Modelling the response of yields and tissue C : N to changes in atmospheric CO2 and N management in the main wheat regions of western Europe

• Published in: Biogeosciences 2015-01, Vol.12 (8), p.2489-2515
• Main Authors: Olin, S, Schurgers, G, Lindeskog, M, Wårlind, D, Smith, B, Bodin, P, Holmér, J, Arneth, A
• Format: Article
• Language: English
• Subjects: 20th century; Agricultural ecosystems; Agricultural management; Agricultural production; Agricultural Sciences; Annan lantbruksvetenskap; Atmospheric models; Biogeochemical cycle; Biogeochemical cycles; Biogeochemistry; Carbon; Carbon cycle; Carbon dioxide; Carbon dioxide atmospheric concentrations; Climate and land use; Climate change; Climate Research; Computer simulation; Crop production; Crop yield; Crops; Earth and Related Environmental Sciences; Ecosystem management; Ecosystems; Environment models; Environmental Sciences related to Agriculture and Land-use; Fertilization; Geovetenskap och miljövetenskap; Harvest; Klimatforskning; Land use; Land use planning; Lantbruksvetenskap och veterinärmedicin; Large-scale models; Miljö- och naturvårdsvetenskap; Model testing; Modelling; Natural Sciences; Natural vegetation; Naturvetenskap; Nitrogen; Other Agricultural Sciences; Phenology; Photosynthesis; Physiology; Plant growth; Productivity; Ratios; Regions; Scale models; Statistical methods; Terrestrial ecosystems; Tissue; Vegetation; Wheat
• ISSN: 1726-4170; 1726-4189; 1726-4189
• DOI: 10.5194/bg-12-2489-2015

Nitrogen (N) is a key element in terrestrial ecosystems as it influences both plant growth and plant interactions with the atmosphere. Accounting for carbon–nitrogen interactions has been found to alter future projections of the terrestrial carbon (C) cycle substantially. Dynamic vegetation models (DVMs) aim to accurately represent both natural vegetation and managed land, not only from a carbon cycle perspective but increasingly so also for a wider range of processes including crop yields. We present here the extended version of the DVM LPJ-GUESS that accounts for N limitation in crops to account for the effects of N fertilisation on yields and biogeochemical cycling.The performance of this new implementation is evaluated against observations from N fertiliser trials and CO2 enrichment experiments. LPJ-GUESS captures the observed response to both N and CO2 fertilisation on wheat biomass production, tissue C to N ratios (C : N) and phenology.To test the model's applicability for larger regions, simulations are subsequently performed that cover the wheat-dominated regions of western Europe. When compared to regional yield statistics, the inclusion of C–N dynamics in the model substantially increase the model performance compared to an earlier version of the model that does not account for these interactions. For these simulations, we also demonstrate an implementation of N fertilisation timing for areas where this information is not available. This feature is crucial when accounting for processes in managed ecosystems in large-scale models. Our results highlight the importance of accounting for C–N interactions when modelling agricultural ecosystems, and it is an important step towards accounting for the combined impacts of changes in climate, [CO2] and land use on terrestrial biogeochemical cycles.