2012
DOI: 10.5902/198050985083
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Ausência de estabilização da curva de acumulação de espécies em florestas tropicais

Abstract: A definição do tamanho da amostra é um dos principais problemas em levantamentos fitossociológicos. A curva de acumulação de espécies é comumente utilizada para definir a suficiência amostral, mas este método apresenta algumas limitações, como a ausência de um ponto de estabilização que possa ser determinado objetivamente e a arbitrariedade da ordem de entrada das unidades amostrais na construção da curva. Uma solução para esse problema é o uso de procedimentos de aleatorização, como a permutação, para obter c… Show more

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Cited by 15 publications
(12 citation statements)
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“…Although higher richness was registered to the Atlantic Forest as a whole, with the highest number recorded by Thomaz & Monteiro (1997) and Saiter et al (2011) to the state of Espirito Santo, among the studies conducted for this vegetation in the state of Rio de Janeiro, including equal or larger sample areas, the Curio MNP was the one with the greater species richness. The lack of stabilization of the species accumulation curve is, in fact, a pattern to be expected for tropical forests (Schilling & Batista 2008, Schilling et al 2012, as well as the high number of species, which also reaffirm the richness and importance for conservation of this forest area. Similarly, the index of species estimation for the study area and the occurrence of threatened species of the national flora also show the importance of the Curio MNP for the maintenance of genetic resources and protection of their habitats.…”
Section: Discussionmentioning
confidence: 85%
“…Although higher richness was registered to the Atlantic Forest as a whole, with the highest number recorded by Thomaz & Monteiro (1997) and Saiter et al (2011) to the state of Espirito Santo, among the studies conducted for this vegetation in the state of Rio de Janeiro, including equal or larger sample areas, the Curio MNP was the one with the greater species richness. The lack of stabilization of the species accumulation curve is, in fact, a pattern to be expected for tropical forests (Schilling & Batista 2008, Schilling et al 2012, as well as the high number of species, which also reaffirm the richness and importance for conservation of this forest area. Similarly, the index of species estimation for the study area and the occurrence of threatened species of the national flora also show the importance of the Curio MNP for the maintenance of genetic resources and protection of their habitats.…”
Section: Discussionmentioning
confidence: 85%
“…In the 2005-2013 interval, fragment III showed a tendency of stabilization at the number of species. This result is explained by the theory of species accumulation curve, which represents the tendency of species increase as sampled area increases (Giácomo et al, 2013;Schilling, Batista, & Couto, 2012). The results found in this study were superior to species level when compared with other studies for the same phytophysiognomies (Almeida et al, 2014;Moura, Gomes-Klein, Felfili, & Ferreira, 2010;Pinto, Lenza, & Pinto, 2009) (Table 2).…”
Section: Resultsmentioning
confidence: 46%
“…The mean species accumulation curve for analysis of sample adequacy did not reach an asymptote, that is, it did not stabilize (Figure 2). Schilling et al (2012) reported that mean species accumulation curves in tropical regions hardly present an asymptotic pattern because of the high environmental heterogeneity. The species richness observed in the plots (54) was close to that indicated by the Chao 1 estimator (59) (Figure 2), corresponding to 91.5% of the richness estimated for this community.…”
Section: Resultsmentioning
confidence: 99%
“…Aiming to verify the sample sufficiency, curves of the mean species accumulation and richness estimation were developed (Magurran, 2011). The method of mean species accumulation curve is more efficient than the collector's curve to evaluate sample adequacy because it is a mean curve, with a 95% confidence interval, generated from several different and random data (Magurran, 2011;Schilling & Batista, 2008;Schilling et al, 2012). In order to develop it, 1,000 simulations were conducted aiming to change the sampling unit entry order and assess the degree of stability of the sample, based on the central limit theorem (Schilling & Batista, 2008).…”
Section: /12mentioning
confidence: 99%