An overview of statistical methods applied to CPR data

• Published in: Progress in Oceanography
• Main Authors: Beaugrand, G, Ibanez, F, Lindley, Ja
• Other Authors: Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2003
• Subjects: [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography; North Atlantic
• Online Access: https://hal.science/hal-03482974; https://doi.org/10.1016/j.pocean.2003.08.006

70th Symposium of the CPR Survey, EDINBURGH, SCOTLAND, AUG 07, 2001 Since the beginning of the Continuous Plankton Recorder (CPR) survey in 1931, information on the abundance of a large number of plankton species or taxa has been obtained on a monthly basis in the northern North Atlantic. The many different ecological issues in which the survey has been involved have led to the application of a range of statistical methods. In this paper, we review some of the methods applied to the CPR data by presenting new and up-to-date analyses. Special attention is devoted to multivariate analysis, which has been used extensively to extract information from the CPR database. Results obtained from recently applied geostatistical methods on CPR data are then considered. An example of a time series decomposition by the use of Eigenvector filtering is presented to illustrate time-series analysis. (C) 2003 Elsevier Ltd. All rights reserved.