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      Leading a stakeholderdriven approach to manage microbial pollution risk

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          Abstract

          Agricultural practices contribute a significant amount of faecal material onto pasture via direct defecation by grazing livestock and through applications of solid and liquid manures. Managing the spatial and temporal input of this faecal loading to pasture is important in order to minimise the proportion of faecal microorganisms, e.g. E. coli, that may be washed from faecal sources and transferred in runoff to nearby watercourses following rainfall. Contaminated runoff can lead to microbial pollution of our streams, rivers and seas. Scientists, environmental regulators, catchment managers and policy-makers are therefore keen to understand how E. coli survives and moves in the environment with a view that better knowledge and data on the behavioural characteristics of these microorganisms will improve our ability to model and predict their interactions with, and responses to, the world around us. Previous NERC-funded research (NE/J004456/1) developed one such model to improve our understanding of the magnitude and spatial distribution of microbial risks in the landscape. The resulting model predicts levels of microbial risk on agricultural land, based on livestock numbers, farming practices and E. coli survival patterns under environmental conditions (e.g. rainfall and temperature fluctuations). While the model is structurally simple its operation & functionality was not originally designed to maximise uptake by those who would benefit most from its use. In response, the original ViPER project used a participatory approach to bring together a range of stakeholders (regulators, catchment managers, scientists and farm networks) to promote engagement, deliberation and joint decision-making. Through a structured process of knowledge exchange the project team developed a freely-available prototype decision support tool (DST) called ViPER. The ViPER DST provides a user-friendly interface and allows end-users without specific modelling skills or knowledge of a modelling system to take advantage of existing NERC science and modelling capability to understand how, when and where E. coli risks accumulate on agricultural land. However, in its current form, ViPER is unable to evaluate what proportion of that E. coli source on agricultural land will actually end up in rivers and streams following rainfall. In response, the aim of ViPER II is to now transition our prototype DST, which maps E. coli risks at the field, farm and catchment scale, into a user-ready toolkit for providing on-farm advice and guidance in the real world. To do this we will combine the ViPER DST with another freely-available NERC-funded hydrological risk-mapping tool called SCIMAP (NE/C508850/1). SCIMAP was designed to identify the origins of sediment and nutrient pollutants in the landscape and importantly, it maps how runoff can transfer sediment and nutrients across the soil surface and into watercourses. However, SCIMAP currently does not map microbial risks in the landscape because, unlike sediment and nutrients, bacteria such as E. coli accommodate a complex life-cycle and will die-off over time. By contrast, ViPER is able to account for the die-off of E. coli but lacks the capacity to predict E. coli transfer with runoff. An opportunity now exists to integrate two NERC-funded outputs (ViPER & SCIMAP) to deliver an innovative DST for mapping microbial pollution risks in catchment systems and to produce a DST that is greater than the sum of its individual parts. The resulting toolkit will provide added value both to land based assessment of microbial risks, and to the applied interests of environmental regulators and the water industry in the UK (& further afield). This represents the next critical step in ensuring that NERC funded models and data deliver real-world impact through innovative conversion of the underpinning evidence-base into a format that is widely accessible by relevant end-users.

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          Author and article information

          Journal
          Impact
          impact
          Science Impact, Ltd.
          2398-7073
          August 21 2018
          August 21 2018
          : 2018
          : 6
          : 30-32
          Article
          10.21820/23987073.2018.6.30
          © 2018

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Earth & Environmental sciences, Medicine, Computer science, Agriculture, Engineering

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