Browsing by Author "Takahashi, Taro"
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Item Open Access Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?(IOP Publishing, 2023-07-18) McAuliffe, Graham A.; Lynch, John; Cain, Michelle; Buckingham, Sarah; Rees, Robert M.; Collins, Adrian L.; Allen, Myles; Pierrehumbert, Raymond; Lee, Michael R. F.; Takahashi, TaroThe vast majority of agri-food climate-based sustainability analyses use GWP100 as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCA), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions. This paper reports a sensitivity analysis using a pasture-based beef production system (a producer of high CH4 emissions) as an exemplar to compare various climate impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation (UKRI) National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different GHG emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.Item Open Access Data underpinning: 'NERC Research Translation: Grassland Management' project(Cranfield University, 2022-09-08 13:38) Giannitsopoulos, Michail; Burgess, Paul; Richter, Goetz; Bell, Matthew; F. E. Topp, Cairistiona; Ingram, Julie; Takahashi, TaroLINGRA-N-Plus along with its Teaching Guide, as developed in the NERC Research Translation: Grassland Management Project, supported by the Sustainable Agriculture Research and Innovation Club (SARIC).Item Open Access Modelling the interactions of soils, climate, and management for grass production in England and Wales(MDPI, 2021-04-02) Giannitsopoulos, Michail L.; Burgess, Paul J.; Richter, Goetz M.; Bell, Matt J.; Topp, Cairistiona F. E.; Ingram, Julie; Takahashi, TaroThis study examines the effectiveness of a model called LINGRA-N-Plus to simulate the interaction of climate, soil and management on the green leaf and total dry matter yields of ryegrass in England and Wales. The LINGRA-N-Plus model includes modifications of the LINGRA-N model such as temperature- and moisture-dependent soil nitrogen mineralization and differential partitioning to leaves and stems with thermal time from the last harvest. The resulting model was calibrated against the green leaf and total grass yields from a harvest interval x nitrogen application experiment described by Wilman et al. (1976). When the LINGRA-N-Plus model was validated against total grass yields from nitrogen experiments at ten sites described by Morrison et al. (1980), its modelling efficiency improved greatly compared to the original LINGRA-N. High predicted yields, at zero nitrogen application, were related to soils with a high initial nitrogen content. The lowest predicted yields occurred at sites with low rainfall and shallow rooting depth; mitigating the effect of drought at such sites increased yields by up to 4 t ha−1. The results highlight the usefulness of grass models, such as LINGRA-N-Plus, to explore the combined effects of climate, soil, and management, like nitrogen application, and harvest intervals on grass productivity.Item Open Access Translating and applying a simulation model to enhance understanding of grassland management(Wiley, 2022-09-27) Giannitsopoulos, Michail L.; Burgess, Paul J.; Bell, Matthew J.; Richter, Goetz M.; Topp, Cairistiona F. E.; Ingram, Julie; Takahashi, TaroEach new generation of grassland managers could benefit from an improved understanding of how modification of nitrogen application and harvest dates in response to different weather and soil conditions will affect grass yields and quality. The purpose of this study was to develop a freely available grass yield simulation model, validated for England and Wales, and to examine its strengths and weaknesses as a teaching tool for improving grass management. The model, called LINGRA-N-Plus, was implemented in a Microsoft Excel spreadsheet and iteratively evaluated by students and practitioners (farmers, consultants, and researchers) in a series of workshops across the UK over 2 years. The iterative feedback led to the addition of new algorithms, an improved user interface, and the development of a teaching guide. The students and practitioners identified the ease of use and the capacity to understand, visualize and evaluate how decisions, such as variation of cutting intervals, affect grass yields as strengths of the model. We propose that an effective teaching tool must achieve an appropriate balance between being sufficiently detailed to demonstrate the major relationships (e.g., the effect of nitrogen on grass yields) whilst not becoming so complex that the relationships become incomprehensible. We observed that improving the user-interface allowed us to extend the scope of the model without reducing the level of comprehension. The students appeared to be interested in the explanatory nature of the model whilst the practitioners were more interested in the application of a validated model to enhance their decision making.