Evaluation of mutagenicity and antimutagenicity of different fractions of Pterogyne nitens (Leguminosae), using Tradescantia pallida micronuclei assay

Pterogyne nitens (Fabaceae-Caesalpinioideae) é uma árvore nativa da América do Sul, onde é empregada na medicina popular para o tratamento da ascaridíase. Recentemente, descrevemos o efeito mutagênico do extrato etanólico das folhas de P. nitens. Dessa forma, o presente estudo teve por objetivo aprofundar a avaliação do potencial mutagênico das frações isoladas das folhas de Pterogyne nitens, acetato de etila (AcOEt), n-butanólica (BuOH) e hidroalcóolica (HA). Quando o efeito mutagênico foi observado somente nas maiores concentrações testadas, o potencial antimutagênico também foi avaliado. Os ensaios mutagênicos e antimutagênicos foram realizados utilizando ensaio de micronúcleo em Trandescantia pallida. Na avaliação de mutagenicidade, observou-se o efeito nas frações AcOEt (0,460 mg/mL), BuOH (0,142, 0,285, 0,570 e 1,14 mg/mL) e HA (0,050, 0,100, 0,200 e 0,400 mg/mL). Considerando que o efeito mutagênico da fração AcOEt foi observado somente na concentração mais elevada (0,460 mg/mL), o potencial antimutagênico da mesma foi avaliado. As concentrações de 0,115 e 0,230 mg/mL da fração AcOEt demonstraram atividade antimutagênica. A partir dos resultados do presente estudo, conclui-se que determinadas frações de P. nitens apresentam mutagenicidade (BuOH e HA), enquanto a fração AcOEt apresentou efeito antimutagênico nas maiores concentrações. Esses resultados tornam o estudo da P. nitens bastante promissor, considerando que esta planta possui distribuição geográfica ampla e tem sido pouco estudada.Pterogyne nitens (Fabaceae-Caesalpinioideae) is a tree native to South American, where it is used in folk treatment of ascaridiasis. Recently, we have been describing the mutagenic effect of the ethanol extract of leaves of P. nitens. Thus, the present study aimed at evaluating the mutagenic potential of the ethyl acetate (EtOAc), n- butanol (BuOH) and hydroalcoholic (HA) fractions. When the mutagenic effect was observed only in the highest tested concentrations, the antimutagenic activity was also evaluated. Both mutagenic and antimutagenic assays were performed using T. pallida micronuclei assay. Mutagenicity was observed between different concentrations of the P nitens fractions, EtOAc (0.460 mg/mL), BuOH (0.142, 0.285, 0.570 and 1.14 mg/mL) and HA (0.050, 0.100, 0.200 and 0.400 mg/mL). Whereas the mutagenic effect of the EtOAc fraction was observed in the highest concentration (0.460 mg/mL), its antimutagenic potential was evaluated. The 0.115 and 0.230 mg/mL concentrations of the EtOAc fraction demonstrated antimutagenic activity. Based on the results of the present study we can conclude that some P. nitens fractions (BuOH and HA) demonstrated mutagenic effects whereas the EtOAc fraction shown low mutagenicity and amtimutagenicity in the two higher concentrations. Those results stimulate the studies with P. nitens, which possess spread geographic distribution and it is still low studied

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution