EFFECTS OF MULTI‐SCALE ENVIRONMENTAL CHARACTERISTICS ON AGRICULTURAL STREAM BIOTA IN EASTERN WISCONSIN1

Abstract

ABSTRACT: The U.S. Geological Survey examined 25 agricultural streams in eastern Wisconsin the determine relations between fish, invertebrate, and algal metrics and multiple spatial scales of land cover, geologic setting, hydrologic, aquatic habitat, and water chemistry data. Spearman correlation and redundancy analyses were used to examine relations among biotic metrics and environmental characteristics. Riparian vegetation, geologic, and hydrologic conditions affected the response of biotic metrics to watershed agricultural land cover but the relations were aquatic assemblage dependent. It was difficult to separate the interrelated effects of geologic setting, watershed and buffer land cover, and base flow. Watershed and buffer land cover, geologic setting, reach riparian vegetation width, and stream size affected the fish IBI, invertebrate diversity, diatom IBI, and number of algal taxa; however, the invertebrate FBI, percentage of EPT, and the diatom pollution index were more influenced by nutrient concentrations and flow variability. Fish IBI scores seemed most sensitive to land cover in the entire stream network buffer, more so than watershed‐scale land cover and segment or reach riparian vegetation width. All but one stream with more than approximately 10 percent buffer agriculture had fish IBI scores of fair or poor. In general, the invertebrate and algal metrics used in this study were not as sensitive to land cover effects as fish metrics. Some of the reach‐scale characteristics, such as width/depth ratios, velocity, and bank stability, could be related to watershed influences of both land cover and geologic setting. The Wisconsin habitat index was related to watershed geologic setting, watershed and buffer land cover, riparian vegetation width, and base flow, and appeared to be a good indicator of stream quality Results from this study emphasize the value of using more than one or two biotic metrics to assess water quality and the importance of environmental characteristics at multiple scales.