Assessing uncertainties in land cover projections

Alexander P, Prestele R, Verburg PH, Arneth A, Baranzelli C, Batista e Silva F, Brown C, Butler A, et al. (2017). Assessing uncertainties in land cover projections. Global Change Biology 23: 767-781. DOI:10.1111/gcb.13447.

[img]
Preview
Text
8075_1_art_file_99201_nz6xy6_convrt.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

Download (510kB) | Preview
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), Metrics, Models and Foresight for European Sustainable Food and Nutrition Security (SUSFANS, H2020 633692)

Abstract

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies, and quantifying the impacts of land cover change on the climate system. Here we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Item Type: Article
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Romeo Molina
Date Deposited: 17 Aug 2016 12:06
Last Modified: 17 Aug 2017 03:00
URI: http://pure.iiasa.ac.at/13736

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313