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dc.contributorRoux, Sebastienen_US
dc.contributorDelmotte, Sylvestreen_US
dc.contributorMerot, Anneen_US
dc.contributorRapidel, Brunoen_US
dc.contributorAdam, Myriamen_US
dc.contributorWery, Jacquesen_US
dc.creatorLamanda, Nathalieen_US
dc.date2012-04-30en_US
dc.date.accessioned2018-09-18T22:07:02Z
dc.date.available2018-09-18T22:07:02Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifierhttps://www.sciencedirect.com/science/article/pii/S1161030111000839en_US
dc.identifier.citationNathalie Lamanda, Sebastien Roux, Sylvestre Delmotte, Anne Merot, Bruno Rapidel, Myriam Adam, Jacques Wery. (30/4/2012). A protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integration. European Journal of Agronomy, 38, pp. 104-116.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/8394
dc.description.abstractInnovative agricultural systems need to combine the production of goods with the provision of environmental services. When agronomists analyse or design multifunctional agro-ecosystems, they thus need to include knowledge of an increasing range of scientific disciplines (plant biology, soil science, ecology, etc.) while continuing to use their systemic approach as a cornerstone. Increasing amounts of knowledge of different types (concepts and data) will thus have to be included in systemic approaches that are developed in the agronomic domain. Knowledge integration and sharing are frequently hampered by the lack of detail in the assumptions made in each discipline. We hypothesise that a standardised description of the conceptual model underlying data collection and the analysis of agro ecosystems would improve transparency and knowledge integration. Here we propose a protocol to formalise the conceptual modelling of an agro-ecosystem (CMA) related to a specific agronomic issue. The CMA protocol is implemented in four iterative steps: (i) structural analysis, (ii) functional analysis, (iii) dynamic analysis, and (iv) consistency check. The final product is a conceptual model of an agro-ecosystem whose key elements are a structured knowledge base and associated graphical representations. The protocol was drawn up based on three case studies concerning three different biophysical objects (coffee agroforest, cotton, grapevine) with different problems to be addressed. They are given here as an illustration of how to apply the CMA protocol, and to show how it can be used as a tool to build a systemic representation of a complex agro-ecosystem, as a tool for agronomic diagnosis and yield gap analysis, or as a tool to elicit a range of expert knowledge to design new field experiments. The CMA protocol proved to be efficient in guiding the process of conceptualisation up to the point at which the variables that need to be measured in the field are identified and interlinked. It enabled elicitation and integration of knowledge from different biophysical disciplines and different types of expertise during the conceptualisation process. It also enabled identification of knowledge gaps, and the design and analysis of experiments to tackle complex problems. The CMA yielded by the protocol could be used again, thanks to its transparency and modularity. Further work is underway to improve the CMA representation and its uses in numerical model specification and in participatory methods for the design of cropping systems.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevieren_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceEuropean Journal of Agronomy;38,(2011) Pagination 104,116en_US
dc.subjectagronomic diagnosisen_US
dc.subjectconceptual diagramsen_US
dc.subjectcrop functioningen_US
dc.subjectexpert knowledge elicitationen_US
dc.subjectknowledge baseen_US
dc.titleA protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integrationen_US
dc.typeJournal Articleen_US
cg.creator.idRapidel, Bruno: 0000-0003-0288-5650en_US
cg.creator.idAdam, Myriam: 0000-0002-8873-6762en_US
cg.creator.idWery, Jacques: 0000-0003-0014-4541en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocsystems analysisen_US
cg.contributor.centerThe French Agricultural Research Center for International Development - CIRADen_US
cg.contributor.centerFrench National Research Institute for Agriculture, Food and Environment - INRAE Franceen_US
cg.contributor.centerFrench National Research Institute for Agriculture, Food and Environment, Sad-Paysage - INRAE - Sad-Paysageen_US
cg.contributor.centerWageningen University & Research Centre - WURen_US
cg.contributor.centerMontpellier SupAgro - SupAgroen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.date.embargo-end-dateTimelessen_US
cg.coverage.regionWestern Africaen_US
cg.coverage.regionWestern Europeen_US
cg.coverage.countryGNen_US
cg.coverage.countryMLen_US
cg.coverage.countryFRen_US
cg.contactnathalie.lamanda@cirad.fren_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.eja.2011.07.004en_US
dc.identifier.statusTimeless limited accessen_US
mel.impact-factor3.192en_US


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