Sources Of Fecal Contamination Research Articles

Evaluation of Conventional and Alternative Monitoring Methods for a Recreational Marine Beach with Nonpoint Source of Fecal Contamination

The objectives of this work were to compare enterococci (ENT) measurements based on the membrane filter, ENT(MF) with alternatives that can provide faster results including alternative enterococci methods (e.g., chromogenic substrate (CS), and quantitative polymerase chain reaction (qPCR)), and results from regression models based upon environmental parameters that can be measured in real-time. ENT(MF) were also compared to source tracking markers (Staphylococcus aureus, Bacteroidales human and dog markers, and Catellicoccus gull marker) in an effort to interpret the variability of the signal. Results showed that concentrations of enterococci based upon MF (<2 to 3320 CFU/100 mL) were significantly different from the CS and qPCR methods (p < 0.01). The correlations between MF and CS (r = 0.58, p < 0.01) were stronger than between MF and qPCR (r ≤ 0.36, p < 0.01). Enterococci levels by MF, CS, and qPCR methods were positively correlated with turbidity and tidal height. Enterococci by MF and CS were also inversely correlated with solar radiation but enterococci by qPCR was not. The regression model based on environmental variables provided fair qualitative predictions of enterococci by MF in real-time, for daily geometric mean levels, but not for individual samples. Overall, ENT(MF) was not significantly correlated with source tracking markers with the exception of samples collected during one storm event. The inability of the regression model to predict ENT(MF) levels for individual samples is likely due to the different sources of ENT impacting the beach at any given time, making it particularly difficult to to predict short-term variability of ENT(MF) for environmental parameters.

Use of Barcoded Pyrosequencing and Shared OTUs To Determine Sources of Fecal Bacteria in Watersheds

While many current microbial source tracking (MST) methods rely on the use of specific molecular marker genes to identify sources of fecal contamination, these methods often fail to determine all point and nonpoint contributors of fecal inputs into waterways. In this study, we developed a new library-dependent MST method that uses pyrosequencing-derived shared operational taxonomy units (OTUs) to define sources of fecal contamination in waterways. A total 56,841 pyrosequencing reads of 16S rDNA obtained from the feces of humans and animals were evaluated and used to compare fecal microbial diversity in three freshwater samples obtained from the Yeongsan river basin in Jeonnam Province, South Korea. Sites included an urbanized agricultural area (Y1) (Escherichia coli counts ≥ 1600 CFU/100 mL), an open area (Y2) with no major industrial activities (940 CFU/100 mL), and a typical agricultural area (Y3) (≥ 1600 CFU/100 mL). Data analyses indicated that the majority of bacteria in the feces of humans and domesticated animals were comprised of members of the phyla Bacteroidetes or Firmicutes, whereas the majority of bacteria in wild goose feces and freshwater samples were classified to the phylum Proteobacteria. Analysis of OTUs shared between the fecal and environmental samples suggested that the potential sources of the fecal contamination at the sites were of human and swine origin. Quantification of fecal contamination was also examined by comparing the density of pyrosequencing reads in each fecal sample within shared OTUs. Taken together, our results indicated that analysis of shared OTUs derived from barcoded pyrosequencing reads provide the necessary resolution and discrimination to be useful as a next generation platform for microbial source tracking studies.

Bacterial source tracking guides management of boat head waste in a coastal resort area

Fecal contamination of water bodies causes a public health problem and economic loss. To control such contamination management actions need to be guided by sound science. From 2007–2009 a study was undertaken to determine the sources of fecal bacteria contamination to the marine waters adjoining the Town of Wrightsville Beach, North Carolina, USA. The research effort included sampling for fecal coliform and Enterococcus bacteria, sampling for optical brighteners, dye studies, and use of molecular bacterial source tracking techniques including polymerase chain reaction (PCR) and terminal restriction fragment polymorphism (T-RFLP) fingerprinting of the Bacteroides–Prevotella group. Of the 96 samples collected from nine locations during the study, the water contact standard for Enterococcus was exceeded on 13 occasions. The T-RFLP fingerprint analyses demonstrated that the most widespread source of fecal contamination was human, occurring in 38% of the samples, with secondary ruminant and avian sources also detected. Optical brightener concentrations were low, reflecting a lack of sewage line leakage or spills. A lack of sewer leaks and lack of septic systems in the town pointed toward discharge from boat heads into the marine waters as the major cause of fecal contamination; this was supported by dye studies. Based on these data, the Town initiated action to have the U.S. Environmental Protection Agency declare the coastal waters (out to 3 nautical miles), the nearby Atlantic Intracoastal Waterway and its tributaries a no-discharge zone (NDZ) to alleviate the human fecal pollution. The Town garnered supporting resolutions from other local communities who jointly petitioned the North Carolina Department of Environmental and Natural Resources. This State regulatory agency supported the local government resolutions and sent an application for an NDZ to the EPA in April 2009. The EPA concurred, and in February 2010 the coastal waters of New Hanover County, NC, became the first marine area on the U.S. eastern seaboard between Delaware and the Florida Keys to be declared a no-discharge zone.

Rapid detection of Escherichia coli in waters using fluorescent in situ hybridization, direct viable counting and solid phase cytometry

We developed an improved Fluorescent In Situ Hybridization FISH-based method to detect viable Escherichia coli cells by solid phase cytometry (SPC), and results were compared to those obtained by the standard culture method. The method includes a direct viable count (DVC) assay, multi-probes labelled and unlabelled (helpers) to detect specifically viable E. coli cells and to enhance SPC cell counts. We demonstrate that helpers increase the fluorescence intensity of hybridized E. coli cells as detected by SPC and assess the high specificity of the DVC-FISH procedure on a large panel of cultured strains. Application to seawater, freshwater and wastewater samples showed a good correlation between SPC cells counts and standard plate counts. The high specificity of the procedure was demonstrated as well as its accuracy for detecting and counting viable E. coli cells in environmental samples. The developed approach may be used to monitor faecal contamination sources and to investigate the occurrence of viable E. coli in natural environments.

Analysis of human and animal fecal microbiota for microbial source tracking

Microbial compositions of human and animal feces from South Korea were analyzed and characterized. In total, 38 fecal samples (14 healthy adult humans, 6 chickens, 6 cows, 6 pigs and 6 geese) were analyzed by 454 pyrosequencing of the V2 region of the 16S rRNA gene. Four major phyla, Actinobacteria, Proteobacteria, Firmicutes and Bacteroidetes, were identified in the samples. Principal coordinate analysis suggested that microbiota from the same host species generally clustered, with the exception of those from humans, which exhibited sample-specific compositions. A network-based analysis revealed that several operational taxonomic units (OTUs), such as Lactobacillus sp., Clostridium sp. and Prevotella sp., were commonly identified in all fecal sources. Other OTUs were present only in fecal samples from a single organism. For example, Yania sp. and Bifidobacterium sp. were identified specifically in chicken and human fecal samples, respectively. These specific OTUs or their respective biological markers could be useful for identifying the sources of fecal contamination in water by microbial source tracking.

Library-dependent and library-independent microbial source tracking to identify spatial variation in faecal contamination sources along a Lake Ontario beach (Ontario, Canada)

Multiple microbial source tracking methods were applied to investigate spatial variation in faecal pollution sources impacting a 1.7 km freshwater beach on Lake Ontario (Canada). The highest E. coli concentrations measured in the study area were from interstitial sand pore water at Sunnyside Beach, reaching 2.6 x 10(6) CFU/100 ml. These E. coli concentrations exceeded those in the nearby Humber River and Black Creek, which are impacted by combined sewer overflows containing municipal wastewater and by stormwater conveying washoff from the urban area. Library-independent Bacteroidales HF183 analyses identified the more frequent occurrence of municipal wastewater contamination in the Humber River and at a Sunnyside Beach location closest to the mouth of the river. Library-dependent E. coli antibiotic resistance and rep-PCR DNA fingerprinting analyses identified the more frequent occurrence of bird faecal contamination at Sunnyside Beach locations away from the river mouth. These microbial source tracking results raise caution about managing beaches with multiple sources of contamination as a single entity without considering spatial variability in faecal pollution sources and the need for more localized beach management practices.

Estimating the primary etiologic agents in recreational freshwaters impacted by human sources of faecal contamination

Epidemiology studies of recreational waters have demonstrated that swimmers exposed to faecally-contaminated recreational waters are at risk of excess gastrointestinal illness. Epidemiology studies provide valuable information on the nature and extent of health effects, the magnitude of risks, and how these risks are modified or associated with levels of faecal contamination and other measures of pollution. However, such studies have not provided information about the specific microbial agents that are responsible for the observed illnesses in swimmers. The objective of this work was to understand more fully the reported epidemiologic results from studies conducted on the Great Lakes in the US during 2003 and 2004 by identifying pathogens that could have caused the observed illnesses in those studies. We used a Quantitative Microbial Risk Assessment (QMRA) approach to estimate the likelihood of pathogen-induced adverse health effects. The reference pathogens used for this analysis were Norovirus, rotavirus, adenovirus, Cryptosporidium spp., Giardia lamblia, Campylobacter jejuni, Salmonella enterica, and Escherichia coli O157:H7. Two QMRA-based approaches were used to estimate the pathogen combinations that would be consistent with observed illness rates: in the first, swimming-associated gastrointestinal (GI) illnesses were assumed to occur in the same proportion as known illnesses in the US due to all non-foodborne sources, and in the second, pathogens were assumed to occur in the recreational waters in the same proportion as they occur in disinfected secondary effluent. The results indicate that human enteric viruses and in particular, Norovirus could have caused the vast majority of the observed swimming-associated GI illnesses during the 2003/2004 water epidemiology studies. Evaluation of the time-to-onset of illness strongly supports the principal finding and sensitivity analyses support the overall trends of the analyses even given their substantial uncertainties.

The use of carbon-utilization profiling to determine sources of fecal contamination in a central Texas watershed

The purpose of this research was to characterize the relationship of Escherichia coli isolates from various animals, sewage, and water based on carbon substrate utilization patterns, and to use these patterns to determine the dominant contributors of nonpoint source fecal pollution to a central Texas reservoir from its watershed. We collected 1028 fecal samples from cattle, companion animals, goat, horse, poultry, sewage, sheep, and wildlife, collectively. From these, 1915 E. coli fecal isolates were analyzed. We collected 100 water samples throughout the North Bosque watershed; 910 E. coli water isolates were analyzed. The Biolog system was used to generate a carbon-utilization pattern for each isolate. A dendrogram constructed from the carbon-utilization patterns demonstrated that isolates from the same source category usually clustered together, excluding water isolates that were spread over many clusters. A bacterial-source tracking library was constructed from the carbon-utilization data obtained from the fecal and sewage isolates and analyzed for internal accuracy. Rates of correct classification for the library ranged from 12.8 to 78.6%. The average rate of correct classification for the library was 45.8%, and specificity values were high, ranging from 75 to 99%. When water isolates were submitted to the library for identification, 43 were classified as originating from cattle, indicating cattle were the dominant source of fecal pollution in the watershed. This was followed by sewage at 27%. Based on these data, our first recommendation for decreasing bacterial pollution in this watershed is to implement strategies that can reduce the contribution of fecal contamination from these 2 sources.

Estimated human health risks from exposure to recreational waters impacted by human and non-human sources of faecal contamination

This work was conducted to determine whether estimated risks following exposure to recreational waters impacted by gull, chicken, pig, or cattle faecal contamination are substantially different than those associated with waters impacted by human sources such as treated wastewater. Previously published Quantitative Microbial Risk Assessment (QMRA) methods were employed and extended to meet these objectives. Health outcomes used in the analyses were infection from reference waterborne pathogens via ingestion during recreation and subsequent gastrointestinal (GI) illness. Illness risks from these pathogens were calculated for exposure to faecally contaminated recreational water at the U.S. regulatory limits of 35 cfu 100 mL −1 enterococci and 126 cfu 100 mL −1 Escherichia coli. The probabilities of GI illness were calculated using pathogen dose-response relationships from the literature and Monte Carlo simulations. Three scenarios were simulated, representing a range of feasible interpretations of the available data. The primary findings are that: 1) GI illness risks associated with exposure to recreational waters impacted by fresh cattle faeces may not be substantially different from waters impacted by human sources; and 2) the risks associated with exposure to recreational waters impacted by fresh gull, chicken, or pig faeces appear substantially lower than waters impacted by human sources. These results suggest that careful consideration may be needed in the future for the management of recreational waters not impacted by human sources.

Escherichia coli phylogenetic group determination and its application in the identification of the major animal source of fecal contamination

BackgroundEscherichia coli strains are commonly found in the gut microflora of warm-blooded animals. These strains can be assigned to one of the four main phylogenetic groups, A, B1, B2 and D, which can be divided into seven subgroups (A0, A1, B1, B22, B23, D1 and D2), according to the combination of the three genetic markers chuA, yjaA and DNA fragment TspE4.C2. Distinct studies have demonstrated that these phylo-groups differ in the presence of virulence factors, ecological niches and life-history. Therefore, the aim of this work was to analyze the distribution of these E. coli phylo-groups in 94 human strains, 13 chicken strains, 50 cow strains, 16 goat strains, 39 pig strains and 29 sheep strains and to verify the potential of this analysis to investigate the source of fecal contamination.ResultsThe results indicated that the distribution of phylogenetic groups, subgroups and genetic markers is non-random in the hosts analyzed. Strains from group B1 were present in all hosts analyzed but were more prevalent in cow, goat and sheep samples. Subgroup B23 was only found in human samples. The diversity and the similarity indexes have indicated a similarity between the E. coli population structure of human and pig samples and among cow, goat and sheep samples. Correspondence analysis using contingence tables of subgroups, groups and genetic markers frequencies allowed the visualization of the differences among animal samples and the identification of the animal source of an external validation set. The classifier tools Binary logistic regression and Partial least square -- discriminant analysis, using the genetic markers profile of the strains, differentiated the herbivorous from the omnivorous strains, with an average error rate of 17%.ConclusionsThis is the first work, as far as we are aware, that identifies the major source of fecal contamination of a pool of strains instead of a unique strain. We concluded that the analysis of the E. coli population structure can be useful as a supplementary bacterial source tracking tool.

Novel application of a statistical technique, Random Forests, in a bacterial source tracking study

In this study, data from bacterial source tracking (BST) analysis using antibiotic resistance profiles were examined using two statistical techniques, Random Forests (RF) and discriminant analysis (DA) to determine sources of fecal contamination of a Texas water body. Cow Trap and Cedar Lakes are potential oyster harvesting waters located in Brazoria County, Texas, that have been listed as impaired for bacteria on the 2004 Texas 303(d) list. Unknown source Escherichia coli were isolated from water samples collected in the study area during two sampling events. Isolates were confirmed as E. coli using carbon source utilization profiles and then analyzed via ARA, following the Kirby–Bauer disk diffusion method. Zone diameters from ARA profiles were analyzed with both DA and RF. Using a two-way classification (human vs nonhuman), both DA and RF categorized over 90% of the 299 unknown source isolates as a nonhuman source. The average rates of correct classification (ARCCs) for the library of 1172 isolates using DA and RF were 74.6% and 82.3%, respectively. ARCCs from RF ranged from 7.7 to 12.0% higher than those from DA. Rates of correct classification (RCCs) for individual sources classified with RF ranged from 23.2 to 0.2% higher than those of DA, with a mean difference of 9.0%. Additional evidence for the outperformance of DA by RF was found in the comparison of training and test set ARCCs and examination of specific disputed isolates; RF produced higher ARCCs (ranging from 8 to 13% higher) than DA for all 1000 trials (excluding the two-way classification, in which RF outperformed DA 999 out of 1000 times). This is of practical significance for analysis of bacterial source tracking data. Overall, based on both DA and RF results, migratory birds were found to be the source of the largest portion of the unknown E. coli isolates. This study is the first known published application of Random Forests in the field of BST.

Spatial dependency of cholera prevalence on potential cholera reservoirs in an urban area, Kumasi, Ghana

Cholera has been a public health burden in Ghana since the early 1970s. Between 1999 and 2005, a total of 25,636 cases and 620 deaths were officially reported to the WHO. In one of the worst affected urban cities, fecal contamination of surface water is extremely high, and the disease is reported to be prevalent among inhabitants living in close proximity to surface water bodies. Surface runoff from dump sites is a major source of fecal and bacterial contamination of rivers and streams in the study area. This study aims to determine (a) the impacts of surface water contamination on cholera infection and (b) detect and map arbitrary shaped clusters of cholera. A Geographic Information System (GIS) based spatial analysis is used to delineate potential reservoirs of the cholera vibrios; possibly contaminated by surface runoff from open space refuse dumps. Statistical modeling using OLS model reveals a significant negative association between (a) cholera prevalence and proximity to all the potential cholera reservoirs (R2=0.18, p<0.001) and (b) cholera prevalence and proximity to upstream potential cholera reservoirs (R2=0.25, p<0.001). The inclusion of spatial autoregressive coefficients in the OLS model reveals the dependency of the spatial distribution of cholera prevalence on the spatial neighbors of the communities. A flexible scan statistic identifies a most likely cluster with a higher relative risk (RR=2.04, p<0.01) compared with the cluster detected by circular scan statistic (RR=1.60, p<0.01). We conclude that surface water pollution through runoff from waste dump sites play a significant role in cholera infection.

The use of antibiotic resistance profiling as a means of tracing sources of fecal contamination in source waters

Fecal contamination of source waters and its associated intestinal pathogens continues to pose risks to public health although the extent and effect of microbial contamination of source waters gets very little attention in designing treatment plants in most developing countries. Coliform counts give an indication of the overall bacterial contamination of water and thus its safety for human consumption. However, their presence fails to provide information about the source of fecal contamination which is vital to managing fecal contamination problems in surface waters. This study explored the use of multiple antibiotic resistance (MAR) indexing as means of differentiating E. coli isolates from different sources. A total of 322 E. coli isolates were obtained from municipal wastewater and from fecal samples from domestic and wild animals. Conventional culture methods and standard chemical and biochemical tests were used for isolation and identification of E. coli. Isolates were assayed against 10 antibiotics using the micro-dilution technique. The results obtained generated antibiotic resistance profiles which were used to statistically group the isolates into different subsets. Correct source classification was obtained for 60% of human-derived and 95% non-human-derived E. coli respectively. These results indicate the validity of the usefulness of MAR indexing as a method of bacterial source tracking.

Relative decay of Bacteroidales microbial source tracking markers and cultivated Escherichia coli in freshwater microcosms.

Fecal indicator bacteria (FIB), commonly used to regulate sanitary water quality, cannot discriminate among sources of contamination. The use of alternative quantitative PCR (qPCR) methods for monitoring fecal contamination or microbial source tracking requires an understanding of relationships with cultivated FIB, as contamination ages under various conditions in the environment. In this study, the decay rates of three Bacteroidales 16S rRNA gene markers (AllBac for general contamination and qHF183 and BacHum for human-associated contamination) were compared with the decay rate of cultivated Escherichia coli in river water microcosms spiked with human wastewater. The following five sets of microcosms were monitored over 11 days: control, artificial sunlight, sediment exposure, reduced temperature, and no autochthonous predation. Decay was characterized by estimation of the time needed to produce a 2-log reduction (t(99)). No treatment-associated differences in the decay of the 4 targets were evident except with reduced predation, where E. coli, qHF183, and BacHum markers had lower levels of decay by day 3. However, there were substantial target-associated differences. Decay curves for the AllBac marker indicated a larger persistent population than those of the other targets. Exposure to sunlight, sediment, and reduced predation resulted in more rapid decay of the human-associated markers relative to cultivable E. coli, but there were no differences in t(99) values among the 4 targets under control conditions or at reduced temperatures. Further evaluation of epidemiological relationships will be needed in order to relate the markers directly to health risk. These findings suggest that the tested human-associated markers can complement E. coli as indicators of the human impact on sanitary water quality under the constrained conditions described in this paper.

Application of library-independent microbial source tracking methods for identifying the sources of faecal contamination in coastal areas

Faecal contamination sources were identified in coastal areas around the Guerande-Atlantique peninsula using two microbial source tracking (MST) methods: (i) Bacteroidales host-specific 16S rRNA gene markers measured by real-time PCR and (ii) F-specific bacteriophage (FRNAPH) genotyping. Both methods were used on 63 water samples from 7 water courses. HF183 marker and bacteriophage genogroup II (FRNAPH II) were detected in all water samples and in the majority of water samples, respectively, from La Torre stream (W5), Piriac (W2), R2000 (W3) and Mazy (W7) rain water drains, and also detected, less frequently, in Le Nau drain (W4), suggesting contamination by human faecal sources at these sites. These human markers were weakly detected in Pouliguen channel (W6). Furthermore, BacR and bacteriophage genogroup I (FRNAPH I) were also detected, but at lower concentration and frequency. So, site W6 seems to be contaminated by multiple sources, though mainly human. Finally, BacR was detected twice in Pont d'Armes channel (W1), whereas HF183 was not detected. FRNAPH I and II were detected in only 3 out of 12 water samples. Site W1 seems mainly contaminated by animal sources. As a result of our findings, actions were taken to remediate water and shellfish quality.

Optimization and validation of rep-PCR genotypic libraries for microbial source tracking of environmental Escherichia coli isolates

Escherichia coli can be used to help identify sources of fecal contamination in the environment. Escherichia coli genotypic fecal libraries and pattern-matching algorithms were assessed for their effectiveness in correctly identifying sources. Fecal samples (n = 172) were collected from various sources from three agricultural landscapes in Canada. Escherichia coli isolates were fingerprinted using BOX- and enterobacterial repetitive intergenic consensus (ERIC) - polymerase chain reaction primers, revealing 769 and 1 057 distinct genotypes, respectively, for the 9 047 isolates collected in 2004 in Ontario. The average rate of correct classification (ARCC) was comparable for BOX- (48%) and ERIC-based (62%) libraries and between libraries with clones removed per sample (55%) and clones removed per unit (54%). ARCC increased with fewer classification units (from 44% to 65%). ARCC for k-nearest neighbour (64%) and maximum similarity (60%) algorithms were comparable, but maximum similarity had better sensitivity and specificity than k-nearest neighbour. Geographical and temporal shifts in community composition resulted in loss of accuracy. Several ERIC genotypes (n = 112) were common between sources and were removed from the library, improving ARCC (77%). The latter library proved to be more accurate, but its accuracy with respect to sourcing environmental isolates remains to be tested.

Surface Runoff Transport of Escherichia coli after Poultry Litter Application on Pastureland

Escherichia coli transported in surface runoff from dissolution of applied poultry litter is a major variable in assessing fecal contamination of streams. However, the relative magnitude of the E. coli concentration from a specific poultry litter application and relative to the time lag between litter application and rainfall are not completely understood. This research investigated E. coli transport in runoff on fourteen 2 m 2 m pastureland plots. Poultry litter was manually applied (4,942 kg ha-1) in twelve plots followed by artificial rainfall with intensities equivalent to 2-year and 5-year storm events. Rainfall was applied in duplicate plots immediately after poultry litter application and 24 and 120 h after litter application. Experiments were also conducted on two control plots without poultry litter application. Surface runoff was collected using a flume installed in a trench. E. coli was quantified from sampled runoff and used as an indicator of fecal contamination by the most probable number (MPN) technique. No significant differences were observed in average event mean concentrations (EMCs) relative to storm intensity. Statistically significant differences were observed in average EMCs relative to time lag between litter application and rainfall. A nonlinear relationship was observed between average E. coli EMC and time lag, with the EMC decreasing between 0 h (1.6 105 MPN/100 mL) and 24 h (1.3 104 MPN/100 mL) and then increasing at 120 h (4.3 104 MPN/100 mL). E. coli were always detected in the control plots (average EMC of 6.8 103 MPN/100 mL), indicating the presence and transport of fecal bacteria from sources independent of the immediate poultry litter application. Even though poultry litter application may increase E. coli concentrations in runoff, other sources of fecal contamination serve as a significant component of the total E. coli EMC, especially as the time lag between litter application and rainfall events increases.

Alternative methods in tracking sources of microbial contamination in waters

A key factor in the management and remediation of impaired ground- and surface water is the ability to distinguish the sources of faecal contamination. Several approaches have been adopted as microbial source tracking methods (MST), which are generally classified as culturing, phenotypic, genetic, and chemical MST. None of the techniques used thus far can be considered a standard; important factors, such as the statistical correlation between the source and the faecal indicator and the understanding of the environmental fate of the faecal pollutants, still need attention. The most promising MST methods available today are based on the genetic fingerprinting of faecal micro-organisms. However, research is very active also in the investigation of pharmaceuticals and personal care products discharged in the environment together with faecal waste.An updated overview of MST methods to distinguish human from animal sources of faecal pollution is presented here, focusing particularly on the potentialities of new chemical tracers.

Die‐off of Escherichia coli in intact and disrupted cowpats

AbstractDiffuse pollution from grazed pastures is recognised as an important source of faecal microbial contamination of surface waters, and farmers urgently require mitigation options to reduce this impact of their farming activities. An obvious mitigation strategy is to reduce the size of the reservoir of faecal material in pastures during critical periods when overland flow is most likely. This work tested the hypothesis that smearing fresh cowpats to increase their surface area would increase exposure to solar radiation and increase desiccation, which in turn would accelerate the die‐off of Escherichia coli in the faecal material. The total solids content and E. coli concentration in intact and disrupted cowpats were monitored during the four seasons. The total solids content was significantly (P &lt; 0.001) higher in the disrupted cowpats compared to the intact cowpats. This indicates that increased desiccation of the faecal material was successful. However, there was no significant difference (P &gt; 0.05) in E. coli concentrations in the disrupted and intact cowpats. The physical disruption of cowpats did not therefore accelerate the die‐off of E. coli in the faecal material. The disrupted cowpats did appear to decompose faster than the intact cowpats. Mitigation options to reduce faecal micro‐organism losses in overland flow from grazed pastures will now need to focus on other methods to reduce the build up of reservoirs of faecal material on farm.

Chemometric approach to validating faecal sterols as source tracer for faecal contamination in water

Faecal sterols detection is a promising method for identifying sources of faecal pollution. In this study, faecal contamination in water samples from point source (sewage treatment plants, chicken farms, quail farms and horse stables) was extracted using the solid phase extraction (SPE) technique. Faecal sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol and stigmastanol) were selected as parameters to differentiate the source of faecal pollution. The results indicated that coprostanol, cholesterol and β-sitosterol were the most significant parameters that can be used as source tracers for faecal contamination. Chemometric techniques, such as cluster analysis, principal component analysis and discriminant analysis were applied to the data set on faecal contamination in water from various pollution sources in order to validate the faecal sterols’ profiles. Cluster analysis generated three clusters: coprostanol was in cluster 1, cholesterol and β-sitosterol formed cluster 2, while cluster 3 contained stigmasterol and stigmastanol. Discriminant analysis suggested that coprostanol, cholesterol and β-sitosterol were the most significant parameters to discriminate between the faecal pollution source. The use of chemometric techniques provides useful and promising indicators in tracing the source of faecal contamination.