Avaliação de métodos para estimativas de dissimilaridade em gradientes ecológicos com alta diversidade beta
Nenhuma Miniatura disponível
Data
2018-04-18
Autores
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Federal de Goiás
Resumo
There are several problems on the analysis of biological communities with sparse data,
resulting from gradients with high beta diversity. I used four strategies to solve this
problem (Beals smoothing, Swan, Shortest Path and Extended Dissimilarity). I
randomly removed from 1% to 50% of the individuals in empirical and simulated
matrices. I then performed PCoA and nMDS ordinations and used Procrustes
correlation of the original two dimensional ordination with the ordination obtained
using the degraded matrices. For the simulated data set, I also correlated the ordenation
in two dimensions with the coordinates of the samples in the two-dimensional simulated
gradients. Finally, I analyzed how robustness to degradation, quantified as Procrustean
correlation, was related to the matrix properties. Different from the expected, in the
comparison of the degraded and original ordinations, the uncorrected data with a
traditional dissimilarity index (Bray-Curtis) produced higher fit than the four methods
evaluated. In relation to the coordinates of the simulated two-dimensional gradients, the
evaluated methods were slightly better than the raw data. Overall, the simulated data
were more robust to the degradation than the empirical ones and the data of abundance
were more robust than matrices of presence and absence. Matrices with small
proportion of zeros were more robust to degradation. I conclude that the correction
methods evaluated distorted the pattern on the original data. Also, data with low beta
diversity (few zeros) are robust to degradation and sufficient to reconstruct the original
gradient.
Descrição
Palavras-chave
Citação
Hoffmann, J. C. Avaliação de métodos para estimativas de dissimilaridade em gradientes ecológicos com alta diversidade beta. 2018. 55 f. Dissertação (Mestrado em Ecologia e Evolução) - Universidade Federal de Goiás, Goiânia, 2018.