Maps of the Location of the Little Miami River Basin in the State of Ohio and the Locations of the Headwater Catchments and the Three Level IV Ecoregions Within the Basin.

Maps of the Location of the Little Miami River Basin in the State of Ohio and the Locations of the Headwater Catchments and the Three Level IV Ecoregions Within the Basin.

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Griffith, Michael B., F. Bernard Daniel, Matthew A. Morrison, Michael E. Troyer, James M. Lazorchak, and Joseph P. Schubauer-Berigan, 2009. Linking Excess Nutrients, Light, and Fine Bedded Sediments to Impacts on Faunal Assemblages in Headwater Agricultural Streams. Journal of the American Water Resources Association (JAWRA) 45(6):1475-1492. Abstra...

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... LMR is a 170 km long tributary of the Ohio River, draining a 4,535 km 2 catchment in southwest- ern Ohio ( Figure 2). The LMR drainage is located within Omernik's (1987) Level III Ecoregion, Eastern Corn Belt Plains, but is subdivided into three Level IV ecoregions, which, from north to south, are the Darby Plains; the Loamy, High Lime Till Plains; and the Pre- Wisconsinan Drift Plains ( Woods et al., 1998). ...

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... Although demonstrating cause and effect has proven difficult, the circumstantial case for a causal link between nutrient enrichment and aquatic community health is strong (Smith et al., 2007;Meador and Carlisle, 2007;Miltner, 2010). Nutrient enrichment indirectly affects sensitive fishes and macroinvertebrates by its effect on dissolved oxygen (DO) concentrations via increased microbial respiration (Sabater et al., 2000;Griffith et al., 2009). Nutrient enrichment is often related to bioassessment indicators of aquatic community condition (Heiskary and Markus, 2003;Miltner, 2010). ...
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... Furthermore, while Wang et al. (2007) found that, combined, nutrients explained 22% of the variability in macroinvertebrate community characteristics, they explained only JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 15% of the fish assemblage measured in wadeable streams. Thus, the direct relationships between nutrients and the IBI can be confounded by distance along the food web and other multiple interacting and mediating factors (e.g., periphyton metrics, benthic sediments, macroinvertebrate community, time lags (Griffith et al., 2009)). ...
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... The connection between the plant communities and the invertebrates, as discussed above, was primarily structural, providing habitat for the invertebrates. However, the combination of nutrients and light availability may also affect other food resources in the spring, such as the microscopic algal community (Griffith et al. 2009;Wojtal and Sobczyk 2012). ...
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... Rebecca M. Kreiling,* Joseph P. Schubauer-Berigan, William B. Richardson, Lynn A. Bartsch, Peter E. Hughes, Jennifer C. Cavanaugh, and Eric A. Strauss I n the Mississippi River basin, nonpoint runoff primarily from agricultural activities and secondarily from urban areas (Goolsby et al., 1999, 2000; Alexander et al., 2008) is having detrimental eff ects on the water quality and ecology of local streams and rivers (Griffi th et al., 2009) and coastal Gulf of Mexico ecosystems (Turner and Rabalais, 1991; Committee on Environment and Natural Resources, 2000; Rabalais et al., 2002; USEPA, 2008; Broussard and Turner, 2009; Battaglin et al., 2010; Sprague et al., 2011). Increased sediment loading leads to the fi lling of off -channel areas (Bhowmik and Adams, 1989), and greater loads of suspended solids limit light transmission into the water column, hindering the growth of aquatic macrophytes (Moore et al., 2010), phytoplankton (Whalen and Benson, 2007), and invertebrates (Griffi th et al., 2009). ...
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... Th e impacts of increased deposited sediment on stream community structure and ecosystem function are well documented (Waters 1995;Wood and Armitage, 1997;Henley et al., 2000). Impacts on biota range from direct eff ects, such as increased macroinvertebrate drift (Culp et al., 1986) and smothering and scouring of periphyton (Griffi th et al., 2009;Molinos and Donohue, 2009), to indirect eff ects, such as reduction of critical habitat used by macroinvertebrates and vertebrates for reproduction, rearing, refuge, and food acquisition (Zweig and Rabeni, 2001;Sutherland et al., 2002;Griffi th et al., 2009). ...
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In this study, the environmental impacts of large scale bioenergy crops were evaluated using the Soil and Water Assessment Tool (SWAT). Daily pesticide concentration data for a study area consisting of four large watersheds located in Michigan (totaling 53,358 km²) was estimated over a six year period (2000-2005). Model outputs for atrazine, bromoxynil, glyphosate, metolachlor, pendimethalin, sethoxydim, triflualin, and 2,4-D model output were used to predict the possible long-term implications that large-scale bioenergy crop expansion may have on the bluegill (Lepomis macrochirus) and humans. Threshold toxicity levels were obtained for the bluegill and for human consumption for all pesticides being evaluated through an extensive literature review. Model output was compared to each toxicity level for the suggested exposure time (96-hour for bluegill and 24-hour for humans). The results suggest that traditional intensive row crops such as canola, corn and sorghum may negatively impact aquatic life, and in most cases affect the safe drinking water availability. The continuous corn rotation, the most representative rotation for current agricultural practices for a starch-based ethanol economy, delivers the highest concentrations of glyphosate to the stream. In addition, continuous canola contributed to a concentration of 1.11 ppm of trifluralin, a highly toxic herbicide, which is 8.7 times the 96-hour ecotoxicity of bluegills and 21 times the safe drinking water level. Also during the period of study, continuous corn resulted in the impairment of 541,152 km of stream. However, there is promise with second-generation lignocellulosic bioenergy crops such as switchgrass, which resulted in a 171,667 km reduction in total stream length that exceeds the human threshold criteria, as compared to the base scenario. Results of this study may be useful in determining the suitability of bioenergy crop rotations and aid in decision making regarding the adaptation of large-scale bioenergy cropping systems.