Using the Q10 model to simulate E. coli survival in cowpats on grazing lands

Mobilization of Escherichia coli and fecal source markers from decomposing cowpats

In rural environments, the sources of fecal contamination in freshwater environments are often diffuse and a mix of fresh and aged fecal sources. It is important for water monitoring purposes, therefore, to understand the impacts of weathering on detection of the fecal source markers available for mobilization from livestock sources. This study targets the impacts of rainfall events on the mobilization of fecal source tracking (FST) markers from simulated cowpats decomposing in situ for five-and-a-half-months. The FST markers analysed were Escherichia coli, microbial source tracking (MST) markers, fecal steroids and a fecal ageing ratio based on the ratio between counts of river microflora and total coliforms. There was a substantial concentration of E. coli (10⁴/100 mL) released from the ageing cowpats suggesting a long-term reservoir of E. coli in the cowpat. Mobilization of fecal markers from rainfall-impacted cowpats, however, was markedly reduced compared with fecal markers in the cowpat. Overall, the Bacteroidales bovine-associated MST markers were less persistent than E. coli in the cowpat and rainfall runoff. The ten fecal steroids, including the major herbivore steroid, 24-ethylcoprostanol, are shown to be stable markers of bovine pollution due to statistically similar degradation rates among all steroids. The mobilizable fraction for each FST marker in the rainfall runoff allowed generation of mobilization decline curves and the derived decline rate constants can be incorporated into source attribution models for agricultural contaminants. Findings from this study of aged bovine pollution sources will enable water managers to improve attribution of elevated E. coli to the appropriate fecal source in rural environments.

Evaluating the Arrhenius equation for developmental processes

The famous Arrhenius equation is well suited to describing the temperature dependence of chemical reactions but has also been used for complicated biological processes. Here, we evaluate how well the simple Arrhenius equation predicts complex multi-step biological processes, using frog and fruit fly embryogenesis as two canonical models. We find that the Arrhenius equation provides a good approximation for the temperature dependence of embryogenesis, even though individual developmental intervals scale differently with temperature. At low and high temperatures, however, we observed significant departures from idealized Arrhenius Law behavior. When we model multi-step reactions of idealized chemical networks, we are unable to generate comparable deviations from linearity. In contrast, we find the two enzymes GAPDH and β-galactosidase show non-linearity in the Arrhenius plot similar to our observations of embryonic development. Thus, we find that complex embryonic development can be well approximated by the simple Arrhenius equation regardless of non-uniform developmental scaling and propose that the observed departure from this law likely results more from non-idealized individual steps rather than from the complexity of the system.

An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment

The new Model for the Agent-based simulation of Faecal Indicator Organisms (MAFIO) is applied to a small (0.42 km²) Scottish agricultural catchment to simulate the dynamics of E. coli arising from sheep and cattle farming, in order to provide a proof-of-concept. The hydrological environment for MAFIO was simulated by the "best" ensemble run of the tracer-aided ecohydrological model EcH₂O-iso, obtained through multi-criteria calibration to stream discharge (MAE: 1.37 L s^-1) and spatially-distributed stable isotope data (MAE: 1.14-3.02‰) for the period April-December 2017. MAFIO was then applied for the period June-August for which twice-weekly E. coli loads were quantified at up to three sites along the stream. Performance in simulating these data suggested the model has skill in capturing the transfer of faecal indicator organisms (FIOs) from livestock to streams via the processes of direct deposition, transport in overland flow and seepage from areas of degraded soil. Furthermore, its agent-based structure allowed source areas, transfer mechanisms and host animals contributing FIOs to the stream to be quantified. Such information is likely to have substantial value in the context of designing and spatially-targeting mitigation measures against impaired microbial water quality. This study also revealed, however, that avenues exist for improving process conceptualisation in MAFIO (e.g. to include FIO contributions from wildlife) and highlighted the need to quantitatively assess how uncertainty in the spatial extent of surface flow paths in the simulated hydrological environment may affect FIO simulations. Despite the consequent status of MAFIO as a research-level model, its encouraging performance in this proof-of-concept study suggests the model has significant potential for eventual incorporation into decision support frameworks.

Fate and transport of antibiotics and antibiotic resistance genes in runoff and soil as affected by the timing of swine manure slurry application

Land application of swine manure slurry is a common practice to supplement nutrients to soil for crop production. This practice can introduce antibiotic residues and antibiotic resistance genes (ARGs) into the environment. Field testing is critical in identifying manure management practices effective in minimizing the environmental impacts of manure-borne antibiotic and ARGs. The objective of this study was to determine how the timing of swine manure application relative to rainfall events impacts the fate and transport of antibiotics and ARGs in surface runoff and manure-amended soil. Swine manure slurry was either broadcast or injected on test plots in the field. A set of three 30-min simulated rainfall events, 24 h apart, were initiated on manured plots 1 day, 1 week, 2 weeks, or 3 weeks after the manure application. Results showed that an interval longer than 2 weeks between application and rainfall often significantly reduced the levels of antibiotics and ARGs tested in runoff with the exception of tet(X). For soil samples from broadcast plots, concentrations of two of the three antibiotics tested (lincomycin and tiamulin) decreased substantially in the first two weeks after manure application. In contrast, concentrations of most of the ARGs tested (tet(Q), tet(X), and erm(A)) in soil did not change significantly during the test period. Information obtained from the study can be beneficial in designing manure management practices and estimating the environmental loading of antibiotics and ARGs resulting from manure application.

High resolution characterisation of E. coli proliferation profiles in livestock faeces

Agricultural intensification can lead to high volumes of livestock faeces being applied to land, either as solid or liquid manures or via direct defecation, and can result in reservoirs of faecal indicator organisms (FIOs) persisting within farmland. Understanding the survival of FIOs, e.g. E. coli, in agricultural environments, and in particular within different livestock faeces, is key to developing catchment management practices for the protection of ecosystem services provided by clean water. Frequently, controlled laboratory studies, under constant temperature regimes, are used to determine the impact of environmental factors on E. coli persistence in livestock faeces; however, such studies oversimplify the diurnal variations and interactions of real world conditions. The aim of this study was to investigate the survival of E. coli using a controlled environment facility, which simulated diurnal variation of temperatures typically experienced during a British spring and summer. The approach provided a comparison of E. coli persistence profiles within faeces of sheep, beef cattle and dairy cattle to allow novel interpretations of E. coli regrowth patterns in contrasting livestock faeces in the period immediately post-defecation. Thus, the coupling of a tightly controlled environment facility with high resolution monitoring enabled the development of a new non-linear, asymptotic description of E. coli proliferation in livestock faeces, with increased potential for E. coli growth observed during warmer temperatures for all livestock types. While this study focused on temperatures typical of the UK, the occurrence of a phase of E. coli regrowth has implications for microbial water quality management worldwide.

Investigating behavioral drivers of seasonal Shiga-Toxigenic Escherichia Coli (STEC) patterns in grazing cattle using an agent-based model

The causes of seasonal variability in pathogen transmission are not well understood, and have not been comprehensively investigated. In an example for enteric pathogens, incidence of Escherichia coli O157 (STEC) colonization in cattle is consistently higher during warmer months compared to cooler months in various cattle production systems. However, actual mechanisms for this seasonality remain elusive. In addition, the influence of host (cattle) behavior on this pattern has not been thoroughly considered. To that end, we constructed a spatially explicit agent-based model that accounted for the effect of temperature fluctuations on cattle behavior (direct contact among cattle and indirect between cattle and environment), as well as its effect on pathogen survival in the environment. We then simulated the model in a factorial approach to evaluate the hypothesis that temperature fluctuations can lead to seasonal STEC transmission dynamics by influencing cattle aggregation, grazing, and drinking behaviors. Simulation results showed that higher temperatures increased the frequency at which cattle aggregated under shade in pasture, resulting in increased direct contact and transmission of STEC between individual cattle, and hence higher incidence over model simulations in the warm season. In contrast, increased drinking behavior during warm season was not an important transmission pathway. Although sensitivity analyses suggested that the relative importance of direct vs. indirect (environmental) pathways depend to upon model parameterization, model simulations indicated that factors influencing cattle aggregation, such as temperature, were likely strong drivers of transmission dynamics of enteric pathogens.

Development and evaluation of the bacterial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

The Agricultural Policy/Environmental eXtender (APEX) is a watershed-scale water quality model that includes detailed representation of agricultural management. The objective of this work was to develop a process-based model for simulating the fate and transport of manure-borne bacteria on land and in streams with the APEX model. The bacteria model utilizes manure erosion rates to estimate the amount of edge-of-field bacteria export. Bacteria survival in manure is simulated as a two-stage process separately for each manure application event. In-stream microbial fate and transport processes include bacteria release from streambeds due to sediment resuspension during high flow events, active release from the streambed sediment during low flow periods, bacteria settling with sediment, and survival. Default parameter values were selected from published databases and evaluated based on field observations. The APEX model with the newly developed microbial fate and transport module was applied to simulate fate and transport of the fecal indicator bacterium Escherichia coli in the Toenepi watershed, New Zealand that was monitored for seven years. The stream network of the watershed ran through grazing lands with daily bovine waste deposition. Results show that the APEX with the bacteria module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water as affected by various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.

Capturing Microbial Sources Distributed in a Mixed-use Watershed within an Integrated Environmental Modeling Workflow

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application - accessing, retrieving, and using real-world data - demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watershed's pour point.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r_s=0.88; p<0.01) than the Wyre (r_s=-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool.

Seasonal persistence of faecal indicator organisms in soil following dairy slurry application to land by surface broadcasting and shallow injection

Dairy farming generates large volumes of liquid manure (slurry), which is ultimately recycled to agricultural land as a valuable source of plant nutrients. Different methods of slurry application to land exist; some spread the slurry to the sward surface whereas others deliver the slurry under the sward and into the soil, thus helping to reduce greenhouse gas (GHG) emissions from agriculture. The aim of this study was to investigate the impact of two slurry application methods (surface broadcast versus shallow injection) on the survival of faecal indicator organisms (FIOs) delivered via dairy slurry to replicated grassland plots across contrasting seasons. A significant increase in FIO persistence (measured by the half-life of E. coli and intestinal enterococci) was observed when slurry was applied to grassland via shallow injection, and FIO decay rates were significantly higher for FIOs applied to grassland in spring relative to summer and autumn. Significant differences in the behaviour of E. coli and intestinal enterococci over time were also observed, with E. coli half-lives influenced more strongly by season of application relative to the intestinal enterococci population. While shallow injection of slurry can reduce agricultural GHG emissions to air it can also prolong the persistence of FIOs in soil, potentially increasing the risk of their subsequent transfer to water. Awareness of (and evidence for) the potential for 'pollution-swapping' is critical in order to guard against unintended environmental impacts of agricultural management decisions.

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

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.

Quantitative PCR Profiling of Escherichia coli in Livestock Feces Reveals Increased Population Resilience Relative to Culturable Counts under Temperature Extremes

The relationship between culturable counts (CFU) and quantitative PCR (qPCR) cell equivalent counts of Escherichia coli in dairy feces exposed to different environmental conditions and temperature extremes was investigated. Fecal samples were collected in summer and winter from dairy cowpats held under two treatments: field-exposed versus polytunnel-protected. A significant correlation in quantified E. coli was recorded between the qPCR and culture-based methods (r = 0.82). Evaluation of the persistence profiles of E. coli over time revealed no significant difference in the E. coli numbers determined as either CFU or gene copies during the summer for the field-exposed cowpats, whereas significantly higher counts were observed by qPCR for the polytunnel-protected cowpats, which were exposed to higher ambient temperatures. In winter, the qPCR returned significantly higher counts of E. coli for the field-exposed cowpats, thus representing a reversal of the findings from the summer sampling campaign. Results from this study suggest that with increasing time post-defecation and with the onset of challenging environmental conditions, such as extremes in temperature, culture-based counts begin to underestimate the true resilience of viable E. coli populations in livestock feces. This is important not only in the long term as the Earth changes in response to climate-change drivers but also in the short term during spells of extremely cold or hot weather.

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.

Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) was conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying release of Escherichia coli, enterococci, and fecal coliforms from manures applied at typical agronomic rates evaluated the efficacy of the Bradford-Schijven model modified by adding terms for release efficiency and transportation loss. Two complementary, parallel approaches were used to calibrate the model and estimate microbial release parameters. The first was a four-step sequential procedure using the inverse model PEST, which provides appropriate initial parameter values. The second utilized a PEST/bootstrap procedure to estimate average parameters across plots, manure age, and microbe, and to provide parameter distributions. The experiment determined that manure age, microbe, and season had no clear relationship to the release curve. Cattle solid pats released microbes at a different, slower rate than did poultry dry litter or swine slurry, which had very similar release patterns. These findings were consistent with other published results for both bench- and field-scale, suggesting the modified Bradford-Schijven model can be applied to microbial release from manure.

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.

Release and Removal of Microorganisms from Land-Deposited Animal Waste and Animal Manures: A Review of Data and Models

Microbial pathogens present a leading cause of impairment to rivers, bays, and estuaries in the United States, and agriculture is often viewed as the major contributor to such contamination. Microbial indicators and pathogens are released from land-applied animal manure during precipitation and irrigation events and are carried in overland and subsurface flow that can reach and contaminate surface waters and ground water used for human recreation and food production. Simulating the release and removal of manure-borne pathogens and indicator microorganisms is an essential component of microbial fate and transport modeling regarding food safety and water quality. Although microbial release controls the quantities of available pathogens and indicators that move toward human exposure, a literature review on this topic is lacking. This critical review on microbial release and subsequent removal from manure and animal waste application areas includes sections on microbial release processes and release-affecting factors, such as differences in the release of microbial species or groups; bacterial attachment in turbid suspensions; animal source; animal waste composition; waste aging; manure application method; manure treatment effect; rainfall intensity, duration, and energy; rainfall recurrence; dissolved salts and temperature; vegetation and soil; and spatial and temporal scale. Differences in microbial release from liquid and solid manures are illustrated, and the influential processes are discussed. Models used for simulating release and removal and current knowledge gaps are presented, and avenues for future research are suggested.

Escherichia coli survival in, and release from, white-tailed deer feces

White-tailed deer are an important reservoir for pathogens that can contribute a large portion of microbial pollution in fragmented agricultural and forest landscapes. The scarcity of experimental data on survival of microorganisms in and release from deer feces makes prediction of their fate and transport less reliable and development of efficient strategies for environment protection more difficult. The goal of this study was to estimate parameters for modeling Escherichia coli survival in and release from deer (Odocoileus virginianus) feces. Our objectives were as follows: (i) to measure survival of E. coli in deer pellets at different temperatures, (ii) to measure kinetics of E. coli release from deer pellets at different rainfall intensities, and (iii) to estimate parameters of models describing survival and release of microorganisms from deer feces. Laboratory experiments were conducted to study E. coli survival in deer pellets at three temperatures and to estimate parameters of Chick's exponential model with temperature correction based on the Arrhenius equation. Kinetics of E. coli release from deer pellets were measured at two rainfall intensities and used to derive the parameters of Bradford-Schijven model of bacterial release. The results showed that parameters of the survival and release models obtained for E. coli in this study substantially differed from those obtained by using other source materials, e.g., feces of domestic animals and manures. This emphasizes the necessity of comprehensive studies of survival of naturally occurring populations of microorganisms in and release from wildlife animal feces in order to achieve better predictions of microbial fate and transport in fragmented agricultural and forest landscapes.

Comparing temperature effects on Escherichia coli, Salmonella, and Enterococcus survival in surface waters

The objective of this study was to compare dependency of survival rates on temperature for indicator organisms Escherichia coli and Enterococcus and the pathogen Salmonella in surface waters. A database of 86 survival datasets from peer-reviewed papers on inactivation of E. coli, Salmonella and Enterococcus in marine waters and of E. coli and Salmonella in lake waters was assembled. The Q10 model was used to express temperature effect on survival rates obtained from linear sections of semi-logarithmic survival graphs. Available data were insufficient to establish differences in survival rates and temperature dependencies for marine waters where values of Q10  = 3 and a survival rate of 0·7 day(-1) could be applied. The Q10 values in lake waters were substantially lower in marine waters, and Salmonella inactivation in lake water was, on average, twice as fast as E. coli; data on E. coli substantially outnumber data on Enterococcus and Salmonella. The relative increase in inactivation with increase in temperature is higher in marine waters than lake water, and differences in inactivation between Salmonella and E. coli at a given temperature were significant in lake water but not in marine waters.

SIGNIFICANCE AND IMPACT OF THE STUDY

Microbiological quality of surface waters is of paramount importance for public health. The novelty of this work is using a large compendium of published data to develop the first comparison of temperature effects on survival of the pathogen Salmonella and water quality indicator micro-organisms Escherichia coli and Enterococcus in natural waters. The existing relatively large body of knowledge on E. coli survival appears to be useful to assess the effect of temperature on survival of Salmonella. Moreover, results of this work constitute an essential input in models to support environmental management decisions on the use of surface water sources in agriculture, aquaculture and recreation.

Rainfall-induced fecal indicator organisms transport from manured fields: model sensitivity analysis

Microbial quality of surface waters attracts attention due to food- and waterborne disease outbreaks. Fecal indicator organisms (FIOs) are commonly used for the microbial pollution level evaluation. Models predicting the fate and transport of FIOs are required to design and evaluate best management practices that reduce the microbial pollution in ecosystems and water sources and thus help to predict the risk of food and waterborne diseases. In this study we performed a sensitivity analysis for the KINEROS/STWIR model developed to predict the FIOs transport out of manured fields to other fields and water bodies in order to identify input variables that control the transport uncertainty. The distributions of model input parameters were set to encompass values found from three-year experiments at the USDA-ARS OPE3 experimental site in Beltsville and publicly available information. Sobol' indices and complementary regression trees were used to perform the global sensitivity analysis of the model and to explore the interactions between model input parameters on the proportion of FIO removed from fields. Regression trees provided a useful visualization of the differences in sensitivity of the model output in different parts of the input variable domain. Environmental controls such as soil saturation, rainfall duration and rainfall intensity had the largest influence in the model behavior, whereas soil and manure properties ranked lower. The field length had only moderate effect on the model output sensitivity to the model inputs. Among the manure-related properties the parameter determining the shape of the FIO release kinetic curve had the largest influence on the removal of FIOs from the fields. That underscored the need to better characterize the FIO release kinetics. Since the most sensitive model inputs are available in soil and weather databases or can be obtained using soil water models, results indicate the opportunity of obtaining large-scale estimates of FIO transport from fields based on publicly available rather than site-specific information.