Distribution of trace element pollutants in a contaminated grassland ecosystem established on metalliferous fluorspar tailings. 2: Zinc

Concentrations of zinc in vegetation, invertebrates and small mammals in a grassland ecosystem derived from a mine waste vegetation scheme indicated the high concentration of zinc in the original tailings. However, the considerable differences in soil and vegetation zinc concentrations between the tailings and an uncontaminated site were not reflected in the invertebrate and small mammal communities. Invertebrate zinc levels and total body concentrations in Microtus agrestis L. (field vole) and Sorex araneus L. (common shrew) suggested a notable buffering of zinc absorption and tissue accumulation in the presence of substantially elevated dietary zinc. In the small mammals the skeleton appeared to function as the major storage site for zinc, possibly contributing to homeostasis in the soft tissues.     

Storm flow export of metolachlor from a coastal plain watershed

During an 18-month (1994-1995) survey of the surface water in an Atlantic Coastal Plain watershed, metolachlor was most frequently detected during storm flow events. Therefore, a sampling procedure, focused on storm flow, was implemented in June of 1996. During 1996, three tropical cyclones made landfall within 150 km of the watershed. These storms, as well as several summer thunderstorms, produced six distinct storm flow events within the watershed. Metolachlor was detected leaving the watershed during each event. In early September, Hurricane Fran produced the largest storm flow event and accounted for the majority of the metolachlor exports. During the storm event triggered by Hurricane Fran, the highest daily average flow (7.5 m2 s-1) and highest concentration (5.1 micrograms L-1) ever measured at the watershed outlet were recorded. Storm flow exports leaving the watershed represented 0.1 g ha-1 or about 0.04% of active ingredient applied.     

Modelling Replicated Weed Growth Data using Spatially-varying Growth Curves

Weed growth in agricultural fields constitutes a major deterrent to the growth of crops, often resulting in low productivity and huge losses for the farmers. Therefore, proper understanding of patterns in weed growth is vital to agricultural research. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data, which enable more sophisticated spatial analysis. Our current application concerns the development of statistical models for conducting spatial analysis of growth patterns in weeds. Our data comes from an experiment conducted in Waseca, Minnesota, that recorded growth of the weed Setariaspp. We capture the spatial variation in Setaria spp. growth using spatially-varying growth curves. An added challenge is that these designs are spatially replicated, with each plot being a lattice of sub-plots. Therefore, spatial variation may exist at different resolutions – a macro level variation between the plots and micro level variation between the sub-plots nested within each plot. We develop a Bayesian hierarchical framework for this setting. Flexible classes of models result which are fitted using simulation-based methods.     

Effectiveness of a fixed-depth sensor deployed from a buoy to estimate water-column cyanobacterial biomass depends on wind speed

Water quality sondes have the advantage of containing multiple sensors, extended deployment times, high temporal resolution, and telecommunication with stakeholder accessible data portals. However, sondes that are part of buoy deployments often suffer from typically being fixed at one depth. Because water treatment plants are interested in water quality at a depth of the water intake and other stakeholders (ex. boaters and swimmers) are interested in the surface, we examined whether a fixed depth of approximately 1 m could cause over- or under-estimation of cyanobacterial biomass. We sampled the vertical distribution of cyanobacteria adjacent to a water quality sonde buoy in the western basin of Lake Erie during the summers of 2015–2017. A comparison of buoy cyanobacteria RFU (Relative Fluorescence Unit) at 1 m to cyanobacteria chlorophyll a (chla) measured throughout the water column showed occurrences when the buoy both under and overestimated the cyanobacteria chla at specific depths. Largest differences between buoy measurements and at-depth grab samples occurred during low wind speeds (< 4.5 m/sec) because low winds allowed cyanobacteria to accumulate at the surface above the buoy's sonde. Higher wind speeds (> 4.5 m/sec) resulted in better agreement between the buoy and at-depth measurements. Averaging wind speeds 12 hr before sample collection decreased the difference between the buoy and at-depth samples for high wind speeds but not low speeds. We suggest that sondes should be placed at a depth of interest for the appropriate stakeholder group or deploy sondes with the ability to sample at various depths.     

A SIMULATION OF RIVER-BASIN RESPONSE TO MESOSCALE METEOROLOGICAL FORCING: THE SUSQUEHANNA RIVER BASIN EXPERIMENT (SRBEX)1

ABSTRACT: A mesoscale meteorological model, a surface hydrology model, and a ground-water hydrology model are linked to simulate the hydrographic response of a large river basin to a single storm. Synoptic climatology is employed to choose a representative hydro-climatic event. The mesoscale meteorological model uses three nested domains to simulate relatively high-resolution precipitation over a sub-basin of the Susquehanna River Basin. The hydrology models simulate surface runoff and ground-water baseflow using both analyzed and simulated precipitation. The hydrologic abstractions are handled using both Curve Number and Green-Ampt routines. To support the linkage of the numerical models, special attention is given to data resampling and reprojection. The mesoscale meteorological model simulation captures the spatial and temporal structure of the storm event, while the hydrology models represent the timing of the event well. The Curve Number method generates a realistic hydrograph with both analyzed and simulated precipitation. In contrast, the hydrographic response generated by the Green-Ampt routine is inferior. Several interrelated factors contribute to these results, including: the nature of the precipitation event chosen for the experiment; the tendency of the mesoscale meteorological model to underpredict low intensity, widespread precipitation in this case; and the influence of the surface soil-texture characteristics on infiltration rates.     

Exudation of dissolved organic carbon by brown algae

The release via exudation of dissolved organic carbon by Ascophyllum nodosum (L.) Le Jol. was investigated under laboratory conditions. In contrast to results previously reported by Sieburth (1969), continuous release of organic matter was found with only 1 specimen out of 21 tested either in stagnant sea water or in sea water flowing through the system. The holdfast of the plants was found to release relatively large amounts of organic material; however, this release lasted only for short periods, and was most probably due to damage caused by removing the plants from their substrate. The possible reasons for the failure to detect exudation are discussed. With Fucus vesiculosus L., no reliable results could be obtained, most probably due to particulate matter sloughing off the plants during the washings and during the experiments under conditions of photosynthesis.     

Dependence of dissolved carbohydrate concentrations upon small scale nanoplankton and bacterioplankton distributions in the western Sargasso Sea

Significant correlations between trophic components of the <20 m microbial plankton and the concentrations of total dissolved carbohydrate (TCHO) and polysaccharide (PCHO) have been found at two drogued buoy stations which were sampled at 3 or 4-h intervals over diel cycles. An attempt was made to sample on two pre-selected isotherms (approximating isopycnals) at each station. Significant inverse correlations of TCHO and of PCHO with numbers of phototrophic nanoplankton (PNAN) were found along both isotherms at a station off the Carolina coast. Off central Florida, TCHO and/or PCHO were significant multiple linear functions of PNAN, heterotrophic bacterioplankton (BAC) and sometimes heterotrophic nanoplankton (HNAN) counts. Partial regression coefficients for PNAN were always negative and those for HNAN were positive. Inverse trends dominated the relations of BAC with PCHO and TCHO. The combined data from the two stations (300 nautical miles apart) produced very similar multiple linear relations. This suggests that the observed relationships are real, resulting from general physiological processes and interactions of the microbial plankton groups rather than from chance occurrences at a particular station, and that the combined activities of the <20 m plankton actively regulate dissolved carbohydrate concentrations in the Sargasso Sea.