Assessing uncertainties in land cover projections
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. In this work, 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 revealmore »
- Authors:
-
more »
- Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences; Land Economy and Environment Research Group, Edinburgh (United Kingdom)
- Vrije Univ., Amsterdam (Netherlands). Dept. of Earth Sciences, Environmental Geography Group
- Inst. of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen (Germany). Karlsruhe Inst.of Technology
- European Commission, Varese (Italy). Directorate B Innovation and Growth, Territorial Development Unit
- Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences
- Biomathematics & Statistics Scotland, Edinburgh (United Kingdom)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Inst.
- Univ. of Namur, Namur (Belgium). Dept. of Geography, Namur Research Group on Sustainable Development
- Netherlands Environmental Assessment Agency (PBL), Bilthoven (Netherlands)
- Univ. of Oxford (United Kingdom). Environmental Change Inst.; Lancaster Environment Centre (United Kingdom). Centre for Ecology & Hydrology
- Lund Univ. (Sweden). Dept. of Geography and Ecosystem Science
- National Inst. for Environmental Studies, Tsukuba (Japan). Center for Social and Environmental Systems Research
- Lancaster Environment Centre (United Kingdom). Centre for Ecology & Hydrology
- International Inst. for Applied Systems Analysis, Laxenburg (Austria). Ecosystem Services and Management Program
- Potsdam Inst. for Climate Impact Research (PIK) (Germany)
- Univ. of Illinois, Urbana, IL (United States). Dept. of Atmospheric Sciences
- Univ. of Exeter, (United Kingdom). College of Life and Environmental Sciences, Earth System Science
- US Dept. of Agriculture (USDA), Washington, DC (United States). Resource and Rural Economics Division
- Univ. of Kassel, Kassel (Germany). Center for Environmental Systems Research
- The World Bank, Washington D.C. (United States). Development Research Group
- Wageningen Univ. and Research Centre, The Hague (Netherlands)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1571930
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Global Change Biology
- Additional Journal Information:
- Journal Volume: 23; Journal Issue: 2; Journal ID: ISSN 1354-1013
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; cropland; land cover; land use; model inter-comparison; uncertainty
Citation Formats
Alexander, Peter, Prestele, Reinhard, Verburg, Peter H., Arneth, Almut, Baranzelli, Claudia, Batista E. Silva, Filipe, Brown, Calum, Butler, Adam, Calvin, Katherine, Dendoncker, Nicolas, Doelman, Jonathan C., Dunford, Robert, Engström, Kerstin, Eitelberg, David, Fujimori, Shinichiro, Harrison, Paula A., Hasegawa, Tomoko, Havlik, Petr, Holzhauer, Sascha, Humpenöder, Florian, Jacobs-Crisioni, Chris, Jain, Atul K., Krisztin, Tamás, Kyle, Page, Lavalle, Carlo, Lenton, Tim, Liu, Jiayi, Meiyappan, Prasanth, Popp, Alexander, Powell, Tom, Sands, Ronald D., Schaldach, Rüdiger, Stehfest, Elke, Steinbuks, Jevgenijs, Tabeau, Andrzej, van Meijl, Hans, Wise, Marshall A., and Roun Sevell, Mark D. A. Assessing uncertainties in land cover projections. United States: N. p., 2016.
Web. doi:10.1111/gcb.13447.
Alexander, Peter, Prestele, Reinhard, Verburg, Peter H., Arneth, Almut, Baranzelli, Claudia, Batista E. Silva, Filipe, Brown, Calum, Butler, Adam, Calvin, Katherine, Dendoncker, Nicolas, Doelman, Jonathan C., Dunford, Robert, Engström, Kerstin, Eitelberg, David, Fujimori, Shinichiro, Harrison, Paula A., Hasegawa, Tomoko, Havlik, Petr, Holzhauer, Sascha, Humpenöder, Florian, Jacobs-Crisioni, Chris, Jain, Atul K., Krisztin, Tamás, Kyle, Page, Lavalle, Carlo, Lenton, Tim, Liu, Jiayi, Meiyappan, Prasanth, Popp, Alexander, Powell, Tom, Sands, Ronald D., Schaldach, Rüdiger, Stehfest, Elke, Steinbuks, Jevgenijs, Tabeau, Andrzej, van Meijl, Hans, Wise, Marshall A., & Roun Sevell, Mark D. A. Assessing uncertainties in land cover projections. United States. https://doi.org/10.1111/gcb.13447
Alexander, Peter, Prestele, Reinhard, Verburg, Peter H., Arneth, Almut, Baranzelli, Claudia, Batista E. Silva, Filipe, Brown, Calum, Butler, Adam, Calvin, Katherine, Dendoncker, Nicolas, Doelman, Jonathan C., Dunford, Robert, Engström, Kerstin, Eitelberg, David, Fujimori, Shinichiro, Harrison, Paula A., Hasegawa, Tomoko, Havlik, Petr, Holzhauer, Sascha, Humpenöder, Florian, Jacobs-Crisioni, Chris, Jain, Atul K., Krisztin, Tamás, Kyle, Page, Lavalle, Carlo, Lenton, Tim, Liu, Jiayi, Meiyappan, Prasanth, Popp, Alexander, Powell, Tom, Sands, Ronald D., Schaldach, Rüdiger, Stehfest, Elke, Steinbuks, Jevgenijs, Tabeau, Andrzej, van Meijl, Hans, Wise, Marshall A., and Roun Sevell, Mark D. A. Sat .
"Assessing uncertainties in land cover projections". United States. https://doi.org/10.1111/gcb.13447. https://www.osti.gov/servlets/purl/1571930.
@article{osti_1571930,
title = {Assessing uncertainties in land cover projections},
author = {Alexander, Peter and Prestele, Reinhard and Verburg, Peter H. and Arneth, Almut and Baranzelli, Claudia and Batista E. Silva, Filipe and Brown, Calum and Butler, Adam and Calvin, Katherine and Dendoncker, Nicolas and Doelman, Jonathan C. and Dunford, Robert and Engström, Kerstin and Eitelberg, David and Fujimori, Shinichiro and Harrison, Paula A. and Hasegawa, Tomoko and Havlik, Petr and Holzhauer, Sascha and Humpenöder, Florian and Jacobs-Crisioni, Chris and Jain, Atul K. and Krisztin, Tamás and Kyle, Page and Lavalle, Carlo and Lenton, Tim and Liu, Jiayi and Meiyappan, Prasanth and Popp, Alexander and Powell, Tom and Sands, Ronald D. and Schaldach, Rüdiger and Stehfest, Elke and Steinbuks, Jevgenijs and Tabeau, Andrzej and van Meijl, Hans and Wise, Marshall A. and Roun Sevell, Mark D. A.},
abstractNote = {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. In this work, 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.},
doi = {10.1111/gcb.13447},
journal = {Global Change Biology},
number = 2,
volume = 23,
place = {United States},
year = {Sat Jul 30 00:00:00 EDT 2016},
month = {Sat Jul 30 00:00:00 EDT 2016}
}
Web of Science
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