A statistical analysis of subsampling and an evaluation of the Folsom plankton splitter

Abstract

Subsampling techniques are important for the determination of precise plankton density estimates. A binomial model of random subsampling, and its Poisson extension, were developed for the purpose of evaluating the performance of compartment-type plankton subsamplers. Two approaches were used to assess the performance of the Folsom plankton splitter on an extensive series of nearshore Lake Michigan crustacean zooplankton samples collected between 1974 and 1979. First, Folsom subsamples were observed to be significantly (p < 0.05) more variable than expected from the random model of subsampling. Second, a random effects ANOVA model was used to compare fractions of the total variance in density estimates that were attributable to subsampling and sampling phases of a specially designed study. Departures from randomness in subsampling were sufficiently small that an analysis of optimal allocation of effort between subsampling and sampling phases, based on the ANOVA model, indicated that only one to three subsamples needed to be examined per sample.