MEPS 276:19-24 (2004)  -  doi:10.3354/meps276019

Effect of sampling design on abundance estimates of benthic invertebrates in environmental monitoring studies

Henrique N. Cabral1,*, Alberto G. Murta2

1Instituto de Oceanografia and Departamento de Biologia Animal, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
2Departamento de Recursos Marinhos, INIAP-IPIMAR, Avenida de Brasília, 1449-006 Lisboa, Portugal

ABSTRACT: Random, stratified, systematic and adaptative sampling designs were analyzed comparatively using data of benthic invertebrate abundance in the mudflats of the Tagus estuary. Intensive core sampling was performed in spring and summer of 1996, in an area of 4 m2. Estimates determined from sub-sets of samples chosen using the various designs were compared. The mean values of the density estimates obtained by the various sampling designs and sample sizes differed significantly, and the main variation trends also differed according to species. For species with low abundace, i.e. Polydora ciliata and Sphaeroma monodi, the estimates obtained by random sampling (RS), systematic sampling (SyS) and stratified sampling (SS) were similar to the real density value, while those that resulted from the adaptive sampling (AS) design tended to overestimate density in the majority of cases. A different pattern was obtained for the abundant species, i.e. Streblospio shrubsolii and Scrobicularia plana. For these species, the mean values of the estimates obtained by RS, SyS and SS were similar and presented a negligible bias, although their variances were usually high. AS designs produced strongly biased estimates, although with low variance. The mean values of these estimates were considerably lower than the true mean density value. Comparison of the mean variance estimates for the sample sizes considered for each sampling design with the RS variance estimates revealed that the lowest variance ratios were obtained with SS designs.


KEY WORDS: Sampling design · Sample size · Adaptive sampling · Benthic invertebrates · Environmental monitoring


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