Molecular tools based on rRNA (rrn) genes are valuable techniques for the study of microbial communities. However, the presence of operon copy number heterogeneity represents a source of systematic error in community analysis. To understand the types and magnitude of such bias, four commonly used rrn-based techniques were used to perform an in silico analysis of a hypothetical community comprised organisms from the Comprehensive Microbial Resource database. Community profiles were generated, and diversity indices were calculated for length heterogeneity PCR, automated ribosomal integenic spacer analysis, denaturing gradient gel electrophoresis, and terminal RFLP (using RsaI, MspI, and HhaI). The results demonstrate that all techniques present a quantitative bias toward organisms with higher copy numbers. In addition, techniques may underestimate diversity by grouping similar ribotypes or overestimate diversity by allowing multiple signals for one organism. The results of this study suggest that caution should be used when interpreting rrn-based community analysis techniques.