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European Journal of Agronomy
Article . 2022 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
Hal-Diderot
Article . 2022
Data sources: Hal-Diderot
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A modelling chain combining soft and hard models to assess a bundle of ecosystem services provided by a diversity of cereal-legume intercrops

Authors: Clémentine Meunier; Lionel Alletto; Laurent Bedoussac; Jacques-Eric Bergez; Pierre Casadebaig; Julie Constantin; Noémie Gaudio; +15 Authors

A modelling chain combining soft and hard models to assess a bundle of ecosystem services provided by a diversity of cereal-legume intercrops

Abstract

International audience; Cereal-legume intercropping is known to improve the sustainability of crop production. However, it remains uncommon on commercial farms in Europe due to a number of socio-technical lock-ins and the many practical issues raised when integrating intercrops in cropping systems (e.g. which species, cultivars, sowing densities). Crop modelling is an option to explore integration scenarios and support farmers' decisions. However, available crop models are not able to simulate bundles of ecosystem services provided by a large diversity of binary cereallegume intercropping scenarios. To address this challenge, we developed a hybrid modelling chain that combines process-based, statistical and knowledge-based models to benefit from the strengths of these three different modelling approaches. The chain (i) simulates potential biomass of the sole cereal and legume crops independently using the crop model STICS; (ii) uses statistical interaction models built in R to convert potential biomass in sole cropping into attainable biomass in intercropping by considering competition effects among species, using a field trial database; (iii) converts attainable biomass into actual biomass by considering pest damage using a knowledge-based multi-attribute DEXi model, and also assesses control of pests (i.e. weeds, insects and diseases); and (iv) uses another set of multi-attribute models to assess five additional ecosystem services (i.e. cereal and legume grain yields, cereal protein content, nitrogen supply to the following crop and impact on soil structure) from the actual biomass of the intercrop at harvest and/or cropping system features. The chain was calibrated for grain cereal-legume intercrops sown simultaneously in a random pattern under low-input French conditions. We used an expert-based approach to assess the performances of each model and evaluate the accuracy of the entire modelling chain. In 18 simulated scenarios, 79% of the predicted levels of ecosystem services were consistent with experts' opinion. Predictions were more accurate for intercropping scenarios that included species from the trial database used to build linear interaction models (relative RMSE of 27-31%) but remained satisfactory for other intercropped species (relative RMSE of 32-37%). This is the first modelling chain able to assess bundles of ecosystem services provided by multiple cereal-legume intercrops in function of their cropping system contexts. This chain is intended to be included in an educational tool that is used face to face with farmers or students to design cropping systems that include intercrops.

Country
France
Subjects by Vocabulary

Microsoft Academic Graph classification: Biomass (ecology) biology Intercropping Agricultural engineering biology.organism_classification Ecosystem services Soil structure Agronomy Field trial Sustainability Cropping system Cropping Mathematics

Keywords

[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Mixed crop, Soil Science, Plant Science, Intercropping, Mixed model, Ecosystem services, Crop model, Agronomy and Crop Science

Alletto, L., 2015. Systèmes de Culture Innovants et Gestion de l ' Eau. Caractérisation des impacts agronomiques et environnementaux de pratiques. Université de Toulouse.

Anglade, J., Billen, G., Garnier, J., 2015. Relationships for estimating N2 fixation in legumes: Incidence for N balance of legume-based cropping systems in europe. Ecosphere 6, 1-24. https://doi.org/10.1890/ES14-00353.1 [OpenAIRE]

Aubertot, J.-N., Robin, M.-H., 2013. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases. https://doi.org/10.1371/journal.pone.0073202 [OpenAIRE]

Aubertot, J.N., Robin, M.H., 2013. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases. PLoS One 8. [OpenAIRE]

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    influence
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    impulse
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    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    5
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
Funded by
EC| ReMIX
Project
ReMIX
Redesigning European cropping systems based on species MIXtures
  • Funder: European Commission (EC)
  • Project Code: 727217
  • Funding stream: H2020 | RIA
Related to Research communities
Sustainable Development Solutions Network - Greece
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