Sources of Error in Biological Indices

The primary objectives of aquatic biological assessment programs are to determine if waterbodies are meeting regulatory standards for the protection of aquatic life and to inform management actions that either protect existing high-quality waters or restore degraded waters to acceptable conditions. However, assessments of biological condition are of little value without estimates of uncertainty. Uncertainty is sometimes assumed to be negligible and quantifying uncertainty can be costly with respect to both time and money, but if the presence or magnitude of uncertainty in bioassessment data is unknown, a conclusion based on those data can be problematic. For example, Type I errors can result in wasted expenditures of time and money by the regulating entity, whereas Type II errors allow waters to further degrade before detection of problems. Thus, an understanding of potential sources of error will ensure that biological assessment data are repeatable and accurately inform management decisions.

In general, sources of uncertainty can include both failure to account for natural variation (spatial and temporal) in the biota used to assess biological condition and human error associated with field sampling, sample processing, and calculation of index scores. To better understand how some of these sources of error can influence the assessment of river ecosystems, we will follow up on the QAQC study in Ostermiller and Hawkins 2004 using a long-term monthly macroinvertebrate dataset from the Logan River, UT. We are specifically interested in quantifying sources of uncertainty associated with (1) laboratory subsampling and (2) taxonomic identification error. The results of this study should help NAMC identify both the sources of error that can potentially influence index scores and which indices are most susceptible to those sources of error.

Literature Cited

• Ostermiller, J. D. and C. P. Hawkins. 2004. Effects of sampling error on bioassessments of stream ecosystems: application to RIVPACS-type models. Journal of the North American Benthological Society 23:363-382.