Forest management planning is a challenge due to the diverse criteria that need to be considered in the underlying decision-making process. This challenge becomes more complex in joint collaborative management areas (ZIF) because the decision now may involve numerous actors with diverse interests, preferences, and goals. In this research, we present an approach to identifying and quantifying the most relevant criteria that actors consider in a forest management planning process in a ZIF context, including quantifying the performance of seven alternative stand-level forest management models (FMM). Specifically, we developed a combined multicriteria decision analysis and group decision-making process by (a) building a cognitive map with the actors to identify the criteria and sub-criteria; (b) structuring the decision tree; (c) structuring a questionnaire to elicit the importance of criteria and sub-criteria in a pairwise comparison process, and to evaluate the FMM alternatives; and (d) applying a Delphi survey to gather actors’ preferences. We report results from an application to a case study area, ZIF of Vale do Sousa, in North-Western Portugal. Actors assigned the highest importance to the criteria income (56.8% of all actors) and risks (21.6% of all actors) and the lowest to cultural services (27.0% of all actors). Actors agreed on their preferences for the sub-criteria of income (diversification of income sources), risks (wildfires) and cultural services (leisure and recreation activities). However, there was a poor agreement among actors on the sub-criteria of the wood demand and biodiversity criteria. For 27.0% of all actors the FMM with the highest performance was the pedunculate oak and for 43.2% of all actors the eucalypt FMM was the least preferable alternative. The findings indicate that this approach can support ZIF managers in enhancing forest management planning by improving its utility for actors and facilitating its implementation.

As the need for more broad-scale solutions to environmental problems is increasingly recognized, traditional hierarchical, government-led models of coordination are being supplemented by or transformed into more collaborative inter-organizational networks (i.e., collaboratives, coalitions, partnerships). As diffuse networks, such regional environmental planning and design (REPD) efforts often face challenges in sharing and using spatial and other types of information. Recent advances in semantic knowledge management technologies, such as knowledge graphs, have the potential to address these challenges. In this paper, we first describe the information needs of three multi-stakeholder REPD initiatives in the western USA using a list of 80 need-to-know questions and concerns. The top needs expressed were for help in tracking the participants, institutions, and information products relevant to the REDP’s focus. To address these needs, we developed a prototype knowledge graph based on RDF and GeoSPARQL standards. This semantic approach provided a more flexible data structure than traditional relational databases and also functionality to query information across different providers; however, the lack of semantic data expertise, the complexity of existing software solutions, and limited online hosting options are significant barriers to adoption. These same barriers are more acute for geospatial data, which also faces the added challenge of maintaining and synchronizing both semantic and traditional geospatial datastores.

Spatial decision support systems for forest management have steadily evolved over the past 20+ years in order to better address the complexities of contemporary forest management issues such as the sustainability and resilience of ecosystems on forested landscapes. In this paper, we describe and illustrate new features of the Ecosystem Management Decision Support (EMDS) system that extend the system’s traditional support for landscape analysis and strategic planning to include a simple approach to feature-based tactical planning priorities. The study area for this work was the Chewaucan watershed of the Fremont-Winema National Forest, located in south-central Oregon, USA. The analysis of strategic priorities recommended five subwatersheds as being of high priority for restoration activities, based primarily on decision criteria related to the stream accessibility to headwaters and upland condition. Among high priority subwatersheds, the most common tactical action recommended was the removal of artificial barriers to fish passages. Other high priority tactical actions recommended in high priority subwatersheds to improve fish habitats were reducing the road density and restoring riparian vegetation. In the discussion, we conclude by describing how the simple tactical planning methods illustrated in this paper can be extended in EMDS to provide a more sophisticated hybrid approach to strategic and tactical planning that can evaluate alternative portfolios of designed management actions applied across landscapes. The latter planned improvement to decision support capabilities in EMDS encapsulates Carl Steinitz’s concept of geodesign.

This paper synthesizes vulnerability, risk, resilience, and sustainability (VRRS) in a way that can be used for decision evaluations about sustainable systems, whether such systems are called coupled natural–human systems, social–ecological systems, coupled human–environment systems, and/or hazards influencing global environmental change, all considered geospatial open systems. Evaluations of V-R-R-S as separate concepts for complex decision problems are important, but more insightful when synthesized for improving integrated decision priorities based on trade-offs of V-R-R-S objectives. A synthesis concept, called VRRSability, provides an overarching perspective that elucidates Tier 2 of a previously developed four-tier framework for organizing measurement-informed ontology and epistemology for sustainability information representation (MOESIR). The new synthesis deepens the MOESIR framework to address VRRSability information representation and clarifies the Tier 2 layer of abstraction. This VRRSability synthesis, composed of 13 components (several with sub-components), offers a controlled vocabulary as the basis of a conceptual framework for organizing workflow assessment and intervention strategies as part of geoinformation decision support software. Researchers, practitioners, and machine learning algorithms can use the vocabulary results for characterizing functional performance relationships between elements of geospatial open systems and the computing technology systems used for evaluating them within a context of complex sustainable systems.

Improving geo-information decision evaluation is an important part of geospatial decision support research, particularly when considering vulnerability, risk, resilience, and sustainability (V-R-R-S) of urban land–water systems (ULWSs). Previous research enumerated a collection of V-R-R-S conceptual component commonalties and differences resulting in a synthesis concept called VRRSability. As a single concept, VRRSability enhances our understanding of the relationships within and among V-R-R-S. This paper reports research that extends and deepens the VRRSability synthesis by elucidating relationships among the V-R-R-S concepts, and organizes them into a VRRSability conceptual framework meant to guide operationalization within decision support systems. The core relationship within the VRRSability framework is ‘functional performance’, which couples land and water concerns within complex ULWS. Using functional performance, we elucidate other significant conceptual relationships, e.g., scale, scenarios and social knowledge, among others. A narrative about the functional performance of green stormwater infrastructure as part of a ULWS offers a practical application of the conceptual framework. VRRSability decision evaluation trade-offs among land and water emerge through the narrative, particularly how land cover influences water flow, which in turn influences water quality. The discussion includes trade-offs along risk–resilience and vulnerability–sustainability dimensions as key aspects of functional performance. Conclusions include knowledge contributions about a VRRSability conceptual framework and the next steps for operationalization within decision support systems using artificial intelligence.