5 resultados para Multivariate Linkage Analysis

em SAPIENTIA - Universidade do Algarve - Portugal


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Dissertação de mestrado, Ecohidrologia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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Tese de Doutoramento, Ciências do Mar, da Terra e do Ambiente, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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The macrofauna assemblages of a XVIIth century shipwreck off southern Portugal were studied and compared with those of nearby natural reefs and sandy bottoms, by underwater visual census. A total of 11 173 specimens of 224 different fauna taxa and 12 phyla were recorded. Natural reefs had the highest density of specimens (35 122 / 1000 m2) followed by the shipwreck (21 392 / 1000 m2) and the sandy bottoms (3771 / 1000 m2). Three biodiversity indices were estimated (Margalef, Shannon- Wiener and Pielou), with the natural reefs showing the highest values. However, the shipwreck presented values relatively similar to those of the natural reefs for the Shannon-Wiener and Pielou indices. The three habitats were clearly distinguishable by multivariate statistical analysis, with the average dissimilarity between sand and shipwreck, and between sand and natural reefs being much higher than that between the shipwreck and the natural reefs. The shipwreck had higher abundances of some commercially important species, such as the pouting Trisopterus luscus, European conger Conger conger, and common spider crab Maja squinado, as well as some vulnerable and threatened species such as the pink seafan Eunicella verrucosa. The results presented emphasize the importance of this habitat on the southern Portuguese coast.

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

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Taxonomic distinction to species level of deep water sharks is complex and often impossible to achieve during fisheries-related studies. The species of the genus Etmopterus are particularly difficult to identify, so they often appear without species assignation as Etmopetrus sp. or spp. in studies, even those focusing on elasmobranchs. During this work, the morphometric traits of two species of Etmopterus, E. spinax and E. pusillus were studied using 27 different morphological measurements, relatively easy to obtain even in the field. These measurements were processed with multivariate analysis in order to find out the most important ones likely to separate the two species. Sexual dimorphism was also assessed using the same techniques, and it was found that it does not occur in these species. The two Etmopterus species presented in this study share the same habitats in the overlapping ranges of distribution and are caught together on the outer shelves and slopes of the north-eastern Atlantic.