Hotspots of uncertainty in land use and land cover change projections: a global scale model comparison

Prestele R, Alexander P, Rounsevell M, Arneth A, Calvin K, Doelman J, Eitelberg D, Engström K, et al. (2016). Hotspots of uncertainty in land use and land cover change projections: a global scale model comparison. Global Change Biology 22 (12): 3967-3983. DOI:10.1111/gcb.13337.

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Project: Land use change: assessing the net climate forcing, and options for climate change mitigation and adaptation (LUC4C, FP7 603542), Stimulating Innovation for Global Monitoring of Agriculture and its Impact on the Environment in support of GEOGLAM (SIGMA, FP7 603719), Integrating human agency in global-scale land change models (GLOLAND, FP7 311819), Metrics, Models and Foresight for European Sustainable Food and Nutrition Security (SUSFANS, H2020 633692)

Abstract

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

Item Type: Article
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Romeo Molina
Date Deposited: 17 May 2016 09:55
Last Modified: 02 May 2017 03:00
URI: http://pure.iiasa.ac.at/13216

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