The Little Miami River (LMR) basin, dominated by agriculture, contains two geologically-distinct regions; a glaciated northern till plain with soils three times more permeable than a southern, pre-Wisconsinan drift plain. The influences of two landscape measures, percent row crop cover (%RCC, computed at three spatial scales), and soil permeability (PERM), on baseflow nutrient concentrations were modeled using linear regressions. Quarterly water samples collected for four years were analyzed for nitrate-N (NN), Kjeldahl-N (KN), total-N (TN), and total-P (TP). In till plain streams (n = 17), NN concentrations were 8.5-times greater than drift plain streams (n = 18), but KN and TP were 20-40% lower at comparable %RCC. These differences resulted in TN/TP molar ratios >80 in till plain streams, but <6 in drift plain streams. For till plain steams regression models based on %RCC accounted for 79% of the variance in NN concentrations but only 27% in drift plain streams. However, regressions on %RCC accounted for 68-75% of the KN and TP concentration variance in the drift plain streams but essentially none in the till plain. Catchment PERM influenced the regional NN/KN ratios which were 10-fold higher in the drift plain streams. For both till and drift streams the catchment scale %RCC gave the best predictions of NN, a water soluble anion, but the smaller spatial scales produced better models for insoluble nutrient species (e.g., KN and TP). Published literature on Ohio streams indicates that these inter-regional differences in nutrient ratios have potential implications for aquatic biota in the receiving streams.
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. Abstract: Biological impairments in streams are typically defined by regulatory agencies in terms of altered invertebrate or fish assemblages. While nutrients, canopy cover, and sediment fines contribute to these impairments, these stressors are often defined, at least in part, by their impacts on periphyton. Path analysis can extend these assessments to impacts on invertebrates and fish by characterizing the direct and indirect relationships among variables along defined model pathways. With data from headwater tributaries in the Little Miami River, Ohio, we tested models of the impacts of nutrients [total nitrogen (TN), total phosphorus (TP), and the nitrogen to phosphorus (N/P) ratio], the percentage of (%) open canopy, and the % sand and fines on three periphyton metrics [periphytic ash‐free dry mass (AFDM), the percent abundance of cyanobacteria (% cyanobacteria), and the percent abundance of Chlorophyta (% Chlorophyta)] and, in turn, on selected invertebrate or fish metrics. Our objective was to develop and evaluate a statistical model that assesses the direct and indirect impacts of excess nutrients on macroinvertebrate and fish in these streams and demonstrate how this approach might be applicable elsewhere. The results suggest indirect pathways for the influences of nutrients, canopy cover, and fine bedded sediments on invertebrates or fish that are mediated by their influences on periphyton. This is in addition to any direct impacts of these stressors on the invertebrate and fish metrics. In most models, all three periphyton metrics increased with % open canopy. Periphytic AFDM increased with TN, while % cyanobacteria decreased. The % cyanobacteria also decreased with % sand and fines, but % Chlorophyta increased. The metrics, percent abundance of (%) three most dominant (macroinvertebrate) taxa, % Trichoptera, and % herbivorous fish all increased with periphytic AFDM, while % climbers, % swimmers, and %Lepomis cyanellus Rafinesque decreased. Lepomis cyanellus is an indicator species, because it is generally common in these streams and relatively tolerant to various common environmental stressors. The % three most dominant macroinvertebrate taxa increased while % Hydropsychidae (Trichoptera) and %L. cyanellus decreased with % cyanobacteria. The % Trichoptera and %L. cyanellus increased with % Chlorophyta. Some macroinvertebrate metrics, such as the % burrowers and number of burrower taxa, did not have any statistically significant relationships with the periphyton metrics but did exhibit a direct pathway with % sand and fines. These analyses illustrate how path analysis can be used to estimate the relationships among the variables in a conceptual model, modify the ...
Storm‐flow transients (i.e., hydrograph rise and fall dynamics) may represent an important aspect of understanding streamflow dynamics. However, little is known about how temporal resolution of transient data and climate variability may color these potential indicators of hydrologic pattern or condition. Warm‐season stream stage and rainfall were monitored continuously (5 min) during the 2002 water year in eight tributaries of the Little Miami River (Ohio), which drain 17‐58 km2 catchments. Rise rates generated using 5‐min data were different than those generated with mean daily data [calculated with the Indicators of Hydrologic Alteration (IHA) software], though fall rates were similar for fine and coarse temporal data. This result suggests that data with low temporal resolution may not be adequate to fully represent the dynamics of storm rise rates. Conversely, fall rates based on daily stage data (via IHA) were similar to those based on the 5‐min data, and so daily mean data may be appropriate for characterizing fall rates. We next analyzed the possible correlations between rainfall variability and storm‐flow stage dynamics. We derived rise and recession rates from storm stage hydrographs by assuming exponential rise and decay of a runoff peak. We found that raw rise rates (Rraw) were correlated with both the maximum rainfall rate and the time to the centroid of a rain event. We subsequently removed the trend based on these rainfall characteristics, which yielded new representations of rise rates abbreviated as Rrate and Rtcent, respectively, and that had lower variability than the uncorrected (raw) data. Fall rates were found to be independent of rainfall characteristics. Due to the predominant influence of stream hydrology upon aquatic biota and nutrient fluxes, our work suggests that these stage data analysis protocols can refine or otherwise reduce variability in these indices by accounting for relevant factors such as rainfall forcing. These protocols for derivation of transient indices should be tested for their potential to improve correlations between stream hydrology and temporally aligned biotic data and dissolved nutrient fluxes in streams.
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