This study examined the relative influence of nutrients (nitrogen and phosphorus) and habitat on algal biomass in five agricultural regions of the United States. Sites were selected to capture a range of nutrient conditions, with 136 sites distributed over five study areas. Samples were collected in either 2003 or 2004, and analyzed for nutrients (nitrogen and phosphorous) and algal biomass (chlorophyll a). Chlorophyll a was measured in three types of samples, fine-grained benthic material (CHLFG), coarse-grained stable substrate as in rock or wood (CHLCG), and water column (CHLS). Stream and riparian habitat were characterized at each site. TP ranged from 0.004–2.69 mg/l and TN from 0.15–21.5 mg/l, with TN concentrations highest in Nebraska and Indiana streams and TP highest in Nebraska. Benthic algal biomass ranged from 0.47–615 mg/m2, with higher values generally associated with coarse-grained substrate. Seston chlorophyll ranged from 0.2–73.1 μg/l, with highest concentrations in Nebraska. Regression models were developed to predict algal biomass as a function of TP and/or TN. Seven models were statistically significant, six for TP and one for TN; r2 values ranged from 0.03 to 0.44. No significant regression models could be developed for the two study areas in the Midwest. Model performance increased when stream habitat variables were incorporated, with 12 significant models and an increase in the r2 values (0.16–0.54). Water temperature and percent riparian canopy cover were the most important physical variables in the models. While models that predict algal chlorophyll a as a function of nutrients can be useful, model strength is commonly low due to the overriding influence of stream habitat. Results from our study are presented in context of a nutrient-algal biomass conceptual model.

Nitrogen sources in the Mississippi River basin have been linked to degradation of stream ecology and to Gulf of Mexico hypoxia. In 2013, the USGS and the USEPA characterized water quality stressors and ecological conditions in 100 wadeable streams across the midwestern United States. Wet conditions in 2013 followed a severe drought in 2012, a weather pattern associated with elevated nitrogen concentrations and loads in streams. Nitrate concentrations during the May to August 2013 sampling period ranged from <0.04 to 41.8 mg L−1 as N (mean, 5.31 mg L−1). Observed mean May to June nitrate concentrations at the 100 sites were compared with May to June concentrations predicted from a regression model developed using historical nitrate data. Observed concentrations for 17 sites, centered on Iowa and southern Minnesota, were outside the 95% confidence interval of the regression‐predicted mean, indicating that they were anomalously high. The sites with a nitrate anomaly had significantly higher May to June nitrate concentrations than sites without an anomaly (means, 19.8 and 3.6 mg L−1, respectively) and had higher antecedent precipitation indices, a measure of the departure from normal precipitation, in 2012 and 2013. Correlations between nitrate concentrations and watershed characteristics and nitrogen and oxygen isotopes of nitrate indicated that fertilizer and manure used in crop production, principally corn, were the dominant sources of nitrate. The anomalously high nitrate levels in parts of the Midwest in 2013 coincide with reported higher‐than‐normal nitrate loads in the Mississippi River. Core Ideas Multiyear precipitation patterns can affect nitrate loading to streams. Anomalously high nitrate concentrations in 2013 in some streams followed the 2012 drought. Nitrate correlated to nitrogen fertilizer applications and multiyear precipitation patterns. High nitrate in small Midwest streams in 2013 coincides with high loading in the Mississippi River.

Fish, habitat, and water chemistry data were collected from 98 streams in the midwestern United States, an area dominated by intense cultivation of row crops, in order to identify important water-quality stressors to fish communities. We focused on 10 stressors including riparian disturbance, riparian vegetative cover, instream fish cover, streambed sedimentation, streamflow variability, total nitrogen, total phosphorus, minimum dissolved oxygen, pesticides, and bed sediment contaminants. Fish community response variables included a measure of observed/expected taxonomic completeness; species-specific tolerances to nitrogen, phosphorus, dissolved oxygen, and water temperature; the percent of species classified as macrohabitat generalists; and an index of pesticide toxicity to fish. Multivariate analysis indicated that total nitrogen was the most important stressor, signifying that fish communities were responding to total nitrogen despite relatively high levels common to an agricultural setting. Individually, fish taxonomic completeness decreased with increasing streambed sedimentation, whereas fish community tolerance to total phosphorus increased with increasing streambed sedimentation, riparian disturbance, and total nitrogen. These findings underscore the importance of multiple biological response metrics to better understand the effects of water-quality stressors on fish communities and highlight the complex relations between total phosphorus and fish communities.(KEY TERMS: fish; rivers/streams; water quality; stressors; nutrients; sedimentation.) Meador

As part of the Great Lakes Restoration Initiative, paired edge-of-field sites were established in high priority subwatersheds to assess the effectiveness of agricultural management practices. One pairing was in Black Creek, a tributary to the Maumee River and Lake Erie. These fields were paired because of similarity in soils, topography, and agricultural management. Following two years of baseline data collection from these fields, consistent differences in water quantity and quality were observed for tile networks draining the fields, despite these fields being adjacent and managed together. Consequently, it was hypothesized that differences in subsurface water movement, specifically tile-drain density and connectivity, were the source of the observed differences. Our objective was to map the tile-drain network using remote sensing methodology in order to improve the understanding of nutrient and water transport as well as management on these fields. A combination of multispectral and thermal imagery, collected in spring of 2017, was incorporated to delineate the tile-drain network within each field. This imagery led to locating a cracked tile, which provided a direct path for overland flow to enter the tile-drain system and suggested that a tile-drain segment under the road connected the two fields. A ground-penetrating radar survey verified multiple tile locations, including the tile segment under the road. The distribution of these tiles helps explain the difference in water quantity and quality in the two fields.