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

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. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south-east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non-lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.

The Moho reflectivity from ambient seismic noise autocorrelations beneath the Western Alps

The lower crustal structure beneath the Western Alps -- including the Moho -- bears the signature of past and present geodynamic processes. It has been the subject of many studies until now. However, its current knowledge still leaves significant open questions. In order to derive new information, independent from previous determinations, here I wish to address this topic using a different method --- ambient seismic noise autocorrelation --- that is for the first time applied to reveal Moho depth in the Western Alps. Moho reflections are identified by picking reflectivity changes in ambient seismic noise autocorrelations. The seismic data is retrieved from more than 200 broadband seismic stations, from the China--Italy--France Alps (CIFALPS) linear seismic network, and from a subset of the AlpArray Seismic Network (AASN). The automatically-picked reflectivity changes along the CIFALPS transect in the southwestern Alps show the best results in the 0.5--1 Hz frequency band. The autocorrelation reflectivity profile of the CIFALPS transect shows a steeper subduction profile,~55 to ~70 km, of the European Plate underneath the Adriatic Plate. The dense spacing of the CIFALPS network facilitates the detection of lateral continuity of crustal structure, and of the Ivrea mantle wedge reaching shallow crustal depths in the southwestern Alps. The data of the AASN stations are filtered in the 0.4--1 and 0.5--1 Hz frequency bands. Although the majority of the stations give the same Moho depth for the different frequency bands, the few stations with different Moho depths shows the care that has to be taken when choosing the frequency band for filtering the autocorrelation stacks. The new Moho depth maps by using the AASN stations are a compilation of the first and second picked reflectivity changes. The results show the complex crust-mantle structure with clear differences between the northwestern and southwestern Alps.