The phylogeny of Simulium (Chirostilbia) (Diptera: Simuliidae) and perspectives on the systematics of the genus in the Neotropical Region

Recently, knowledge of Neotropical Simuliidae has been accumulating quickly. However, information about supra-specific relationships is scarce and diagnoses of Simulium subgenera are unsatisfactory. To investigate the relationships among Simulium (Chirostilbia) species and test the subgenus monophyly, we performed a cladistic analysis. The ingroup included all species of this subgenus and the outgroup included representatives of the 17 species groups of Neotropical Simulium and three Holarctic species. The study was based on a data matrix with 31 terminal taxa and 45 morphological characteristics of adult, pupa and larva. The phylogenetic analysis under equal weights resulted in eight most-parsimonious trees (length = 178, consistency index = 34, retention index = 67). The monophyly of the S. (Chirostilbia) was not supported in our analysis. The Simulium subpallidum species group was closer to Simulium (Psilopelmia) and Simulium (Ectemnaspis) than to the Simulium pertinax species group. Additionally, we describe the three-dimensional shape of the terminalia of male and female of Simulium (Chirostilbia) for the first time and provide comments about the taxonomic problems involving some species of the subgenus: Simulium acarayense, Simulium papaveroi, S. pertinax, Simulium serranum, Simulium striginotum and S. subpallidum.

The Standard Biplot

Biplots are graphical displays of data matrices based on the decomposition of a matrix as the product of two matrices. Elements of these two matrices are used as coordinates for the rows and columns of the data matrix, with an interpretation of the joint presentation that relies on the properties of the scalar product. Because the decomposition is not unique, there are several alternative ways to scale the row and column points of the biplot, which can cause confusion amongst users, especially when software packages are not united in their approach to this issue. We propose a new scaling of the solution, called the standard biplot, which applies equally well to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. The standard biplot also handles data matrices with widely different levels of inherent variance. Two concepts taken from correspondence analysis are important to this idea: the weighting of row and column points, and the contributions made by the points to the solution. In the standard biplot one set of points, usually the rows of the data matrix, optimally represent the positions of the cases or sample units, which are weighted and usually standardized in some way unless the matrix contains values that are comparable in their raw form. The other set of points, usually the columns, is represented in accordance with their contributions to the low-dimensional solution. As for any biplot, the projections of the row points onto vectors defined by the column points approximate the centred and (optionally) standardized data. The method is illustrated with several examples to demonstrate how the standard biplot copes in different situations to give a joint map which needs only one common scale on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot readable. The proposal also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important.

Análise de parcimônia de endemismo de cercopídeos neotropicais (Hemiptera, Cercopidae)

The spittlebugs have an extent distribution in the American continent. Their diversity may determinate endemism areas based on their occurence in different localities. We have used Parsimony Analysis of Endemicity method, which is an important historic biogeography tool for detecting and establishing the relationship among endemics areas. A data matrix was built up based on the occurence registration for the species by 66 genus in whole localities divided in five degrees quadrats in the Neotropical Region, using 49 OGUs (Operative Geografic Units). The presence of the taxa in the areas was coded 1 and the absence 0. The data matrix was analysed based on parsimony analysis through the computer program Hennig 86. Nine endemic areas were stipulated (Mexico + Central America, Venezuelan Savana, Guiana + Suriname, Chaco, Trans-andean, Cerrado, Amazon, Pampa and Atlantic Forest) in the first analysis corroborated with ecological and physiographic patterns in each region. The second analysis was made using 48 genera to obtain the relationship among the nine areas stipulated before. In this analysis just one cladogram (3((1,2)((8,9)(6(7(4,5)))))) was obtained with 192 steps, consistence index 0.80 and retention index 0.85.

Seeing the Wood through the Trees: The Current State of Higher Systematics in the Strepsirhini.

Strepsirhines comprise 10 living or recently extinct families, ≥50% of extant primate families. Their phylogenetic relationships have been intensively studied, but common topologies have only recently emerged; e.g. all recent reconstructions link the Lepilemuridae and Cheirogaleidae. The position of the indriids, however, remains uncertain, and molecular studies have placed them as the sister to every clade except Daubentonia, the preferred sister group of morphologists. The node subtending Afro-Asian lorisids has been similarly elusive. We probed these phylogenetic inconsistencies using a test data set including 20 strepsirhine taxa and 2 outgroups represented by 3,543 mtDNA base pairs, and 43 selected morphological characters, subjecting the data to maximum parsimony, maximum likelihood and Bayesian inference analyses, and reconstructing topology and node ages jointly from the molecular data using relaxed molecular clock analyses. Our permutations yielded compatible but not identical evolutionary histories, and currently popular techniques seem unable to deal adequately with morphological data. We investigated the influence of morphological characters on tree topologies, and examined the effect of taxon sampling in two experiments: (1) we removed the molecular data only for 5 endangered Malagasy taxa to simulate 'extinction leaving a fossil record'; (2) we removed both the sequence and morphological data for these taxa. Topologies were affected more by the inclusion of morphological data only, indicating that palaeontological studies that involve inserting a partial morphological data set into a combined data matrix of extant species should be interpreted with caution. The gap of approximately 10 million years between the daubentoniid divergence and those of the other Malagasy families deserves more study. The apparently contemporaneous divergence of African and non-daubentoniid Malagasy families 40-30 million years ago may be related to regional plume-induced uplift followed by a global period of cooling and drying. © 2013 S. Karger AG, Basel.

Contribution biplots

In order to interpret the biplot it is necessary to know which points usually variables are the ones that are important contributors to the solution, and this information is available separately as part of the biplot s numerical results. We propose a new scaling of the display, called the contribution biplot, which incorporates this diagnostic directly into the graphical display, showing visually the important contributors and thus facilitating the biplot interpretation and often simplifying the graphical representation considerably. The contribution biplot can be applied to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. In the contribution biplot one set of points, usually the rows of the data matrix, optimally represent the spatial positions of the cases or sample units, according to some distance measure that usually incorporates some form of standardization unless all data are comparable in scale. The other set of points, usually the columns, is represented by vectors that are related to their contributions to the low-dimensional solution. A fringe benefit is that usually only one common scale for row and column points is needed on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot legible. Furthermore, this version of the biplot also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important, when they are in fact contributing minimally to the solution.

Weighted metric multidimensional scaling

This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

Simultaneous spectrophotometric determination of ezetimibe and simvastatin in pharmaceutical preparations using chemometric techniques

Two spectrophotometric methods are described for the simultaneous determination of ezetimibe (EZE) and simvastatin (SIM) in pharmaceutical preparations. The obtained data was evaluated by using two different chemometric techniques, Principal Component Regression (PCR) and Partial Least-Squares (PLS-1). In these techniques, the concentration data matrix was prepared by using the mixtures containing these drugs in methanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range of 240 - 300 nm in the intervals with Δλ = 1 nm at 61 wavelengths in their zero order spectra, then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of EZE and SIM in their mixture. The procedure did not require any separation step. The linear range was found to be 5 - 20 µg mL-1 for EZE and SIM in both methods. The accuracy and precision of the methods were assessed. These methods were successfully applied to a pharmaceutical preparation, tablet; and the results were compared with each other.

Resolução multivariada de curvas com mínimos quadrados alternantes: descrição, funcionamento e aplicações

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.

Modélisation des bi-grappes et sélection des variables pour des données de grande dimension : application aux données d’expression génétique

Les simulations ont été implémentées avec le programme Java.

A survey of primary homology assessment: different botanists perceive and define characters in different ways

Cladistic analyses begin with an assessment of variation for a group of organisms and the subsequent representation of that variation as a data matrix. The step of converting observed organismal variation into a data matrix has been considered subjective, contentious, under-investigated, imprecise, unquantifiable, intuitive, as a black-box, and at the same time as ultimately the most influential phase of any cladistic analysis (Pimentel and Riggins, 1987; Bryant, 1989; Pogue and Mickevich, 1990; de Pinna, 1991; Stevens, 1991; Bateman et al., 1992; Smith, 1994; Pleijel, 1995; Wilkinson, 1995; Patterson and Johnson, 1997). Despite the concerns of these authors, primary homology assessment is often perceived as reproducible. In a recent paper, Hawkins et al. (1997) reiterated two points made by a number of these authors: that different interpretations of characters and coding are possible and that different workers will perceive and define characters in different ways. One reviewer challenged us: did we really think that two people working on the same group would come up with different data sets? The conflicting views regarding the reproducibility of the cladistic character matrix provoke a number of questions. Do the majority of workers consistently follow the same guidelines? Has the theoretical framework informing primary homology assessment been adequately explored? The objective of this study is to classify approaches to primary homology assessment, and to quantify the extent to which different approaches are found in the literature by examining variation in the way characters are defined and coded in a data matrix.

Cladistic analysis of the suborder Conulariina Miller and Gurley, 1896 (Cnidaria, Scyphozoa; Vendian-Triassic)

Results of a cladistic analysis of the suborder Conulariina Miller and Gurley, 1896, a major extinct (Vendian-Triassic) group of scyphozoan cnidarians, are presented. The analysis sought to test whether the three conulariid subfamilies (Conulariinae Walcott, 1886, Paraconulariinae Sinclair, 1952 and Ctenoconulariinae Sinclair, 1952) recognized in the Treatise on Invertebrate Paleontology ( TIP) are monophyletic. A total of 17 morphological characters were scored for 16 ingroup taxa, namely the genera Archaeoconularia, Baccaconularia, Climacoconus, Conularia, Conulariella, Conularina, Ctenoconularia, Eoconularia, Glyptoconularia, Metaconularia, Notoconularia, Paraconularia, Pseudoconularia, Reticulaconularia, Teresconularia and Vendoconularia. The extant medusozoan taxa Cubozoa, Stauromedusae, Coronatae and Semaeostomeae served as outgroups. Unweighted analysisof the data matrix yielded 1057 trees, and successive weighting analysis resulted in one of the 1057 original trees. The ingroup is monophyletic with two autapomorphies: (1) the quadrate geometry of the oral region; and (2) the presence of a mineralized (phosphatic) periderm. Within the ingroup, the clade (Vendoconularia, Teresconularia, Conularina, Eoconularia) is supported by the sinusoidal longitudinal geometry of the transverse ridges, and the much larger clade (Baccaconularia, Glyptoconularia, Metaconularia, Pseudoconularia, Conularia, Ctenoconularia, Archaeoconularia, Notoconularia, Climacoconus, Paraconularia, Reticulaconularia) is supported by the presence of external tubercles, which, however, were lost in the clade (Notoconularia, Climacoconus, Paraconularia, Reticulaconularia). As proposed by Van Iten et al. (2000), the clade (Notoconularia, Climacoconus, Paraconularia, Reticulaconularia) is supported by the termination and alternation of the transverse ribs in the corner sulcus. The previously recognized subfamilies Conulariinae, Paraconulariinae and Ctenoconulariinae were not recovered from this analysis. The diagnostic features of Conulariinae (continuation of the transverse ornament across the corner sulcus and lack of carinae) and Ctenoconulariinae ( presence of carinae) are symplesiomorphic or homoplastic, and Paraconulariinae is polyphyletic. The families Conulariellidae Kiderlen, 1937 and Conulariopsidae Sugiyama, 1942, also recognized in the TIP, are monogeneric, and since they provide no additional phylogenetic information, should be abandoned.

Revision and cladistic analysis of Isoctenus and description of a new neotropical genus (Araneae, Ctenidae, Cteninae)

A cladistic analysis was applied to test the monophyly of the genus Isoctenus. The data matrix comprised 28 taxa scored for 53 morphological and two behavioural characters. The analysis resulted in two equally parsimonious trees of 89 steps. The strict consensus was used to discuss the relationships of Isoctenus and related Cteninae genera. Ctenopsis Schmidt is synonymized with Isoctenus. Isoctenus foliifer Bertkau, I. strandi Mello-Leitao, I. eupalaestrus Mello-Leitao, I. janeirus (Walckenaer), I. coxalis (Pickard-Cambridge), I. corymbus Polotow, Brescovit & Pellegatti-Franco and I. malabaris Polotow, Brescovit & Ott are maintained in Isoctenus. Four species currently included in Ctenus are transferred to Isoctenus: I. griseolus (Mello-Leitao) comb. nov., I. taperae (Mello-Leitao) comb. nov., I. herteli (Mello-Leitao) comb. nov. and I. minusculus (Keyserling) comb. nov. The following specific names are synonymized: Ctenus sanguineus Walckenaer, C. semiornatus Mello-Leitao and Ctenopsis stellata Schmidt with Isoctenus janeirus (Walckenaer), Ctenus mourei Mello-Leitao with Isoctenus herteli (Mello-Leitao) and Ctenus pauper Mello-Leitao with Isoctenus strandi Mello-Leitao. Isoctenus sigma Schenkel, described from French Guiana, is transferred to Ctenus. Four species are newly described: Isoctenus areia sp. nov. from Paraiba, Brazil, I. charada sp. nov. and I. segredo sp. nov. from Parana, Brazil, and I. ordinario sp. nov. from south and south-eastern Brazil and north-eastern Argentina. Isoctenus latevittatus Caporiacco is considered species inquirenda. Parabatinga gen. nov. is proposed to include Ctenus brevipes Keyserling. The following synonymies are established: Ctenus taeniatus Keyserling, C. tatarandensis Tullgren, C. anisitsi Strand, C. atrivulvus Strand, C. mentor Strand, C. brevipes brevilabris Strand, Isoctenus masculus Mello-Leitao and Ctenus birabeni Mello-Leitao with Parabatinga brevipes (Keyserling) comb. nov. (C) 2009 The Linnean Society of London, Zoological Journal of the Linnean Society, 2009, 155, 583-614.

Phylogenetic relationships of the Neotropical spider genus Itatiaya (Araneae)

A cladistic analysis using parsimony under equal weights is applied to test the phylogenetic relationships of Itatiaya Mello-Leitao, previously described in Ctenidae. The data matrix comprised 25 taxa scored for a total of 47 characters. The cladistic analysis yielded two equally parsimonious trees of 124 steps. The consensus of the two most parsimonious trees is used to discuss the phylogenetic relationships and justify taxonomic modifications. The results indicate that this genus is a representative of Zoropsidae, which is newly recorded from the Neotropical region. The monophyly of Itatiaya is supported by three non-ambiguous synapomorphies and three homoplastic synapomorphies. A new diagnosis is provided for Itatiaya. Itatiaya pucupucu is placed as sister species to the remaining species of the genus. A polytomic clade composed of Itatiaya modesta, Itatiaya iuba, Itatiaya apipema and the clade formed by Itatiaya tacamby + Itatiaya pykyyra is supported by the presence of modified cylindrical gland spigots. Additionally, the male of I. pykyyra Polotow & Brescovit is described for the first time.

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis