Development and testing of a risk indexing framework to determine field-scale critical source areas of faecal bacteria on grassland

Oliver, David M.; Page, Trevor; Hodgson, C. J.; Heathwaite, A. Louise; Chadwick, D. R.; Fish, Robert; Winter, Michael

doi:10.1016/j.envsoft.2009.10.003

Cited by 28 publications

(14 citation statements)

References 64 publications

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“…; Oliver et al . ). This variability in shedding is not only linked to large‐scale faecal surveys across multiple farms, regions or countries; some studies have reported large variation from within a single herd (e.g.…”

Section: Introductionmentioning

confidence: 97%

“…The concentrations of E. coli found in freshly excreted livestock faeces can vary by several orders of magnitude (Cox et al 2005;Muirhead et al 2006;Ferguson et al 2009). The factors that contribute to this variation have been suggested to include diet, animal age and livestock type, among others (Russell et al 2000;Moriarty et al 2008;Oliver et al 2010b). This variability in shedding is Letters in Applied Microbiology 59, 86--92 © 2014 The Society for Applied Microbiology not only linked to large-scale faecal surveys across multiple farms, regions or countries; some studies have reported large variation from within a single herd (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Seasonal and within-herd variability of E. coli concentrations in fresh dairy faeces

Oliver

2014

Lett Appl Microbiol

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Significance and Impact of the Study: This study provides a comprehensive temporal data set of faecal indicator organism (FIO) counts (both E. coli and other coliforms) in fresh dairy faeces for Scotland. Such faecal audits for the UK are scarce which is surprising given that livestock constitute one of the largest agricultural sources of diffuse microbial pollution of surface waters and contributors to poor bathing water quality. Such FIO concentration data (and evaluation of variability across seasonal, within-herd and year-on-year counts) in fresh faeces is a fundamental precursor to the robust parameterization of models that aim to predict the fate and transfer of both FIOs and pathogens in agricultural catchments. AbstractThe aim of this study was to determine concentrations of culturable faecal indicator organisms (FIOs) in freshly excreted dairy faeces and assess seasonal, within-herd and year-on-year variability in counts. Such values are essential in order to provide input parameters and associated uncertainty bounds for empirical models designed to determine the burden of FIOs on pasture. A longitudinal faecal analysis survey (n = 80) was conducted at a conventional dairy farm in central Scotland over a 2-year period. The analysis quantified counts of Escherichia coli and other nonE. coli coliforms and compared the concentrations of these FIO groups across contrasting seasons. The overall mean concentration of E. coli was 6Á63 and 6Á58 log 10 CFU g À1 dry weight in 2012 and 2013, respectively. However, concentrations of E. coli in faecal pats on each seasonal sampling event were highly variable and spanned several orders of magnitude on all occasions. Concentrations of E. coli in faeces excreted in winter were found to be lower than those excreted in all other seasons in 2012, though patterns of seasonal shedding were not consistent in observations the following year highlighting additional sources of uncertainty in FIO loading to land from dairy herds.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Seasonal and within-herd variability of E. coli concentrations in fresh dairy faeces

Oliver

2014

Lett Appl Microbiol

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“…Indeed, different modelling approaches can be used, often combining hydrological information with livestock grazing densities and associated E. coli content of faecal matter to inform regulators and decision-makers of spatial and temporal risks in catchment systems34. However, this can be a challenging undertaking due to the naturally high variation of E. coli in different environmental matrices in both space and time3536, further reinforced by our study and the complex patterns observed in E. coli persistence (both in terms of growth and die-off) across multiple seasons and years.…”

Section: Discussionmentioning

confidence: 99%

Effects of seasonal meteorological variables on E. coli persistence in livestock faeces and implications for environmental and human health

Oliver

Page

2016

Sci Rep

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Agriculture contributes significant volumes of livestock faeces to land. Understanding how faecal microbes respond to shifts in meteorological patterns of contrasting seasons is important in order to gauge how environmental (and human health) risks may alter under a changing climate. The aim of this study was to: (i) quantify the temporal pattern of E. coli growth within dairy faeces post defecation; and (ii) derive E. coli seasonal population change profiles associated with contrasting environmental drivers. Evaluation of the die-off dynamics of E. coli revealed that a treatment mimicking drought and warming conditions significantly enhanced persistence relative to E. coli in faeces that were exposed to field conditions, and that this pattern was consistent across consecutive years. The internal temperature of faeces was important in driving the rate of change in the E. coli population in the immediate period post defecation, with most E. coli activity (as either die-off or growth) occurring at low dry matter content. This study highlighted that the use of seasonal E. coli persistence profiles should be approached with caution when modelling environmental and human health risks given the increased likelihood of atypical seasonal meteorological variables impacting on E. coli growth and die-off.

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“…The connectivity factor is related to the critical source area concept and the likelihood of the mobilized FIOs reaching the stream channel. The risk factors and weightings used in the FIORIT calculations are based on expert opinion (Oliver et al, 2010). The FIORIT is designed to operate at a field scale and is dominated by overland flow delivery of FIOs to the stream and therefore will be more reflective of storm-flow loadings to the stream rather than the base-flow conditions.…”

Section: Introductionmentioning

confidence: 99%

“…A risk‐index may be a useful approach for managing fecal microbial losses in catchments. Goss and Richards (2008) highlight the issues with the development of a full process‐based model and propose a risk‐index as an “interim stage in the establishment of a fully quantitative microbial risk assessment approach.” Oliver et al (2010) describes the development and testing of a FIO risk‐index tool (FIORIT) for use in the United Kingdom. The FIORIT calculation is based on three factors: source, transfer, and connectivity.…”

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confidence: 99%

A Farm-Scale Risk-Index for Reducing Fecal Contamination of Surface Waters

Muirhead

2015

J. Environ. Qual.

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There is increasing recognition of the adverse impacts of agricultural practices on microbial water quality leading to increased expectation on farmers to manage environmental impacts on water quality. Therefore, farmers require a tool to help them prioritize mitigations targeted at reducing fecal contamination of surface water. A farm-scale risk-index was developed from modeled data on the predicted losses of from selected farm practices. The farm-scale data were then converted to a catchment scale risk value and calibrated against stream concentration data measured in five catchments. The data from the five catchments indicate that there is a relationship between the risk of losses from some farm practices and the resulting levels in the streams. The results show that the adoption of existing mitigation options for fecal contamination should result in a substantial reduction of concentrations in streams flowing through catchments used for intensive dairy farming. However, the relatively high concentrations in the stream when the calculated risk-index values are low indicate that currently available mitigation practices may not be sufficient to achieve contact recreational water quality standards in many catchments due to other sources of . This risk-index approach can be incorporated into existing decision support tools to enable farmers to manage fecal contamination impacts from their farming operations.

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Development and testing of a risk indexing framework to determine field-scale critical source areas of faecal bacteria on grassland

Cited by 28 publications

References 64 publications

Seasonal and within-herd variability of E. coli concentrations in fresh dairy faeces

Seasonal and within-herd variability of E. coli concentrations in fresh dairy faeces

Effects of seasonal meteorological variables on E. coli persistence in livestock faeces and implications for environmental and human health

A Farm-Scale Risk-Index for Reducing Fecal Contamination of Surface Waters

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