FLORISTIC COMPOSITION ANALYSIS, DIVERSITY AND SIMILARITY OF ATLANTIC FOREST FRAGMENTS IN MINAS GERAIS STATE-BRAZIL

• Autor(a) principal: Reis, Hermógenes
• Data de Publicação: 2015
• Outros Autores: Scolforo, José Roberto Soares, Oliveira, Antônio Donizette de, Filho, Ary Teixeira de Oliveira, Mello, José Márcio de
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Cerne (Online)
• Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/321
• topic: Floristic composition; Plateau; Diversity; Similarity; Atlantic Forest; Forest Exploration

The objectives of this study were: to analyze, to describe and to discriminate the distribution of the floristic composition in 4 forest fragments in Zona da Mata of Minas Gerais; to estimate the sampling sufficiency, using the method of the linear plateau regression; to know the diversity and similarity of the fragments; to establish the correspondence between similarity and the geographical distance between fragments. The studied areas corresponded to 4 forest fragments located in the counties of Piranga and Diogo de Vasconcelos in the State of Minas Gerais. Three of the fragments were explored, while for the other, any record of intervention in the last years was identified. The systematic sampling method was applied. The number and distance of transects, and the distance between sampling plots varied with the form and size of each fragment. The inventoried individuals were those with a circumference at breast height (CBH) 15.70 cm. In the fragments, 12,709 individuals were found, distributed in 397 species, 190 genus and 67 families. The sampling was enough to represent the floristic composition of the fragments. About 11 families possess, together, more than 50% of the total of species. About 48 species (12.09% of the total) presented high plasticity in distribution, reaching 100% of occurrence among the fragments. The Shannon s diversity index varied from 3.91 to 4.71. The four fragments are highly similar among them with index values above 44%. The geographical distance influenced the similarity indexes.