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The world’s population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model-based assessments of land-use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land-change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land-use change assessments, the results indicate a large range of estimates with important consequences for model-based assessments.
The main files are Global_high_estimate.asc, Global_medium_estimate.asc, and Global_low_estimate.asc which can be imported in ArcGIS. The map is created in equal area projection Eckert IV with a resolution of 9.25 x 9.25 km (corresponding to 5 arcminutes).
Map value 0 = unavailable cropland Map value 1 = available cropland
– Institute for Environmental Studies, VU University Amsterdam
David A. Eitelberg (david.eitelberg@vu.nl)
VU Amsterdam
Jasper van Vliet
VU Amsterdam
Peter H. Verburg
VU Amsterdam
Land-cover data were derived from the Global Land Cover 2000 dataset (GLC2000). We reclassified the original 22 GLC2000 land-cover classes to match the 17 International Geosphere-Biosphere Programme (IGBP) land-coverclasses according to the groupings described in Herold et al.
(2008).
See this image for an overview of the data used in this study.
Bij gebruik van de data refereert u naar:
Eitelberg, D. A., van Vliet, J., & Verburg, P. H. (2015). A review of global potentially available cropland estimates and their consequences for model‐based assessments. Global change biology, 21(3), 1236-1248.
http://dx.doi.org/10.1111/gcb.12733