A decision support system for a multi stakeholder’s decision process in a Portuguese National Forest

J. Garcia-Gonzalo, J. Palma, J. Freire, M. Tomé, R. Mateus, L.C.E. Rodriguez, V. Bushenkov, J.G. Borges


Aim of study: In this paper, we present a decision support system (DSS) to support decision making where different stakeholders have to generate landscape and forest level strategic plans. We further present an interactive approach that may take advantage of a posteriori preference modelling (i.e. Pareto frontier technique) to facilitate the specification of the levels of achievement of various objectives.

Area of study: The approach was applied to one planning cycle of a real world study case, the Leiria National Forest in Portugal. The Leiria National Forest, a managed area of approximately eleven thousand hectares in which 8,679 hectares are even aged stands of maritime pine (Pinus pinaster Ait) aimed at the production of wood.

Material and methods: The interactive approach, at first, tries to generate Pareto efficient frontiers for different objectives. Then, multiple decision makers are involved in the process to seek an agreement towards the definition of a consensual strategic plan.

Main results: The system developed in this article integrates an information management subsystem, a module to generate alternative management regimes, growth model routines and a decision module that generates and solves mathematical formulations. It also provides a module to display reports and view the resulting solutions (management plans). We also build the Pareto frontier for different criteria. The results show that the proposed DSS can help solve strategic planning problems subject to sustainable management constraints where people organize themselves and participate jointly to manage their natural resources.

Research highlights: The interactive approach facilitates the involvement of multiple stakeholders in the decision making process.

Keywords: decision support system; participatory planning; linear programming; mixed integer goal programming; sustainable forest management.

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DOI: 10.5424/fs/2013222-03793

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