Assessing key traits to promote overyielding in mixtures of legumes and non-legumes: A case study using the Virtual Grassland model - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Assessing key traits to promote overyielding in mixtures of legumes and non-legumes: A case study using the Virtual Grassland model

Résumé

The role of various plant traits involved in carbon (C) and nitrogen (N) economy on species balance and total aboveground biomass production in binary mixtures of legumes and non-legumes was evaluated through a modelling approach using the Virtual Grassland model (VGL). A first step allowed us to identify the model parameters most sensible to inter-specific competition trough a sensitivity analysis. A second step consisted in testing the impact of individual traits values (i.e. selected among sensible parameters) on virtual mixture performance. Based on our simulation results, we concluded that maximal overyielding was achieved in cases where trait values were divergent for N acquisition (i.e. allowed complementarity in the use of different N pools) but convergent for light interception (i.e. limiting the asymmetric competition for light). The best combination of traits was not the same in all the pedo-climatic conditions tested and depended on the level of mineral N available into the soil. Random trait combinations could frequently lead to reduced mixture yields (as expected from a neutral situation of competition) and even to under-yielding (i.e. less than the average of monocultures) in some situations.
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Dates et versions

hal-02736990 , version 1 (02-06-2020)

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Gaëtan Louarn, Romain Barillot, Didier Combes, Abraham Escobar-Gutierrez. Assessing key traits to promote overyielding in mixtures of legumes and non-legumes: A case study using the Virtual Grassland model. 6. International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA2018), Nov 2018, Hefei, China. 151 p., ⟨10.1109/PMA.2018.8611602⟩. ⟨hal-02736990⟩
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