The role of carbohydrates in seed germination and seedling establishment of Himatanthus sucuuba, an Amazonian tree with populations adapted to flooded and non-flooded conditions

Background and Aims In the Amazonian floodplains plants withstand annual periods of flooding which can last 7 months. Under these conditions seedlings remain submerged in the dark for long periods since light penetration in the water is limited. Himatanthus sucuuba is a tree species found in the `varzea` (VZ) floodplains and adjacent non-flooded `terra-firme` (TF) forests. Biochemical traits which enhance flood tolerance and colonization success of H. sucuuba in periodically flooded environments were investigated. Methods Storage carbohydrates of seeds of VZ and TF populations were extracted and analysed by HPAEC/PAD. Starch was analysed by enzyme (glucoamylase) degradation followed by quantification of glucose oxidase. Carbohydrate composition of roots of VZ and TF seedlings was studied after experimental exposure to a 15-d period of submersion in light versus darkness. Key Results The endosperm contains a large proportion of the seed reserves, raffinose being the main nonstructural carbohydrate. Around 93% of the cell wall storage polysaccharides (percentage dry weight basis) in the endosperm of VZ seeds was composed of mannose, while soluble sugars accounted for 2.5%. In contrast, 74% of the endosperm in TF seeds was composed of galactomannans, while 22% of the endosperm was soluble sugars. This suggested a larger carbohydrate allocation to germination in TF populations whereas VZ populations allocate comparatively more to carbohydrates mobilized during seedling development. The concentration of root non-structural carbohydrates in non-flooded seedlings strongly decreased after a 15-d period of darkness, whereas flooded seedlings were less affected. These effects were more pronounced in TF seedlings, which showed significantly lower root non-structural carbohydrate concentrations. Conclusions There seem to be metabolic adjustments in VZ but not TF seedlings that lead to adaptation to the combined stresses of darkness and flooding. This seems to be important for the survival of the species in these contrasting environments, leading these populations to different directions during evolution.

Expression pattern of four storage xyloglucan mobilization-related genes during seedling development of the rain forest tree Hymenaea courbaril L.

During seedling establishment, cotyledons of the rain forest tree Hymenaea courbaril mobilize storage cell wall xyloglucan to sustain growth. The polysaccharide is degraded and its products are transported to growing sink tissues. Auxin from the shoot controls the level of xyloglucan hydrolytic enzymes. It is not yet known how important the expression of these genes is for the control of storage xyloglucan degradation. In this work, partial cDNAs of the genes xyloglucan transglycosylase hydrolase (HcXTH1) and beta-galactosidase (HcBGAL1), both related to xyloglucan degradation, and two other genes related to sucrose metabolism [alkaline invertase (HcAlkIN1) and sucrose synthase (HcSUS1)], were isolated. The partial sequences were characterized by comparison with sequences available in the literature, and phylogenetic trees were assembled. Gene expression was evaluated at intervals of 6 h during 24 h in cotyledons, hypocotyl, roots, and leaves, using 45-d-old plantlets. HcXTH1 and HcBGAL1 were correlated to xyloglucan degradation and responded to auxin and light, being down-regulated when transport of auxin was prevented by N-1-naphthylphthalamic acid (NPA) and stimulated by constant light. Genes related to sucrose metabolism, HcAlkIN1 and HcSUS1, responded to inhibition of auxin transport in consonance with storage mobilization in the cotyledons. A model is proposed suggesting that auxin and light are involved in the control of the expression of genes related to storage xyloglucan mobilization in seedlings of H. courbaril. It is concluded that gene expression plays a role in the control of the intercommunication system of the source-sink relationship during seeding growth, favouring its establishment in the shaded environment of the rain forest understorey.

Relief influence on tree species richness in secondary forest fragments of Atlantic Forest, SE, Brazil

(Relief influence on tree species richness in secondary forest fragments of Atlantic Forest, SE, Brazil). The aim of this work was to explore the relationship between tree species richness and morphological characteristics of relief at the Ibiuna Plateau (SE Brazil). We sampled 61 plots of 0.30 ha, systematically established in 20 fragments of secondary forest (2-274 ha) and in three areas within a continuous secondary forest site, Morro Grande Reserve (9,400 ha). At each plot, 100 trees with diameter at breast height > 5 cm were sampled by the point centered quarter method, and total richness and richness per dispersal and succession class were obtained. The relief was characterized by the mean and variance of slope, elevation, aspect and slope location. There was no significant relationship between relief heterogeneity and tree species richness. Relief parameters generally did not affect tree richness, but elevation was particularly important especially in the continuous forest. Despite the limited range of altitudinal variation (150 m), species richness increases with elevation. The highest areas were also those with the largest forest cover and the lowest disturbance degree, which should contribute to the greater richness of those sites. Our results suggest an indirect influence of relief, due to the fact that deforestation is less intense in higher regions, rather than a direct influence of abiotic factors related to the altitudinal gradient.

Seasonal metabolic changes in a year-round reproductively active subtropical tree-frog (Hypsiboas prasinus)

Although seasonal metabolic variation in ectothermic tetrapods has been investigated primarily in the context of species showing some level of metabolic depression during winter, but several species of anurans maintain their activity patterns throughout the year in tropical and subtropical areas. The tree-frog Hypsiboas prasinus occurs in the subtropical Atlantic Forest and remains reproductively active during winter, at temperatures below 10 degrees C. We compared males calling in summer and winter, and found that males of H. prasinus exhibit seasonal adjustments in metabolic and morphometric variables. Individuals calling during winter were larger and showed higher resting metabolic rates than those calling during summer. Calling rates were not affected by season. Winter animals showed lower liver and heart activity level of citrate synthase (CS), partially compensated by larger liver mass. Winter individuals also showed higher activity Of pyruvate kinase (PK) and lower activity of CS in trunk muscles, and higher activity of CS in leg muscles. Winter metabolic adjustments seem to be achieved by both compensatory mechanisms to the lower environmental temperature and a seasonally oriented aerobic depression of several organs. The impact of seasonal metabolic changes on calling performance and the capacity of subtropical anurans for metabolic thermal acclimatization are also discussed. (C) 2008 Elsevier Inc. All rights reserved.

Paleoamerican Morphology in the Context of European and East Asian Late Pleistocene Variation: Implications for Human Dispersion Into the New World

Early American crania show a different morphological pattern from the one shared by late Native Americans. Although the origin of the diachronic morphological diversity seen on the continents is still debated, the distinct morphology of early Americans is well documented and widely dispersed. This morphology has been described extensively for South America, where larger samples are available. Here we test the hypotheses that the morphology of Early Americans results from retention of the morphological pattern of Late Pleistocene modern humans and that the occupation of the New World precedes the morphological differentiation that gave rise to recent Eurasian and American morphology. We compare Early American samples with European Upper Paleolithic skulls, the East Asian Zhoukoudian Upper Cave specimens and a series of 20 modern human reference crania. Canonical Analysis and Minimum Spanning Tree were used to assess the morphological affinities among the series, while Mantel and Dow-Cheverud tests based on Mahalanobis Squared Distances were used to test different evolutionary scenarios. Our results show strong morphological affinities among the early series irrespective of geographical origin, which together with the matrix analyses results favor the scenario of a late morphological differentiation of modern humans. We conclude that the geographic differentiation of modern human morphology is a late phenomenon that occurred after the initial settlement of the Americas. Am J Phys Anthropol 144:442-453, 2011. (c) 2010 Wiley-Liss, Inc.

A Plant Needs Ants like a Dog Needs Fleas: Myrmelachista schumanni Ants Gall Many Tree Species to Create Housing

Hundreds of tropical plant species house ant colonies in specialized chambers called domatia. When, in 1873, Richard Spruce likened plant-ants to fleas and asserted that domatia are ant-created galls, he incited a debate that lasted almost a century. Although we now know that domatia are not galls and that most ant-plant interactions are mutualisms and not parasitisms, we revisit Spruce`s suggestion that ants can gall in light of our observations of the plant-ant Myrmelachista schumanni, which creates clearings in the Amazonian rain forest called ""supay-chakras,"" or ""devil`s gardens."" We observed swollen scars on the trunks of nonmyrmecophytic canopy trees surrounding supay-chakras, and within these swellings, we found networks of cavities inhabited by M. schumanni. Here, we summarize the evidence supporting the hypothesis that M. schumanni ants make these galls, and we hypothesize that the adaptive benefit of galling is to increase the amount of nesting space available to M. schumanni colonies.

Anthocyanins and tannins in ozone-fumigated guava trees

Psidium guajava ""Paluma"", a tropical tree species, is known to be an efficient ozone indicator in tropical countries. When exposed to ozone, this species displays a characteristic leaf injury identified by inter-veinal red stippling on adaxial leaf surfaces. Following 30 days of three ozone treatments consisting of carbon filtered air (CF - AOT40 = 17 ppb h), ambient non-filtered air (NF - AOT40 = 542 ppb h) and ambient non-filtered air + 40 ppb ozone (NF + O(3) - AOT40 - 7802 ppb h), the amounts of residual anthocyanins and tannins present in 10 P. guajava (""Paluma"") saplings were quantified. Higher amounts of anthocyanins were found in the NF + O(3) treatment (1.6%) when compared to the CF (0.97%) and NF (1.30%) (p < 0.05), and of total tannins in the NF + O(3) treatment (0.16%) compared to the CIF (0.14%). Condensed tannins showed the same tendency as enhanced amounts. Regression analyses using amounts of tannins and anthocyanins, AOT40 and the leaf injury index (LII), showed a correlation between the leaf injury index and quantities of anthocyanins and total tannins. These results are in accordance with the association between the incidence of red-stippled leaves and ozone polluted environments. (C) 2009 Elsevier Ltd. All rights reserved.

Building binary-tree-based multiclass classifiers using separability measures

Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.

Heteroscedastic Nonlinear Regression Models

In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Methods of Estimation in Multiple Linear Regression: Application to Clinical Data

Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.