Publications

This study examines the potential of combining decision support approaches to identify optimal bundles of ecosystem services in a framework characterized by multiple decision-makers. A forested landscape, Zona de Intervenção Florestal of Paiva and Entre-Douro and Sousa (ZIF_VS) in Portugal, is used to test and demonstrate this potential. The landscape extends over 14,388 ha, representing 1976 stands. The property is fragmented into 376 holdings. The overall analysis was performed in three steps. First, we selected six alternative solutions (A to F) in a Pareto frontier generated by a multiple criteria method within a web-based decision support system (SADfLOR) for subsequent analysis. Next, an aspatial strategic multicriteria decision analysis (MCDA) was performed with the Criterium DecisionPlus (CDP) component of the Ecosystem Management Decision Support (EMDS) system to assess the aggregate performance of solutions A to F for the entire forested landscape with respect to their utility for delivery of ecosystem services. For the CDP analysis, SADfLOR data inputs were grouped into two sets of primary criteria: Wood Harvested and Other Ecosystem Services. Finally, a spatial logic-based assessment of solutions A to F for individual stands of the study area was performed with the NetWeaver component of EMDS. The NetWeaver model was structurally and computationally equivalent to the CDP model, but the key NetWeaver metric is a measure of the strength of evidence that solutions for specific stands were optimal for the unit. We conclude with a discussion of how the combination of decision support approaches encapsulated in the two systems could be further automated in order to rank several efficient solutions in a Pareto frontier and generate a consensual solution. 

The Ecosystem Management Decision Support (EMDS) system is an application framework for designing and implementing spatially enabled knowledge-based decision support systems for environmental analysis and planning at any geographic scale(s). The system integrates state-of-the-art geographic information system, as well as knowledge-based reasoning and decision modeling, technologies to provide decision support for the adaptive management process of ecosystem management. It integrates a logic engine to perform landscape evaluations, and a decision engine for developing management priorities. The logic component: (1) reasons about large, abstract, multi-faceted ecosystem management problems; (2) performs useful evaluations with incomplete information; (3) evaluates the influence of missing information, and (4) determines priorities for missing information. The planning component determines priorities for management activities, taking into account not only ecosystem condition, but also criteria that account for logistical concerns of potential management actions. Both components include intuitive diagnostic features that facilitate communicating modeling results to a broad audience. Features of the system design that have figured in its success over the past 20 years are highlighted, together with design features planned for the next several versions needed to provide spatial decision support for adaptive management under climate change.

The Ecosystem Management Decision Support (EMDS) system has been used by the US Department of Agriculture, Forest Service and Bureaus of the Department of the Interior since 2006 to evaluate wildfire potential across all administrative units in the continental US, and to establish priorities for allocating fuel-treatment budgets. This article discusses an EMDS fuels-treatment decision-support application, agency experiences with the application, and the extent to which it addressed concerns in Congress, and those of the General Accountability Office. EMDS aids the budget allocation process by providing a rational, transparent, and reproducible process that can be clearly communicated to Congressional staff and oversight personnel. However, practical application of this decision-support process was not without challenges, which included missing or suboptimal data, clearly articulated fuels management objectives, and improved understanding (via re-assessing decision logic from prior years) of trade-offs in decision-making

We evaluated changes (hereafter, departures) in spatial patterns of various patch types of forested landscapes in two subwatersheds ("east" and "west") in eastern Washington, USA, from the patterns of two sets of reference conditions; one representing the broad variability of pre-management era (~1900) conditions, and another representing the broad variability associated with one possible warming and drying climate-change scenario. We used a diagnostic set of class and landscape spatial pattern metrics to compare current spatial patterns of test subwatersheds against the two sets of reference conditions. In a companion decision support model built with the EMDS modeling system, we considered the degree of departure in the subwatersheds, relative to the two sets of reference conditions along with two additional criteria (vulnerability to severe wildfire and timber harvest opportunity), to determine the relative priority of landscape restoration treatments, and the potential for timber harvest to underwrite the treatments. In the decision support model, the current spatial pattern conditions of physiognomic types, cover types, forest structural classes, and those of late-successional and old forest patches of the two subwatersheds were compared against the two sets of reference conditions. The degree of departure in spatial patterns of physiognomic conditions was moderate in both subwatersheds in the pre-management era and climate-change comparisons. The situation was similar for the cover-type departure analysis, but spatial patterns of cover types increased in similarity to the reference conditions in the western subwatershed under the climate-change scenario. Spatial patterns of structural conditions showed a high degree of departure in both subwatersheds when compared to either set of reference conditions, but similarity improved in the eastern subwatershed under the climate-change scenario. Spatial patterns of late-successional + old forest structure were strongly similar to the broad envelope of conditions represented by the pre-management era reference in the western and moderately similar in the eastern subwatershed, but declined in both subwatersheds when compared with the climate-change reference conditions. When the degree of departure in spatial patterns of all patch types was considered along with vulnerability to severe wildfire and timber harvest opportunity, the eastern subwatershed rated higher priority for landscape improvement using either set of reference conditions. We conclude by considering uncertainties inherent in the analysis approach, types of sensitivity analysis needed to investigate model performance, and broad implications for forest managers. c 2008.

We present a decision support application that evaluates danger of severe wildland fire and prioritizes subwatersheds for vegetation and fuels treatment. We demonstrate the use of the system with an example from the Rocky Mountain region in the State of Utah; a planning area of 4.8 million ha encompassing 575 subwatersheds. In a logic model, we evaluate fire danger as a function of three primary topics: fire hazard, fire behavior, and ignition risk. Each primary topic has secondary topics under which data are evaluated. The logic model shows the state of each evaluated watershed with respect to fire danger. In a decision model, we place summarized fire danger conditions of each watershed in the context of the amount of associated wildland-urban interface (WUI). The logic and decision models are executed in EMDS, a decision support system that operates in ArcGIS. We show that a decision criterion such as relationship to WUI can significantly influence the outcome of a decision to determine treatment priorities. For example, we show that subwatersheds that were in the relatively poor condition with respect to fire hazard, behavior, and ignition risk may not be the best candidates for treatment. Additional logistical factors such as proximity to population centers, presence of endangered species, slope steepness, and road access all might be taken into account in selection of specific watersheds within a management area for treatment. Thus, the ecological status of each ecosystem can be placed in one or more social values contexts to further inform decision-making. The application can be readily expanded to support strategic planning at national and regional scales, and tactical planning at local scales

We present a decision support application that evaluates danger of severe wildland fire and prioritizes subwatersheds for vegetation and fuels treatment. We demonstrate the use of the system with an example from the Rocky Mountain region in the State of Utah; a planning area of 4.8 million ha encompassing 575 subwatersheds. In a logic model, we evaluate fire danger as a function of three primary topics: fire hazard, fire behavior, and ignition risk. Each primary topic has secondary topics under which data are evaluated. The logic model shows the state of each evaluated watershed with respect to fire danger. In a decision model, we place summarized fire danger conditions of each watershed in the context of the amount of associated wildland-urban interface (WUI). The logic and decision models are executed in EMDS, a decision support system that operates in ArcGIS. We show that a decision criterion such as relationship to WUI can significantly influence the outcome of a decision to determine treatment priorities. For example, we show that subwatersheds that were in the relatively poor condition with respect to fire hazard, behavior, and ignition risk may not be the best candidates for treatment. Additional logistical factors such as proximity to population centers, presence of endangered species, slope steepness, and road access all might be taken into account in selection of specific watersheds within a management area for treatment. Thus, the ecological status of each ecosystem can be placed in one or more social values contexts to further inform decision-making. The application can be readily expanded to support strategic planning at national and regional scales, and tactical planning at local scales

The historical patterns of Inland Northwest United States forests have been dramatically altered by a little more than two centuries of human settlement and land use. Spatial patterns of forest structural conditions, tree species composition, snags and down wood, and temporal variation in these patterns, have been altered to such an extent that the natural ebb and flow of terrestrial habitats and their linkages has been disrupted. Closely coupled with these changes, fire and other disturbance processes in most dry and many mesic forest types have also shifted, with a bias for increased severity and extent. Here, in the context of planning restoration of some semblance of historical vegetation pattern-disturbance process interactions, we briefly revisit why it is theoretically sound to estimate the range and variation in historical forest spatial patterns. We call these estimates of range and variation, reference conditions or reference variation (RV), and discuss how forest managers might use them when evaluating current landscape patterns to identify changes that may have important ecological implications. We term such evaluations, departure analyses, and we describe how departure analysis is implemented in a decision support system (DSS) for integrated landscape evaluation and restoration planning. The initial phase of the DSS uses logic-based modeling to evaluate existing patterns of forest vegetation in subwatersheds of one ecoregion against a corresponding envelope of historical reference conditions for the same region, thereby highlighting key departures. The secondary planning phase uses results from the analysis phase in a decision model to prioritize watersheds for possible management actions related to landscape restoration and maintenance. We conclude from our example that there are at least two advantages to a decision-support approach that treats evaluation and planning as distinct but integrated phases: (1) the overall decision process is rendered conceptually simpler and (2) practical considerations of efficacy and feasibility of management actions can be easily accommodated