USDA Forest Service PNW Research Station USDA Forest Service PNW Research Station Logic ‑ based...

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


AcknowledgmentsAcknowledgments

USDA Forest Service Washington Office National Forest System, Ecosystem Management

Pacific Northwest Research Station Human and Natural Resource Interactions RD&A

Program


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.


BackgroundBackground

Knowledge bases and logic modeling Analysis Model design issues


Knowledge bases (logic model)Knowledge bases (logic model)

A formal logical representation of how to evaluate information

Networks of interrelated topics Mental map Executable


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


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


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).


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.


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.


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.


Design issuesDesign issues

Model organization Options for synthesis Weighting Reference conditions Qualitative measures Uncertainties revisited


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


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.


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

mailto:[email protected]

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