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http://hdl.handle.net/10261/292013
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Título: | Selecting the best forest management alternative by aggregating ecosystem services indicators over time A case study in central Spain |
Autor: | Díaz-Balteiro, Luis; Alonso, Rafael; Martínez-Jauregui, María; Pardos, Marta CSIC ORCID | Palabras clave: | Multi-criteria decision making techniques Sustainable forest management PICUS Stakeholders Climate scenarios |
Fecha de publicación: | 2017 | Editor: | Elsevier | Citación: | Ecological Indicators 72: 322-329 (2017) | Resumen: | Sustainable forest management has been approached on many occasions by defining and subsequently measuring a set of initially accepted indicators. This methodology permits the aggregation of multiple goods and services with heterogeneous characteristics into forest management. However, the calculation of these indicators has usually been static. When we find ourselves in situations in which there is a need to make long-term evaluations of the effects of possible scenarios affecting forest management, a procedure has to be set up to define and aggregate the different indicators over time, as well as to integrate the preferences of the stakeholders involved in management. This study shows a goal programming-based methodology, which permits to select the best management alternative in 6 climate change scenarios when different indicators are aggregated over 100 years in a mountain forest in Central Spain. The results revealed the predominance of one management alternative (no management) when the preferences of the stakeholders were aggregated. However, when the preferential weights corresponding to some stakeholders were included separately, the solution may notably vary, especially in the case of forest owners. It was concluded that the methodology proposed allows a dynamic aggregation of diverse sustainable forest management in addition to presenting a great flexibility at the moment of selecting various solutions proposed by the goal programming model, and the preferences of the different stakeholders. © 2016 Elsevier Ltd | URI: | http://hdl.handle.net/10261/292013 | DOI: | 10.1016/j.ecolind.2016.06.025 | ISSN: | 1470-160X |
Aparece en las colecciones: | (INIA) Artículos |
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