Keith Reynolds Pacific Northwest Research Station USDA Forest Service EMDS 4.0 a modeling framework for coping with complexity in environmental assessment and planning Keith Reynolds Pacific Northwest Research Station USDA Forest Service

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

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

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

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

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)

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

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.

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

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

A logical discourse:

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

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.

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.

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.

Priority analyst output Aspatial output Spatial output

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.

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

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

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

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%).

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.

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

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?

Contact information Phone: +01-541-750-7434 Email: kreynolds@fs.fed.us Website: http://www.spatial.redlands.edu/emds/ Wikipedia: http://en.wikipedia.org/wiki/Ecosystem_Management_Decision_Support