José G. Borges

A New Mixed-Integer Programming Model for Harvest Scheduling Subject to Maximum Area Restrictions

Forest ecosystem management often requires spatially explicit planning because the spatial arrangement of harvests has become a critical economic and environmental concern. Recent research on exact methods has addressed both the design and the solution of forest management problems with constraints on the clearcut size, but where simultaneously harvesting two adjacent stands in the same period does not necessarily exceed the maximum opening size. Two main integer programming approaches have been proposed for this area restriction model. However, both encompass an exponential number of variables or constraints. In this work, we present a new integer programming model with a polynomial number of variables and constraints. Branch and bound is used to solve it. The model was tested with both real and hypothetical forests ranging from 45 to 1,363 polygons. Results show that the proposed models solutions were within or slightly above 1% of the optimal solution and were obtained in a short computation time.

Characterization of wildfires in Portugal

Forest fires severity has increased in Portugal in the last decades. Climate change scenarios suggest the reinforcement of this severity. Forest ecosystem managers and policy-makers thus face the challenge of developing effective fire prevention policies. The characterization of forest fires is instrumental for meeting this challenge. An approach for characterizing fire occurrence in Portugal, combining the use of geographic information systems and statistical analysis techniques, is presented. Emphasis was on the relationships between ecological and socioeconomic features and fire occurrence. The number and sizes of wildfires in Portugal were assessed for three 5-year periods (1987–1991, 1990–1994, and 2000–2004). Features maps were overlaid with perimeters of forest fires, and the proportion of burned area for each period was modeled using weighted generalized linear models (WGLM). Descriptive statistics showed variations in the distribution of fire size over recent decades, with a significant increase in the number of very large fires. Modeling underlined the impact of the forest cover type on the proportion of area burned. The statistical analysis further showed that socioeconomic features such as the proximity to roads impact the probability of fires occurrence. Results suggest that this approach may provide insight needed to develop fire prevention policies.

Decision Support Systems in Forest Management

Numerous decision support systems have been developed for forest management over the past 20 years or more. In this chapter, the authors briefly review some of the more important and recent developments, including examples from North America, Europe, and Asia. In addition to specific systems, we also review some of the more-significant methodological approaches such as artificial neural networks, knowledge-based systems, and multicriteria decision models. A basic conclusion that emerges from this review is that the availability of DSSs in forest management has enabled more-effective analysis of the options for and implications of alternative management approaches for all components of forest ecosystems. The variety of tools described herein, and the approaches taken by the different systems, provide a sample of the possible methods that can be used to help stakeholders and decision makers arrive at reasoned and reasonable decisions.

A column generation approach for solving a non-temporal forest harvest model with spatial structure constraints

Abstract We present an integer programming model for a non-temporal forest harvest problem with constraints on the clearcut size and on the total area of old growth patches with a minimum size requirement. The model has a very large number of variables for operationally sized problems which precludes the use of exact solution methods. We propose column generation to solve the linear relaxation of the model and a linear programming rounding heuristic to obtain a solution to the model. Column generation may not solve exactly the linear relaxation because the optimization problems associated with the pricing subproblems are NP -hard. We present heuristics for these subproblems. Computational results for test instances and for a real life instance that corresponds to a large Portuguese forest are reported.

HEURISTICS IN MULTI-OBJECTIVE FOREST MANAGEMENT

Heuristics have been used extensively to support forest management scheduling in the last two decades. The need for spatial definition, and the combined shortcomings of available technology and traditional mathematical programming approaches, sparked interest in alternative forest management scheduling techniques in the early 1980s. Concerns with the environmental impacts of forest management options further encouraged the development of heuristics to address adjacency relationships in harvesting decisions. More recently, heuristics have been used to target other multi-objective management issues. Namely, they have been used to provide information to help sustain both traditional forest products flows (e.g. timber and cork) and landscape structural characteristics (e.g., mosaic elements such as patch number and size, amounts of edge or interior space). In this chapter, we describe the current state of the art of heuristic application in forest management scheduling. Heuristic approaches are presented and discussed in the framework of forest management scheduling needs. Results from some heuristic research efforts are used to outline the application potential and shortcomings of these techniques.

An enterprise architecture approach to forest management support systems design: an application to pulpwood supply management in Portugal

A key requirement for the success of a forest management information system is that it may effectively address its users’ needs. Yet, the development of models and methods to address-specific forest ecosystem management processes has not been matched by architectures that may take into account the human dimension of information systems. This paper presents an approach to pulpwood supply system architecture. Emphasis is on participatory business modeling that may effectively address users’ needs and enhance system resilience. An Enterprise Architecture methodology is proposed so that the information systems’ functional requirements for pulpwood supply may emerge from business and information architectures in workshops with the stakeholders. Results of its application to a vertically integrated Portuguese pulp and paper company are presented. The case study focuses on processes and business information required to support the pulp mills entire pulpwood supply management. Results show that the proposed approach addressed effectively end-users’ involvement in pulpwood supply system design. It provided an architecture that addresses all stakeholders’ perspectives and concerns and it was thus instrumental to develop a Pulp and Paper Supply Chain Process Framework. Results further show that it may effectively identify and integrate information systems’ components, ensuring business information integrity.

A switching detection method based on projected subspace classification

In this paper an innovative switching detection method for piecewise linear systems is presented. The principle used for switching detection is based on finding projected subspaces from batches of input-output data, which are taken from the full data set. The method runs off-line, incrementally over all the data and, at each time, a different batch is used to compute the projected subspace. In this way, the segmentation and classification of data are entirely based on the information retrieved from the projected subspace, i.e. the subspace dimension and basis. The output of the method is a matrix of weights that assigns each pair of input-output measured data to the respective local system. Simulation experiments show the effectiveness of the proposed approach.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

A web-based ToolBox approach to support adaptive forest management under climate change

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.

Coordinating Management Decisions of Neighboring Stands with Dynamic Programming

Stands are typically thought of as the basic analysis area (AA) or building block of a forest. Historically, forest management planning has focused on how stand management activities can be coordinated across the forest to provide a sustainable flow of products over time. With increasing concerns about sustaining environmental conditions, spatial facets of the management situation also become a concern. Often, how a stand is managed impacts not only the condition of the stand, but also the condition of a “neighborhood” surrounding the stand. These impacts can have a lasting impact over time, thus adding a temporal dimension to spatial concerns. Spatial concerns add substantial complexity for analyzing management options because forests include many stands, each with its own potential unique neighborhood. Generally, it is too simplified to separate the forest into independent neighborhoods, ignoring conditions along neighborhood boundaries. In recent years adjacency constraints have received considerable attention as one policy tool for addressing spatial management objectives. Adjacency constraints set maximum limits on the size of harvest blocks. Specific management limitations for adjacency constraints vary, without any one accepted best set of rules. Typically, the rules involve only regeneration harvests associated with even-aged management. Rules may limit harvesting of adjacent stands within a given time period or set a maximum limit on the size (total area) of any contiguous harvest block. Rules involve an “exclusion period” during which harvesting is prohibited for adjacent stands around a harvest block. Definitions of exclusion periods also vary by user. Some assume a fixed time length for the exclusion period (e.g. 10 years) or tie its definition to the condition of the harvest block (e.g. not until the trees regenerated in the harvest block reach 20% of their height at rotation). Methods for incorporating adjacency constraints into forest planning models have received considerable