Publications

Use of decision support systems (DSS) has thus far been framed as a social process of adoption or technical process of usability. We analyze the development of a DSS as a process of institutionalization of new as well as drift of existing practices. We write an Actor-Network-Theory (ANT) account, i.e. an interpretive study, that follows the traces left by both human and non-human actors (e.g. technology, methodologies, etc.) to understand how a DSS development project institutionalizes DSS technology in several forest management organizations in the German state of Rheinland Pfalz. The research has an innovative value since it uses ANT in the design of a DSS, hence affecting it, while commonly ANT has been used to understand why networks work or do not. Moreover, we use a new technology (PREZITM, www.prezi.com) for the visualization of the whole actor network coherent to the ANT methodology, i.e. ?keeping the social flat.? As a result, the development of the ANT account proposed in the present paper, even if still partial, supports the design of new technologies being introduced in current practice and generates an important learning effect thanks to the underpinning interpretative approach.Use of decision support systems (DSS) has thus far been framed as a social process of adoption or technical process of usability. We analyze the development of a DSS as a process of institutionalization of new as well as drift of existing practices. We write an Actor-Network-Theory (ANT) account, i.e. an interpretive study, that follows the traces left by both human and non-human actors (e.g. technology, methodologies, etc.) to understand how a DSS development project institutionalizes DSS technology in several forest management organizations in the German state of Rheinland Pfalz. The research has an innovative value since it uses ANT in the design of a DSS, hence affecting it, while commonly ANT has been used to understand why networks work or do not. Moreover, we use a new technology (PREZITM, www.prezi.com) for the visualization of the whole actor network coherent to the ANT methodology, i.e. ?keeping the social flat.? As a result, the development of the ANT account proposed in the present paper, even if still partial, supports the design of new technologies being introduced in current practice and generates an important learning effect thanks to the underpinning interpretative approach.

Combining stand simulation and forest-level optimization is an efficient way to study harvest scenarios of a forest area. A simulator first generates for each treatment unit a number of treatment schedules. Linear programming (LP) can then be used to study how stand-level schedules can be combined at the forest level with respect to alternative goals and constraints. The special structure of the obtained LP problems can be utilized using the generalized upper-bound technique which takes care of the so-called area constraints. JLP software was based on this technique. Later J software was developed to replace JLP. Now J is developed to deal with factory problems where the transportations costs and capacities of factories are included in the problem definition. The generalized upper-bound technique was modified to handle transportation constraints which tell that each timber unit produced is transported to some of the factories. The number of these constraints is very large. This paper describes the basic features of the algorithm and its implementation in the J software.Combining stand simulation and forest-level optimization is an efficient way to study harvest scenarios of a forest area. A simulator first generates for each treatment unit a number of treatment schedules. Linear programming (LP) can then be used to study how stand-level schedules can be combined at the forest level with respect to alternative goals and constraints. The special structure of the obtained LP problems can be utilized using the generalized upper-bound technique which takes care of the so-called area constraints. JLP software was based on this technique. Later J software was developed to replace JLP. Now J is developed to deal with factory problems where the transportations costs and capacities of factories are included in the problem definition. The generalized upper-bound technique was modified to handle transportation constraints which tell that each timber unit produced is transported to some of the factories. The number of these constraints is very large. This paper describes the basic features of the algorithm and its implementation in the J software.

This paper provides an integrated model for harvesting and logistic planning for tactical purposes over several years. The logistic planning includes both road upgrading and transportation between harvest areas and industries. The former is particularly important when dealing with problems when the accessibility of the road network is low due to, for example, thawing and heavy rains. The optimization model uses a detailed description of harvest areas including their spatial location, volume output of different assortment computations and net present value (NPV) for each year in the planning horizon. The model also uses a detailed description of the road network using the Swedish national road database. The model is very large and hard to solve, and hence, we are developing a solution approach based on an aggregation technique. An important part of the planning process is to select areas for the next 5 years, for example, and we analyze three different approaches. One approach is based on maximizing the NPV of the forest value, that is, the value at roadside. The second one is based on minimizing the logistic cost, and the third one combines NPV of the forest value at roadside and logistic. We analyze differences in a case study with over 6000 areas from the Swedish forest company Sveaskog. The results show that an integrated approach is necessary in order to avoid sub-optimal solutions.This paper provides an integrated model for harvesting and logistic planning for tactical purposes over several years. The logistic planning includes both road upgrading and transportation between harvest areas and industries. The former is particularly important when dealing with problems when the accessibility of the road network is low due to, for example, thawing and heavy rains. The optimization model uses a detailed description of harvest areas including their spatial location, volume output of different assortment computations and net present value (NPV) for each year in the planning horizon. The model also uses a detailed description of the road network using the Swedish national road database. The model is very large and hard to solve, and hence, we are developing a solution approach based on an aggregation technique. An important part of the planning process is to select areas for the next 5 years, for example, and we analyze three different approaches. One approach is based on maximizing the NPV of the forest value, that is, the value at roadside. The second one is based on minimizing the logistic cost, and the third one combines NPV of the forest value at roadside and logistic. We analyze differences in a case study with over 6000 areas from the Swedish forest company Sveaskog. The results show that an integrated approach is necessary in order to avoid sub-optimal solutions.

In this study, we propose a procedure for integrating several ecosystem services into forest management by using the well-known multi-criteria approach called goal programming. It shows how interactions with various stakeholders are essential in order to choose the goal programming model applied, as well as some of its basic components (variant, targets, preferential weights, etc.). This methodology has been applied to a real forest management case where five criteria have been selected: timber production, wild edible mushroom production, carbon sequestration, net present value of the underlying investment, and a criterion associated with the sustainability of forest management defined by the idea of a normal forest. Given the characteristics of some of these criteria, such as mushroom production, the model has been developed in two scenarios: one deterministic and another with a Monte Carlo analysis. The results show a considerable degree of conflict between the proposed criteria. By applying several goal programming models, different Paretian efficient solutions were obtained. In addition, some results in Monte Carlo analysis for several criteria show notable variations. This fact is especially notable for the mushroom production criterion. Finally, the proposed approach seems attractive and can be directly applied to other forest management situations.

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.