Definition of priority areas for forest conservation through the ordered weighted averaging method
Roberta de Oliveira Averna Valente*, Carlos Alberto Vettorazzi
Rural Engineering Department, Luiz de Queiroz School of Agriculture, University of São Paulo (USP), Av. Pádua Dias 11, Caixa Postal 9, 13418-900 Piracicaba, SP, Brazil
* Corresponding author. Tel.: +55 19 34478533; fax: +55 19 34178571.
E-mail addresses: roavalen@esalq.usp.br (R.O.A. Valente), cavettor@esalq.usp.br (C.A. Vettorazzi)
Forest Ecology and Management. Volume 256, Issue 6, 5 September 2008, Pages 1408-1417.
Abstract
The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads; distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns.
Keywords: Forest fragmentation; Multicriteria evaluation; Sensitivity analysis |
