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Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Luz Maria Castro (), Fabian Härtl, Santiago Ochoa, Baltazar Calvas, Leonardo Izquierdo and Thomas Knoke
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Luz Maria Castro: Universidad Tecnica Particular de Loja
Fabian Härtl: Technische Universität München
Santiago Ochoa: Universidad Tecnica Particular de Loja
Baltazar Calvas: Technische Universität München
Leonardo Izquierdo: Universidad Tecnica Particular de Loja
Thomas Knoke: Technische Universität München

Journal of Bioeconomics, 2018, vol. 20, issue 2, 183-211

Abstract: Abstract Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.

Keywords: Optimization; Uncertainty; System dynamics; Time; Objective functions; Q57 (search for similar items in EconPapers)
Date: 2018
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