Cite as:
Castro, L.M.; H&auml;rtl, F.; Ochoa Moreno, S.; Calvas, B.; Izquierdo Montoya, G.L. &amp; Knoke, T. (2018): <b>Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations</b>. <i>Journal of Bioeconomics</i> <b>online </b>, online<br>DOI: <a href="" target="_blank"></a>.

Resource Description

Title: Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations
FOR816dw ID: 1707
Publication Date: 2018-02-20
License and Usage Rights:
Resource Owner(s):
Individual: Luz Maria Castro
Individual: Fabian Härtl
Individual: Santiago Ochoa Moreno
Individual: Baltazar Calvas
Individual: Gonzalo Leonardo Izquierdo Montoya
Individual: Thomas Knoke
Bio-economic modelling has become a useful tool for anticipating the<br/> outcomes of policies and technologies before their implementation. Advances in mathematical<br/> programming have made it possible to build more comprehensive models. In<br/> an overview of recent studies about bio-economic models applied to land-use problems<br/> in agriculture and forestry,we evaluated howaspects such as uncertainty,multiple<br/> objective functions, system dynamics and time have been incorporated into models.<br/> We found that single objective models were more frequently applied at the farm level,<br/> while multiple objective modelling has been applied to meet concerns at the landscape<br/> level. Among the objectives, social aspects are seldom represented in allmodels, when<br/> being compared to economic and environmental aspects. The integration of uncertainty<br/> is occasionally a topic, while stochastic approaches are more frequently applied than<br/> non-stochastic robust methods. Mostmultiple-objectivemodels do not integrate uncertainty<br/> or sequential decision making. Static approaches continue to be more recurrent<br/> than truly dynamic models. Even though integrating multiple aspects may enhance<br/> our understanding of a system; it involves a tradeoff between complexity and robustness<br/> of the results obtained. Land-use models have to address this balance between<br/> complexity and robustness in order to evolve towards robust multiple-objective spatial<br/> optimization as a prerequisite to achieve sustainability goals.
| Uncertainty analysis | land use modeling |
Literature type specific fields:
Journal: Journal of Bioeconomics
Volume: online
Page Range: online
Metadata Provider:
Individual: Carola Paul
Online Distribution:
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