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For the Caatinga vegetation, it has not yet been definitively established which adaptive strategies best define the functional groups of woody plants and which syndromes emerge from the relationships between functional traits to achieve success in a semi-arid tropical region. To fill some of these gaps, we analyzed a specific set of characteristics that make up the LHS scheme of the plant ecological strategy (leaf-heigh-seed). The LHS scheme captures the functional niche of plants regarding the functional traits specific leaf area (SLA), plant height (HE), and seed mass (SM). We associate wood density (WD) to this scheme because this trait is a key feature for the identification of functional strategies in seasonally dry vegetation such as the Caatinga. We measured these characteristics in eight woody species and classified them according to their leaf phenology into deciduous and evergreen. The experiment was carried out between December 2017 and November 2018 in Caatinga areas located in the municipality of Barra de Santana, PB, a semiarid region of Brazil. Using cluster analysis, principal component analysis (PCA) and Pearson correlation analyses, we found significant relations between SLA and SM, and HE and WD. The SLA was the main predictor of plant strategy in the Caatinga. According to this characteristic, we identified two functional groups: species with a low SLA and species with a high SLA. We also recognized differences between deciduous and evergreen species based on the same trait. The traits measured, which represent the axes of the plant ecological strategy scheme LHS and wood density, are efficient in the discrimination of functional groups in the Brazilian semiarid. These groups relate to leaf phenology of woody species in this vegetation.

Despite many studies on fragmentation of tropical forests, the extent to which plant and animal communities are altered in small, isolated forest fragments remains obscure if not controversial. We examined the hypothesis that fragmentation alters the relative abundance of tree species with different vegetative and reproductive traits. In a fragmented landscape (670 km(2) ) of the Atlantic Forest of northeastern Brazil, we categorized 4056 trees of 182 species by leafing pattern, reproductive phenology, and morphology of seeds and fruit. We calculated relative abundance of traits in 50 1-ha plots in three types of forest configurations: forest edges, small forest fragments (3.4-83.6 ha), and interior of the largest forest fragment (3500 ha, old growth). Although evergreen species were the most abundant across all configurations, forest edges and small fragments had more deciduous and semideciduous species than interior forest. Edges lacked supra-annual flowering and fruiting species and had more species and stems with drupes and small seeds than small forest fragments and forest interior areas. In an ordination of species similarity and life-history traits, the three types of configurations formed clearly segregated clusters. Furthermore, the differences in the taxonomic and functional (i.e., trait-based) composition of tree assemblages we documented were driven primarily by the higher abundance of pioneer species in the forest edge and small forest fragments. Our work provides strong evidence that long-term transitions in phenology and seed and fruit morphology of tree functional groups are occurring in fragmented tropical forests. Our results also suggest that edge-induced shifts in tree assemblages of tropical forests can be larger than previously documented., (© 2010 Society for Conservation Biology.)

Coffee samples were analyzed by GC/MS in order to determine the most important peaks for the discrimination of the varieties Arabica and Robusta. The resulting peak tables from chromatographic analysis were aligned and pretreated before being submitted to multivariate analysis. A rapid and easy-to-perform peak alignment procedure, which does not require advanced programming skills to use, was compared with the tedious manual alignment procedure. The influence of three types of data pretreatment, normalization, logarithmic and square root transformations and their combinations, on the variables selected as most important by the regression coefficients of partial least squares-discriminant analysis (PLS-DA), are shown. Test samples different from those used in the calibration and comparison with the substances already known as being responsible for Arabica and Robusta coffees discrimination were used to determine the best pretreatments for both datasets. The data pretreatment consisting of square root transformation followed by normalization (RN) was chosen as being the most appropriate. The results obtained showed that the much quicker automated aligned method could be used as a substitute for the manually aligned method, allowing all the peaks in the chromatogram to be used for multivariate analysis., (Copyright © 2010 Elsevier B.V. All rights reserved.)