Publications

Climate change has altered and further will change the environmental conditions for many sectors. Whereas annual cropping systems can be adapted yearly, decisions in forest management usually have long-lasting effects. Depending on the region and tree species rotation periods range between 80 and 180 years in Central Europe. Therefore, todays tree species selection should also take into account the impacts of climate change in the future. Although many attempts have been made to understand single aspects of climate change impacts on forests, the available knowledge has to be conflated into an integrated assessment to support decision making. A comprehensive system comprising different impact models and an economic assessment suitable for Central European forests and driven by high-resolution temporal- and spatial data is currently missing. We present a conceptional design and a reference implementation of a Decision Support System (DSS) tailored to assess climate change impacts on German forests. To provide high ease-of-use, the system was implemented as a web application and offers information for single stands on-demand as well as interactive maps and preprocessed assessments on a coarser level for entire Germany. To create such a complex, integrated system from legacy models written in different programming languages the interfaces had to be developed carefully. The key of this DSS is its building blocks: established models describing different climate change impacts. Since the DSS is a very modular system, it is easy to replace submodels and to adapt it to other study areas, forest systems or research questions if suitable parameterized models and input data are available. The presented technical solution is adaptable to other systems integrating existing models and the source code is available.

Climate change may strongly impact on forests and affect the provisioning of forest ecosystem services. The identification, design, selection and implementation of adaptive measures in forest management requires a sound knowledge base as well as tools to support the forest manager in decision making. Decision support systems (DSS) are considered as particularly useful to assist in dealing with ill structured decision making problems. Forest management planning and decision making deals with highly complex socio-ecological systems with multiple interacting spatial and temporal dimensions. Finding ways and means to communicate findings about such complex relationships in forest ecosystems and their management via information technology is a challenge in itself. This is amplified if decision problems include land use and climate change issues as inherent uncertainty in planning outcomes increases. The literature reports numerous attempts to develop DSS for forest management. However, recently several review papers conclude that there has been only limited uptake of DSS into practice in case that the user demands and the characteristic of decision problems are not considered properly.
In this contribution we propose five design principles for forest management DSS: (i) modularity, (ii) accessibility via the internet, (iii) inclusion of different types of knowledge and information, (iv) possibility to use different data sources, and (v) support of specific problem types. Based on these principles we promote a ToolBox approach attempting to meet context specificity and flexibility addressing different user and problem types simultaneously. The AFM (Adaptive Forest Management) ToolBox is introduced and the conceptual design and technical implementation of the ToolBox is presented. The combination of different kind of decision support techniques (e.g. vulnerability assessment, multi-criteria analysis, optimization) allows to support all phases of the decision making process and provides the user with the flexibility to interpret the information in various forms. The results of a self-assessment of the ToolBox against eight evaluation criteria for DSS are combined with a feedback from a panel of expert users who had tested the usability and had evaluated the conceptual approach of the ToolBox. The feedback allows stimulating the further development and increasing the level of acceptance of potential users. It is concluded, that the ToolBox approach focusing on modularity while avoiding to over-emphasis technical integration provides the right frame to secure the flexibility to add new tools and improve the support of decision making processes which is mandatory if a DSS should be taken up by practice.

Current Mexican forest management is the product of a history that dates back to 1926. Earlier approaches were directly or indirectly aimed at attaining the normal forest model. Around 1980, multi-resource and environmental impact considerations were mandated for all private timber operations. Timber-oriented silviculture was deemed insufficient to take proper care of non-timber values in the forest. Concerns about water quality, biodiversity, and natural conservation were the motives for promoting voluntary best management practices, in 2012 and afterwards. In this research, two traditional Mexican forest management schemes, Sicodesi and Plan Costa, enhanced with best management practices, are compared to Mapa, a management method specifically designed to manage landscape attributes. Results from two successive forest inventories 10 and 13 years apart show that Sicodesi and Plan Costa, even when modified to comply with best management practices, failed to maintain proper stewardship of non-timber values. Mapa, however, employed multiple means to drive forest dynamics to fulfill multi-resource objectives, constrained by self-financing and competitive profitability. These capabilities in Mapa enabled some degree of control over non-timber values, but many more important processes occur beyond the property boundary, and beyond the planning scope considered in Mapa and all other forest planning methods.

Integrated forest management is faced with the challenge that the contribution of forests to economic and ecological planning targets must be assessed in a socio-ecological system context. This paper introduces a way to model spatio-temporal dynamics of biomass production at a regional scale in order to derive land use strategies that enhance biomass provision and avoid trade-offs for other ecosystem services. The software platform GISCAME was employed to bridge the gap between local land management decisions and regional planning by linking growth and yield models with an integrative mesoscale modeling and assessment approach. The model region is located in Saxony, Germany. Five scenarios were simulated, which aimed at testing different alternatives for adapted land use in the context of climate change and increasing biomass demand. The results showed, for example, that forest conversion towards climate-change-adapted forest types had positive effects on ecological integrity and landscape aesthetics. In contrast, negative impacts on landscape aesthetics must be expected if agricultural sites were converted into short rotation coppices. Uncertainties with stem from assumptions regarding growth and yield models were discussed. Future developmental steps which consider, for example, accessibility of the resources were identified.

Programme-based Planning of Natural Resources (PBPNR) is an evolving planning frame for solving complex land use, environmental and forest management problems within hierarchically administrated funding and decision-making schemes. PBPNR acknowledges that an effective planning process requires the combined consideration of environmental, technological, economic and socio-political factors. To reach acceptability, commitment and operability, PBPNR processes need to foster collaboration and learning. For this study, an analysis of 43 collaborative planning methods was conducted to examine their potential to be applied within PBPNR. We present the approach of screening the applicability of methods for specific needs that may occur in PBPNR. The approach is based on a list of key criteria for the phases of a collaborative planning process: problem identification, problem modelling and problem solving. The features of each method were qualitatively assessed and peer-reviewed by a team of experts. Most of the methods are able to deal with qualitative data, support processes to increase transparency in planning and capture the preferences of the participating stakeholders. They also produce understandable results for the three phases. Contrarily, many methods do not offer features to handle uncertainty, nor do they satisfactorily stimulate creativity and innovation in the planning process. The results show that the overall applicability of the reviewed methods for the three planning phases varies according to a cluster analysis basing on the capabilities of the methods. Methods such as “Planning for Real”, “Open Space” and “A'WOT” seem to be particularly promising for a broad range of planning situations.

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.