Long-term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa
Antoine Couëdel
(1, 2)
,
Gatien N Falconnier
(1, 2, 3, 4)
,
Myriam Adam
(5, 6, 7)
,
Rémi Cardinael
(1, 2, 4)
,
Kenneth Boote
(8)
,
Eric Justes
(2, 9)
,
Ward Smith
(10)
,
Anthony Whitbread
(11)
,
François Affholder
(1, 2)
,
Juraj Balkovic
(12)
,
Bruno Basso
(13)
,
Arti Bhatia
(14)
,
Bidisha Chakrabarti
(14)
,
Regis Chikowo
(4)
,
Mathias Christina
(1, 2)
,
Babacar Faye
(15)
,
Fabien Ferchaud
(16)
,
Christian Folberth
(12)
,
Folorunso Akinseye
(17)
,
Thomas Gaiser
(18)
,
Marcelo Galdos
(19)
,
Sebastian Gayler
(20)
,
Aram Gorooei
(18)
,
Brian Grant
(10)
,
Hervé Guibert
(1, 2)
,
Gerrit Hoogenboom
(8)
,
Bahareh Kamali
(18)
,
Moritz Laub
(21)
,
Fidel Maureira
(13)
,
Fasil Mequanint
(20)
,
Claas Nendel
(22, 23, 24)
,
Cheryl Porter
(8)
,
Dominique Ripoche
(25)
,
Alex Ruane
(26)
,
Leonard Rusinamhodzi
(27)
,
Shikha Sharma
(14)
,
Upendra Singh
(28)
,
Johan Six
(21)
,
Amit Srivastava
(18)
,
Bernard Vanlauwe
(29)
,
Antoine Versini
(30, 2)
,
Murilo Vianna
(18)
,
Heidi Webber
(22, 31)
,
Tobias K.D. Weber
(20, 32)
,
Congmu Zhang
(8)
,
Marc Corbeels
(1, 2)
,
Marc Corbeels
(1, 2, 29)
1
UPR AIDA -
Agroécologie et Intensification Durables des cultures annuelles
2 Cirad-PERSYST - Département Performances des systèmes de production et de transformation tropicaux
3 CIMMYT - International Maize and Wheat Improvement Center [Zimbabwe]
4 UZ - University of Zimbabwe
5 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
6 Cirad-BIOS - Département Systèmes Biologiques
7 NUBB - National University of Battambang
8 UF - University of Florida [Gainesville]
9 Cirad-DG - Cirad Direction Générale
10 AAFC - Agriculture and Agri-Food
11 ILRI - International Livestock Research Institute [CGIAR, Tanzanie]
12 IIASA - International Institute for Applied Systems Analysis [Laxenburg]
13 Michigan State University [East Lansing]
14 IARI - Indian Agricultural Research Institute
15 UCAD - Université Cheikh Anta Diop de Dakar [Sénégal]
16 UMR Eco&Sols - Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes
17 ICRISAT - International Crops Research Institute for the Semi-Arid Tropics [Senegal]
18 Universität Bonn = University of Bonn
19 Rothamsted Research
20 University of Hohenheim
21 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
22 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
23 CAS - Czech Academy of Sciences [Prague]
24 University of Potsdam = Universität Potsdam
25 AGROCLIM - Agroclim
26 GISS - NASA Goddard Institute for Space Studies
27 IITA-Ghana - International Institute of Tropical Agriculture
28 IFDC - International Fertilizer Development Center
29 IITA Kenya - International Institute of Tropical Agriculture
30 UPR Recyclage et risque - Recyclage et risque
31 BTU - Brandenburg University of Technology [Cottbus – Senftenberg]
32 University of Kassel
2 Cirad-PERSYST - Département Performances des systèmes de production et de transformation tropicaux
3 CIMMYT - International Maize and Wheat Improvement Center [Zimbabwe]
4 UZ - University of Zimbabwe
5 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
6 Cirad-BIOS - Département Systèmes Biologiques
7 NUBB - National University of Battambang
8 UF - University of Florida [Gainesville]
9 Cirad-DG - Cirad Direction Générale
10 AAFC - Agriculture and Agri-Food
11 ILRI - International Livestock Research Institute [CGIAR, Tanzanie]
12 IIASA - International Institute for Applied Systems Analysis [Laxenburg]
13 Michigan State University [East Lansing]
14 IARI - Indian Agricultural Research Institute
15 UCAD - Université Cheikh Anta Diop de Dakar [Sénégal]
16 UMR Eco&Sols - Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes
17 ICRISAT - International Crops Research Institute for the Semi-Arid Tropics [Senegal]
18 Universität Bonn = University of Bonn
19 Rothamsted Research
20 University of Hohenheim
21 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
22 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
23 CAS - Czech Academy of Sciences [Prague]
24 University of Potsdam = Universität Potsdam
25 AGROCLIM - Agroclim
26 GISS - NASA Goddard Institute for Space Studies
27 IITA-Ghana - International Institute of Tropical Agriculture
28 IFDC - International Fertilizer Development Center
29 IITA Kenya - International Institute of Tropical Agriculture
30 UPR Recyclage et risque - Recyclage et risque
31 BTU - Brandenburg University of Technology [Cottbus – Senftenberg]
32 University of Kassel
Gatien N Falconnier
- Fonction : Auteur
- PersonId : 1089919
- ORCID : 0000-0003-3291-650X
- IdRef : 25036770X
Myriam Adam
- Fonction : Auteur
- PersonId : 1239730
- ORCID : 0000-0002-8873-6762
Rémi Cardinael
- Fonction : Auteur
- PersonId : 170813
- IdHAL : remi-cardinael
- ORCID : 0000-0002-9924-3269
- IdRef : 192789465
Eric Justes
- Fonction : Auteur
- PersonId : 1202901
- ORCID : 0000-0001-7390-7058
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 longterm 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-tocrop 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.