Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison

Research output: Contribution to journalArticle

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Hotspots of uncertainty in land-use and land-cover change projections : a global-scale model comparison. / Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A.; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K.; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D.; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H.

In: Global Change Biology, Vol. 22, No. 12, 01.12.2016, p. 3967-3983.

Research output: Contribution to journalArticle

Harvard

Prestele, R, Alexander, P, Rounsevell, MDA, Arneth, A, Calvin, K, Doelman, J, Eitelberg, DA, Engström, K, Fujimori, S, Hasegawa, T, Havlik, P, Humpenöder, F, Jain, AK, Krisztin, T, Kyle, P, Meiyappan, P, Popp, A, Sands, RD, Schaldach, R, Schüngel, J, Stehfest, E, Tabeau, A, Van Meijl, H, Van Vliet, J & Verburg, PH 2016, 'Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison', Global Change Biology, vol. 22, no. 12, pp. 3967-3983. https://doi.org/10.1111/gcb.13337

APA

Prestele, R., Alexander, P., Rounsevell, M. D. A., Arneth, A., Calvin, K., Doelman, J., ... Verburg, P. H. (2016). Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison. Global Change Biology, 22(12), 3967-3983. https://doi.org/10.1111/gcb.13337

CBE

Prestele R, Alexander P, Rounsevell MDA, Arneth A, Calvin K, Doelman J, Eitelberg DA, Engström K, Fujimori S, Hasegawa T, Havlik P, Humpenöder F, Jain AK, Krisztin T, Kyle P, Meiyappan P, Popp A, Sands RD, Schaldach R, Schüngel J, Stehfest E, Tabeau A, Van Meijl H, Van Vliet J, Verburg PH. 2016. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison. Global Change Biology. 22(12):3967-3983. https://doi.org/10.1111/gcb.13337

MLA

Vancouver

Prestele R, Alexander P, Rounsevell MDA, Arneth A, Calvin K, Doelman J et al. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison. Global Change Biology. 2016 Dec 1;22(12):3967-3983. https://doi.org/10.1111/gcb.13337

Author

Prestele, Reinhard ; Alexander, Peter ; Rounsevell, Mark D A ; Arneth, Almut ; Calvin, Katherine ; Doelman, Jonathan ; Eitelberg, David A. ; Engström, Kerstin ; Fujimori, Shinichiro ; Hasegawa, Tomoko ; Havlik, Petr ; Humpenöder, Florian ; Jain, Atul K. ; Krisztin, Tamás ; Kyle, Page ; Meiyappan, Prasanth ; Popp, Alexander ; Sands, Ronald D. ; Schaldach, Rüdiger ; Schüngel, Jan ; Stehfest, Elke ; Tabeau, Andrzej ; Van Meijl, Hans ; Van Vliet, Jasper ; Verburg, Peter H. / Hotspots of uncertainty in land-use and land-cover change projections : a global-scale model comparison. In: Global Change Biology. 2016 ; Vol. 22, No. 12. pp. 3967-3983.

RIS

TY - JOUR

T1 - Hotspots of uncertainty in land-use and land-cover change projections

T2 - Global Change Biology

AU - Prestele, Reinhard

AU - Alexander, Peter

AU - Rounsevell, Mark D A

AU - Arneth, Almut

AU - Calvin, Katherine

AU - Doelman, Jonathan

AU - Eitelberg, David A.

AU - Engström, Kerstin

AU - Fujimori, Shinichiro

AU - Hasegawa, Tomoko

AU - Havlik, Petr

AU - Humpenöder, Florian

AU - Jain, Atul K.

AU - Krisztin, Tamás

AU - Kyle, Page

AU - Meiyappan, Prasanth

AU - Popp, Alexander

AU - Sands, Ronald D.

AU - Schaldach, Rüdiger

AU - Schüngel, Jan

AU - Stehfest, Elke

AU - Tabeau, Andrzej

AU - Van Meijl, Hans

AU - Van Vliet, Jasper

AU - Verburg, Peter H.

PY - 2016/12/1

Y1 - 2016/12/1

N2 - Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

AB - Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

KW - land-use allocation

KW - land-use change

KW - land-use model uncertainty

KW - map comparison

KW - model intercomparison

KW - model variation

UR - http://www.scopus.com/inward/record.url?scp=84995593480&partnerID=8YFLogxK

U2 - 10.1111/gcb.13337

DO - 10.1111/gcb.13337

M3 - Article

VL - 22

SP - 3967

EP - 3983

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 12

ER -