Lookup NU author(s): Marco Girardello,
Professor Mark Whittingham,
Professor Stephen Rushton
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
The current study combines the use of niche modelling with a site prioritization method to identify important areas for butterfly conservation in Italy. A novel machine learning method (bagging predictors) was used to predict the distribution of 232 species of butterflies across the Italian Peninsula. The results of the models were used to identify high-value sites with a multispecies prioritization method called zonation. In order to identify important areas for species of conservation concern, we incorporated a species weighting scheme to zonation analyses. We also used the results of the zonation analyses to identify a series of management landscapes on the basis of the similarity in species composition among sites. The basic zonation showed that most important areas for butterfly conservation are located in the Alps, the Appennine, the Apulia region and in the island of Sardinia. The inclusion of a species weighting scheme in the zonation analyses revealed the importance of two new areas located in Southern Italy and emphasized the importance of the Alps for species of conservation concern. The landscape identification procedure selected a series of landscapes, which provide protection to a full range of species ranging from the Alps to Mediterranean areas. Our study shows that the areas selected in our analyses should be given high priority in future conservation plans and monitoring schemes.
Author(s): Girardello M, Griggio M, Whittingham MJ, Rushton SP
Publication type: Article
Publication status: Published
Journal: Animal Conservation
ISSN (print): 1367-9430
ISSN (electronic): 1469-1795
Publisher: Wiley-Blackwell Publishing Ltd.
Altmetrics provided by Altmetric