Relações entre as variáveis edáficas e vegetacionais em cerrado hiperestacional, cerrado estacional e campo úmido no Parque Nacional das Emas (GO).
AMORIM, Priscilla Kobayashi. Relações entre as variáveis edáficas e vegetacionais em cerrado hiperestacional, cerrado estacional e campo úmido no Parque Nacional das Emas (GO).. 2005. 53 f. Dissertação (Mestrado em Ciências Biológicas) - Universidade Federal de São Carlos, São Carlos, 2005.
Amorim, Priscilla Kobayashi
The Cerrado Domain occupied formerly 2 million km2 of the Brazilian territory, especially in the Central Plateau. The cerrado vegetation is not uniform in physiognomy, ranging from grassland to tall woodland, but with most of its physiognomies within the range defined as tropical savanna. In cerrado, there are few areas that become waterlogged during the rainy season due to the poor drainage of the soil, allowing the appearance of a hyperseasonal cerrado, characterized by two contrasting stresses, one induced by drought and fire during the winter, the other by soil saturation in the summer. As long as soil is important in the ecology of the cerrado, limiting the cerrado distribution and the occurrence of its physiognomies, we investigated the soil-vegetation relationships in a cerrado core area in Emas National Park, in three vegetation forms: hyperseasonal cerrado, seasonal cerrado, and wet grassland. We collected vegetation and soil samples in these three vegetation forms and submitted obtained data to a canonical correspondence analysis. Our results showed a distinction among hyperseasonal cerrado, seasonal cerrado and wet grassland, which presented different floristic compositions and species abundances. The edaphic variables best related to the hyperseasonal and seasonal cerrados were sand, base saturation, pH, and magnesium. The wet grassland was related to higher concentrations of clay, organic matter, aluminium saturation, aluminium, phosphorus, and potassium. We also investigated the relationships between number of species and soil characteristics, with simple multiple linear regressions, and found that aluminium and pH were the best predictors of species density, the former positively related to species density and the latter negatively related.
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