Classification of South Brazilian grasslands: implications for conservation.
Aims: We offer a first classification of South Brazilian grasslands (Campos Sulinos) based on quantitative vegetation data and describing grassland types in terms of dominant and indicator species. Location: South Brazilian grasslands (Paraná, Santa Catarina, Rio Grande do Sul states). Methods: We described vegetation plots in 167 sampling units throughout the region using a stratified nested design, totalizing 1,502 1 m2 quadrats. We classified vegetation using cluster analysis based on Bray-Curtis dissimilarities, establishing three vegetation types and ten subtypes. We conducted indicator species analysis within the resulting subtypes, and for all possible combinations of subtypes. Results: In the cluster analyses, a clear separation of poorly drained grasslands from the drier sites appeared. Further, a clear distinction between grasslands in the South Brazilian highland region, situated in the Atlantic Forest biome, and the grasslands of the Pampa biome, to the south, emerged, reflecting climatic and management differences. Highland grasslands showed lower species cover dominance, while in the Pampa, Paspalum notatum clearly was the most important species and the abundance of exotic species was higher. Conclusions: Our study provides the first classification of South Brazilian grasslands based on quantitative vegetation data recorded in a standardized sampling design. The data support the division of grasslands into the main phytogeographic units of the region (Brazilian biome classification). Grasslands in these two regions also differ in terms of species dominance pattern (higher dominance in Pampa grasslands, likely also due to higher grazing levels) and in terms of conservation state (low presence of exotic species in highland grasslands). Our results are important for conservation policies, which can now consider the presence of different grassland types in different region, but more data will be necessary for a more detailed classification that considers different abiotic features in more detail.