Socio-ecological System Models for Supporting Farm Resilience: Research Needs, Gaps and Promising Approaches - Public Seminar at Department of Biological Sciences, NUS

cg.contactQ.Le@cgiar.orgen_US
cg.contributor.centerCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderNot Applicableen_US
cg.contributor.project-lead-instituteCGIAR Research Program on Dryland Systems - DSen_US
cg.coverage.end-date2016-12-31en_US
cg.coverage.start-date2015-01-11en_US
cg.creator.idLe, Quang Bao: 0000-0001-8514-1088en_US
cg.subject.agrovocresilienceen_US
cg.subject.agrovocmodellingen_US
dc.creatorLe, Quang Baoen_US
dc.date.accessioned2016-02-10T10:39:30Z
dc.date.available2016-02-10T10:39:30Z
dc.description.abstractIt is important to increase the resilience of food production systems in the face of a changing climate, land scarcity, and changing demographics and market conditions. As farm resilience is a high-level system property emerged from social-ecological interactions, its direct measurement is difficult because it requires measuring the thresholds or boundaries that separate alternate stability regimes of the farm system. However, systems' modeling for supporting agricultural resilience is still in an early stage. Through critical review of state-of-the art literature, we highlighted the new requirements of agricultural system modeling as they apply to management for farm resilience, limitations of contemporary agricultural systems modeling approaches, and promising directions for future research on the field. We conceptualized criteria for evaluating models' suitability for farm resilience studies. Multi-agent systems (MAS) modeling has appeared as a promising approach for understanding farming resilience that results from rich interactions and feedback among adaptive decision-making and natural processes (e.g. energy, mineral nutrient and water flows). Using the above-mentioned criteria we also analyzed the current limitations of this model family and elaborate possible future developments as subjects of follow-up studies. I will show progresses of our on-going projects on agrarian landscape transitions using hybrid MAS modeling. At the end, I introduce a CGIAR working group on Integrated Systems Analysis and Modeling (iSAMG), in which our work embedded, to support building agricultural livelihood security in dryland at scale.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/2RGZ4W44/v/d0217a5ab65a3d458c3905f1491d3f54en_US
dc.identifier.citationQuang Bao Le. (1/7/2015). Socio-ecological System Models for Supporting Farm Resilience: Research Needs, Gaps and Promising Approaches - Public Seminar at Department of Biological Sciences, NUS.en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/4300
dc.languageenen_US
dc.rightsCC-BY-NC-SA-4.0en_US
dc.subjectagent-based systemsen_US
dc.subjectbio-economic modelingen_US
dc.subjectforesight studyen_US
dc.subjectmulti-agent systems (mas)en_US
dc.subjecttransdisciplinaryen_US
dc.subjecttrade-offen_US
dc.subjectscenariosen_US
dc.subjectinterdisciplinaryen_US
dc.titleSocio-ecological System Models for Supporting Farm Resilience: Research Needs, Gaps and Promising Approaches - Public Seminar at Department of Biological Sciences, NUSen_US
dc.typePresentationen_US
dcterms.available2015-07-01en_US

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