Logic-based Evaluation of Forest Logic-based Evaluation of Forest - - PowerPoint PPT Presentation

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Logic-based Evaluation of Forest Ecosystem Sustainability Logic-based Evaluation of Forest Ecosystem Sustainability

Keith M. Reynolds, USDA Forest Service Keith M. Reynolds, USDA Forest Service Sean N. Gordon, USDA Forest Service Sean N. Gordon, USDA Forest Service

• K. Norman Johnson, Oregon State University
• K. Norman Johnson, Oregon State University

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Logic models Logic models

• A form of meta database

A form of meta database

• A formal logical representation of how to evaluate

A formal logical representation of how to evaluate information information

• Networks of interrelated topics

Networks of interrelated topics

• Mental map

Mental map

• Executable specification

Executable specification

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Forms of uncertainty Forms of uncertainty

• Probabilistic uncertainty

Probabilistic uncertainty

• Uncertainty of events

Uncertainty of events

• Linguistic uncertainty

Linguistic uncertainty

• Uncertainty about the definition of events

Uncertainty about the definition of events

• Vagueness or imprecision

Vagueness or imprecision

• A proposition is the smallest unit of thought to which

A proposition is the smallest unit of thought to which

• ne can assign a measure of strength of evidence
• ne can assign a measure of strength of evidence

Logic networks Logic networks

Concern 1

Ecostate A Ecostate B Ecostate C Ecostate D Data link Data link Data link Data link Data link

= topic Concern 2

Etc.

Data

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Logic topics Logic topics

• Each topic evaluates a proposition

Each topic evaluates a proposition

• Attributes of a topic

Attributes of a topic

• Name (e.g., biodiversity)

Name (e.g., biodiversity)

• Proposition (e.g., biodiversity is being maintained)

Proposition (e.g., biodiversity is being maintained)

• Strength of evidence for the proposition

Strength of evidence for the proposition

• A formal logic specification (e.g., a proof)

A formal logic specification (e.g., a proof)

• Documentation

Documentation

• Explanation, source, citations, assumptions

Explanation, source, citations, assumptions

Logic processing Logic processing

Concern 1

Ecostate A Ecostate B Ecostate C Data link Data link Data link

Get data requirements Evaluate data

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Strength of evidence Strength of evidence

An example: slope is suitable for tractor logging. An example: slope is suitable for tractor logging.

0.2 0.4 0.6 0.8 1 15 20 25 30 35 Percent slope Strength of evidence

Bivalent reasoning Bivalent reasoning

Yes No

0.2 0.4 0.6 0.8 1 15 20 25 30 35 Percent slope Strength of evidence

Degrees of support Degrees of support

Yes No Partial

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Evaluation of national C&I Evaluation of national C&I

• The Montreal specifications provide relatively

The Montreal specifications provide relatively clear definitions of biophysical, socioeconomic, clear definitions of biophysical, socioeconomic, and framework attributes requiring evaluation and framework attributes requiring evaluation (WGCICSMTBF 1995) ... (WGCICSMTBF 1995) ...

• But, design of evaluation procedures that allow

But, design of evaluation procedures that allow interpretation of the National C&I is one of the interpretation of the National C&I is one of the major technical issues that remain to be resolved major technical issues that remain to be resolved (Raison et al. 2001). (Raison et al. 2001).

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Conceptual framework (Davis et al., 2001) Conceptual framework (Davis et al., 2001)

1.

• 1. Specified conditions or outcomes to be sustained (the

Specified conditions or outcomes to be sustained (the indicators). indicators). 2.

• 2. A measure for each condition or outcome.

A measure for each condition or outcome. 3.

• 3. Calculation of the level of the indicator over some time

Calculation of the level of the indicator over some time period using the selected measure. period using the selected measure. 4.

• 4. A frame of reference for gauging sustainability.

A frame of reference for gauging sustainability. 5.

• 5. Methods for evaluating sustainability (sustainability

Methods for evaluating sustainability (sustainability check). check). 6.

• 6. A monitoring program.

A monitoring program. 7.

• 7. A formalism that supports requirements 1 to 6.

A formalism that supports requirements 1 to 6.

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Logic models as design frameworks Logic models as design frameworks

• Logic models (knowledge bases) provide a formal

Logic models (knowledge bases) provide a formal specification for organizing and interpreting specification for organizing and interpreting information information. .

• Problem represented in terms of propositions

Problem represented in terms of propositions about topics of interest and their about topics of interest and their interdependencies. interdependencies.

• Topics translated into propositions.

Topics translated into propositions.

• Lexical uncertainty.

Lexical uncertainty.

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Logic models as design frameworks (continued) Logic models as design frameworks (continued)

• Need for transparency (

Need for transparency (Prabhu Prabhu et al. 2001) et al. 2001)

• Models embody important policy decisions.

Models embody important policy decisions.

• Models depend on value judgments and critical

Models depend on value judgments and critical assumptions that need clear documentation. assumptions that need clear documentation.

• Explanation

Explanation

• Graphic representation is an effective basis for

Graphic representation is an effective basis for

• rganizing discussion and for evolution of design.
• rganizing discussion and for evolution of design.
• Communication between scientists and policy makers.

Communication between scientists and policy makers.

• Communication with interested publics.

Communication with interested publics.

Forest sustainability AND Biophysical criteria Socioeconomic criterion Framework criterion Biodiversity Production capacity Ecosystem health Conservation Carbon cycle AND AND Production Recreation Investment Culture Employment AND Institutional Economic Monitoring capacity Legal R&D capacity 1 2 3 4 5 6 7

Design issues: model organization Design issues: model organization

Basic organization Basic organization

• f topics.
• f topics.

For example, For example, evaluation of evaluation of criteria in the criteria in the current prototype. current prototype.

Forest sustainability AND Socioeconomic criterion Framework criterion Biodiversity Production capacity Ecosystem health Conservation Carbon cycle AND Production Recreation Investment Culture Employment AND Institutional Economic Monitoring capacity Legal R&D capacity 1 2 3 4 5 6 7

Design issues: model organization Design issues: model organization

An alternative An alternative

• rganization with
• rganization with

very different very different emphasis on emphasis on criteria. criteria.

Ecosystem diversity Indicators 6 & 7 Species diversity Indicator 8 Genetic diversity SUM Indicator 2 Stage Indicator 3 Reserves Indicator 4 Admin withdrawn Indicator 5 Fragmentation Ecosystem diversity calc [-4, 4] Biodiversity AND 1

Design issues: synthesis Design issues: synthesis

• AND operator: arguments evaluated as limiting

AND operator: arguments evaluated as limiting factors. factors.

• SUM operator: arguments contribute

SUM operator: arguments contribute incrementally to evaluation and can compensate. incrementally to evaluation and can compensate.

SUM Indicator 44 Employment rate Indicator 45 Wage rate Indicator 45 Injury rate OR Indicator 46

• Comm. viability

Indicator 46 Comm.adaptability Indicator 47 Subsistence area AND Indicator 44 Employment rate Wood value Wood volume Indicator 13 Harvest volume Standing volume Employment calc Employment [-5, 6]

Design issues: synthesis Design issues: synthesis

Another example, including the OR operator. Another example, including the OR operator.

0.00 0.04 0.08 0.12 0.16 20 40 60 80 100 Old growth cover (percent) Probability 0.00 0.50 1.00 1.50 2.00 Evidence Probability Evidence 15 35 60 80

Design issues: reference conditions Design issues: reference conditions

• Each elementary

Each elementary network evaluates a network evaluates a measurement measurement endpoint against endpoint against reference reference conditions. conditions.

• Lack of reference

Lack of reference conditions is a basic conditions is a basic problem for many problem for many measurement measurement endpoints. endpoints.

SUM Indicator 48 Property calc SUM Indicator 49 Planning calc Indicator 50 Public partic. calc Indicator 52 Conservation calc SUM SUM SUM Indicator 51 Best practices Property rights Land tenure Traditional rights Dispute resolution Forest planning Policy review Planning and review coordination Policy formulation Decision making Access to information Special environ. values Cultural values Social values Scientific values Legal Legal calc [-30, 30] SOR Alternative legal calc [0, 4] Legal summary: None Weak Unknown Moderate Strong 0.25 0.75 1 0.5

Design issues: qualitative measures Design issues: qualitative measures

Outcomes evaluated on an ordinal scale. Outcomes evaluated on an ordinal scale.

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Design issues: reliability of data Design issues: reliability of data

• Reliability of data for evaluation of National C&I.

Reliability of data for evaluation of National C&I.

• Stochastic, rather than lexical, uncertainty

Stochastic, rather than lexical, uncertainty

• Formal representation of stochastic uncertainty is

Formal representation of stochastic uncertainty is problematic in the context of a logic model. problematic in the context of a logic model.

• Not addressed in the current Montreal C&I prototype.

Not addressed in the current Montreal C&I prototype.

• Possible solution

Possible solution

• Adjusting network weights with a normalized metric

Adjusting network weights with a normalized metric such as standard error of the mean. such as standard error of the mean.

• Problems: availability, unknown error correlations

Problems: availability, unknown error correlations

SUM Indicator 48 Property calc SUM Indicator 49 Planning calc Indicator 50 Public partic. calc Indicator 52 Conservation calc SUM SUM SUM Indicator 51 Best practices Property rights Land tenure Traditional rights Dispute resolution Forest planning Policy review Planning and review coordination Policy formulation Decision making Access to information Special environ. values Cultural values Social values Scientific values Legal Legal calc [-30, 30] SOR Alternative legal calc [0, 4] Legal summary: None Weak Unknown Moderate Strong 0.25 0.75 1 0.5

Sequential OR Sequential OR (SOR) to (SOR) to specify specify multiple multiple alternative alternative pathways in pathways in

• rder of
• rder of

preference. preference.

Design issues: precision of knowledge Design issues: precision of knowledge

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Peer review Peer review

• John Gordon, Yale

John Gordon, Yale

• Jerry Franklin, UW

Jerry Franklin, UW

• Norm Johnson, OSU

Norm Johnson, OSU

• Hal

Hal Salwasser Salwasser, OSU , OSU

• Richard Haynes, PNW

Richard Haynes, PNW

• Darrel

Darrel Kenops Kenops, R6 , R6

• Gloria Brown, R6

Gloria Brown, R6

• Dick Phillips, R6

Dick Phillips, R6

• Sara

Sara Crim Crim, R6 , R6

• Jon Martin, R6

Jon Martin, R6

• Denise

Denise Lach Lach, OSU , OSU

• Gordie

Gordie Reeves, PNW Reeves, PNW

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Criterion 5. Maintenance of forest contribution to global carbon cycles Criterion 5. Maintenance of forest contribution to global carbon cycles

• Criterion 5 includes three indicators:

Criterion 5 includes three indicators:

• Total forest ecosystem biomass and carbon pool.

Total forest ecosystem biomass and carbon pool.

• Contribution of forest ecosystems to the total global

Contribution of forest ecosystems to the total global carbon budget, including absorption and release of carbon budget, including absorption and release of carbon (standing biomass, coarse woody debris, peat carbon (standing biomass, coarse woody debris, peat and soil carbon). and soil carbon).

• Contribution of forest products to the global carbon

Contribution of forest products to the global carbon budget. budget.

Biophysical criteria

Pacific Coast Interior west Northeast South Carbon Cycle Biodiversity Productive Capacity Ecosystem Health

Evidence

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

Evidence

Criterion 1 – Forest Biodiversity Criterion 1 – Forest Biodiversity

0.51 0.45 0.64 0.43 West 0.56 0.42 0.86 0.40 Inter-Mtn West 0.46 0.42 0.59 0.38 East 0.41 0.53 0.36 0.34 South

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

Evidence

Socio-economic Indicators

Pacific Coast Interior west Northeast South Production capacity Recreation Investment Employment

Evidence

Criterion 5 – Forest Carbon Criterion 5 – Forest Carbon

0.24 0.71 West 0.67 1.0 1.0 Inter-Mtn West 0.33 1.0 East 0.60 .80 1.0 South

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Some observations Some observations

1.

• 1. Lexical uncertainty is an important issue in evaluation of many

Lexical uncertainty is an important issue in evaluation of many measurement endpoints. measurement endpoints. 2.

• 2. Many aspects of evaluating sustainability cannot be answered

Many aspects of evaluating sustainability cannot be answered by science alone by science alone. . 3.

• 3. Acquiring data on sustainability is necessary, but not sufficien

Acquiring data on sustainability is necessary, but not sufficient, t, for setting policy or management evaluation for setting policy or management evaluation. . 4.

• 4. Evaluating sustainability is not the same as defining desired

Evaluating sustainability is not the same as defining desired future conditions. future conditions. 5.

• 5. Evaluating the state of sustainability and deciding how to

Evaluating the state of sustainability and deciding how to respond are separate but interdependent decision processes. respond are separate but interdependent decision processes. 6.

• 6. The clearest, and most critical, role of science is in

The clearest, and most critical, role of science is in development of reference conditions. development of reference conditions.

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The author The author

• Keith M. Reynolds

Keith M. Reynolds

• USDA Forest Service

USDA Forest Service

• Pacific Northwest Research Station

Pacific Northwest Research Station

• Email:

Email: kreynolds@fs.fed.us kreynolds@fs.fed.us

• Website:

Website: www.institute.redlands.edu/emds www.institute.redlands.edu/emds

• Phone: 541

Phone: 541-

• 750

750-

• 7434

7434