Assessing uncertainties in land cover projections

Peter Alexander, Reinhard Prestele, Peter H. Verburg, Almut Arneth, Claudia Baranzelli, Filipe Batista e Silva, Calum Brown, Adam Butler, Katherine Calvin, Nicolas Dendoncker, Jonathan C. Doelman, Robert Dunford, Kerstin Engström, David Eitelberg, Shinichiro Fujimori, Paula A. Harrison, Tomoko Hasegawa, Petr Havlik, Sascha Holzhauer, Florian Humpenöder & 18 others Chris Jacobs-Crisioni, Atul K. Jain, Tamás Krisztin, Page Kyle, Carlo Lavalle, Tim Lenton, Jiayi Liu, Prasanth Meiyappan, Alexander Popp, Tom Powell, Ronald D. Sands, Rüdiger Schaldach, Elke Stehfest, Jevgenijs Steinbuks, Andrzej Tabeau, Hans van Meijl, Marshall A. Wise, Mark D A Rounsevell

Research output: Contribution to journalArticle

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.

LanguageEnglish
Pages767-781
Number of pages15
JournalGlobal Change Biology
Volume23
Issue number2
DOIs
Publication statusPublished - 1 Feb 2017

Fingerprint

land cover
Land use
climate
land use
Projection systems
Uncertainty
Earth (planet)
mitigation
Economics
economics
modeling
simulation

Keywords

  • cropland
  • land cover
  • land use
  • model inter-comparison
  • uncertainty

Cite this

Alexander, P., Prestele, R., Verburg, P. H., Arneth, A., Baranzelli, C., Batista e Silva, F., ... Rounsevell, M. D. A. (2017). Assessing uncertainties in land cover projections. Global Change Biology, 23(2), 767-781. 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. ; Rounsevell, Mark D A. / Assessing uncertainties in land cover projections. In: Global Change Biology. 2017 ; Vol. 23, No. 2. pp. 767-781.
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Alexander, P, Prestele, R, Verburg, PH, Arneth, A, Baranzelli, C, Batista e Silva, F, Brown, C, Butler, A, Calvin, K, Dendoncker, N, Doelman, JC, Dunford, R, Engström, K, Eitelberg, D, Fujimori, S, Harrison, PA, Hasegawa, T, Havlik, P, Holzhauer, S, Humpenöder, F, Jacobs-Crisioni, C, Jain, AK, Krisztin, T, Kyle, P, Lavalle, C, Lenton, T, Liu, J, Meiyappan, P, Popp, A, Powell, T, Sands, RD, Schaldach, R, Stehfest, E, Steinbuks, J, Tabeau, A, van Meijl, H, Wise, MA & Rounsevell, MDA 2017, 'Assessing uncertainties in land cover projections' Global Change Biology, vol. 23, no. 2, pp. 767-781. https://doi.org/10.1111/gcb.13447

Assessing uncertainties in land cover projections. / 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.; Rounsevell, Mark D A.

In: Global Change Biology, Vol. 23, No. 2, 01.02.2017, p. 767-781.

Research output: Contribution to journalArticle

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AU - Verburg, Peter H.

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AU - Baranzelli, Claudia

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AU - Brown, Calum

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AU - Calvin, Katherine

AU - Dendoncker, Nicolas

AU - Doelman, Jonathan C.

AU - Dunford, Robert

AU - Engström, Kerstin

AU - Eitelberg, David

AU - Fujimori, Shinichiro

AU - Harrison, Paula A.

AU - Hasegawa, Tomoko

AU - Havlik, Petr

AU - Holzhauer, Sascha

AU - Humpenöder, Florian

AU - Jacobs-Crisioni, Chris

AU - Jain, Atul K.

AU - Krisztin, Tamás

AU - Kyle, Page

AU - Lavalle, Carlo

AU - Lenton, Tim

AU - Liu, Jiayi

AU - Meiyappan, Prasanth

AU - Popp, Alexander

AU - Powell, Tom

AU - Sands, Ronald D.

AU - Schaldach, Rüdiger

AU - Stehfest, Elke

AU - Steinbuks, Jevgenijs

AU - Tabeau, Andrzej

AU - van Meijl, Hans

AU - Wise, Marshall A.

AU - Rounsevell, Mark D A

PY - 2017/2/1

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N2 - 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.

AB - 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.

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Alexander P, Prestele R, Verburg PH, Arneth A, Baranzelli C, Batista e Silva F et al. Assessing uncertainties in land cover projections. Global Change Biology. 2017 Feb 1;23(2):767-781. https://doi.org/10.1111/gcb.13447