Isotopic view of vegetation and carbon and nitrogen cycles in a cerrado ecosystem, southeastern Brazil

Carbon and nitrogen biogeochemical cycles in savannas are strongly regulated by the seasonal distribution of precipitation and pulses of nutrients released during the wetting of the dry soil and are critical to the dynamics of microorganisms and vegetation. The objective of this study was to investigate the spatial and temporal variability of C and N isotope ratios as indicators of the cycling of these elements in a cerrado sensu stricto area, within a protected area in a State Park in the state of São Paulo, Brazil. The foliar δ13C and δ15N values varied from -33.6 to -24.4 ‰ and -2.5 to 4.5 ‰, respectively. The δ13C values showed a consistent relationship with canopy height, revealing the importance of structure of the canopy over the C isotopic signature of the vegetation. Carbon isotopic variations associated with the length of the dry season indicated the importance of recent fixed C to the integrated isotopic signature of the leaf organic C. The studied Cerrado species showed a depleted foliar δ15N, but a wide range of foliar Nitrogen with no difference among canopy heights. However, seasonal variability was observed, with foliar δ15N values being higher in the transition period between dry and rainy seasons. The variation of the foliar C and N isotope ratios presented here was consistent with highly diverse vegetation with high energy available but low availability of water and N.

Influence of soil properties on the abundance of plant species in ferruginous rocky soils vegetation, southeastern Brazil

Ferruginous "campos rupestres" are a particular type of vegetation growing on iron-rich primary soils. We investigated the influence of soil properties on plant species abundance at two sites of ferruginous "campos rupestres" and one site of quartzitic "campo rupestre", all of them in "Quadrilátero Ferrífero", in Minas Gerais State, southeastern Brazil. In each site, 30 quadrats were sampled to assess plant species composition and abundance, and soil samples were taken to perform chemical and physical analyses. The analyzed soils are strongly acidic and presented low fertility and high levels of metallic cations; a principal component analysis of soil data showed a clear segregation among sites due mainly to fertility and heavy metals content, especially Cu, Zn, and Pb. The canonical correspondence analysis indicated a strong correlation between plant species abundance and soil properties, also segregating the sites.

Saving our science from ourselves: the plight of biological classification

Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics) is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Molecular phylogeny of advanced snakes (Serpentes, Caenophidia) with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

We present a molecular phylogenetic analysis of caenophidian (advanced) snakes using sequences from two mitochondrial genes (12S and 16S rRNA) and one nuclear (c-mos) gene (1681 total base pairs), and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypotheses for the composition and relationships of others. The major salient points of our analysis are: (1) placement of Acrochordus, Xenodermatids, and Pareatids as successive outgroups to all remaining caenophidians (including viperids, elapids, atractaspidids, and all other "colubrid" groups); (2) within the latter group, viperids and homalopsids are sucessive sister clades to all remaining snakes; (3) the following monophyletic clades within crown group caenophidians: Afro-Asian psammophiids (including Mimophis from Madagascar), Elapidae (including hydrophiines but excluding Homoroselaps), Pseudoxyrhophiinae, Colubrinae, Natricinae, Dipsadinae, and Xenodontinae. Homoroselaps is associated with atractaspidids. Our analysis suggests some taxonomic changes within xenodontines, including new taxonomy for Alsophis elegans, Liophis amarali, and further taxonomic changes within Xenodontini and the West Indian radiation of xenodontines. Based on our molecular analysis, we present a revised classification for caenophidians and provide morphological diagnoses for many of the included clades; we also highlight groups where much more work is needed. We name as new two higher taxonomic clades within Caenophidia, one new subfamily within Dipsadidae, and, within Xenodontinae five new tribes, six new genera and two resurrected genera. We synonymize Xenoxybelis and Pseudablabes with Philodryas; Erythrolamprus with Liophis; and Lystrophis and Waglerophis with Xenodon.

A new classification of foods based on the extent and purpose of their processing

This paper describes a new food classification which assigns foodstuffs according to the extent and purpose of the industrial processing applied to them. Three main groups are defined: unprocessed or minimally processed foods (group 1), processed culinary and food industry ingredients (group 2), and ultra-processed food products (group 3). The use of this classification is illustrated by applying it to data collected in the Brazilian Household Budget Survey which was conducted in 2002/2003 through a probabilistic sample of 48,470 Brazilian households. The average daily food availability was 1,792 kcal/person being 42.5% from group 1 (mostly rice and beans and meat and milk), 37.5% from group 2 (mostly vegetable oils, sugar, and flours), and 20% from group 3 (mostly breads, biscuits, sweets, soft drinks, and sausages). The share of group 3 foods increased with income, and represented almost one third of all calories in higher income households. The impact of the replacement of group 1 foods and group 2 ingredients by group 3 products on the overall quality of the diet, eating patterns and health is discussed.

Carbon Stocks and Isotopic Composition of the Organic Matter in Soils Covered by Native Vegetation and Pasture in Sorocaba, SP, Brazil

Land cover change constitutes one of main way of alteration of soil organic matter in both quantitative and qualitative terms. The goal of this study was to compare the carbon stock and the isotopic signature of the organic matter in the soil of areas with different land use,covered with forest and grass (pasture). The study area is located at Sorocaba, SP, Brazil. Using un-deformed soil samples, we measured the carbon content and bulk density. The isotopic signature of soil carbon was determined through the analysis of isotopic ratio (12)C/(13)C. The pasture soil stocks 48% less carbon than the soil covered by natural forest. The isotopic signature indicated that 42.2% of organic matter of the soil covered by pasture is originated from grasses. This characterizes a highly degradation of organic matter in the environment, both quantitatively and qualitatively. Hence, some guidelines of recuperation are described in order to restore the soil organic matter, structure and porosity.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

LIPSCHITZ CLASSIFICATION OF FUNCTIONS ON A HOLDER TRIANGLE

The problem of semialgebraic Lipschitz classification of quasihomogeneous polynomials on a Holder triangle is studied. For this problem, the ""moduli"" are described completely in certain combinatorial terms.

Discharge-calcium concentration relationships in streams of the Amazon and Cerrado of Brazil: soil or land use controlled

Stream discharge-concentration relationships are indicators of terrestrial ecosystem function. Throughout the Amazon and Cerrado regions of Brazil rapid changes in land use and land cover may be altering these hydrochemical relationships. The current analysis focuses on factors controlling the discharge-calcium (Ca) concentration relationship since previous research in these regions has demonstrated both positive and negative slopes in linear log(10)discharge-log(10)Ca concentration regressions. The objective of the current study was to evaluate factors controlling stream discharge-Ca concentration relationships including year, season, stream order, vegetation cover, land use, and soil classification. It was hypothesized that land use and soil class are the most critical attributes controlling discharge-Ca concentration relationships. A multilevel, linear regression approach was utilized with data from 28 streams throughout Brazil. These streams come from three distinct regions and varied broadly in watershed size (< 1 to > 10(6) ha) and discharge (10(-5.7)-10(3.2) m(3) s(-1)). Linear regressions of log(10)Ca versus log(10)discharge in 13 streams have a preponderance of negative slopes with only two streams having significant positive slopes. An ANOVA decomposition suggests the effect of discharge on Ca concentration is large but variable. Vegetation cover, which incorporates aspects of land use, explains the largest proportion of the variance in the effect of discharge on Ca followed by season and year. In contrast, stream order, land use, and soil class explain most of the variation in stream Ca concentration. In the current data set, soil class, which is related to lithology, has an important effect on Ca concentration but land use, likely through its effect on runoff concentration and hydrology, has a greater effect on discharge-concentration relationships.

Late Pleistocene and Holocene vegetation changes in northeastern Brazil determined from carbon isotopes and charcoal records in soils

Northeastern Brazil represents a strategic area in terms of Quaternary records of environmental changes in South America due to its distinct semi-arid climate in near equatorial latitudes. In this study, carbon isotope and charcoal distribution records in soils are used to characterize vegetation dynamics, forest fires and their relation to climate change since the Late Pleistocene in the States of Ceara, Piaui and Paraiba, Northeastern Brazil. At the Ceara site, the carbon isotope record showed an enrichment trend from -24%(o) to 19%(o) during the early-mid Holocene, indicating an opening of vegetation and expansion of savanna vegetation (C(4) plants) during this period. A trend toward more depleted delta(13)C values (similar to-32%.) in the late Holocene indicates an expansion of forest vegetation (C(3) plants). A similar trend is observed at the Piaui and Paraiba sites where values of similar to-24%0 are associated with open forest vegetation during the late Pleistocene. In the early-mid Holocene, delta(13)C values of up to -18.0%(o), suggest the expansion of C4 plants. Based on the carbon isotope data, it is postulated that from similar to 18,000 cal yr B.P. to similar to 11,800 cal yr B.P.-similar to 10,000 cal yr B.P. arboreal vegetation was dominant in northeastern Brazil and is associated with humid climates. The savanna expanded from similar to 10,000 cal yr B.P. to similar to 4500-3200 cal yr B.P. due to a less humid/drier climatic phase, also supported by the significant presence of fires (charcoal fragments in the soil). From approximately 3200-2000 cal yr B.P. to the present, carbon isotope records suggest forest expansion and a more humid phase. These results form part of a regional pattern since they are in agreement with paleovegetation records obtained in regions of Maranhao, northeastern Brazil and in the Amazon and Rondonia States, northern Brazil. (C) 2010 Elsevier B.V. All rights reserved.

Last glacial maximum (LGM) vegetation changes in the Atlantic Forest, southeastern Brazil

This study was carried out in a continental Atlantic Forest located in the southern region of Sao Paulo State, southeastern Brazil. The aim of the study was to evaluate the vegetation dynamics in similar to 70 km forest ecosystem transect that occurred during the late Pleistocene and Holocene in this region, using the stable carbon isotopes (delta C-13) analysis on soil organic matter (SOM) and the C-14 dating of buried charcoal fragments and the humin fraction of SOM. The isotope data (delta C-13) of SOM in the deeper horizons, indicating the presence of more open vegetation than the present, with a probable mixture of C-3 and C-4 plants, suggesting the presence of a drier climate in the period of similar to 20 ka to similar to 16-14 ka BP. From similar to 16 to 14 ka BP to the present, a significant predominance Of C3 plants was observed, indicating an expansion of the forest, probably associated with the presence of a more humid climate than the previous period. The results indicated the presence of open vegetation during the late glacial, probably associated with a drier period, also observed in other regions of Brazil. The Atlantic Forest ecosystem seems to have developed at least since the early Holocene in Southeastern Brazil. (c) 2007 Elsevier Ltd and INQUA. All rights reserved.