1. Keith Reynolds Pacific Northwest Research Station USDA Forest Service
EMDS a modeling framework for coping with complexity in environmental assessment and planning
Keith Reynolds
Pacific Northwest Research Station
USDA Forest Service

2. EMDS Consortium PNW Station University of Redlands, Redlands Institute
System design & project oversight
University of Redlands, Redlands Institute
ArcGIS implementation
Rules of Thumb, Inc.
NetWeaver logic engine
InfoHarvest, Inc.
Priority Analyst engine

3. Design objectives
Improve the efficiency with which landscape evaluation is conducted
Optimize use of information
Improve the quality of evaluation products
More comprehensive analysis
Better integration of diverse topics
Integrated support for planning
What’s the state? AND what to do about it? 2

4. Integrated evaluation and planning
Evaluation within scale
Concurrent evaluation of possibly numerous states and processes within a single analysis
Across scale
Explicit linkage of evaluations across spatial scales
Comparing evaluations over time
Across phases of adaptive management
Going from landscape evaluation to planning

5. Major EMDS applications
Ecological site classification, UK Forestry Commission
Timber suitability assessment, Tongass NF
Aquatic/Riparian Effectiveness Monitoring Program , USFS Region 6
Spotted owl dispersal habitat, WA DNR
North Coast Watershed Assessment, State of CA
Soil impacts associated with logging and wildfire, Okan-Wen NF
Integrated resource restoration and protection, USFS Region 1
Roads analysis for wildlife habitat, Tahoe NF
Wildland fuels, USFS WO and Regions, BLM, BIA, FWS, NPS
Managing critical loads associated with atmospheric S deposition in the southern Appalachians, US EPA
Integrated landscape restoration, Okanogan-Wenatchee NF
National Terrestrial Condition Assessment, USFS WO

6. Version 4.0 implementation
ArcGIS 10+ (Environmental Systems Research Institute)
ArcMap component
Web services coming in EMDS 5.0 (about October 2014)
Microsoft Windows XP, Vista, and Win7
Microsoft .Net
Major components
Project environment (core)
Logic engine (logic-based evaluation)
Hotlink tool (intuitive graphic explanation)
Data Influence and Priority Manager (priority of missing data)
Priority Analyst (priority setting in planning)

7. Development tools Logic modeling Decision modeling
NetWeaver Developer (Rules of Thumb)
Decision modeling
Criterium DecisionPlus (InfoHarvest)

8. NetWeaver logic engine
Evaluation of landscape condition.
The engine
supports design of logic specifications for the types of large, complex, and abstract problems typically posed by ecosystem management,
evaluates data against a model that provides a formal specification for interpretation of data, and
allows partial evaluations of ecosystem states and processes based on available information.
Ideal for use in landscape evaluation where data are often incomplete.

9. Logic models: forms of uncertainty
A form of meta database
A formal logical representation of how to evaluate information
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 truth (strength of evidence)
SE: a measure that quantifies the degree of support for a proposition provided by its premises

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

11. A logical discourse:

12. Map products Basic EMDS output is maps.
Symbology displays strength of evidence for a conclusion.
Beyond pretty maps…

13. Dealing with missing data
Data are treated as evidence.
Missing data are treated as lack of evidence.
Influence of missing information is very dynamic.
The logic engine evaluates the influence of missing information on the logical completeness of an analysis.
One component for determining priority of missing data.

14. Data Influence and Priorities
Data gaps are common in early stages of landscape evaluation.
The DIP assists with establishing priorities for obtaining missing data to improve the logical completeness of an analysis in the most efficient way.

15. Priority Analyst (PA)
PA is a Multi-Criteria Decision Analysis (MCDA) component
Ranks landscape elements, based on how well each rates against a set of decision criteria.
Uses output from the landscape evaluation and a decision model.
Rates landscape elements with respect to
their condition, AND
factors related to the feasibility and efficacy of management.

16. Priority analyst output
Aspatial output
Spatial output

17. Priority analyst diagnostics
In this example, a 13.4% change in the weight on the WS condition criterion would lead to a change in ordering of priorities.
How primary criteria in a decision model contribute to the total priority score for a watershed.

19. Fire Danger 4 FIREHARM event FIREHARM probabilistic FSim MaxEnt
Ensemble AND
Ensemble UNION
Ensemble OR
Fire danger 4

20. Fire Danger 4 with ensemble union
Fire Behavior
Ensemble UNION
Ignition Risk
Climate Influence
Fire Hazard

21. Decision model for fuel treatment
Decision criteria are the wildfire danger topics, threat to WUI, and biomass opportunity in a watershed.
Ensemble union,
structural variant 4

22. Priority scores from PA engine (CDP)
Highlighted region in histogram corresponds to selected watersheds in the map.
117 top-rated watersheds for fuel treatment priority (2.3%).

23. Linking multiple spatial scales
Basic approach: summarize information from one scale in a manner that makes the information applicable at another scale.
In general, some type of transformation of information is needed when moving information from one scale of evaluation to the next.

24. Adaptive, coherent planning (EMS, ISO 14001)
Revise
implementation
ID key questions
and data needs
Evaluation with
single model
Implement
selected alternative
Applies to initial condition, alternatives, and
plan performance.
Unified approach to evaluation adds coherence through institutional memory.
Generate
alternatives

25. Outputs versus outcomes
Change in performance standards of federal agencies
Old (outputs): acres treated per year
New (outcomes): acres of reduced fire danger per year
New planning rule and EMS
Adaptive management (ISO 14001)
Hypothesis testing
Shift in distribution of outcomes?

26. Contact information
Phone:
Website:
Wikipedia: