A simple multivariate analysis to assess diversity in a complex long-term managed forest area in central Italy

Abstract

Today wood and nonwood forest resources management meets and often clashes with environment and biological diversity protection. A main problem is to understand relationships between the different roles of forest biodiversity, site, and management parameters. A multivariate statistical analysis has been carried out in order to interpret relationships between some forest biodiversity components and forest inventory data. Several indices of floristic diversity, species abundance, and structural heterogeneity at stand level have been calculated. The different components of forest biodiversity were separated by principal components analysis. Relations between forest biodiversity indices and site and management attributes have been investigated by two multivariate statistical techniques: bivariate correlation analysis and multiple linear regression. Results showed a high correlation between all the investigated components of forest biodiversity and some topographic and/or forest management attributes. Results also gave ancillary information to define sustainable forest management criteria.

Keywords:

• Correlation
• forest biodiversity
• forest ecosystems
• principal components analysis
• sustainable forest management

Acknowledgements

The authors thank Regione Molise and Istituto Nazionale di Economia Agraria (INEA) for providing data. The authors also thank Prof. Roberto Tognetti from University of Molise and Dr Gianfranco Fabbio from the Italian Forestry Research Centre for the useful suggestions in designing the work. The authors particularly acknowledge Prof Alberto Rojo Alboreca and his staff of the University of Santiago de Compostela (Galicia – Spain) for contributing during the elaboration phase.