Browsing by Author "Jones, Aled"

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    AgriFoodPy: a package for modelling food systems
    (The Open Journal, 2024-05-27) Cordero, Juan P; Donkers, Kevin; Harrison, Ian; Bridle, Sarah L; Frankowska, Angelina; Cain, Michelle; Ward, Neil; Frendenburgh, Jez; Pope, Edward; Kluczkovski, Alana; Schmidt, Ximena; Silva, Jacqueline; Reynolds, Christian; Denby, Katherine; Doherty, Bob; Jones, Aled
    AgriFoodPy is an open-source Python package for processing, simulation, and modeling of agrifood datasets and systems. By employing xarray (Hoyer & Hamman, 2017) as the primary data structure, AgriFoodPy provides methods to manipulate tabular data by extending xarray functionality via accessor classes. It acts as an accessibility and interoperability layer between data sources and external packages, and also bundles with a library of models for use without any additional requirements. A separate repository, agrifoodpy_data, is actively maintained in parallel to provide access to local and global agrifood datasets, including geospatial land use and classification data (Morton, 2022), food supply (FAO, 2023), life cycle assessment (Poore & Nemecek, 2018), and population data (United Nations, 2022). The AgriFoodPy framework is region-agnostic and provides facilities to model and simulate processes and intervention impacts regardless of their geographic origin.
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    Scoping potential routes to UK civil unrest via the food system: results of a structured expert elicitation
    (MDPI, 2023-10-12) Jones, Aled; Bridle, Sarah; Katherine, Denby; Burgess, Paul
    We report the results of a structured expert elicitation to identify the most likely types of potential food system disruption scenarios for the UK, focusing on routes to civil unrest. We take a backcasting approach by defining as an end-point a societal event in which 1 in 2000 people have been injured in the UK, which 40% of experts rated as “Possible (20–50%)”, “More likely than not (50–80%)” or “Very likely (>80%)” over the coming decade. Over a timeframe of 50 years, this increased to 80% of experts. The experts considered two food system scenarios and ranked their plausibility of contributing to the given societal scenario. For a timescale of 10 years, the majority identified a food distribution problem as the most likely. Over a timescale of 50 years, the experts were more evenly split between the two scenarios, but over half thought the most likely route to civil unrest would be a lack of total food in the UK. However, the experts stressed that the various causes of food system disruption are interconnected and can create cascading risks, highlighting the importance of a systems approach. We encourage food system stakeholders to use these results in their risk planning and recommend future work to support prevention, preparedness, response and recovery planning.