Translating and applying a simulation model to enhance understanding of grassland management

A - Papers appearing in refereed journals

Giannitsopoulos, M. L., Burgess, P. J., Bell, M. J., Richter, G. M., Topp, C. F. E., Ingram, J. and Takahashi, T. 2022. Translating and applying a simulation model to enhance understanding of grassland management. Grass and Forage Science. https://doi.org/10.1111/gfs.12584

AuthorsGiannitsopoulos, M. L., Burgess, P. J., Bell, M. J., Richter, G. M., Topp, C. F. E., Ingram, J. and Takahashi, T.
Abstract

Each 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.

KeywordsAgronomy; Decision support; Education; Grassland management; LINGRA
Year of Publication2022
JournalGrass and Forage Science
Digital Object Identifier (DOI)https://doi.org/10.1111/gfs.12584
Open accessPublished as ‘gold’ (paid) open access
FunderNatural Environment Research Council
Biotechnology and Biological Sciences Research Council
Funder project or codeSARIC Translation: Grassland Management
S2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales
Publisher's version
Copyright license
CC BY 4.0
Output statusPublished
Publication dates
Online27 Sep 2022
Publication process dates
Accepted01 Aug 2022
PublisherWiley
ISSN0142-5242

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