Alison C C Colby’s research while affiliated with Wisconsin Department of Natural Resources and other places

The Wisconsin Department of Natural Resources (WDNR), with support from the U.S. EPA, conducted an assessment of wadeable streams in the Driftless Area ecoregion in western Wisconsin using a probabilistic sampling design. This ecoregion encompasses 20% of Wisconsin's land area and contains 8,800 miles of perennial streams. Randomly-selected stream sites (n = 60) equally distributed among stream orders 1-4 were sampled. Watershed land use, riparian and in-stream habitat, water chemistry, macroinvertebrate, and fish assemblage data were collected at each true random site and an associated "modified-random" site on each stream that was accessed via a road crossing nearest to the true random site. Targeted least-disturbed reference sites (n = 22) were also sampled to develop reference conditions for various physical, chemical, and biological measures. Cumulative distribution function plots of various measures collected at the true random sites evaluated with reference condition thresholds, indicate that high proportions of the random sites (and by inference the entire Driftless Area wadeable stream population) show some level of degradation. Study results show no statistically significant differences between the true random and modified-random sample sites for any of the nine physical habitat, 11 water chemistry, seven macroinvertebrate, or eight fish metrics analyzed. In Wisconsin's Driftless Area, 79% of wadeable stream lengths were accessible via road crossings. While further evaluation of the statistical rigor of using a modified-random sampling design is warranted, sampling randomly-selected stream sites accessed via the nearest road crossing may provide a more economical way to apply probabilistic sampling in stream monitoring programs.

Most indices of biotic integrity (IBIs) are designed to represent the biological condition of individual sampling locations in a river or stream. Characterizing the biological condition of an entire stream is often of interest and requires data from multiple sites. The representativeness of these data depends on the variability in the scores between sampling locations. We compared the variability in IBI scores using two parameters whose values can be obtained easily—stream size and ecoregion. The variability in IBI scores tended to be greater in smaller Wisconsin streams (first and second order) than in larger ones (third and fourth order) but there was no difference in the variability between ecoregions. Thus, in order to confidently characterize the true mean IBI score for a smaller stream, essentially a census of the entire stream would be required. In order to confidently characterize the mean IBI score of a larger stream, approximately six scores are necessary, which is equivalent to one station per 2 km of stream given the mean length of third and fourth order streams in Wisconsin.