PCR-based high-throughput sequencing has permitted comprehensive resolution analyses of zooplankton diversity dynamics. However, significant methodological issues still surround analyses of complex bulk community samples, not least as in prevailing PCR-based approaches. Marine drifting animals—zooplankton—play essential ecological roles in the pelagic ecosystem, transferring energy and elements to higher trophic levels, such as fishes, cetaceans and others. In the present study, we collected 48 size-fractionated zooplankton samples in the vicinity of a coral reef island with environmental gradients. To investigate the spatiotemporal dynamics of zooplankton diversity patterns and the effect of PCR amplification biases across these complex communities, we first took metatranscriptomics approach. Comprehensive computational analyses revealed a clear pattern of higher/lower homogeneity in smaller/larger zooplankton compositions across samples respectively. Our study thus suggests changes in the role of dispersal across the sizes. Next, we applied in silico PCR to the metatranscriptomics datasets, in order to estimate the extent of PCR amplification bias. Irrespective of stringency criteria, we observed clear separations of size fraction sample clusters in both metatranscriptomics and in silico datasets. In contrast, the pattern—smaller-fractioned communities had higher compositional homogeneity than larger ones—was observed in the metatranscriptomics data but not in the in silico datasets. To investigate this discrepancy further, we analysed the mismatches of widely used mitochondrial CO1 primers and identified priming site mismatches likely driving PCR-based biases. Our results suggest the use of metatranscriptomics or, although less ideal, redesigning the CO1 primers is necessary to circumvent these issues.