Analysis of the error associated with the subsampling of Chironomidae in an intermittent stream of semi-arid Brazil

作者:de Farias Rafaela Lima; Braga Alencar Thuanny Fernanda; de Sena Lima Jessica Alcoforado; Figueredo Medeiros Elvio Sergio
来源:BIOTA NEOTROPICA, 2015, 15(1).
DOI:10.1590/1676-06032015003914

摘要

Chironomidae is a common family in freshwaters, often occurring at high densities, which hinders the processing of large samples, given that time and labor are usually limited. The present study aims at evaluating the extent of the error related with the subsampling of Chironomidae from a larger sample with regard to the size of the individuals between a sample and the subsample. A total of 9195 chironomids were collected from three sites in an intermittent stream. Samples were taken using a Dshaped net (250 mu m) on eight occasions. Individuals from each sample were homogenized in a gridded Petri dish and coordinates from lines and columns were randomly drawn. Individuals from the assigned coordinates were selected until 100 individuals or 10% of the sample were chosen. Comparisons were made between the proportion of larger (>= 5mm) and smaller individuals (<5mm) between the samples and subsamples, and it was established the correlation between the size of the error and the size of the sample, using the rank coefficient of Spearman. The highest error observed was 12.7%, meaning that the difference in larger individuals between the sample and subsample reached that value. However on six of the eight samples the error was below 3%. Spearman correlation showed no significance between the error observed and the size of the sample (rho=0.38, p=0.35), meaning that larger samples will not yield larger error associated with the size of the individuals. The present study indicates that the subsampling technique used is capable of drawing a random subset of individuals from a sample of chironomids with regard to their size. This technique can be used in ecological or biomonitoring studies in order to reduce sample processing time without creating a bias in the analysis.

  • 出版日期2015

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