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dc.contributorVillamor, Graveen_US
dc.contributorThiombiano, Boundia Alexandreen_US
dc.creatorLe, Quang Baoen_US
dc.date.accessioned2020-02-24T20:04:34Z
dc.date.available2020-02-24T20:04:34Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/cf85b9bc5a9af51dfb01a89e0a3166deen_US
dc.identifier.citationQuang Bao Le, Grave Villamor, Boundia Alexandre Thiombiano. (6/10/2019). Multi-agent system for integrating ecological processes at multiple scales with human decision-making: Solutions and lessons learned from a modelling framework applied in different landscape ecosystems.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10818
dc.description.abstractModelling socio-ecological systems, in which social and ecological systems interact each other and co-evolve, are useful for supporting decisions in managing landscape ecosystems. Inter-linking socially interactive decision-making to relevant ecological processes faces a great challenge due to at least two reasons: (1) the inherent mismatches in the spatial and temporal scales the considered processes operate, (2) differences in relevant methods for modelling the processes and (3) different data availabilities for the processes. There has been a direction that uses multi-agent system (MAS) as a conceptual framework and unified computer platform for integrating different specific modelling methods of relevant ecological processes with human decisions on agriculture and ecosystem management. This study analyses and illustrate how the above challenge is addressed by Land Use Dynamics Simulator (LUDAS) framework with implementations in selected landscape ecosystems in West Africa (Burkina Faso) and Southeast Asia (Vietnam and Indonesia). We modeled inter-linkages between interactive household land-use decisions and four relevant ecological processes: crop production, forest timber growth, vegetation type transitions, and changes in plant species diversity. First, each of these ecological processes was modelled by relevant methods, which are response crop production function, system dynamics, cellular automata and species-area relation for crop production, forest timber growth, vegetation transitions, and plant species diversity, respectively. Second, these sub-models were encoded within a MAS framework to establish inter-linkages. Third, through structural sensitivity analyses (i.e. comparison of simulated socio-ecological systems between WITH and WITHOUT socioecological inter-linkages), as well as multi-criteria discussions of methodological options, we constructed a matrix of methodological options for modelling socio-ecological linkages, their benefits and limitations. The matrix would be a provisional knowledgebase that adds methodological choices for socio-ecological landscape modelers. By concept and current technological availabilities, MAS would be an option being well suited to simulate the co-evolutions of the community and landscape ecosystems.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.rightsCC-BY-4.0en_US
dc.subjectmulti-agent systemen_US
dc.subjectsocio-ecological systemsen_US
dc.subjectreduce inequalityen_US
dc.subjectagent-based modellingen_US
dc.subjectsocio-ecological linkagesen_US
dc.subjectsocio-ecological co-evolutionen_US
dc.titleMulti-agent system for integrating ecological processes at multiple scales with human decision-making: Solutions and lessons learned from a modelling framework applied in different landscape ecosystemsen_US
dc.typePresentationen_US
dcterms.available2019-10-06en_US
cg.creator.idLe, Quang Bao: 0000-0001-8514-1088en_US
cg.subject.agrovocgoal 1 no povertyen_US
cg.subject.agrovocgoal 2 zero hungeren_US
cg.subject.agrovocgoal 15 life on landen_US
cg.subject.agrovocfinger milleten_US
cg.subject.agrovocmaizeen_US
cg.subject.agrovocsorghumen_US
cg.subject.agrovoccottonen_US
cg.subject.agrovoccowpeaen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerPolytechnic University of Bobo-Dioulassoen_US
cg.contributor.centerNazi BONI University, Institute for Rural Development - UNB - IDRen_US
cg.contributor.centerNew Zealand Forest Research Institute Limited - SCIONen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes and Dryland Cereals - GLDCen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionWestern Africaen_US
cg.coverage.regionEastern Asiaen_US
cg.coverage.regionEastern Africaen_US
cg.coverage.regionSouth-Eastern Asiaen_US
cg.coverage.countryBFen_US
cg.coverage.countryCNen_US
cg.coverage.countryETen_US
cg.coverage.countryIDen_US
cg.coverage.countryVNen_US
cg.coverage.start-date2018-08-01en_US
cg.coverage.end-date2019-10-01en_US
cg.contactQ.Le@cgiar.orgen_US
dc.identifier.statusOpen accessen_US
cg.subject.sdgSDG 1 - No povertyen_US
cg.subject.sdgSDG 2 - Zero hungeren_US
cg.subject.sdgSDG 10 - Reduced inequalitiesen_US
cg.subject.sdgSDG 15 - Life on landen_US


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