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  Assessing uncertainties in land cover projections

Alexander, P., Prestele, R., Verburg, P. H., Arneth, A., Baranzelli, C., Batista e Silva, F., Brown, C., Butler, A., Calvin, K., Dendoncker, N., Doelman, J. C., Dunford, R., Engström, K., Eitelberg, D., Fujimori, S., Harrison, P. A., Hasegawa, T., Havlik, P., Holzhauer, S., Humpenöder, F., Jacobs-Crisioni, C., Jain, A. K., Krisztin, T., Kyle, P., Lavalle, C., Lenton, T., Liu, J., Meiyappan, P., Popp, A., Powell, T., Sands, R. D., Schaldach, R., Stehfest, E., Steinbuks, J., Tabeau, A., Meijl, H. v., Wise, M. A., 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

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 Creators:
Alexander, P.1, Author
Prestele, R.1, Author
Verburg, P. H.1, Author
Arneth, A.1, Author
Baranzelli, C.1, Author
Batista e Silva, F.1, Author
Brown, C.1, Author
Butler, A.1, Author
Calvin, K.1, Author
Dendoncker, N.1, Author
Doelman, J. C.1, Author
Dunford, R.1, Author
Engström, K.1, Author
Eitelberg, D.1, Author
Fujimori, S.1, Author
Harrison, P. A.1, Author
Hasegawa, T.1, Author
Havlik, P.1, Author
Holzhauer, S.1, Author
Humpenöder, Florian2, Author              
Jacobs-Crisioni, C.1, AuthorJain, A. K.1, AuthorKrisztin, T.1, AuthorKyle, P.1, AuthorLavalle, C.1, AuthorLenton, T.1, AuthorLiu, J.1, AuthorMeiyappan, P.1, AuthorPopp, Alexander2, Author              Powell, T.1, AuthorSands, R. D.1, AuthorSchaldach, R.1, AuthorStehfest, E.1, AuthorSteinbuks, J.1, AuthorTabeau, A.1, AuthorMeijl, H. van1, AuthorWise, M. A.1, AuthorRounsevell, M. D. A.1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 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.

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 Dates: 2017
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1111/gcb.13447
PIKDOMAIN: Sustainable Solutions - Research Domain III
eDoc: 7387
Research topic keyword: Land use
Research topic keyword: Food & Agriculture
Research topic keyword: Mitigation
Research topic keyword: Climate impacts
Model / method: Model Intercomparison
Model / method: MAgPIE
Regional keyword: Global
Organisational keyword: RD3 - Transformation Pathways
Working Group: Land-Use Management
 Degree: -

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Title: Global Change Biology
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 23 (2) Sequence Number: - Start / End Page: 767 - 781 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals192