Castro, L.M.; Härtl, F.; Ochoa Moreno, S.; Calvas, B.; Izquierdo Montoya, G.L. & 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.
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
Contact:
email:
luces_c <at> yahoo.es
Ecuador
Individual:
Fabian Härtl
Contact:
email:
webmaster <at> tropicalmountainforest.org
Individual:
Santiago Ochoa Moreno
Contact:
email:
wsochoa <at> utpl.edu.ec
Individual:
Baltazar Calvas
Contact:
email:
bcalvas <at> utpl.edu.ec
Hans-Carl-von- Carlowitz-Platz 2
Fachgebiet für Waldinventur und nachhaltige Nutzung
85354, Freising
85354 Freising
Germany
Individual:
Gonzalo Leonardo Izquierdo Montoya
Contact:
email:
glizquierdo <at> utpl.edu.ec
Loja
Ecuador
Individual:
Thomas Knoke
Contact:
email:
knoke <at> forst.tu-muenchen.de
Center of Life and Food Science Weihenstephan
Institute of Forest Management
Technische Universität München
Hans-Carl-von-Carlowitz-Platz 2
85354 Freising
Germany
Abstract:
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.
Keywords:
| Uncertainty analysis | land use modeling |
Literature type specific fields:
ARTICLE
Journal:
Journal of Bioeconomics
Volume:
online
Page Range:
online
Metadata Provider:
Individual:
Carola Paul
Contact:
email:
carola.paul <at> tum.de
Center of Life and Food Sciences Weihenstephan
Institute of Forest Management
Technische Universität München
Hans-Carl-von-Carlowitz-Platz 2
85354 Freising
Germany
