Browsing by Author "Jones, R."

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    A comparison of three modelling approaches for quantitative risk assessment using the case study of Salmonella spp. in poultry meat.
    (Elsevier Science B.V., Amsterdam., 2005-01-15T00:00:00Z) Parsons, David J.; Orton, Thomas G.; D'Souza J.; Moore, A.; Jones, R.; Dodd, Christine E. R.
    A comprehensive review of both the scientific literature and industry practices was undertaken to identify and quantify all sources of contamination throughout the entire poultry meat production chain by Salmonella spp. This information was used to develop a quantitative risk assessment (QRA) model for Salmonella in the production chain from the breeder farm to the chilled carcass. This was subsequently used as the basis on which to compare the merits of three approaches to QRA modelling in such systems. The original model used a Bayesian Network (BN). The second method was a Markov chain Monte Carlo (MCMC) approach, a numerical Bayesian technique which retained a similar network structure but allowed further development, such as the separation of variability and uncertainty. The third method was a more detailed simulation model. The BN responds immediately to changes, such as entering evidence, because it does not use simulation and can propagate information from any point in the network to all others by Bayesian inference. However, it requires all the variables to be discrete, which introduces errors if continuous variables have to be discretized. These errors can accumulate. The MCMC approach does not require discrete variables while retaining some of the properties of the BN model, such as the ability to draw inferences from evidence. Finally, the simulation offers greater flexibility, such as consideration of the individual carcass, but may be more complex to implement as a result and sacrifices the ability to propagate evidence.
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    Tracing of particulate organic C sources across the terrestrial-aquatic continuum, a case study at the catchment scale (Carminowe Creek, southwest England)
    (Elsevier, 2017-11-06) Glendell, M.; Jones, R.; Dungait, J. A. J.; Meusburger, K.; Schwendel, A. C.; Barclay, R.; Barker, Sam; Haley, S.; Quine, Timothy; Meersmans, Jeroen
    Soils deliver crucial ecosystem services, such as climate regulation through carbon (C) storage and food security, both of which are threatened by climate and land use change. While soils are important stores of terrestrial C, anthropogenic impact on the lateral fluxes of C from land to water remains poorly quantified and not well represented in Earth system models. In this study, we tested a novel framework for tracing and quantifying lateral C fluxes from the terrestrial to the aquatic environment at a catchment scale. The combined use of conservative plant-derived geochemical biomarkers n-alkanes and bulk stable δ13C and δ15N isotopes of soils and sediments allowed us to distinguish between particulate organic C sources from different land uses (i.e. arable and temporary grassland vs. permanent grassland vs. riparian woodland vs. river bed sediments) (p < 0.001), showing an enhanced ability to distinguish between land use sources as compared to using just n-alkanes alone. The terrestrial-aquatic proxy (TAR) ratio derived from n-alkane signatures indicated an increased input of terrestrial-derived organic matter (OM) to lake sediments over the past 60 years, with an increasing contribution of woody vegetation shown by the C27/C31 ratio. This may be related to agricultural intensification, leading to enhanced soil erosion, but also an increase in riparian woodland that may disconnect OM inputs from arable land uses in the upper parts of the study catchment. Spatial variability of geochemical proxies showed a close coupling between OM provenance and riparian land use, supporting the new conceptualization of river corridors (active river channel and riparian zone) as critical zones linking the terrestrial and aquatic C fluxes. Further testing of this novel tracing technique shows promise in terms of quantification of lateral C fluxes as well as targeting of effective land management measures to reduce soil erosion and promote OM conservation in river catchments.