STATISTICAL ANALYSIS OF PLEISTOCENE CALCAREOUS MICROPLANKTONIC ASSEMBLAGES: AN ATTEMPT FOR UNDERSTANDING THE VARIATIONS OF ENVIRONMENTAL PARAMETERS

Article Sidebar

PDF
Published: Jan 13, 2011
DOI: https://doi.org/10.26382/
Keywords:
calcareous nannofossils, planktonic foraminifera, Principal Component Analysis

Main Article Content

Claudia Lupi
Dipartimento di Scienze della Terra, Università di Pavia, Pavia
Claudia Lupi
Dipartimento di Scienze della Terra, Università di Pavia, Pavia
Miriam Cobianchi
Dipartimento di Scienze della Terra, Università di Pavia, Pavia
Luciani Valeria
Dipartimento di Scienze della Terra, Università di Ferrara, Ferrara
Manuela Bordiga
Dipartimento di Scienze della Terra, Università di Ferrara, Ferrara

Abstract

Lupi C. et al., Statistical analysis of Pleistocene calcareous microplanktonic assemblages: an attempt for understanding the variations of environmental parameters (IT ISSN 0394-3356, 2011) The application of a multivariate statistical approach to a database concerning the occurrence of the two major calcareous planktonic groups (calcareous nannofossils and foraminifera) provides a potential additional instrument to identify the variation over time of the sea surface water parameters

Article Details

How to Cite
Lupi, Claudia, Claudia Lupi, Miriam Cobianchi, Luciani Valeria, and Manuela Bordiga , trans. 2011. “STATISTICAL ANALYSIS OF PLEISTOCENE CALCAREOUS MICROPLANKTONIC ASSEMBLAGES: AN ATTEMPT FOR UNDERSTANDING THE VARIATIONS OF ENVIRONMENTAL PARAMETERS”. Alpine and Mediterranean Quaternary 24 (Extended Abstract): 212-14. https://doi.org/10.26382/.
Issue
Vol. 24 No. Extended Abstract (2011): IL QUATERNARIO
Section
Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The Author grants usage rights to others using an open license (Creative Commons or equivalent) allowing for immediate free access to the work and permitting any user to read, download, copy, distribute, print, search, or link to the full texts of articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose.