The effect of fixed-count subsampling on macroinvertebrate biomonitoring in small streams

1. When rigorous standards of collecting and analysing data are maintained, biological monitoring adds valuable information to water resource assessme nts. Decisions, from study design and field methods to laboratory procedure s and data analysis, affect assessment quality. Subsampling - a laboratory procedure in which researchers count and identify a random subset of field samples - is widespread yet controversial. What are the consequences of sub sampling? 2. To explore this question, random subsamples were computer generated for subsample sizes ranging from 100 to 1000 individuals as compared with the r esults of counting whole samples. The study was done on benthic invertebrat e samples collected from five Puget Sound lowland streams near Seattle, WA, USA. For each replicate subsample, values for 10 biological attributes (e. g. total number of taxa) and for the 10-metric benthic index of biological integrity (B-IBI) were computed. 3. Variance of each metric and B-IBI for each subsample size was compared w ith variance associated with fully counted samples generated using the boot strap algorithm. From the measures of variance, we computed the maximum num ber of distinguishable classes of stream condition as a function of sample size for each metric and for B-IBI. 4. Subsampling significantly decreased the maximum number of distinguishabl e stream classes for B-IBI, from 8.2 for fully counted samples to 2.8 class es for 100-organism subsamples. For subsamples containing 100-300 individua ls, discriminatory power was low enough to mislead water resource decision makers.