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Revisiting Patterns of Tree Species Composition and their Driving Forces in the Atlantic Forests of Southeastern Brazil
Authors:Pedro V. Eisenlohr  Ary Teixeira de Oliveira‐Filho
Affiliation:1. Faculdade de Ciências Biológicas e Agrárias, Universidade do Estado de Mato Grosso, Alta Floresta, Mato Grosso, Brazil;2. Departamento de Botanica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
Abstract:The elucidation of phytogeographic patterns and their drivers in biodiversity hotspots is essential to the study of ecology and the conservation of these areas. In 2000, an important study by Oliveira‐Filho and Fontes led to changes in the paradigms that define our understanding of the Atlantic Forest (Brazil). Here, our aim was to revisit this study using a more comprehensive set of environmental predictors, an updated and much larger tree species dataset and checklist, and more refined data analyses. We performed exploratory and confirmatory analyses, including the modeling of the spatial components with Moran's Eigenvector Maps, using data from 483 sites in southeastern Brazil, which encompass a total of 3546 species and 33 geo‐climatic variables. We observed strong floristic similarities between rain‐ and seasonal forests and a species distribution continuum across the main gradients. The environmental and spatial variables were significantly correlated with floristic patterns, and we demonstrated that the tree flora of the seasonal forests should no longer be considered a simple subset of the rain forest flora. The findings of the original paper were not only confirmed but we also unveiled additional, important phytogeographic patterns. We also reinforced the main conclusion of the paper that the Atlantic Forest concept must encompass all of the forest types east of the dry corridor in South America, a designation of utmost importance for the conservation of this biodiversity hotspot.
Keywords:conservation issues  environmental predictors  phytogeographic gradients  spatial predictors  tree flora
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