Publications

The potential for development in decision support for forest management is set by decision theory, available technology and methods. Demands for decision support are emerging from contemporary challenges and problems of forest management which act as stimuli for the science community. Objectives and approaches in forest management as well as technologies have been changing throughout history. Accordingly, the demand for tools to support planning and decision-making has evolved. In this contribution, the authors review the historic development of decision support systems (DSS) for forest management and discuss past, current and future drivers. Based on evidence from scientific literature, case studies in the frame of the Forest Management Decision Support Systems (FORSYS) action, as well as experiences of the authors some hypotheses about the future of DSS are drawn. It is shown that in the past, the drivers evolving from forest management as well as decision support technologies have influenced the way of how models and methods have been applied as well as how DSS architectures have been designed. It is concluded that in the future, the challenges for DSS development will increase, as the complexity of decision-making processes and the related models will compete with the user demands which ask for simplicity.

The design and implementation of the adaptive forest management (AFM) ToolBox is presented. Design principles derived from previous experiences in decision support system (DSS) development include support for (1) modularity, (2) accessibility via the Internet, (3) inclusion of different types of knowledge and information, (4) the use of different data sources, and (5) specific problem types. As major components of the AFM ToolBox DataBase, Vulnerability Assessment Tools (single user version, group mode) and an optimization tool to generate optimized management plans at the level of management units or landscapes are highlighted. A key feature is the distinction of two archetypical user profiles (manager, analyst). The AFM ToolBox is evaluated against eight criteria for the assessment of DSS. It is concluded that the ToolBox approach setting focus on modularity while avoiding to over-emphasis technical integration provides the right frame to secure the flexibility regarding tools and decision-making processes which is mandatory if a DSS should be taken up by practice.

Semantic wikis support collaboratively editing, categorising, interlinking and retrieving web pages for a group of experts working in a certain domain. The use of semantic technologies allows the expression of wiki content in a more structured way, which increases its potential use. This contribution presents an overview of the development process towards a semantic wiki related to a repository of forest decision support systems, including models, methods and data used, as well as case studies and lessons learned. An international group of experts took part in the conceptualisation of the semantic wiki (i.e. identification of wiki properties and forms), provided content and developed queries to analyse the information gathered. The resulting ForestDSS wiki gives an overview of the current use, development and application of forest decision support systems worldwide. Based on the experiences gathered during the process, some challenges are reported and conclusions on further developments are made.

Decision-making for multi-purpose forestry requires well-aligned public participation and stakeholder interaction. The operational research community has developed both the theory and practice of problem-structuring methods (PSMs) to help stakeholders determine a solvable joint problem perception. Problem structuring is typically conducted via facilitated modelling (group negotiation) in workshops. This review investigates problem-structuring activity within participatory forest planning over the period 2002-2011. A total of 32 research articles were studied and summarized. It was found that problem structuring is widely scattered in different continents, but most of the explicitly named PSMs arise from south-eastern Asia or Africa. Sophisticated problem structuring seems rather rare in forest planning, but some good examples bring evidence that encourages the use of facilitated modelling in participatory forest planning. Evoked activeness among stakeholders signals meaningful social learning, while improved knowledge exchange, anticipated 'sense of ownership' by stakeholders and commitment to the process were the main observed positive effects of problem structuring. However, problem structuring needs good facilitation as well as modelling and decision-analysis expertise. Attention must be paid to ensure participants' comprehension and to explicate the goals and rules of problem structuring with participants. © 2012 Elsevier B.V.

Aim of study: This review presents the state-of-art of using computerized techniques for problem structuring (PS) in participatory forest planning. Frequency and modes of using different computerized tool types and their contribution for planning processes as well as critical observations are described, followed by recommendations on how to better integrate PS with the use of forest decision support systems. Area of study: The reviewed research cases are from Asia, Europe, North-America, Africa and Australia. Material and methods: Via Scopus search and screening of abstracts, 32 research articles from years 2002-2011 were selected for review. Explicit and implicit evidence of using computerized tools for PS was recorded and assessed with content-driven qualitative analysis. Main results: GIS and forest-specific simulation tools were the most prevalent software types whereas cognitive modelling software and spreadsheet and calculation tools were less frequently used, followed by multi-criteria and interactive tools. The typical use type was to provide outputs of simulation-optimization or spatial analysis to negotiation situations or to compile summaries or illustrations afterwards; using software during group negotiation to foster interaction was observed only in a few cases. Research highlights: Expertise in both decision support systems and group learning is needed to better integrate PS and computerized decision analysis. From the knowledge management perspective, it is recommended to consider how the results of PS -e.g. conceptual models- could be stored into a problem perception database, and how PS and decision making could be streamlined by retrievals from such systems.

We introduce a Knowledge Transfer Portal (KTP) which supports knowledge transfer among researchers and forest managers. The KTP will be used for supporting transfer of knowledge generated in the FunDivEUROPE (FUNctional significance of forest bioDIVersity in EUROPE) after project life. It uses semantic web technologies to achieve a common understanding throughout a knowledge representation based on an expert elicitation process. Knowledge transfer tools (KTTs) take use of knowledge elements within the knowledge base and implement various knowledge transfer functionalities. The knowledge base shows interactions of biodiversity effects on the sustainable provision of ecosystem services. In this contribution we focus on the ongoing knowledge base engineering process and show first results that were based on a series of workshops with domain experts to generate a common understanding about terms, definitions and their relations. Relations were generated upon FunDivEUROPE project hypothesis with respect to project results and expert beliefs. We use a web-based, collaborative knowledge base engineering cycle and create a thesaurus which was initiated with terms from these expert workshops. Copyright ©2013 SCITEPRESS.

Aim of study: Knowledge Management (KM) tools facilitate the implementation of knowledge processes by identifying, creating, structuring, and sharing knowledge through use of information technology in order to improve decision-making. In this contribution, we review the way in which KM tools and techniques are used in forest management, and categorize a selected set of them according to their contribution to support decision makers in the phases of problem identification, problem modelling, and problem solving. Material and methods: Existing examples of cognitive mapping tools, web portals, workflow systems, best practices, and expert systems as well as intelligent agents are screened for their applicability and use in the context of decision support for sustainable forest management. Evidence from scientific literature and case studies is utilized to evaluate the contribution of the different KM tools to support problem identification, problem modelling, and problem solving. Main results: Intelligent agents, expert systems and cognitive maps support all phases of the forest planning process strongly. Web based tools have good potential to support participatory forest planning. Based on the needs of forest management decision support and the thus-far underutilized capabilities of KM tools it becomes evident that future decision analysis will have to consider the use of KM more intensively. Research highlights: As the problem-solving process is the vehicle for connecting both knowledge and decision making performance, the next generation of DSS will need to better encapsulate practices that enhance and promote knowledge management. Web based tools will substitute desktop applications by utilizing various model libraries on the internet.

Multi-objective forest planning is a multi-methodological endeavor whose success largely depends on how well the combined use of different methods contributes to the goals of the planning. This review assessed the benefits of mixing methods in natural resources planning. A sample of 30 peer-reviewed research articles was analyzed using an evaluation framework, designed based on democracy and planning theories, and participatory planning literature, including four dimensions: transparency, flexibility, consensus building, and operability. According to analyses, mixing different types (i.e. qualitative and quantitative) of methods generally yields greater benefits than the combination of similar methods. The subsample of 12 planning cases that utilized simulation-optimization software (SOS) appeared operable and moderately transparent, whereas flexibility and consensus building were often lacking. In comparison to the wide scholarly discussion on multi-methodology and mixing methods, it was observed that successful mixing examples in natural resource planning are still scarce and there are weaknesses in bridging the methods together. There is an evident need to pursue and to better communicate the benefits of mixing. Some good mixing examples utilizing SOS provided evidence that forest planning processes would make an excellent venue for studying the benefits and caveats of using mixed methods.Multi-objective forest planning is a multi-methodological endeavor whose success largely depends on how well the combined use of different methods contributes to the goals of the planning. This review assessed the benefits of mixing methods in natural resources planning. A sample of 30 peer-reviewed research articles was analyzed using an evaluation framework, designed based on democracy and planning theories, and participatory planning literature, including four dimensions: transparency, flexibility, consensus building, and operability. According to analyses, mixing different types (i.e. qualitative and quantitative) of methods generally yields greater benefits than the combination of similar methods. The subsample of 12 planning cases that utilized simulation-optimization software (SOS) appeared operable and moderately transparent, whereas flexibility and consensus building were often lacking. In comparison to the wide scholarly discussion on multi-methodology and mixing methods, it was observed that successful mixing examples in natural resource planning are still scarce and there are weaknesses in bridging the methods together. There is an evident need to pursue and to better communicate the benefits of mixing. Some good mixing examples utilizing SOS provided evidence that forest planning processes would make an excellent venue for studying the benefits and caveats of using mixed methods.

The forest planning system of large Swedish forest owners follows a three step procedure: long-term, medium-term, and short-term planning. The system is sequential and hierarchical in the sense that longer-term plans form the framework for shorter-term plans, and that top-level management prepares the long range plans and the lower management levels develop plans with successively shorter horizons. Studies indicate that this approach does not fully use existing knowledge within the organization. Problems associated with the top-down approach are also recognized in the general literature on organization and management. A proposal for a bottom-up approach is developed that aim at the use of local level knowledge to enhance accuracy and applicability of the forest plans. After top-level management has issued some fundamental planning directives, medium-term planning is conducted by the districts. Then the district plans are consolidated at the top-level for coordination and revision. A simulated planning process provides an illustration of the approach. The Heureka system is used here to optimize harvests and road costs with a mixed integer programming model of the problem, spanning 10 years with three seasons per year. The importance of detailed local knowledge to the outcome of planning is indicated, and needs for continued decision support systems development is discussed.The forest planning system of large Swedish forest owners follows a three step procedure: long-term, medium-term, and short-term planning. The system is sequential and hierarchical in the sense that longer-term plans form the framework for shorter-term plans, and that top-level management prepares the long range plans and the lower management levels develop plans with successively shorter horizons. Studies indicate that this approach does not fully use existing knowledge within the organization. Problems associated with the top-down approach are also recognized in the general literature on organization and management. A proposal for a bottom-up approach is developed that aim at the use of local level knowledge to enhance accuracy and applicability of the forest plans. After top-level management has issued some fundamental planning directives, medium-term planning is conducted by the districts. Then the district plans are consolidated at the top-level for coordination and revision. A simulated planning process provides an illustration of the approach. The Heureka system is used here to optimize harvests and road costs with a mixed integer programming model of the problem, spanning 10 years with three seasons per year. The importance of detailed local knowledge to the outcome of planning is indicated, and needs for continued decision support systems development is discussed.

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.