Escherichia coli runoff from sheep and dairy cow grazed pasture: A plot scale simulation.

Animal agriculture is recognized as a key source of fecal microbial impacts on water quality and associated risks to human health. Most of the research effort has focused on losses of fecal microbes from cow/cattle feces with little research effort on sheep fecal risks. The literature on fecal microbial risks from pasture is complicated by the fact that experiments are carried out in different environments leading to difficulties in making direct comparisons between sheep and cow/cattle losses from pasture areas. In this study, a plot scale simulation was conducted on the same pasture plots, using simulated rainfall to generate comparable runoff conditions, and using simulated grazing to create similar relative stocking rates. The Escherichia coli concentrations in the runoff were similar from simulated or natural rainfall events. At an equivalent stocking rate, the E. coli runoff concentrations from the sheep grazed pastures were four times higher than the cow grazed pasture. These results show that at an equivalent stocking rate, the E. coli runoff risk from sheep grazed pasture is higher than for cow grazed pasture. Further research is needed to understand the relative impacts of different grazing species of animals as well as stocking rate or management effects on these relative risks to water quality.

A Heuristic Method for Determining Changes of Source Loads to Comply with Water Quality Limits in Catchments.

A common land and water management task is to determine where and by how much source loadings need to change to meet water quality limits in receiving environments. This paper addresses the problem of quantifying changes in loading when limits are specified in many locations in a large and spatially heterogeneous catchment, accounting for cumulative downstream impacts. Current approaches to this problem tend to use either scenario analysis or optimization, which suffer from difficulties of generating scenarios that meet the limits, or high complexity of optimization approaches. In contrast, we present a novel method in which simple catchment models, load limits, upstream/downstream spatial relationships and spatial allocation rules are combined to arrive at source load changes. The process iteratively establishes the critical location (river segment or lake) where the limits are most constraining, and then adjusts sources upstream of the critical location to meet the limit at that location. The method is demonstrated with application to New Zealand (268,000 km2) for nutrients and the microbial indicator E. coli, which was conducted to support policy development regarding water quality limits. The model provided useful insights, such as a source load excess (the need for source load reduction) even after mitigation measures are introduced in order to comply with E. coli limits. On the other hand, there was headroom (ability to increase source loading) for nutrients. The method enables assessment of the necessary source load reductions to achieve water quality limits over broad areas such as large catchments or whole regions.

Variability of Escherichia coli Concentrations in Rivers during Base-Flow Conditions in New Zealand.

concentrations in rivers are known to vary considerably. Much research has focused on storm events and the relationships between fecal microbe concentrations and flows. However, there is still considerable variability in microbial concentrations during base-flow conditions, and little research has been conducted to understand this short-term variability in rivers. We investigated the variability of concentrations in base flows at the time scales of minutes, hours, and days and compared this to variability from laboratory replication of the measurement methods. This was conducted in three different-sized rivers in both summer and winter seasons. Estimates of variability were analyzed using the coefficient of variation (CV). The variability at the minute time scale was 17%, compared with the laboratory replication variability of 15%. The CV then increased to approximately 32 and 60% at the hourly and daily time scales, respectively. There is strong evidence that both time scale ( < 0.001) and river ( < 0.001) significantly affect the variation in concentrations. The concentrations were higher in summer than winter, with a marked effect in the smallest stream, where at one site the concentrations were >2000 most probable number (mpn) 100 mL in all summer samples. This variability of concentrations should be considered when interpreting the results from a one-off grab sample used to compare against water quality standards or for calibrating models.

Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities.

Natural waters serve as habitat for a wide range of microorganisms, a proportion of which may be derived from fecal material. A number of watershed models have been developed to understand and predict the fate and transport of fecal microorganisms within complex watersheds, as well as to determine whether microbial water quality standards can be satisfied under site-specific meteorological and/or management conditions. The aim of this review is to highlight and critically evaluate developments in the modeling of microbial water quality of surface waters over the last 10 years and to discuss the future of model development and application at the watershed scale, with a particular focus on fecal indicator organisms (FIOs). In doing so, an agenda of research opportunities is identified to help deliver improvements in the modeling of microbial water quality draining through complex landscape systems. This comprehensive review therefore provides a timely steer to help strengthen future modeling capability of FIOs in surface water environments and provides a useful resource to complement the development of risk management strategies to reduce microbial impairment of freshwater sources.

Mapping of Escherichia coli Sources Connected to Waterways in the Ruamahanga Catchment, New Zealand.

Rivers and streams in New Zealand are natural with free access and used by many people for swimming and fishing. However, pastoral farming with free grazing animals is a common land use in New Zealand and faecal microorganisms from them often end up in waterways. These microorganisms can seriously affect human and animal health if ingested. This paper describes spatial modeling using GIS of Escherichia coli sources in a large catchment (350 000 ha), the Ruamahanga. By examining the pathway of water over and through soils, it is possible to determine whether E. coli sources are connected to waterways or not. The map of E. coli sources connected to waterways provides useful context to those setting water quality limits. This approach avoids the complexity of modeling the fate and transport of E. coli in waterways, yet still permits the assessment of catchment-wide mitigation and best management practice. Fencing of waterways would minimize E. coli sources directly defecated to water and would reduce total E. coli sources by approximately 35%. Introduction of dung beetles would minimize sources connected to waterways by overland flow and would reduce total E. coli sources by approximately 35%. Construction of dairy effluent ponds would minimize sources connected to waterways through high bypass flow in soils and would reduce total E. coli sources by approximately 25%.

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments.

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

Differences in the fecal concentrations and genetic diversities of Campylobacter jejuni populations among individual cows in two dairy herds.

Dairy cows have been identified as common carriers of Campylobacter jejuni, which causes many of the human gastroenteritis cases reported worldwide. To design on-farm management practices that control the human infection sourced from dairy cows, the first step is to acquire an understanding of the excretion patterns of the cow reservoir. We monitored the same 35 cows from two dairy farms for C. jejuni excretion fortnightly for up to 12 months. The objective was to examine the concentration of C. jejuni and assess the genetic relationship of the C. jejuni populations excreted by individual cows. Significant differences (P < 0.01) in C. jejuni fecal concentration were observed among the 35 cows, with median concentrations that varied by up to 3.6 log(10) · g(-1) feces. A total of 36 different genotypes were identified from the 514 positive samples by using enterobacterial repetitive intergenic consensus (ERIC)-PCR. Although 22 of these genotypes were excreted by more than one cow, the analysis of frequencies and distribution of the genotypes by model-based statistics revealed a high degree of individuality in the C. jejuni population in each cow. The observed variation in the frequency of excretion of a genotype among cows and the analysis by multilocus sequence typing (MLST) of these genotypes suggest that excretion of C. jejuni in high numbers is due to a successful adaptation of a particular genotype to a particular cow's gut environment, but that animal-related factors render some individual cows resistant to colonization by particular genotypes. The reasons for differences in C. jejuni colonization of animals warrant further investigation.

A model framework to assess the effect of dairy farms and wild fowl on microbial water quality during base-flow conditions.

There is concern regarding microbial water quality in many pastoral catchments in New Zealand which are home to numerous livestock and wild animals. Information on microbial impacts on water quality from these animals is scarce. A framework is needed to summarise our current knowledge and identify gaps at the scale of an individual farm. We applied a Monte Carlo modelling approach to a hypothetical dairy farm based on the extensive data sets available for the Toenepi Catchment, Waikato, New Zealand. The model focused on quantifiable direct inputs to the stream from ducks, cows and farm dairy effluent (FDE) during base-flow conditions. Most of the inputs of Escherichia coli from dairy farms occur sporadically and, therefore, have little effect on the expected median stream concentrations. These sporadic inputs do however, have a strong influence on extrema such as 95th percentile values. Current farm mitigations of fencing streams and using improved management practices for applying FDE to land, such as low application rate deferred FDE irrigation systems, would appreciably reduce faecal microbial inputs to the stream. However, the concentrations of E. coli in rural streams may not reduce as much as expected as wild fowl living in streams would have a larger effect on water quality than a farm in which environmental mitigations are widely implemented.

Lyophilization prior to direct DNA extraction from bovine feces improves the quantification of Escherichia coli O157:H7 and Campylobacter jejuni.

Lyophilization was used to concentrate bovine feces prior to DNA extraction and analysis using real-time PCR. Lyophilization significantly improved the sensitivity of detection compared to that in fresh feces and was associated with reliable quantification of both Escherichia coli O157:H7 and Campylobacter jejuni bacteria present in feces at concentrations ranging between 2 log(10) and 6 log(10) CFU g(-)(1).