Richard Muirhead

Prioritisation of farm scale remediation efforts for reducing losses of nutrients and faecal indicator organisms to waterways: a case study of New Zealand dairy farming.

The international competitiveness of the New Zealand (NZ) dairy industry is built on low cost clover-based systems and a favourable temperate climate that enables cows to graze pastures mostly all year round. Whilst this grazed pasture farming system is very efficient at producing milk, it has also been identified as a significant source of nutrients (N and P) and faecal bacteria which have contributed to water quality degradation in some rivers and lakes. In response to these concerns, a tool-box of mitigation measures that farmers can apply on farm to reduce environmental emissions has been developed. Here we report the potential reduction in nutrient losses and costs to farm businesses arising from the implementation of individual best management practices (BMPs) within this tool-box. Modelling analysis was carried out for a range of BMPs targeting pollutant source reduction on case-study dairy farms, located in four contrasting catchments. Due to the contrasting physical resources and management systems present in the four dairy catchments evaluated, the effectiveness and costs of BMPs varied. Farm managements that optimised soil Olsen P levels or used nitrification inhibitors were observed to result in win-win outcomes whereby nutrient losses were consistently reduced and farm profitability was increased in three of the four case study farming systems. Other BMPs generally reduced nutrient and faecal bacteria losses but at a small cost to the farm business. Our analysis indicates that there are a range of technological measures that can deliver substantial reductions in nutrient losses to waterways from dairy farms, whilst not increasing or even reducing other environmental impacts (e.g. greenhouse gas emissions and energy use). Their implementation will first require clearly defined environmental goals for the catchment/water body that is to be protected. Secondly, given that the major sources of water pollutants often differed between catchments, it is important that BMPs are matched to the physical resources and management systems of the existing farm businesses.

Nutrient, Sediment, and Bacterial Losses in Overland Flow from Pasture and Cropping Soils Following Cattle Dung Deposition

Abstract The loss of phosphorus (P), suspended sediment (SS), ammonia (NH4 +‐N), nitrate (NO3 −‐N), and Escherichia coli in overland flow (OF) from dairy cattle dung can impair surface water quality. However, the risk of P and N loss from grazed pastures varies with time. Current practice in southern New Zealand is to select a field, cultivate, sow in Brassica spp., and graze in winter to save remaining pasture from damage. This deposits dung when soil is wet and OF likely. Hence, we determined P, NH4 +‐N, NO3 −‐N, and E. coli loss from dung in OF via simulated rainfall from intact grazed pasture and cropland treatments of a soil. Analysis of OF, 0, 1, 4, 11, 24, and 43 days after dung deposition at the upslope end of soil boxes indicated that total P (TP), NH4 +‐N, and SS concentrations decreased sharply from day zero and leveled out after 11 days. More particulate P and SS were lost from the cultivated than pasture treatment, whereas the reverse occurred for dissolved organic P because of greater sorption of phytase active materials. Escherichia coli losses were high (1×105 100 mL−1) in both treatments throughout. Using the equations of fit in an example field site indicated that management of dung deposition could affect up to 25–33% of TP lost in OF.

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.

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.

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.

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

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.

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.

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.

Transcriptome Changes of Escherichia coli, Enterococcus faecalis, and Escherichia coli O157:H7 Laboratory Strains in Response to Photo-Degraded DOM

In this study, we investigated gene expression changes in three bacterial strains (Escherichia coli C3000, Escherichia coli O157:H7 B6914, and Enterococcus faecalis ATCC 29212), commonly used as indicators of water quality and as control strains in clinical, food, and water microbiology laboratories. Bacterial transcriptome responses from pure cultures were monitored in microcosms containing water amended with manure-derived dissolved organic matter (DOM), previously exposed to simulated sunlight for 12 h. We used RNA sequencing (RNA-seq) and quantitative real-time reverse transcriptase (qRT-PCR) to compare differentially expressed temporal transcripts between bacteria incubated in microcosms containing sunlight irradiated and non-irradiated DOM, for up to 24 h. In addition, we used whole genome sequencing simultaneously with RNA-seq to identify single nucleotide variants (SNV) acquired in bacterial populations during incubation. These results indicate that E. coli and E. faecalis have different mechanisms for removal of reactive oxygen species (ROS) produced from irradiated DOM. They are also able to produce micromolar concentrations of H2O2 from non-irradiated DOM, that should be detrimental to other bacteria present in the environment. Notably, this study provides an assessment of the role of two conjugative plasmids carried by the E. faecalis and highlights the differences in the overall survival dynamics of environmentally-relevant bacteria in the presence of naturally-produced ROS.