The effect of the addition of synthetic sheep urine (SSU) and plant species on the bacterial community composition of upland acidic grasslands was studied using a microcosm approach. Low, medium, and high concentrations of SSU were applied to pots containing plant species typical of both unimproved (Agrostis capillaris) and agriculturally improved (Lolium perenne) grasslands, and harvests were carried out 10 days and 50 days after the addition of SSU. SSU application significantly increased both soil pH (P < 0.005), with pH values ranging from pH 5.4 (zero SSU) to pH 6.4 (high SSU), and microbial activity (P < 0.005), with treatment with medium and high levels of SSU displaying significantly higher microbial activity (triphenylformazan dehydrogenase activity) than treatment of soil with zero or low concentrations of SSU. Microbial biomass, however, was not significantly altered by any of the SSU applications. Plant species alone had no effect on microbial biomass or activity. Bacterial community structure was profiled using bacterial automated ribosomal intergenic spacer analysis. Multidimensional scaling plots indicated that applications of high concentrations of SSU significantly altered the bacterial community composition in the presence of plant species but at different times: 10 days after application of high concentrations of SSU, the bacterial community composition of L. perenne-planted soils differed significantly from those of any other soils, whereas in the case of A. capillaris-planted soils, the bacterial community composition was different 50 days after treatment with high concentrations of SSU. Canonical correspondence analysis also highlighted the importance of interactions between SSU addition, plant species, and time in the bacterial community structure. This study has shown that the response of plants and bacterial communities to sheep urine deposition in grasslands is dependent on both the grass species present and the concentration of SSU applied, which may have important ecological consequences for agricultural grasslands.Intensification of upland pastures has been widespread in northwestern Europe, with formerly rough grazing areas undergoing improvement through fertilization, liming, and increased grazing (5). Intensification leads to shifts in the floristic composition in acidic upland grasslands, resulting in diminished floristic diversity (19). In Ireland and the United Kingdom, the predominant upland grassland formation on acidic soils is a species-rich but low-yielding plant community, with Agrostis capillaris as the predominant grass species and Nardus stricta, Holcus lanatus, Festuca rubra, and Festuca ovina typically at lower abundances (36). These seminatural grasslands can be improved to species-poor but high-yielding types dominated by Lolium perenne through intensive practices such as fertilization, grazing, and/or reseeding. A loss of diversity through intensification has been a cause for some concern (20, 23), particularly since little is known about impacts on belowground bi...
The revised Bathing Water Directive (2006/7/EC) requires EU member states to minimise the risk to public health from faecal pollution at bathing waters through improved monitoring and management approaches. While increasingly sophisticated measurement methods (such as microbial source tracking) assist in the management of bathing water resources, the use of deterministic predictive models for this purpose, while having the potential to provide decision making support, remains less common.This study explores an integrated, deterministic catchment-coastal hydro-environmental model as a decision-making tool for beach management which, based on advance predictions of bathing water quality, can inform beach managers on appropriate management actions (to prohibit bathing or advise the public not to bathe) in the event of a poor water quality forecast. The model provides a 'moving window' five-day forecast of E. coli at a bathing water compliance point off the Irish coast and the accuracy of bathing water management decisions were investigated for model predictions under two scenarios over the period from the 11 th August to the 5 th September, 2012. Decisions for Scenario 1 were based on model predictions where rainfall forecasts from a meteorological source (www.yr.no) were used to drive the rainfall-runoff processes in the catchment component of the model, and for Scenario 2, were based on predictions that were improved by incorporating real-time rainfall data Manuscript Click here to view linked References 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 2 from a sensor network within the catchment into the forecasted meteorological input data. The accuracy of the model in the decision-making process was assessed using the contingency table and its metrics.The predictive model gave reasonable outputs to support appropriate decision making for public health protection. Scenario 1 provided real-time predictions that, on 77% of instances during the study period where both predicted and E. coli concentrations were available, would correctly inform a beach manager to either take action to mitigate for poor bathing water quality or take no action. However, Scenario 1 also provided data to support a decision to take action (when none was necessary -a type I error) in 4% of instances and to take no action (when action was required -a type II error) in 19% of the instances analysed. Type II errors are critical in terms of public health protection given that for this error, bathers can be exposed to risks from poor bathing water quality. Scenario 2, on the other hand, provided predictions that would support correct management actions for 79% of the instances but would result in type I and type II errors for 4% and 17% of the instances respectively.Comparison of Scenarios 1 and 2 for this study indicate that Scenario 2...
A three-dimensional model is used to assess the bathing water quality of two beaches following changes to the sewage management system. The model, firstly was first calibrated to hydrodynamic and water quality data from the period prior to upgrade of sewage treatment works (STWs), was .tThen it was used to simulate Escherichia coli distributions for discharge scenarios of the periods prior to and following the upgrade of the STWs under dry and wet weather conditions. Escherichia coli distributions under dry weather conditions demonstrate that the upgrade in the treatment worksSTWs has remarkably improved the bathing water qualityquality to a Blue Flag status.Consequently, the Blue Flag status at the two beaches would be regained.The new discharge strategy is expected to drastically reduce the rainfall-related incidents in which environmental limits of the Bathing Water Directive are breached. However, significant exceedances to these limits may still occur under wet weather conditions at Bray beach due to storm overflows that may still be discharged through the two Bray outfalls.
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