In order to develop niche models for tree species characteristic of the cerrado vegetation (woody savannas) of central South America, and to hindcast their distributions during the Last Glacial Maximum and Last Inter‐Glacial, we compiled a dataset of tree species checklists for typical cerrado vegetation (n = 282) and other geographically co‐occurring vegetation types, e.g. seasonally dry tropical forest (n = 355). We then performed an indicator species analysis to select ten species that best characterize typical cerrado vegetation and developed niche models for them using the Maxent algorithm. We used these models to assess the probability of occurrence of each species across South America at the following time slices: Current (0 ka pre‐industrial), Holocene (6 ka BP), Last Glacial Maximum (LGM – 21 ka BP), and Last Interglacial (LIG – 130 ka BP). The niche models were robust for all species and showed the highest probability of occurrence in the core area of the Cerrado Domain. The palaeomodels suggested changes in the distributions of cerrado tree species throughout the Quaternary, with expansion during the LIG into the adjacent Amazonian and Atlantic moist forests, as well as connections with other South American savannas. The LGM models suggested a retraction of cerrado vegetation to inter‐tableland depressions and slopes of the Central Brazilian Highlands. Contrary to previous hypotheses, such as the Pleistocene refuge theory, we found that the widest expansion of cerrado tree species seems to have occurred during the LIG, most probably due to its warmer climate. On the other hand, the postulated retractions during the LGM were likely related to both decreased precipitation and temperature. These results are congruent with palynological and phylogeographic studies in the Cerrado Domain.
Aim The aim of this study was to test the role of environmental factors and spatially autocorrelated processes, such as historical fragmentation and dispersal limitation, in driving floristic variation across seasonally dry tropical forests (SDTFs) in eastern South America.Location SDTFs extending from the Caatinga phytogeographical domain of north-eastern Brazil to the Chaco phytogeographical domain of northern Argentina, an area referred to as the Dry Diagonal.Methods We compiled a database of 282 inventories of woody vegetation in SDTFs from across the Dry Diagonal and combined this with data for 14 environmental variables. We assessed the relative contribution of spatially autocorrelated processes and environmental factors to the floristic turnover among SDTFs across the Dry Diagonal using variation partitioning methods. In addition, we used multivariate analyses to determine which environmental factors were most important in explaining the turnover.Results We found that the environmental factors measured (temperature, precipitation and edaphic conditions) explained 21.3% of the variation in species composition, with 14.1% of this occurring independently of spatial autocorrelation. A spatially structured fraction of 4.2% could not be accounted for by the environmental factors measured. The main axis of compositional variation was significantly correlated with a north-south gradient in temperature regime. At the extreme south of the Dry Diagonal, a cold temperature regime, in which frost occurred, appeared to underlie floristic similarities between chaco woodlands and southern SDTFs.Main conclusions Environmental variables, particularly those related to temperature regime, seem to be the most significant factors affecting variation in species composition of SDTFs. Thus historical fragmentation and isolation alone cannot explain the turnover in species composition within SDTFs, as is often assumed. Compositional and environmental heterogeneity needs to be taken into account both to understand the past distribution of SDTFs and to manage and conserve this key tropical biome.
35Aim: We aimed to assess the contribution of marginal habitats to the tree species 36 richness of the Mata Atlântica (Atlantic Forest) biodiversity hotspot. In addition, we 37 aimed to determine which environmental factors drive the occurrence and 38 distribution of these marginal habitats. Brazil where it largely occurs, stretches for over 3,500km across equatorial, tropical 73 and subtropical latitudes, and is renowned worldwide for being one of the 35 74 biodiversity hotspots for conservation prioritisation (Myers et al., 2000). Its 75 importance is also demonstrated by its designation as one of the five primary 76 vegetation 'Domains' of Brazil (IBGE, 1993; Ab'Sáber, 2003), the others being the The prevailing land cover of these bordering Domains are semi-arid thorn woodlands distribution of rain forest species in the Atlantic Domain, which at its harshest 88 extremes give rise to distinct habitats (one for each factor), referred to as marginal 89 habitats. Therefore, the rain forest is placed by Scarano (2009) (Galindo-Leal et al., 2003; Tabarelli et al., 2004; 2005; Joly et al., 2014 203The data were originally compiled from an extensive survey of published and 217It also excludes checklists with low species richness (< 20 species), because this is 218 often due to low sampling/collecting efforts, which results in poor descriptive power. 219This study used a subset of tree inventories from the NTT database, The distribution of the sites in the ordination space yielded by NMDS (Fig. 3a waterlogged soils at positive scores (tropical riverine forests). 377The floristic composition of marginal habitats is not simply a nested subset of 378 the more species rich rain forest. The turnover component accounts for most of the 379 floristic dissimilarity of each marginal habitat in relation to rain forests (Fig. 4). 380Nestedness is higher than the turnover component in very few cases (i.e., few The forward selection procedure retained 13 environmental variables in the 390 model to explain the variation in tree species composition (Table 1). In partitioning 391 the variation explained by the retained environmental and spatial predictors, we 392 found that the environmental fraction explained 27% of the variation, 5% of which 393 was independent of spatial autocorrelation (P < 0.01). The environmental predictors 394could not account for a spatially structured variation of 12% (P < 0.01), and 61% of 395 the variation remained unexplained (see discussion for more details). 396The harshest extremes of the retained environmental variables (Table 1) rock outcrops (including campos rupestres) from all others vegetation types (Fig. 3a). 404Within the rock outcrop habitat, the frequency of frost was associated with the forests and tropical riverine forests (Figs. 2b and 3b). At the harshest extreme of the 414 drought-stress gradient (Fig. 3b) Fig. S1). Because the overall floristic dissimilarity between cloud forests and rain 430forests was relatively low (Fig. 3), we assessed the rates of endemism con...
1. The Cerrado Domain of central Brazil houses the largest extent of savanna in the Neotropics, but despite its simple characterization as a giant savanna, it contains considerable vegetation heterogeneity that is poorly understood. 2. We aimed to determine how vegetation types in the Cerrado diverge in their tree species composition and what role ecological factors play in driving compositional patterns.3. We used a dataset of 1,165 tree species inventories spread across the Cerrado Domain, which come from six vegetation types that have a substantial arboreal component: woody savannas, dystrophic cerradão, mesotrophic cerradão, seasonally dry tropical forests, semideciduous forests and evergreen forests. We found three extremes in terms of tree species composition, with clear underlying ecological drivers, which leads us to propose a ternary model, the Cerrado Vegetation Triangle, to characterize woody vegetation in the Cerrado. At one extreme, we found that semideciduous and evergreen forests are indistinguishable floristically and are found in areas with high water availability. At another extreme lie seasonally dry tropical forests which are found on more fertile soils. At the third extreme, we found that all types of savanna, and dystrophic cerradão, are highly similar in tree species composition and are commonly found in areas of poor soils and high flammability. Mesotrophic cerradão is transitional in tree species composition between savannas and seasonally dry tropical forest. The lack of variation in tree species composition attributed to climatic variablesindicates that within homogeneous macroclimatic zones, many types of forest and savanna co-exist due to complex mosaics of local substrate heterogeneity and fire history. |
The evolutionary processes underlying the high diversity and endemism in the Cerrado, the most extensive Neotropical savanna, remain unclear, including the factors promoting the presence and evolution of savanna enclaves in the Amazon forest. In this study, we investigated the effects of past climate changes on genetic diversity, dynamics of species range and the historical connections between the savanna enclaves and Cerrado core for Qualea grandiflora, a tree species widely distributed in the biome. Totally, 40 populations distributed in the Cerrado core and Amazon savannas were analyzed using chloroplast and nuclear DNA sequences. We used phylogeographic, coalescent and ecological niche modeling approaches. Genetic data revealed a phylogeographic structure shaped by Pleistocene climatic oscillations. An eastern-western split in the Cerrado core was observed. The central portion of the Cerrado core harbored most of the sampled diversity for cpDNA. Ecological niche models predicted the presence of a large historical refuge in this region and multiple small refuges in peripheral areas. Relaxed Random Walk (RRW) models indicated the ancestral population in the north-western border of the central portion of the Cerrado core and cyclical dynamics of colonization related to Pleistocene climatic oscillations. Central and western ancient connections between Cerrado core and Amazonian savannas were observed. No evidence of connections among the Amazonian savannas was detected. Our study highlights the importance of Pleistocene climatic oscillations for structuring the genetic diversity of Q. grandiflora and complex evolutionary history of ecotonal areas in the Cerrado. Our results do not support the recent replacement of a large area in the Amazon forest by savanna vegetation. The Amazonian savannas appear to be fragmented and isolated from each other, evolving independently a long ago.
The aim of this work was to compare the performance of isotopeselective non-dispersive infrared spectrometry (IRIS) for the 13 C-urea breath test with the combination of the 14 C-urea breath test ( 14 C-UBT), urease test and histologic examination for the diagnosis of H. pylori (HP) infection. Fifty-three duodenal ulcer patients were studied. All patients were submitted to gastroscopy to detect HP by the urease test, histologic examination and 14 C-UBT. To be included in the study the results of the 3 tests had to be concordant. Within one month after admission to the study the patients were submitted to IRIS with breath samples collected before and 30 min after the ingestion of 75 mg 13 Curea dissolved in 200 ml of orange juice. The samples were mailed and analyzed 11.5 (4-21) days after collection. Data were analyzed statistically by the chi-square and Mann-Whitney test and by the Spearman correlation coefficient. Twenty-six patients were HP positive and 27 negative. There was 100% agreement between the IRIS results and the HP status determined by the other three methods. Using a cutoff value of delta-over-baseline (DOB) above 4.0 the IRIS showed a mean value of 19.38 (minimum = 4.2, maximum = 41.3, SD = 10.9) for HPpositive patients and a mean value of 0.88 (minimum = 0.10, maximum = 2.5, SD = 0.71) for negative patients. Using a cutoff value corresponding to 0.800% CO 2 /weight (kg), the 14 C-UBT showed a mean value of 2.78 (minimum = 0.89, maximum = 5.22, SD = 1.18) in HP-positive patients. HP-negative patients showed a mean value of 0.37 (minimum = 0.13, maximum = 0.77, SD = 0.17). IRIS is a lowcost, easy to manage, highly sensitive and specific test for H. pylori detection. Storing and mailing the samples did not interfere with the performance of the test.
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