Exploratory multi-criteria analysis in sustainability impact assessment of forest-wood chains: the example of a regional case study in Baden–Württemberg

• DOI: 10.1007/s10342-011-0499-z
• Publication Date: 2011-02-18T14:55:02Z
• Authors: Bernhard Wolfslehner; Franka Brüchert; Janine Fischbach; Werner Rammer; Gero Becker; Marcus Lindner; Manfred J. Lexer
• Keywords: Baseline (sea); Scenario analysis; Sustainable Forest Management

Sustainability impact assessment (SIA) is a prospective, integrated assessment approach for potential impacts of policy actions. Multi-criteria analysis (MCA) can be used to facilitate a multi-indicator evaluation in this framework in order to foster rational and transparent decision-making processes for SIA. Based on the outputs of the EFORWOOD project, this paper presents an exploratory MCA to a regional forest-wood chain (FWC) in Baden–Wurttemberg. This assessment is based on a set of sustainability indicators at process level for a baseline year 2005, reference futures ‘A1’ and ‘B2’ following the definition of the IPCC and a bio-energy scenario implanted into the reference future ‘A1’. The indicator values were calculated by the process tool ToSIA. It is demonstrated how time steps for parts of the regional FWC (forest management, harvest and transport to the mill gate) can be evaluated, as well as the outcomes of different scenarios for a time period. For this purpose, a novel software tool, ToSIA-MCA, is used to calculate relative sustainability impact rating (SIR) based on a PROMETHEE II algorithm. Further, we performed uncertainty analysis to test the stability of ranking results in the absence of real preference information with regard to uncertainty in indicator data. By comparing different indicator weighting patterns, the sensitivity of SIR calculation was further tested. The exploratory MCA outcomes are critically evaluated against the background of assumptions, and data used in the regional case, and an outlook is given on the importance to gain stronger stakeholder involvement in real-life applications.