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Land 2015, 4(2), 475-512; doi:10.3390/land4020475

Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region

1
Department of Civil, Environmental and Geomatic Engineering, Planning of Landscape and Urban Systems, Swiss Federal Institute of Technology, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland
2
Department of Environmental Systems Science, Natural and Social Science Interface, Swiss Federal Institute of Technology, Universitätsstrasse 22, 8092 Zurich, Switzerland
3
Earth System Science Group, Wageningen University and Research Center, Droevendaalsesteeg 4, 6708 PB Wageningen, The Netherlands
4
Department of Environmental Systems Science, Agricultural Economics, Swiss Federal Institute of Technology, Sonneggstrasse 33, 8092 Zurich, Switzerland
5
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: James Millington and John Wainwright
Received: 1 January 2015 / Revised: 25 May 2015 / Accepted: 29 May 2015 / Published: 8 June 2015
(This article belongs to the Special Issue Agent-Based Modelling and Landscape Change)
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Abstract

Land abandonment and the subsequent re-forestation are important drivers behind the loss of ecosystem services in mountain regions. Agent-based models can help to identify global change impacts on farmland abandonment and can test policy and management options to counteract this development. Realigning the representation of human decision making with time scales of ecological processes such as reforestation presents a major challenge in this context. Models either focus on the agent-specific behavior anchored in the current generation of farmers at the expense of representing longer scale environmental processes or they emphasize the simulation of long-term economic and forest developments where representation of human behavior is simplified in time and space. In this context, we compare the representation of individual and aggregated decision-making in the same model structure and by doing so address some implications of choosing short or long term time horizons in land-use modeling. Based on survey data, we integrate dynamic agents into a comparative static economic sector supply model in a Swiss mountain region. The results from an extensive sensitivity analysis show that this agent-based land-use change model can reproduce observed data correctly and that both model versions are sensitive to the same model parameters. In particular, in both models the specification of opportunity costs determines the extent of production activities and land-use changes by restricting the output space. Our results point out that the agent-based model can capture short and medium term developments in land abandonment better than the aggregated version without losing its sensitivity to important socio-economic drivers. For comparative static approaches, extensive sensitivity analysis with respect to opportunity costs, i.e., the measure of benefits forgone due to alternative uses of labor is essential for the assessment of the impact of climate change on land abandonment and re-forestation in mountain regions. View Full-Text
Keywords: land abandonment; re-forestation; mountain regions; agent-based modeling; sector supply model; sensitivity analysis land abandonment; re-forestation; mountain regions; agent-based modeling; sector supply model; sensitivity analysis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Brändle, J.M.; Langendijk, G.; Peter, S.; Brunner, S.H.; Huber, R. Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region. Land 2015, 4, 475-512.

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