Due to several ecosystem services provided to the community, the multifunctional management of forests has acquired an important role over the years. The current Sustainable Forest Management (SFM) guidelines are based on planning programmes which are able to achieve targets from socio-economic and environmental points of view. In this paper, SFM indicators have been studied and compared to estimate the sustainability of three coppice options, from both an economic and a socio-environmental viewpoint. Each indicator was studied in relationship to the treatment and to the considered areas. The results of the statistical analysis show differences among treatments, and the possible correlations between the indicators. Moreover, by using principal component analysis (PCA), the correlations between the indicators were analysed, while the ways in which they influenced the examined sites were also considered. In particular, specific homogeneous clusters separating the observed sites were observed based on treatment and geographical gradient. Overall, the set of indicators used has proven to be effective when carrying out an evaluation of the existing types of forest management based on the analysis of three fundamental aspects of the SFM.
Indicators of sustainable forest management to evaluate the socio-economic functions of coppice in Tuscany, Italy
Riccioli F.
;
2020-01-01
Abstract
Due to several ecosystem services provided to the community, the multifunctional management of forests has acquired an important role over the years. The current Sustainable Forest Management (SFM) guidelines are based on planning programmes which are able to achieve targets from socio-economic and environmental points of view. In this paper, SFM indicators have been studied and compared to estimate the sustainability of three coppice options, from both an economic and a socio-environmental viewpoint. Each indicator was studied in relationship to the treatment and to the considered areas. The results of the statistical analysis show differences among treatments, and the possible correlations between the indicators. Moreover, by using principal component analysis (PCA), the correlations between the indicators were analysed, while the ways in which they influenced the examined sites were also considered. In particular, specific homogeneous clusters separating the observed sites were observed based on treatment and geographical gradient. Overall, the set of indicators used has proven to be effective when carrying out an evaluation of the existing types of forest management based on the analysis of three fundamental aspects of the SFM.File | Dimensione | Formato | |
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