974 resultados para canonical correspondence analysis(CCA)


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In this study we investigate the potential of organic-walled dinoflagellate cysts (dinocysts) as tools for quantifying past sea-surface temperatures (SST) in the Southern Ocean. For this purpose, a dinocyst reference dataset has been formed, based on 138 surface sediment samples from different circum-Antarctic environments. The dinocyst assemblages of these samples are composed of phototrophic (gonyaulacoid) and heterotrophic (protoperidinioid) species that provide a broad spectrum of palaeoenvironmental information. The relationship between the environmental parameters in the upper water column and the dinocyst distribution patterns of individual species has been established using the statistical method of Canonical Correspondence Analysis (CCA). Among the variables tested, summer SST appeared to correspond to the maximum variance represented in the dataset. To establish quantitative summer SST reconstructions, a Modern Analogue Technique (MAT) has been performed on data from three Late Quaternary dinocyst records recovered from locations adjacent to prominent oceanic fronts in the Atlantic sector of the Southern Ocean. These dinocyst time series exhibit periodic changes in the dinocyst assemblage during the last two glacial/interglacial-cycles. During glacial conditions the relative abundance of protoperidinioid cysts was highest, whereas interglacial conditions are characterised by generally lower cyst concentrations and increased relative abundance of gonyaulacoid cysts. The MAT palaeotemperature estimates show trends in summer SST changes following the global oxygen isotope signal and a strong correlation with past temperatures of the last 140,000 years based on other proxies. However, by comparing the dinocyst results to quantitative estimates of summer SSTs based on diatoms, radiolarians and foraminifer-derived stable isotope records it can be shown that in several core intervals the dinocyst-based summer SSTs appeared to be extremely high. In these intervals the dinocyst record seems to be highly influenced by selective degradation, leading to unusual temperature ranges and to unrealistic palaeotemperatures. We used the selective degradation index (kt-index) to determine those intervals that have been biased by selective degradation in order to correct the palaeotemperature estimates. We show that after correction the dinocyst based SSTs correspond reasonably well with other palaeotemperature estimates for this region, supporting the great potential of dinoflagellate cysts as a basis for quantitative palaeoenvironmental studies.

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Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.

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The influence of different primary productivity regimes on live (Rose Bengal stained) and dead benthic foraminiferal distribution, as well as on the stable carbon isotopic composition of foraminiferal tests, was investigated in sediment surface samples (0-1 cm) from the upwelling region off Morocco between Cape Ghir (31°N) and Cape Yubi (27°N). A combination of factor analysis, detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) was applied to the benthic foraminiferal data sets. Five major assemblages for both the live and dead fauna were revealed by factor analysis. In the cape regions organic matter fluxes are enhanced by high chlorophyll-a concentrations in the overlying surface waters. Here, benthic foraminiferal faunas are characterized by identical live and dead assemblages, high standing stocks, and low species delta13C values, indicating constant year-round high productivity. Bulimina marginata dominates the unique fauna at the shallowest station off Cape Ghir indicating highest chlorophyll-a concentrations. Off both capes, the succession of the Bulimina aculeata/Uvigerina mediterranea assemblage, the Sphaeroidina bulloides/Gavelinopsis translucens assemblage, and the Hoeglundina elegans assemblage from the shelf to the deep sea reflects the decrease in chlorophyll-a concentrations, hence the export flux. In contrast, the area between the capes is characterized by differently composed live and dead assemblages, low standing stocks, and less depleted delta13C values, thus reflecting low primary productivity. High foraminiferal numbers of Epistominella exigua, Eponides pusillus, and Globocassidulina subglobosa in the dead fauna indicate a seasonally varying primary productivity signal. Significantly lower mean delta13C values were recorded in Bulimina mexicana, Cibicidoides kullenbergi, H. elegans, U. mediterranea and Uvigerina peregrina. Cibicidoides wuellerstorfi is a faithful recorder of bottom water delta13C in the Canary Islands regions. The mean delta13C signal of this species is not significantly influenced by constant high organic matter fluxes. The species-specific offset between live and dead specimens is the same.

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(Estrutura da comunidade arbórea e suas relações com fatores edáficos na floresta de restinga paludosa da estrada Velha, Rio Grande, Rio Grande do Sul). O presente estudo tem como objetivo estudar a estrutura da comunidade arbórea da floresta de restinga paludosa da Estrada Velha (32º07’S; 52º09’W) localizada no município do Rio Grande, na Planície Costeira do Rio Grande do Sul e suas correlações com fatores edáficos. Para a amostragem do componente arbóreo foram demarcadas três transecções paralelas, ao longo das quais foram alocadas 30 unidades amostrais de 10m X 10m, de forma não contígua e amostrados todos os indivíduos com perímetro a altura do peito maior ou igual a 15 cm. Foram coletadas amostras de solo para análises químicas e granulométricas e realizadas medidas da coluna d’água nas unidades amostrais. Os principais parâmetros fitossociológicos foram estimados para descrever a estrutura da floresta, bem como os índices de Diversidade de Shannon (H’) e de Equabilidade de Pielou (J’). A similaridade com outras florestas no Rio Grande do Sul foi estimada pelo índice de Jaccard (ISj). As relações entre a abundância das espécies nas unidades amostrais e fatores edáficos foram avaliadas por meio de análise de componentes principais (PCA) e análise de correspondência canônica (CCA). Foram registrados 585 indivíduos distribuídos em 19 espécies, 17 gêneros e 16 famílias. A família com maior riqueza específica foi Moraceae e as espécies com maiores valores de importância foram Citronela gongonha (Mart.) R.A. Howard, Erythrina crista-galli L., Sebastiania brasiliensis Spreng., Ficus cestrifolia Schott. e Syagrus romanzoffiana (Cham.) Glassman. O Índice de diversidade foi 1,99 nat.ind-1 e o de Equabilidade foi 0,68. As análises multivariadas de ordenação evidenciaram um gradiente de distribuição das espécies correlacionado principalmente com a densidade de C. gongonha e fatores edáficos como pH, Ca, CTC(t), MO, K e nível de alagamento. O componente arbóreo mostrou similaridade florística (ISj) com outras florestas paludosas localizadas em maiores latitudes no Estado.

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Neste estudo foi investigado como a distribuição das espécies e a produção de biomassa de macrófitas aquáticas são influenciadas pelas condições físico-químicas do ambiente. Também foi avaliado como uma espécie com maior potencial competitivo pode interferir na diversidade de espécies da comunidade macrofítica. Para tanto, em cada um dos três arroios, foram dispostos seis transecções, perpendiculares à margem. Em cada transecção foram demarcadas três unidades amostrais de 1m², nas quais foram registrados os parâmetros fitossociológicos cobertura e frequência relativas e valor de importância. A diversidade de espécies foi estimada pelo índice de Shannon, utilizando os valores de cobertura de espécies. Para determinar a biomassa das macrófitas aquáticas foram usados quadrats de 0,25m², alocados dentro da unidade amostral de 1m² usadas para quantificar os dados fitossociológicos, nos mesmos pontos onde foi feito o levantamento de cobertura da vegetação. Utilizamos como variáveis preditoras a velocidade da corrente, radiação solar incidente, coeficiente de sombreamento, vegetação ripária arbórea adjacente, nitrogênio orgânico dissolvido, carbono orgânico dissolvido e condutividade elétrica. Foram registradas 32 espécies de macrófitas aquáticas, distribuídas em 19 famílias e 28 gêneros. Conforme Análise de Correspondência Canônica (CCA), as espécies com maiores valores de biomassa foram relacionadas a unidades amostrais com alta incidência luminosa. As unidades amostrais com dominância de Pistia stratiotes apresentaram menor diversidade de espécies indicando que esta espécie, quando encontra condições que permitam sua proliferação, pode excluir espécies de menor potencial competitivo. De acordo com GLM (Generalized Linear Model), a ausência de vegetação ripária ou presente em apenas uma das margens e baixas velocidades de corrente configura-se em condições favoráveis ao estabelecimento e desenvolvimento de macrófitas aquáticas, possibilitando produção maiores valores de biomassa.

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Although correspondence analysis is now widely available in statistical software packages and applied in a variety of contexts, notably the social and environmental sciences, there are still some misconceptions about this method as well as unresolved issues which remain controversial to this day. In this paper we hope to settle these matters, namely (i) the way CA measures variance in a two-way table and how to compare variances between tables of different sizes, (ii) the influence, or rather lack of influence, of outliers in the usual CA maps, (iii) the scaling issue and the biplot interpretation of maps,(iv) whether or not to rotate a solution, and (v) statistical significance of results.

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We show the equivalence between the use of correspondence analysis (CA)of concadenated tables and the application of a particular version ofconjoint analysis called categorical conjoint measurement (CCM). Theconnection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of theanalysis and shows how to pass between the results of each analysis.

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A high resolution mixed carbonate and siliciclastic sequence from DSDP Site 594 contains a detailed record of climate change in the late Pliocene. The sequence can be accurately dated by the LAD of Nitzschia weaveri, the LAD of Thalassiosira insigna, the LAD of T. vulnifica and the LAD of T. kolbei diatom datums. Carbonate content and delta18O signatures provide added resolution and place the sequence between isotope stage 100 and 92. The sequence contains well-preserved and diverse dinoflagellate cyst floras. Use of principal component (PCA) and canonical correspondence analyses (CCA) identifies changes in the assemblages that principally reflect warming and cooling trends. Species association with warmer climates included Impagidinium patulum, I. paradoxum and I. sp. cf. paradoxum while those from cooler climates include Invertecysta tabulata and I. velorum. CCA is shown to be a valuable method of determining the past environmental preferences of extinct species such as I. tabulata.

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The mechanisms involved in the control of growth in chickens are too complex to be explained only under univariate analysis because all related traits are biologically correlated. Therefore, we evaluated broiler chicken performance under a multivariate approach, using the canonical discriminant analysis. A total of 1920 chicks from eight treatments, defined as the combination of four broiler chicken strains (Arbor Acres, AgRoss 308, Cobb 500 and RX) from both sexes, were housed in 48 pens. Average feed intake, average live weight, feed conversion and carcass, breast and leg weights were obtained for days 1 to 42. Canonical discriminant analysis was implemented by SAS((R)) CANDISC procedure and differences between treatments were obtained by the F-test (P < 0.05) over the squared Mahalanobis` distances. Multivariate performance from all treatments could be easily visualised because one graph was obtained from two first canonical variables, which explained 96.49% of total variation, using a SAS((R)) CONELIP macro. A clear distinction between sexes was found, where males were better than females. Also between strains, Arbor Acres, AgRoss 308 and Cobb 500 (commercial) were better than RX (experimental), Evaluation of broiler chicken performance was facilitated by the fact that the six original traits were reduced to only two canonical variables. Average live weight and carcass weight (first canonical variable) were the most important traits to discriminate treatments. The contrast between average feed intake and average live weight plus feed conversion (second canonical variable) were used to classify them. We suggest analysing performance data sets using canonical discriminant analysis.

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We compare correspondance análisis to the logratio approach based on compositional data. We also compare correspondance análisis and an alternative approach using Hellinger distance, for representing categorical data in a contingency table. We propose a coefficient which globally measures the similarity between these approaches. This coefficient can be decomposed into several components, one component for each principal dimension, indicating the contribution of the dimensions to the difference between the two representations. These three methods of representation can produce quite similar results. One illustrative example is given

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Starting with logratio biplots for compositional data, which are based on the principle of subcompositional coherence, and then adding weights, as in correspondence analysis, we rediscover Lewi's spectral map and many connections to analyses of two-way tables of non-negative data. Thanks to the weighting, the method also achieves the property of distributional equivalence

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When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

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We compare two methods for visualising contingency tables and developa method called the ratio map which combines the good properties of both.The first is a biplot based on the logratio approach to compositional dataanalysis. This approach is founded on the principle of subcompositionalcoherence, which assures that results are invariant to considering subsetsof the composition. The second approach, correspondence analysis, isbased on the chi-square approach to contingency table analysis. Acornerstone of correspondence analysis is the principle of distributionalequivalence, which assures invariance in the results when rows or columnswith identical conditional proportions are merged. Both methods may bedescribed as singular value decompositions of appropriately transformedmatrices. Correspondence analysis includes a weighting of the rows andcolumns proportional to the margins of the table. If this idea of row andcolumn weights is introduced into the logratio biplot, we obtain a methodwhich obeys both principles of subcompositional coherence and distributionalequivalence.

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Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.

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The application of correspondence analysis to square asymmetrictables is often unsuccessful because of the strong role played by thediagonal entries of the matrix, obscuring the data off the diagonal. A simplemodification of the centering of the matrix, coupled with the correspondingchange in row and column masses and row and column metrics, allows the tableto be decomposed into symmetric and skew--symmetric components, which canthen be analyzed separately. The symmetric and skew--symmetric analyses canbe performed using a simple correspondence analysis program if the data areset up in a special block format.