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Farming system models for supporting farm resilience: Research needs, gaps and promising approaches

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Title Farming system models for supporting farm resilience: Research needs, gaps and promising approaches
 
Creator Le, Quang Bao
 
Subject agent-based systems
bio-economic modeling
decision
component-based model
bayesian belief network (bbn)
system dynamics (sd)
 
Description It 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, this study aims at highlighting 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.
 
Date 2016-02-10T10:39:05Z
2016-02-10T10:39:05Z
 
Type Conference Paper
 
Identifier https://mel.cgiar.org/reporting/download/hash/N5DLQZ66
Quang Bao Le. (7/9/2015). Farming system models for supporting farm resilience: Research needs, gaps and promising approaches. Montpellier, France: Emmanuel S. Gritti (Curator), Jacques Wery.
https://hdl.handle.net/20.500.11766/4296
Open access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher AGRO2015
 
Source 5th International Symposium for Farming Systems Design;