Evaluating the spatial uncertainty of future land abandonment in a mountain valley (Vicdessos, Pyrenees - France): Insights from model parameterization and experiments

Journal of Mountain Science - Tập 12 - Trang 1095-1112 - 2015
Thomas Houet1, Laure Vacquié1, David Sheeren2
1GEODE UMR 5602 CNRS -UT2J, Université Toulouse Jean Jaurès, Maison de la recherche, Toulouse Cedex, France
2Dynafor UMR 1201 INRA/INPT-ENSAT, Ecole Nationale Supérieure Agronomique de Toulouse, Castanet-Tolosan Cédex, France

Tóm tắt

European mountains are particularly sensitive to climatic disruptions and land use changes. The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services, LUCC models offer new opportunities for land managers to adapt or mitigate their strategies. Assessing the spatial uncertainty of future LUCC is crucial for the definition of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains (France) and two scenarios illustrating two land use strategies. The model was parameterized with the same driving factors used for its calibration. The definition of ’static vs. dynamic’ and ’quantitative vs. qualitative (discretized)’ driving factors, and their combination resulted in four parameterizations. The combination of model outcomes produced maps of the spatial uncertainty of future LUCC. This work involves adapting the definition of spatial uncertainty in the literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the uncertainty of the future to provide maps to help decision makers and land managers.

Tài liệu tham khảo

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