New methodology for the valuation and monitoring of riverbanks and management techniques applied to several riverbeds in northern Spain

Author(s): Herrero, A.I.M. Salgueiro, J.A
Publication Year: 2018
Publication Type: Journal Article
Source: Bosque (Valdivia) (39, 2)
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Permanent Resource Identifier: Open link
FSC Resource Identifier: Open link
Collections: FSC Research Portal
Abstract

In the present work, a new method for the environmental assessment of riverbanks integrating the Forest Stewardship Council (FSC) certification scheme is proposed. The method collects and evaluates the attributes detailed in the Glossary of Spanish Forest Management Standards for FSC certification, which enabled the detection of many High Conservation Value Forests (MAVC). FSC defines High Conservation Value Forests as those that contain one or more of the biological, social and cultural attributes considered of critical or exceptional importance to a certain area. As the included indicators were objectified, results did not depend on subjectivity and could be compared to different areas studied by different people. At first, this method was applied in small plots in northern Spain and FSC forest certification was obtained. Later it was applied in two rivers, Carrión and Valdavia, located in the northern Spanish sub-plateau. In all cases, application was simple, no values were detected in the areas studied that were not in accordance with the method. Moreover, the use of the FSC certification scheme with international implantation allowed us to consider applying this method in other riverbanks around the world.

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Citation
Magide Herrero, A.I. and Oria de Rueda Salgueiro, J.A., 2018. New methodology for the valuation and monitoring of riverbanks and management techniques applied to several riverbeds in northern Spain. Bosque, 39(2), pp.309-320
Access Rights: Public, Open access
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Sustainability dimension(s): Environmental
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Subject Keywords: Forests Certification
Regions: Europe
Countries: Spain
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Evidence Category: FSC effect-related studies
Evidence Type: Modeling study
Evidence Subtype: Patterns at a large scale using context variables
Data Type: Company data, Field Measurements