Assessing uncertainties in land cover projections

P Alexander, R Prestele, PH Verburg, A Arneth, C Baranzelli, F Batista E Silva, C Brown, A Butler, K Calvin, N Dendoncker, JC Doelman, R Dunford, K Engstrom, D Eitelberg, S Fujimori, PA Harrison, T Hasegawa, P Havlik, S Holzhauer, F HumpenoderC Jacobs-Crisioni, AK Jain, T Krisztin, P Kyle, C Lavalle, T Lenton, J Liu, P Meiyappan, A Popp, T Powell, RD Sands, R Schaldach, E Stehfest, J Steinbuks, A Tabeau, H van Meijl, MA Wise, MDA Rounsevell

Research output: Contribution to journalArticle

37 Citations (Scopus)
2 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)767 - 781
Number of pages15
JournalGlobal Change Biology
Volume23
Issue number2
Early online date20 Aug 2016
DOIs
Publication statusFirst published - 20 Aug 2016

Fingerprint

land cover
climate
land use
mitigation
economics
modeling
simulation

Bibliographical note

1030978

Keywords

  • Cropland
  • Land cover
  • Land use
  • Model inter-comparison
  • Uncertainty

Cite this

Alexander, P., Prestele, R., Verburg, PH., Arneth, A., Baranzelli, C., Batista E Silva, F., ... Rounsevell, MDA. (2016). Assessing uncertainties in land cover projections. Global Change Biology, 23(2), 767 - 781. https://doi.org/10.1111/gcb.13447
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 ; Engstrom, K ; Eitelberg, D ; Fujimori, S ; Harrison, PA ; Hasegawa, T ; Havlik, P ; Holzhauer, S ; Humpenoder, 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. / Assessing uncertainties in land cover projections. In: Global Change Biology. 2016 ; Vol. 23, No. 2. pp. 767 - 781.
@article{22ff8059279d422198f19fd35547d23b,
title = "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. 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.",
keywords = "Cropland, Land cover, Land use, Model inter-comparison, Uncertainty",
author = "P Alexander and R Prestele and PH Verburg and A Arneth and C Baranzelli and {Batista E Silva}, F and C Brown and A Butler and K Calvin and N Dendoncker and JC Doelman and R Dunford and K Engstrom and D Eitelberg and S Fujimori and PA Harrison and T Hasegawa and P Havlik and S Holzhauer and F Humpenoder and C Jacobs-Crisioni and AK Jain and T Krisztin and P Kyle and C Lavalle and T Lenton and J Liu and P Meiyappan and A Popp and T Powell and RD Sands and R Schaldach and E Stehfest and J Steinbuks and A Tabeau and {van Meijl}, H and MA Wise and MDA Rounsevell",
note = "1030978",
year = "2016",
month = "8",
day = "20",
doi = "10.1111/gcb.13447",
language = "English",
volume = "23",
pages = "767 -- 781",
journal = "Global Change Biology",
issn = "1354-1013",
publisher = "Wiley",
number = "2",

}

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, Engstrom, K, Eitelberg, D, Fujimori, S, Harrison, PA, Hasegawa, T, Havlik, P, Holzhauer, S, Humpenoder, 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 2016, '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, 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; Engstrom, K; Eitelberg, D; Fujimori, S; Harrison, PA; Hasegawa, T; Havlik, P; Holzhauer, S; Humpenoder, 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.

In: Global Change Biology, Vol. 23, No. 2, 20.08.2016, p. 767 - 781.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Assessing uncertainties in land cover projections

AU - Alexander, P

AU - Prestele, R

AU - Verburg, PH

AU - Arneth, A

AU - Baranzelli, C

AU - Batista E Silva, F

AU - Brown, C

AU - Butler, A

AU - Calvin, K

AU - Dendoncker, N

AU - Doelman, JC

AU - Dunford, R

AU - Engstrom, K

AU - Eitelberg, D

AU - Fujimori, S

AU - Harrison, PA

AU - Hasegawa, T

AU - Havlik, P

AU - Holzhauer, S

AU - Humpenoder, F

AU - Jacobs-Crisioni, C

AU - Jain, AK

AU - Krisztin, T

AU - Kyle, P

AU - Lavalle, C

AU - Lenton, T

AU - Liu, J

AU - Meiyappan, P

AU - Popp, A

AU - Powell, T

AU - Sands, RD

AU - Schaldach, R

AU - Stehfest, E

AU - Steinbuks, J

AU - Tabeau, A

AU - van Meijl, H

AU - Wise, MA

AU - Rounsevell, MDA

N1 - 1030978

PY - 2016/8/20

Y1 - 2016/8/20

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.

KW - Cropland

KW - Land cover

KW - Land use

KW - Model inter-comparison

KW - Uncertainty

U2 - 10.1111/gcb.13447

DO - 10.1111/gcb.13447

M3 - Article

VL - 23

SP - 767

EP - 781

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 2

ER -

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. 2016 Aug 20;23(2):767 - 781. https://doi.org/10.1111/gcb.13447