Estrutura e composição de espécies arbóreas em um trecho de floresta ombrófila densa atlântica no litoral norte do estado de São Paulo e padrões de similaridade florística em escala regional

Pós-graduação em Ciências Biológicas (Biologia Vegetal) - IBRC

Estimating abundance and spatial distribution patterns of the bubble crab Dotilla fenestrata (Crustacea : Brachyura)

The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.

Seasonal changes in fecal testosterone concentrations and their relationship to the reproductive behavior, antler cycle and grouping patterns in free-ranging male Pampas deer (Ozotoceros bezoarticus bezoarticus)

The purpose of this study was to validate noninvasive endocrine monitoring techniques for Pampas deer and to evaluate seasonal changes in testicular steroidogenic activity and their correlation to reproductive behavior, antler cycle and group size. Thus, fecal samples, behavioral data and observations of antler status were collected at monthly intervals during 1 year from free-ranging Pampas deer stags (three radio-collared individuals and 15 random individuals) living in Emas National Park, Brazil (18 degrees S latitude). Fecal steroids were extracted using 80% methanol and steroid concentrations were quantified by a commercial enzyme immunoassay (EIA). Fecal testosterone concentrations peaked in December-January (summer), March (early autumn) and in August-September (winter-spring), with minimal values from April-July. Reproductive behavior had two peaks, the first in December-January, characterized by predominately anogenital sniffing, flehmen, urine sniffing, chasing and mounting behavior, and the second peak in July-September (behavior primarily related to gland marking). There were significant correlations between fecal testosterone and reproductive behavior (r = 0.490), and between fecal testosterone and antler phases (r = 0.239). Antler casting and regrowth occurred under low testosterone concentrations, whereas velvet shedding was associated with high concentrations of testosterone. We inferred that Pampas deer stags exhibited a seasonal cycle that modulated sexual behavior and the antler cycle, and we concluded that fecal steroid analysis was a practical and reliable non-invasive method for the evaluation of the endocrine status of free-ranging Pampas deer. (c) 2004 Elsevier B.V. All rights reserved.

Strain differentiation of Trichophyton rubrum by random amplification of polymorphic DNA (RAPD)

Trichophyton rubrum é um importante agente causal de dermatomicose. Os métodos de tipagem molecular têm sido recentemente desenvolvidos para responder questões sobre epidemiologia e auxiliar no esclarecimento de recidivas, após o tratamento. As seqüências aleatórias 1- (5'-d[GGTGCGGGAA]-3') e 6- (5'-d[CCCGTCAGCA]-3') foram usadas para tipagem molecular deste fungo por RAPD produzindo variabilidade intraespecífica. Cinco padrões foram observados entre os 10 isolados de T. rubrum, com ambas as seqüências. Foi concluído que a análise por RAPD pode ser utilizada para estudos epidemiológicos.

Identification of a gene encoding adaptin-like protein in the Paracoccidioides brasiliensis genome by random amplified polymorphic DNA analysis

Paracoccidioides brasiliensis isolates are not homogeneous in their patterns of pathogenicity in animals and adhesion to epithelial cells. During this investigation, genotypic differences were observed between two samples of P. brasiliensis strain 18 yeast phase (Pbl 8) previously cultured many times, one taken before (Pb18a) and the other after (Pb18b) animal inoculation. Random amplified polymorphic DNA analysis using the primer OPJ4 distinguished Pb18b from Pbl Ba by one 308 bp DNA fragment, which after cloning and sequencing was shown to encode a polypeptide sequence homologous to the protein beta-adaptin. It is suggested, by comparison to other micro-organisms, that this protein might play an important role in the virulence of P. brasiliensis. This result demonstrates the influence of in vitro subculturing on the genotype of this organism.

PCR primed with minisatellite core sequences yields species-specific patterns and assessment of population variability in fishes of the genus Brycon

Minisatellite core sequences were used as single primers in polymerase chain reaction (PCR) to amplify genomic DNA in a way similar to the random amplified polymorphic DNA methodology. This technique, known as Directed Amplification of Minisatellite-region DNA, was applied in order to differentiate three neotropical fish species (Brycon orbignyanus, B. microlepis and B. lundii ) and to detect possible genetic variations among samples of the threatened species, B. lundii , collected in two regions with distinct environmental conditions in the area of influence of a hydroelectric dam. Most primers generated species-specific banding patterns and high levels of intraspecific polymorphism. The genetic variation observed between the two sampling regions of B. lundii was also high enough to suggest the presence of distinct stocks of this species along the same river basin. The results demonstrated that minisatellite core sequences are potentially useful as single primers in PCR to assist in species and population identification. The observed genetic stock differentiation in B. lundii associated with ecological and demographic data constitute a crucial task to develop efficient conservation strategies in order to preserve the genetic diversity of this endangered fish species.

The shared influence of phylogeny and ecology on the reproductive patterns of Myrteae (Myrtaceae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic variability analysis among clinical Candida spp. isolates using random amplified polymorphic DNA

The patterns of genetic variation of samples of Candida spp. isolated from patients infected with human immunodeficiency virus in Vitória, state of Espírito Santo, Brazil, were examined. Thirty-seven strains were isolated from different anatomical sites obtained from different infection episodes of 11 patients infected with the human immunodeficiency virus (HIV). These samples were subjected to randomly amplified polymorphic DNA (RAPD) analysis using 9 different primers. Reproducible and complex DNA banding patterns were obtained. The experiments indicated evidence of dynamic process of yeast colonization in HIV-infected patients, and also that certain primers are efficient in the identification of species of the Candida genus. Thus, we conclude that RAPD analysis may be useful in providing genotypic characters for Candida species typing in epidemiological investigations, and also for the rapid identification of pathogenic fungi.

Virulence profile of ten Paracoccidioides brasiliensis isolates: association with morphologic and genetic patterns

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spatial patterns or trees in the Picinguara coastal sandy forest (state of Sao-Paulo, Brazil)

The species of the sandy plains forests (forests of the ''restingas'') have not yet had their spatial patterns studied as aids to the understanding of the diversity found in the different physiognomies along the Brazilian coast. In this paper a 10 x 10 m quadrat framework laid in a hectare of a tree dominant forest in the sandy plains of the Picinguaba area of the Serra do Mar State Park (municipality of Ubatuba, state of São Paulo, Brazil) was used to assess the spatial pattern of distribution for the ten most important species : Pera glabrata, Euterpe edulis, Eugenia brasiliensis, Alchornea triplinervea, Guatteria australis, Myrcia racemosa, Jacaranda semiserrata, Guarea macrophylla, Euplassa cantareirae and Nectandra oppositifolia. The spatial patterns were inferred through the calculations of their T-Square Index (C) and Dispersal Distance Index (I). P. glabrata shows a random pattern, E. edulis aggregate, E. brasiliensis, A. triplinervia, G. australis, E. cantareirae and N. oppositifolia with a tendency between aggregate and uniform and, M. racemosa, J. semiserrata and G. macrophylla between aggregate and random. Although the indexes are dependent of the sample size and of the technique adjustments, the relationship of the pattern with the environmental factors is shown by clustering methods. The results give confirmation of how the spatial patterns bring associations between populations and shape of the vegetation physiognomy.

HIERARCHICAL VERSUS NONHIERARCHICAL PATTERNS OF GENETIC DISTANCES AMONG POPULATIONS - A SIMULATION STUDY

A simulation study was made of the effects of mixing two evolutionary forces (natural selection and random genetic drift), combined in a single data matrix of gene frequencies, on the resulting genetic distances among populations. Twenty-one, kinds of simulated gene frequencies surfaces, for 15 populations linearly distributed over geographic space, were used to construct 21 data matrices, combining different proportions of two types of surfaces (gradients and random surfaces). These matrices were analysed by Unweighted Pair-Group Method - Arithmetic Averages (UPGMA), clustering and Principal Coordinate Analysis. The results obtained show that ordination is more accurate than UPGMA in revealing the spatial patterns in the genetic distances, in comparison with results obtained using the Mantel test comparing directly genetic and geographic distances.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)