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Abstract

Estimating spatially resolved grassland productivity is essential for benchmarking the total UK productive potential to assess food, feed and fuel trade-offs in the context of whole systems analyses. Our objectives were to adapt and evaluate a well-known process-based model (PBM) and estimate productivity of improved (permanent, temporary) and semi-natural grassland systems using meta-models (MM) trained by extensive PBM scenario simulations. Observed dry matter (DM) yields in multi-site nitrogen (N) response (0, 150 and 300 kg N ha−1) experiments were well emulated describing the average productivity of rough grazing, permanent and temporary grassland (3.1, 7.4 and 9.8 t DM ha−1, respectively). Cross-validated with independent and long-term data (Park Grass Experiment), the PBM explained more variation when considering all systems combined (81%) than across all improved grasslands (61%) but little for rough grazing (26%). The PBM-trained MMs explained 48, 72 and 70% of the simulated yield variation in the grasslands of increasing management intensity, and 43 and 75% of observed variation in the combined improved and all three grassland systems, respectively. Considering the assessment of ecosystem services, like drainage and water productivity, PBM scenario simulations are essential. Compared to improved grassland rough grazing will result in 40% more groundwater recharge due to its lower simulated water use and water productivity (12 versus 25 and 43 kg ha−1 mm−1 for permanent and temporary grassland, respectively).
Original languageEnglish
Pages (from-to)148-158
Number of pages11
JournalEuropean Journal of Agronomy
Volume89
Early online date24 May 2017
DOIs
Publication statusPublished - 30 Sept 2017

Keywords

  • improved grassland
  • semi-natural
  • sink-source interaction model
  • up-scaling
  • water balance

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