| Text | 353277 2016 10.1016/j.ecolind.2015.10.024 ISI Web of Science WOS 000367411200055 Scopus 2 s2.0 84949729169 Macroinvertebrates Taxonomy based metrics Lakes Reservoirs Quantile regression Oxygen Predictive models Quantile regression analysis as a predictive tool for lake macroinvertebrate biodiversity Fornaroli, R.; Cabrini, R.; Zaupa, S.; Bettinetti, R.; Ciampittiello, M.; Boggero, A. Fornaroli, Riccardo DISAT, Universita degli Studi di Milano Bicocca, Piazza della Scienza 1, 20126 Milano, Italy; Cabrini, Riccardo DISAT, Universita degli Studi di Milano Bicocca, Piazza della Scienza 1, 20126 Milano, Italy; Zaupa, Silvia CNR ISE, Pallanza Verbania; Bettinetti, Roberta University of Insubria, Theoretical and Applied Science Department, Via Valleggio 11, 22100 Como, Italy; Ciampittiello, Marzia CNR ISE, Pallanza Verbania; Boggero, Angela CNR ISE, Pallanza Verbania The Water Framework Directive introduced in Europe major changes to improve the management of water resources. This study aims to highlight some of the potential implications of its implementation for lake water monitoring in Italy. A Life project was launched to plan the first monitoring of lake macroinvertebrates standardized at the national level. Quantile regression analysis was used to explain different metrics of diversity describing macroinvertebrate communities in response to twenty one variables representing chemical, physical and morphological characteristics of the environment. Nine lakes located in two Italian regions Piedmont and Sardinia were analyzed covering a wide trophic spectrum, from oligotrophy to hyper eutrophy. The lakes were sampled following the national standardized protocol with samples covering the three recognized lake zones littoral, sublittoral, profundal. 61 Published version Articolo 2016_RegrQuant_lowland.pdf Articolo in rivista Elsevier Science Ireland. 1470 160X Ecological indicators Ecological indicators Ecological indicators. angela.boggero BOGGERO ANGELA marzia.ciampittiello CIAMPITTIELLO MARZIA |
