evaluation of Forest Ecosystem Sustainability Keith M. Reynolds, USDA Forest Service

2. Acknowledgments • USDA Forest Service Washington Office • National Forest System, Ecosystem Management • Pacific Northwest Research Station • Human and Natural Resource Interactions RD&A Program

3. Objectives • Illustrate the utility of a logic-based approach in designing a formal specification to evaluate the National criteria and indicators. • Highlight the roles of science and policy in this effort. • Illustrate the current national prototype.

4. Background • Knowledge bases and logic modeling • Analysis • Model design issues

5. Knowledge bases (logic model) • A formal logical representation of how to evaluate information • Networks of interrelated topics • Mental map • Executable

6. Knowledge bases: forms of uncertainty • Probabilistic uncertainty • Uncertainty of events • Linguistic uncertainty • Uncertainty about the definition of events • Vagueness or imprecision • A proposition is the smallest unit of thought to which one can assign a measure of strength of evidence

7. Knowledge bases: networks of networks = network Concern 1 Concern 2 Ecostate A Ecostate B Etc. Ecostate C Ecostate D Data link Data link Data link Data link Data link Data

8. Knowledge bases: evaluation Concern 1 Ecostate A Get data requirements Evaluate data Ecostate B Ecostate C Data link Data link Data link

9. Degrees of support Bivalent reasoning Yes Partial Yes No No Logic models: strength of evidence An example: slope is suitable for tractor logging.

10. Analysis: National C&I • The Montreal specifications provide relatively clear definitions of biophysical, socioeconomic, and framework attributes requiring evaluation (WGCICSMTBF 1995) ... • But, design of evaluation procedures that allow interpretation of the National C&I is one of the major technical issues that remain to be resolved (Raison et al. 2001).

11. Analysis: conceptual framework (Davis et al., 2001) • Specified conditions or outcomes to be sustained (the indicators). • A measure for each condition or outcome. • Calculation of the level of the indicator over some time period using the selected measure. • A frame of reference for gauging sustainability. • Methods for evaluating sustainability (sustainability check). • A monitoring program. • A formalism that supports requirements 1 to 6.

12. Analysis: logic models as design frameworks • Logic models (knowledge bases) provide a formal specification for organizing and interpreting information. • NetWeaver and logic • Problem represented in terms of propositions about topics of interest and their interdependencies. • Topics translated into propositions. • Lexical uncertainty.

13. Analysis: logic models as design frameworks (continued) • Need for transparency (Prabhu et al. 2001) • Models embody important policy decisions. • Models depend on value judgments and critical assumptions that need clear documentation. • Model development • Graphic representation is an effective basis for organizing discussion and for evolution of design. • Communication • Between scientists and policy makers. • With interested publics.

14. Design issues • Model organization • Options for synthesis • Weighting • Reference conditions • Qualitative measures • Uncertainties revisited

15. John Gordon, Yale Jerry Franklin, UW Norm Johnson, OSU Hal Salwasser, OSU Richard Haynes, PNW Darrel Kenops, R6 Gloria Brown, R6 Dick Phillips, R6 Sara Crim, R6 Jon Martin, R6 Denise Lach, OSU Gordie Reeves, PNW Peer review

16. Biophysical criteria PacificCoast Interiorwest Northeast South Evidence CarbonCycle Biodiversity ProductiveCapacity EcosystemHealth

17. Indicators 6-7 – Species Diversity Criterion 1 – Forest Biodiversity Evidence Indicator 8-9 – Genetic Diversity Indicators 1-5 – Ecosystem Diversity

18. Indicator 27 – Biomass Accumulation Rate Criterion 5 – Forest Carbon Evidence Indicator 26 – Total Biomass Indicator 28 – Product Storage

19. Socio-economic Indicators PacificCoast Interiorwest Northeast South Evidence Production capacity Employment Recreation Investment

20. Some final thoughts • Lexical uncertainty is an important issue in evaluation of many measurement endpoints. • Many aspects of evaluating sustainability cannot be answered by science alone. • Acquiring data on sustainability is necessary, but not sufficient, for setting policy or management evaluation. • Evaluating sustainability is not the same as defining desired future conditions. • Evaluating the state of sustainability and deciding how to respond are separate but interdependent decision processes. • The clearest, and most critical, role of science is in development of reference conditions.

21. The author • Keith M. Reynolds • USDA Forest Service • Pacific Northwest Research Station • Email: kreynolds@fs.fed.us • Website: www.institute.redlands.edu/emds • Phone: 541-750-7434