Journal Article

An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

Karim Erzini, Cheikh A. O. Inejih and Kim A. Stobberup

in ICES Journal of Marine Science

Published on behalf of ICES/CIEM

Volume 62, issue 3, pages 353-359
Published in print January 2005 | ISSN: 1054-3139
Published online January 2005 | e-ISSN: 1095-9289 | DOI: http://dx.doi.org/10.1016/j.icesjms.2004.12.009
An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

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Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (>15–25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982–2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series.

Keywords: dynamic factor analysis; indicators; Mauritania; metrics; min/max autocorrelation factor analysis; multispecies; time-series

Journal Article.  2862 words.  Illustrated.

Subjects: Environmental Science ; Marine and Estuarine Biology

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