Our aims were to quantify and map the plant sub regions of the the Caatinga, that covers 844,453 km2 and is the largest block of seasonally dry forest in South America. We performed spatial analyses of the largest dataset of woody plant distributions in this region assembled to date (of 2,666 shrub and tree species; 260 localities), compared these distributions with the current phytogeographic regionalizations, and investigated the potential environmental drivers of the floristic patterns in these sub regions. Phytogeographical regions were identified using quantitative analyses of species turnover calculated as Simpson dissimilarity index. We applied an interpolation method to map NMDS axes of compositional variation over the entire extent of the Caatinga, and then classified the compositional dissimilarity according to the number of biogeographical sub regions identified a priori using k-means analysis. We used multinomial logistic regression models to investigate the influence of contemporary climatic productivity, topographic complexity, soil characteristics, climate stability since the last glacial maximum, and the human footprint in explaining the identified sub regions. We identified nine spatially cohesive biogeographical sub regions. Current productivity, as indicated by an aridity index, was the only explanatory variable retained in the best model, explaining nearly half of the floristic variability between sub regions. The highest rates of endemism within the Caatinga were in the Core and Periphery Chapada Diamantina sub regions. Our findings suggest that the topographic complexity, soil variation, and human footprint in the Caatinga act on woody plant distributions at local scales and not as determinants of broad floristic patterns. The lack of effect of climatic stability since the last glacial maximum probably results from the fact that a single measure of climatic stability does not adequately capture the highly dynamic climatic shifts the region suffered during the Pleistocene. There was limited overlap between our results and previous Caatinga classifications.

Despite its implications for carbon storage, animal conservation, and plant regeneration, the variation in the structure of heath vegetation in South America is still poorly studied. In this study, we aimed at examining the edaphic and topographic determinants of this variation along 85 plots (5 9 5 m) randomly distributed in a restinga heath vegetation occurring on coastal dune fields in northeastern Brazil. We carried out a PCA analysis to reduce eleven vegetation descriptors into a small number of structural gradients, which were then assessed by a stepwise standard least-squares multiple regression to reveal the effects of the abiotic environment on structure. The three following hypotheses were tested: (1) both soils and topography are important to explain variation in vegetation structure at local scale; (2) herbaceous plants, cactus, and woody plants show differential responses to soil and topographic variations; and (3) soil acidity and salinity are more important determinants of herbaceous cover than woody plant variation. PCA analysis revealed three major structural gradients related to biomass, herbaceous cover, and leaning plants, respectively. These gradients were only related to calcium and nitrogen contents, which partially supports our first hypothesis. Our results also suggest that different groups of plants have different responses to abiotic gradients that are exposed. The effect of the soil acidity and salinity did not appear to present an immediate strong influence on the herbaceous community. It seems that a reduced number of edaphic factors promote the variation in vegetation structure in the restinga heath vegetation.

Despite growing knowledge on the distribution and functioning of dryland vegetation types, their internal biodiversity structure (i.e., subregions) is much less studied. In the delineation of subregions, the use of species occurrence or abundance data may reveal different aspects of metacommunity structure. We revisit the issue of the bioregionalization of the woody flora of the Caatinga, the largest block of the dry forest and woodland biome in Latin America, using abundance data. We also evaluated the drivers of the spatial distribution of plant subregions: historical, current environmental and human effects. Using a K-means partition on interpolated NMDS axes, we identified 10 abundance subregions. Aridity, topography and soil, biome stability since the Pleistocene, and historical indigenous effects were retained by a Multinomial Logistic regression model, and their combined fractions explained most of the abundance variability in subregions. The subregions we present may support spatialized conservation and management decisions in the lack of detailed local data.The present results confirm the Caatinga woody flora broad composition patterns uncovered using presence-absence data in previous studies. Additionally, we found larger subregions than those identified with presence and absence data, suggesting the existence of oligarchies of dominant species in distinct parts of the Caatinga biome.