@inproceedings{fdi:010085503,
  title = {{E}valuation of the {D}ay{C}ent model to predict carbon fluxes in {F}rench crop sites [r{\'e}sum{\'e}]},
  author = {{F}ujisaki, {K}enji and {M}artin, {M}.{P}. and {Z}hang, {Y}. and {B}ernoux, {M}artial and {C}hapuis {L}ardy, {L}ydie},
  editor = {},
  language = {{ENG}},
  abstract = {{C}roplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. {T}herefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. {T}his study was part of the {C}omete-{G}lobal project funded by the multi-{P}artner call {FACCE} {JPI}. {C}arbon fluxes, net ecosystem exchange ({NEE}), leaf area index ({LAI}), biomass, and grain production were simulated at the site level in three {F}rench crop experiments from the {C}arbo{E}urope project. {S}everal crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. {D}aily {NEE} was measured with eddy covariance and could be partitioned between gross primary production ({GPP}) and total ecosystem respiration ({TER}). {M}easurements were compared to {D}ay{C}ent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. {W}e compared two versions of the model: the original one with a simplified plant module and a newer version that simulates {LAI}. {I}nput data for modelling were soil properties, climate, and management practices. {S}imulations of grain yields and biomass production were acceptable when using optimized crop parameters. {S}imulation of {NEE} was also acceptable. {GPP} predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. {TER} was underestimated by the model. {P}redicted {NEE} was more sensitive to soil tillage and nitrogen applications than measured {NEE}. {D}ay{C}ent was therefore a relevant tool to predict carbon fluxes in {F}rench crops at the site level. {T}he introduction of {LAI} in the model improved its performance.},
  keywords = {{ZONE} {TEMPEREE}},
  volume = {19},
  numero = {},
  pages = {{EGU}2017--17409--1 [1 ]},
  booktitle = {},
  year = {2017},
  ISSN = {1607-7962},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085503},
}