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	Provedor de dados ArchiMer (2) Autor Cazelles, B (2) Fromentin, Jean-marc (2) Rouyer, Tristan (2) Corbineau, A (1) Fonteneau, A (1) Menard, Felix (1) Stenseth, N (1) Mais... Palavra-chave Dipole Mode Index (1) Indian Ocean (1) Longline fisheries (1) Maximum covariance analysis (1) Multivariate time series (1) Non stationarity (1) Pelagic fishes (1) Surrogates (1) Time series analysis (1) Wavelet analysis (1) Wavelet clustering (1) Wavelet significance testing (1) Mais... Tipo do documento Text (2) Ano 2008 (2) País France (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Time series analysis of tuna and swordfish catches and climate variability in the Indian Ocean (1968-2003) ArchiMer Corbineau, A; Rouyer, Tristan; Cazelles, B; Fromentin, Jean-marc; Fonteneau, A; Menard, Felix. We analysed the patterns of variation that characterize 33 catch time series of large pelagic fishes exploited by the Japanese and Taiwanese longline fisheries in the Indian Ocean from 1968 to 2003. We selected four species, the yellowfin (Thunnus albacares), the bigeye (T. obesus), the albacore (T. alalunga), and the swordfish (Xiphias gladius) and aggregated data into five biogeographic provinces of Longhurst (2001). We carried out wavelet analyses, an efficient method to study non-stationary time series, in order to get the time-scale patterns of each signals. We then compared and grouped the different wavelet spectra using a multivariate analysis to identify the factors (species, province or fleet) that may influence their clustering. We also... Tipo: Text Palavras-chave: Indian Ocean; Dipole Mode Index; Longline fisheries; Wavelet analysis; Time series analysis; Pelagic fishes. Ano: 2008 URL: http://archimer.ifremer.fr/doc/2008/publication-4714.pdf Analysing multiple time series and extending significance testing in wavelet analysis ArchiMer Rouyer, Tristan; Fromentin, Jean-marc; Stenseth, N; Cazelles, B. In nature, non-stationarity is rather typical, but the number of statistical tools allowing for non-stationarity remains rather limited. Wavelet analysis is such a tool allowing for non-stationarity but the lack of an appropriate test for statistical inference as well as the difficulty to deal with multiple time series are 2 important shortcomings that limits its use in ecology. We present 2 approaches to deal with these shortcomings. First, we used 1/f beta models to test cycles in the wavelet spectrum against a null hypothesis that takes into account the highly autocorrelated nature of ecological time series. To illustrate the approach, we investigated the fluctuations in bluefin tuna trap catches with a set of different null models. The 1/f beta models... Tipo: Text Palavras-chave: Maximum covariance analysis; Surrogates; Wavelet significance testing; Wavelet clustering; Multivariate time series; Non stationarity. Ano: 2008 URL: http://archimer.ifremer.fr/doc/2008/publication-4291.pdf Registros recuperados: 2 Primeira ... 1 ... Última

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