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  Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions

Ehrhardt, F., Soussana, J.-F., Bellocchi, G., Grace, P., McAuliffe, R., Recous, S., Sándor, R., Smith, P., Snow, V., Antoni Migliorati, M. d., Basso, B., Bhatia, a., Brilli, L., Doltra, J., Dorich, C. D., Doro, L., Fitton, N., Giacomini, S. J., Grant, B., Harrison, M. T., Jones, S. K., Kirschbaum, M. U. F., Klumpp, K., Laville, P., Léonard, J., Liebig, M., Lieffering, M., Martin, R., Massad, R. S., Meier, E., Merbold, L., Moore, A. D., Myrgiotis, M., Newton, P., Pattey, E., Rolinski, S., Sharp, J., Smith, W. N., Wu, L., Zhang, Q. (2018): Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions. - Global Change Biology, 24, 2, e603-e616.
https://doi.org/10.1111/gcb.13965

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 Creators:
Ehrhardt, F.1, Author
Soussana, J.-F.1, Author
Bellocchi, G.1, Author
Grace, P.1, Author
McAuliffe, R.1, Author
Recous, S.1, Author
Sándor, R.1, Author
Smith, P.1, Author
Snow, V.1, Author
Antoni Migliorati, M. de1, Author
Basso, B.1, Author
Bhatia, a.1, Author
Brilli, L.1, Author
Doltra, J.1, Author
Dorich, C. D.1, Author
Doro, L.1, Author
Fitton, N.1, Author
Giacomini, S. J.1, Author
Grant, B.1, Author
Harrison, M. T.1, Author
Jones, S. K.1, AuthorKirschbaum, M. U. F.1, AuthorKlumpp, K.1, AuthorLaville, P.1, AuthorLéonard, J.1, AuthorLiebig, M.1, AuthorLieffering, M.1, AuthorMartin, R.1, AuthorMassad, R. S.1, AuthorMeier, E.1, AuthorMerbold, L.1, AuthorMoore, A. D.1, AuthorMyrgiotis, M.1, AuthorNewton, P.1, AuthorPattey, E.1, AuthorRolinski, Susanne2, Author              Sharp, J.1, AuthorSmith, W. N.1, AuthorWu, L.1, AuthorZhang, Q.1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield‐scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed.

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 Dates: 2018
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1111/gcb.13965
PIKDOMAIN: Climate Impacts & Vulnerabilities - Research Domain II
eDoc: 8080
Research topic keyword: Food & Agriculture
Research topic keyword: Land use
Research topic keyword: Ecosystems
Model / method: LPJmL
Regional keyword: Europe
Organisational keyword: RD2 - Climate Resilience
Working Group: Land Use and Resilience
 Degree: -

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Title: Global Change Biology
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 24 (2) Sequence Number: - Start / End Page: e603 - e616 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals192