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This research will set a precedent for improving the credibility of modelled faecal bacteria population dynamics within the larger context of Environment, Pollution and Human Health. The overall aim of this project is to challenge the use of 1st-order decline for modelling reservoirs of pathogen indicators in terrestrial systems because of the potential for population growth within faecal habitats. It will quantify the error associated with the adoption of 1st-order approximations (and models more generally) of bacterial die-off in dairy faeces under field relevant conditions. Exploring the implications associated with population increases of faecal bacteria is an important but rarely investigated area of environmental microbiology.

Hyp (A) There are discrete intervals of faecal bacteria population dynamics in dairy faeces comprising population growth, decline and re-growth phases and these are driven by particular environmental variables, most notably temperature, UV radiation and episodic rewetting.

Hyp (B) The reliance on 1st-order die-off approximations will significantly underestimate the size of faecal bacteria populations on grassland.

The project delivers major contributions to knowledge by testing Hypotheses A and B and addressing the following objectives:

(O1) to provide the first targeted quantification of the temporal pattern of faecal indicator organism (FIO) population increase within dairy faeces post defecation, unaccounted for by 1st-order die-off equations, and determine whether the occurrence of faecal bacteria population growth exhibits a seasonal trend.

(O2) to derive much needed seasonal population change profiles (previously termed die-off coefficients) associated with contrasting environmental drivers such as episodic rehydration and temperature.

(O3) to provide a cross-comparison of culture- versus molecular (qPCR)-based enumeration of E. coli and provide a mechanism of 'future-proofing' any resulting data and model.

(O4) to quantify the underestimation of FIO burden on land resulting from the use of 1st-order models that fail to account for the FIO population increase phases within dairy faeces and thus provide a critical advance in the parameterisation of existing pathogen-risk models.

The four project objectives are delivered using an approach that combines environmental microbiology, applied environmental mathematics and laboratory and field experimentation to address this complex and unresolved problem. A rule-based approach is used for microbial budgeting to quantify the potential under- or over- estimation of microbial burden to land inherent to those models which ignore the observed bacterial population growth phase in the 20 or so days post-defecation, and instead assume 1st-order approximations of faecal bacterial die-off in livestock faeces.

The core deliverables from the project are:

(i) A model structure that explicitly describes cell 'growth' relative to variable environmental drivers and which shifts the paradigm and associated terminology of environmental 'die-off coefficients' into the 21st century;

(ii) The first targeted quantification of the temporal pattern of FIO population increase within dairy faeces (using both culture and molecular methods), in addition to deriving much needed 'die-off' coefficients associated with contrasting seasons to parameterise pathogen-risk models better.

The study will establish a defined, replicable and generic approach which is transferable to other geographical locations and faecal matrices and is exemplified here using dairy faeces. The results can be used to significantly enhance model output by accounting for faecal bacteria growth in terrestrial stores. The growth of faecal bacteria outside of the animal gut is an important yet ignored phase in catchment microbial dynamics.