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

被引:178
作者
Prestele, Reinhard [1 ]
Alexander, Peter [2 ]
Rounsevell, Mark D. A. [2 ]
Arneth, Almut [3 ]
Calvin, Katherine [4 ]
Doelman, Jonathan [5 ]
Eitelberg, David A. [1 ]
Engstrom, Kerstin [6 ]
Fujimori, Shinichiro [7 ]
Hasegawa, Tomoko [7 ]
Havlik, Petr [8 ]
Humpenoeder, Florian [9 ]
Jain, Atul K. [10 ]
Krisztin, Tamas [8 ]
Kyle, Page [4 ]
Meiyappan, Prasanth [10 ]
Popp, Alexander [9 ]
Sands, Ronald D. [11 ]
Schaldach, Ruediger [12 ]
Schuengel, Jan [12 ]
Stehfest, Elke [5 ]
Tabeau, Andrzej [1 ,13 ]
Van Meijl, Hans [13 ]
Van Vliet, Jasper [1 ]
Verburg, Peter H. [1 ,14 ]
机构
[1] Vrije Univ Amsterdam, Dept Earth Sci, Environm Geog Grp, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands
[2] Univ Edinburgh, Sch GeoSci, Drummond St, Edinburgh EH8 9XP, Midlothian, Scotland
[3] Karlsruhe Inst Technol, Dept Atmospher Environm Res IMK IFU, Kreuzeckbahnstr 19, D-82467 Garmisch Partenkirchen, Germany
[4] Pacific Northwest Natl Lab, Joint Global Change Res Inst, College Pk, MD 20740 USA
[5] PBL Netherlands Environm Assessment Agcy, POB 303, NL-3720 AH Bilthoven, Netherlands
[6] Lund Univ, Dept Geog & Ecosyst Sci, Solvegatan 12, Lund, Sweden
[7] Natl Inst Environm Studies, Ctr Social & Environm Syst Res, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan
[8] Int Inst Appl Syst Anal, Ecosyst Serv & Management Program, A-2361 Laxenburg, Austria
[9] Potsdam Inst Climate Impact Res PIK, POB 60 12 03, D-14412 Potsdam, Germany
[10] Univ Illinois, Dept Atmospher Sci, 105 S Gregory Ave, Urbana, IL 61801 USA
[11] USDA, Resource & Rural Econ Div, Econ Res Serv, Washington, DC 20250 USA
[12] Univ Kassel, Ctr Environm Syst Res, Wilhelmshoher Allee 17, D-34109 Kassel, Germany
[13] Wageningen Univ & Res Ctr, LEI, POB 29703, NL-2502 LS The Hague, Netherlands
[14] Swiss Fed Res Inst WSL, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland
基金
欧洲研究理事会; 美国国家科学基金会;
关键词
land-use allocation; land-use change; land-use model uncertainty; map comparison; model intercomparison; model variation; CLIMATE-CHANGE; CARBON STOCKS; IMPACT; SYSTEM; AGRICULTURE; MITIGATION; SCENARIOS; POLICY; MAPS; SET;
D O I
10.1111/gcb.13337
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
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.
引用
收藏
页码:3967 / 3983
页数:17
相关论文
共 70 条
[1]  
Alexander P, ASSESSING U IN PRESS
[2]  
Alexandratos N., 2012, World agriculture towards 2030/2050: the 2012 revision
[3]  
[Anonymous], 2012, DISCUSSION PAPER SER, DOI DOI 10.1016/S1043-2760(97)84344-5
[4]   Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty [J].
Ballantyne, A. P. ;
Andres, R. ;
Houghton, R. ;
Stocker, B. D. ;
Wanninkhof, R. ;
Anderegg, W. ;
Cooper, L. A. ;
DeGrandpre, M. ;
Tans, P. P. ;
Miller, J. B. ;
Alden, C. ;
White, J. W. C. .
BIOGEOSCIENCES, 2015, 12 (08) :2565-2584
[5]  
Bontemps S., 2011, technical report, V136, P1
[6]   Effect of Anthropogenic Land-Use and Land-Cover Changes on Climate and Land Carbon Storage in CMIP5 Projections for the Twenty-First Century [J].
Brovkin, V. ;
Boysen, L. ;
Arora, V. K. ;
Boisier, J. P. ;
Cadule, P. ;
Chini, L. ;
Claussen, M. ;
Friedlingstein, P. ;
Gayler, V. ;
van den Hurk, B. J. J. M. ;
Hurtt, G. C. ;
Jones, C. D. ;
Kato, E. ;
de Noblet-Ducoudre, N. ;
Pacifico, F. ;
Pongratz, J. ;
Weiss, M. .
JOURNAL OF CLIMATE, 2013, 26 (18) :6859-6881
[7]  
Brown D.G., 2014, Advancing Land Change Modeling: Opportunities and Research Requirements, DOI DOI 10.17226/18385
[8]   Opportunities to improve impact, integration, and evaluation of land change models [J].
Brown, Daniel G. ;
Verburg, Peter H. ;
Pontius, Robert Gilmore, Jr. ;
Lange, Mark D. .
CURRENT OPINION IN ENVIRONMENTAL SUSTAINABILITY, 2013, 5 (05) :452-457
[9]   Multimodel inference - understanding AIC and BIC in model selection [J].
Burnham, KP ;
Anderson, DR .
SOCIOLOGICAL METHODS & RESEARCH, 2004, 33 (02) :261-304