Periphyton is commonly used as a biomonitoring tool for stream research. Often only one or few sites are sampled and assumed to be representative of an entire stream reach. Current literature focuses on periphyton heterogeneity at a smaller scale, on individual rocks within a riffle, and larger scales, within a watershed or ecoregion. The intermediate scales, within a single riffle or among riffles have not been adequately addressed. The purpose of this research was to determine how many riffles need to be sampled in order to be representative of an entire stream reach and whether the number of necessary riffles varied according to stream health. Since periphyton is very sensitive to changes in the environment, it is hypothesized that heterogeneity will be found among riffles. For the purpose of this research, four nested spatial scales were used: eight reaches (each nested within a different stream), ten riffles (nested within a reach), five samples (nested within a riffle), and ten rock scrapings (nested within a sample). The eight streams sampled included three non-attaining, three partially-attaining, and two fully-attaining water quality standards, based on fish and macroinvertebrate data collected in 2004.
These data were analyzed using the Bray-Curtis Similarity Index, Hill’s N2 dominance diversity index, and the acid mine drainage diatom index of biotic integrity (AMD-DIBI). Results indicated that at intermediate scales, within a stream reach, diatoms appear to be patchily distributed. These patchy distributions often lead to different diatom assemblages from one riffle to the next. In order to account for this variation within a stream reach, when diatoms are sampled for water quality monitoring, at least two riffles should be sampled, cleaned and counted separately and the species counts should then be added together for analysis. The degree of variation does not appear to correspond directly to stream health, but rather species richness and diversity. Streams dominated by a single taxon may be represented by a one-riffle sample. The use of indices has the potential to correctly classify streams based on a one-riffle sample.