Agritrop
Accueil

Long term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa

Couedel Antoine, Falconnier Gatien N., Adam Myriam, Cardinael Rémi, Boote Kenneth J., Justes Eric, Smith Ward N., Whitbread Anthony M., Affholder François, Balkovic Juraj, Basso Bruno, Bhatia Arti, Chakrabarti Bidisha, Chikowo Régis, Christina Mathias, Faye Babacar, Ferchaud Fabien, Folberth Christian, Akinseye Folorunso M., Gaiser Thomas, Corbeels Marc. 2024. Long term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa. European Journal of Agronomy, 155:127109, 16 p.

Article de revue ; Article de recherche ; Article de revue à facteur d'impact
[img] Version publiée - Anglais
Accès réservé aux personnels Cirad
Utilisation soumise à autorisation de l'auteur ou du Cirad.
Couëdel2024 Long-term soil organic carbon and crop yield feedbacks differ between 16.pdf

Télécharger (6MB) | Demander une copie

Résumé : Food insecurity in sub-Saharan Africa is partly due to low staple crop yields, resulting from poor soil fertility and low nutrient inputs. Integrated soil fertility management (ISFM), which includes the combined use of mineral and organic fertilizers, can contribute to increasing yields and sustaining soil organic carbon (SOC) in the long term. Soil-crop simulation models can help assess the performance and trade-offs of a range of crop management practices including ISFM, under current and future climate. Yet, uncertainty in model simulations can be high, resulting from poor model calibration and/or inadequate model structure. Multi-model simulations have been shown to be more robust than those with single models and help understand and reduce modelling uncertainty. In this study, we aim to perform the first multi-model comparison for long-term simulations of crop yield and SOC and their feedbacks in SSA. We evaluated the performance of 16 soil-crop models using data from four long-term maize experiments at sites in SSA with contrasting climates and soils. Each experiment had four treatments: i) no exogenous inputs, ii) addition of mineral nitrogen (N) fertilizer, iii) use of organic amendments, and iv) combined use of mineral and organic inputs. We assessed model performance in two steps: through blind calibration involving a minimum level of experimental data provided to the modeling teams, and subsequently through full calibration, which included a more extensive set of observational data. Model ensemble accuracy was greater with full calibration than blind calibration. Improvement in model accuracy was larger for maize yields (nRMSE 48 vs 18%) than for topsoil SOC (nRMSE 22 vs 14%). Model ensemble uncertainty (defined as the coefficient of variation across the 16 models) increased over the duration of the long-term experiments. Uncertainty of SOC simulations increased when organic amendments were used, whilst uncertainty of yield predictions was largest when no inputs were applied. Our study revealed large discrepancies among the models in simulating i) crop-to-soil feedbacks due to uncertainties in simulated carbon coming from roots, and ii) soil-to-crop feedbacks due to large uncertainties in simulated crop N supply from soil organic matter decomposition. These discrepancies were largest when organic amendments were applied. The results highlight the need for long-term experiments in which root and soil N dynamics are monitored. This will provide the corresponding data to improve and calibrate soil-crop models, which will lead to more robust and reliable simulations of SOC and crop productivity, and their interactions.

Mots-clés Agrovoc : modèle de simulation, rendement des cultures, matière organique du sol, modélisation des cultures, carbone, modèle mathématique, amendement organique, fertilité du sol, engrais organique, gestion intégrée de la fertilité des sols

Mots-clés géographiques Agrovoc : Côte d'Ivoire, Kenya

Mots-clés libres : Soil organic carbon, Crop yield, Crop modeling, Sub Saharan Africa

Classification Agris : F01 - Culture des plantes
P33 - Chimie et physique du sol
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques

Agences de financement hors UE : Agropolis Fondation, Agence Nationale de la Recherche, Total Foundation

Projets sur financement : (FRA) Agricultural Intensification and Dynamics of Soil Carbon Sequestration in Tropical and Temperate Farming Systems, (FRA) Agricultural Sciences for sustainable Development

Auteurs et affiliations

  • Couedel Antoine, CIRAD-PERSYST-UPR AIDA (FRA) - auteur correspondant
  • Falconnier Gatien N., CIRAD-PERSYST-UPR AIDA (FRA) ORCID: 0000-0003-3291-650X
  • Adam Myriam, CIRAD-BIOS-UMR AGAP (KHM) ORCID: 0000-0002-8873-6762
  • Cardinael Rémi, CIRAD-PERSYST-UPR AIDA (ZWE) ORCID: 0000-0002-9924-3269
  • Boote Kenneth J., University of Florida (USA)
  • Justes Eric, CIRAD-DG-Direction générale (FRA) ORCID: 0000-0001-7390-7058
  • Smith Ward N., Ottawa Research and Development Center (CAN)
  • Whitbread Anthony M., ILRI (TZA)
  • Affholder François, CIRAD-PERSYST-UPR AIDA (MOZ) ORCID: 0000-0002-3919-4805
  • Balkovic Juraj, IIASA (AUT)
  • Basso Bruno, MSU (USA)
  • Bhatia Arti, ICAR (IND)
  • Chakrabarti Bidisha, ICAR (IND)
  • Chikowo Régis, University of Zimbabwe (ZWE)
  • Christina Mathias, CIRAD-PERSYST-UPR AIDA (FRA) ORCID: 0000-0003-3618-756X
  • Faye Babacar, USSEIN (SEN)
  • Ferchaud Fabien, INRAE (FRA)
  • Folberth Christian, IIASA (AUT)
  • Akinseye Folorunso M., ICRISAT (MLI)
  • Gaiser Thomas, Universität Bonn (DEU)
  • Corbeels Marc, CIRAD-PERSYST-UPR AIDA (KEN)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/608294/)

Voir la notice (accès réservé à Agritrop) Voir la notice (accès réservé à Agritrop)

[ Page générée et mise en cache le 2024-04-26 ]