USDA Forest Service PNW Research Station
Logic‑based Evaluation of Forest Ecosystem Sustainability Logic‑based Evaluation of Forest Ecosystem Sustainability
Keith M. Reynolds, USDA Forest Service
USDA Forest Service PNW Research Station
AcknowledgmentsAcknowledgments
USDA Forest Service Washington Office National Forest System, Ecosystem Management
Pacific Northwest Research Station Human and Natural Resource Interactions RD&A
Program
USDA Forest Service PNW Research Station
ObjectivesObjectives
1. Illustrate the utility of a logic-based approach in designing a formal specification to evaluate the National criteria and indicators.
2. Highlight the roles of science and policy in this effort.
3. Illustrate the current national prototype.
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BackgroundBackground
Knowledge bases and logic modeling Analysis Model design issues
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Knowledge bases (logic model)Knowledge bases (logic model)
A formal logical representation of how to evaluate information
Networks of interrelated topics Mental map Executable
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Knowledge bases: forms of uncertaintyKnowledge 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
Knowledge bases: networks of networksKnowledge bases: networks of networks
Concern 1
Ecostate A Ecostate B
Ecostate C Ecostate D Data link Data link
Data link Data linkData link
= networkConcern 2
Etc.
Data
Knowledge bases: evaluationKnowledge bases: evaluation
Concern 1
Ecostate A
Ecostate B Ecostate C
Data link Data linkData link
Get
dat
a re
quir
emen
ts
Eva
luat
e da
ta
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Logic models: strength of evidenceLogic models: strength of evidence
An example: slope is suitable for tractor logging.
0
0.2
0.4
0.6
0.8
1
15 20 25 30 35
Percent slopeS
tre
ng
th o
f e
vid
en
ce
Bivalent reasoning
Yes No
0
0.2
0.4
0.6
0.8
1
15 20 25 30 35
Percent slope
Str
en
gth
of
ev
ide
nc
e
Degrees of support
Yes
No
Partial
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Analysis: National C&IAnalysis: 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).
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Analysis: conceptual framework (Davis et al., 2001)Analysis: conceptual framework (Davis et al., 2001)
1. Specified conditions or outcomes to be sustained (the indicators).
2. A measure for each condition or outcome.3. Calculation of the level of the indicator over some time
period using the selected measure.4. A frame of reference for gauging sustainability. 5. Methods for evaluating sustainability (sustainability
check).6. A monitoring program. 7. A formalism that supports requirements 1 to 6.
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Analysis: logic models as design frameworksAnalysis: 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.
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Analysis: logic models as design frameworks (continued)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.
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Design issuesDesign issues
Model organization Options for synthesis Weighting Reference conditions Qualitative measures Uncertainties revisited
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Peer reviewPeer review
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
Biophysical criteriaPacificCoast
Interiorwest
Northeast
South
CarbonCycle
Biodiversity
ProductiveCapacity
EcosystemHealth
Evidence
Criterion 1 – Forest Biodiversity
Indicators 1-5 – Ecosystem Diversity
Indicators 6-7 – Species Diversity
Indicator 8-9 – Genetic Diversity
Evidence
Criterion 5 – Forest Carbon
Indicator 26 – Total Biomass
Indicator 27 – Biomass Accumulation Rate
Indicator 28 – Product Storage
Evidence
Socio-economic Indicators
PacificCoast
Interiorwest Northeast
South
Production capacity
Recreation Investment
Employment
Evidence
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Some final thoughtsSome final thoughts
1. Lexical uncertainty is an important issue in evaluation of many measurement endpoints.
2. Many aspects of evaluating sustainability cannot be answered by science alone.
3. Acquiring data on sustainability is necessary, but not sufficient, for setting policy or management evaluation.
4. Evaluating sustainability is not the same as defining desired future conditions.
5. Evaluating the state of sustainability and deciding how to respond are separate but interdependent decision processes.
6. The clearest, and most critical, role of science is in development of reference conditions.
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The authorThe author
Keith M. Reynolds USDA Forest Service Pacific Northwest Research Station Email: [email protected] Website: www.institute.redlands.edu/emds Phone: 541-750-7434