Description
Key points
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Successful adoption of decision support tools (DS tools) to address grassland management issues requires careful attention in design to ensure ease-of-use, accuracy in prediction and the flexibility to simulate actual practices.
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DS tools must handle spatial variability and where possible include facilities for automatic sourcing of essential information for initialisation.
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Advances in the development of DS tools will depend on resolution of scientific issues in grassland biology including investment in dedicated experiments to determine parameter values for model equations.
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The use of mechanistic models, the integration of remote sensing technology and cooperation between research groups to develop modular simulation frameworks to share models will enhance the value of DS tools in grassland management.
Citation
Donnelly, J. R.; Salmon, L.; Cohen, R. D. H.; Liu, ZL.; and Xin, XP., "Decision Support for Temperate Grasslands: Challenges and Pitfalls" (2023). IGC Proceedings (1993-2023). 7.
https://uknowledge.uky.edu/igc/20/satellitesymposium4/7
Included in
Agricultural Science Commons, Agronomy and Crop Sciences Commons, Plant Biology Commons, Plant Pathology Commons, Soil Science Commons, Weed Science Commons
Decision Support for Temperate Grasslands: Challenges and Pitfalls
Key points
-
Successful adoption of decision support tools (DS tools) to address grassland management issues requires careful attention in design to ensure ease-of-use, accuracy in prediction and the flexibility to simulate actual practices.
-
DS tools must handle spatial variability and where possible include facilities for automatic sourcing of essential information for initialisation.
-
Advances in the development of DS tools will depend on resolution of scientific issues in grassland biology including investment in dedicated experiments to determine parameter values for model equations.
-
The use of mechanistic models, the integration of remote sensing technology and cooperation between research groups to develop modular simulation frameworks to share models will enhance the value of DS tools in grassland management.