2 resultados para YVL guides

em University of Connecticut - USA


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Beth Owen is just one of many Yale School of Forestry and Environmental Studies graduate students and alumni to participate in an independent research project through the support of Connecticut Sea Grant. The internships have been as ambitious as they are diverse, and all have given participants a new perspective on the role of research in their future. The program is based at Yale’s Center for Coastal and Watershed Systems. Beth sampled and analyzed sediments for heavy metals from the lower Quinnipiac River.

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Nutrient leaching studies are expensive and require expertise in water collection and analyses. Less expensive or easier methods that estimate leaching losses would be desirable. The objective of this study was to determine if anion-exchange membranes (AEMs) and reflectance meters could predict nitrate (NO3-N) leaching losses from a cool-season lawn turf. A two-year field study used an established 90% Kentucky bluegrass (Poa pratensis L.)-10% creeping red fescue (Festuca rubra L.) turf that received 0 to 98 kg N ha-1 month-1, from May through November. Soil monolith lysimeters collected leachate that was analyzed for NO3-N concentration. Soil NO3-N was estimated with AEMs. Spectral reflectance measurements of the turf were obtained with chlorophyll and chroma meters. No significant (p > 0.05) increase in percolate flow-weighted NO3-N concentration (FWC) or mass loss occurred when AEM desorbed soil NO3-N was below 0.84 µg cm-2 d-1. A linear increase in FWC and mass loss (p < 0.0001) occurred, however, when AEM soil NO3-N was above this value. The maximum contaminant level (MCL) for drinking water (10 mg L-1 NO3-N) was reached with an AEM soil NO3-N value of 1.6 µg cm-2 d-1. Maximum meter readings were obtained when AEM soil NO3 N reached or exceeded 2.3 µg cm-2 d-1. As chlorophyll index and hue angle (greenness) increased, there was an increased probability of exceeding the NO3-N MCL. These data suggest that AEMs and reflectance meters can serve as tools to predict NO3-N leaching losses from cool-season lawn turf, and to provide objective guides for N fertilization.