Integrating global socio-economic influences into a regional land use change model for China

doi:10.1007/s11707-013-0421-8

Front. Earth Sci.

2014, Vol. 8

Issue (1) : 81-92 https://doi.org/10.1007/s11707-013-0421-8

RESEARCH ARTICLE

Integrating global socio-economic influences into a regional land use change model for China

Xia XU^1,², Qiong GAO¹, Changhui PENG², Xuefeng CUI^1,³(

), Yinghui LIU⁴, Li JIANG^1,⁵

¹. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
². Department of Biology Sciences, institute of environment Science, University of Quebec at Montreal, Montreal H3C 3P8, Canada
³. College of Global Change and Earth System Research, Beijing Normal University, Beijing 100875, China
⁴. Academy of Resource, Beijing Normal University, Beijing 100875, China
⁵. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China

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Abstract

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socio-economic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Keywords global socio-economic influence land use change model integrating China

Corresponding Author(s): Xuefeng CUI

Issue Date: 05 March 2014

Cite this article:

Xia XU,Qiong GAO,Changhui PENG, et al. Integrating global socio-economic influences into a regional land use change model for China[J]. Front. Earth Sci., 2014, 8(1): 81-92.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-013-0421-8
https://academic.hep.com.cn/fesci/EN/Y2014/V8/I1/81

1	J Bolliger, H Lischke, D G Green (2005). Simulating the spatial and temporal dynamics of landscapes using generic and complex models. Ecol Complex, 2(2): 107–116 https://doi.org/10.1016/j.ecocom.2004.11.005
2	F Bousquet, C le Page (2004). Multi-agent simulations and ecosystem management: a review. Ecol Modell, 176(3–4): 313–332 https://doi.org/10.1016/j.ecolmodel.2004.01.011
3	S D Brody (2003). Implementing the principles of ecosystem management through local land use planning. Popul Environ, 24(6): 511–540 https://doi.org/10.1023/A:1025078715216
4	D G Brown, B C Pijanowski, J D Duh (2000). Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA. Environ Manage, 59(4): 247–263 https://doi.org/10.1006/jema.2000.0369
5	M E Brown, C C Funk (2008). Food security under climate change. Science, 319(5863): 580–581 https://doi.org/10.1126/science.1154102 pmid: 18239116
6	J C Castella, P H Verburg (2007). Combination of process-oriented and pattern oriented models of land-use change in a mountain area of Vietnam. Ecol Modell, 202(3–4): 410–420 https://doi.org/10.1016/j.ecolmodel.2006.11.011
7	T W Crawford, J P Messina, S Manson, D O’Sullivan (2005). Complexity science, complex systems, and land use research: guest editorial. Environment plan B, 32: 792–798
8	C T de Wit, H van Keulen, N G Seligman, I Spharim (1988). Application of interactive multiple goal programming techniques for analysis and planning of regional agricultural development. Agric Syst, 26(3): 211–230 https://doi.org/10.1016/0308-521X(88)90012-1
9	C Dietzel, K C Clarke (2007). Toward optimal calibration of the SLEUTH land use change model. Transactions in GIS, 11(1): 29–45 https://doi.org/10.1111/j.1467-9671.2007.01031.x
10	G Engelen, R White, I Uljee, P Drazan (1995). Using cellular automata for integrated modeling of socio-environmental system. Environ Monit Assess, 34(2): 203–214 https://doi.org/10.1007/BF00546036
11	FAO (1995). Planning for sustainable use of land resource. Towards a new approach. Background paper to FAOs Task Managership for Chapter 10 of Agenda 21 of the United Nations Conference on Environment and Development (UNCED). Prepared by Land and Water Development Division and approved by Interdepartmental Working Group on Land Use Planning, FAO
12	J A Foley, R Defries, G P Asner, C Barford, G Bonan, S R Carpenter, F S Chapin, M T Coe, G C Daily, H K Gibbs, J H Helkowski, T Holloway, E A Howard, C J Kucharik, C Monfreda, J A Patz, I C Prentice, N Ramankutty, P K Snyder (2005). Global consequences of land use. Science, 309(5734): 570–574 https://doi.org/10.1126/science.1111772 pmid: 16040698
13	Q Gao, M Yu, Y H Liu, H M Xu, X Xu (2007). Modeling interplay between regional net ecosystem carbon balance and soil erosion for a crop-pasture region. J Geophys Res, 112(G4): G04005 https://doi.org/10.1029/2007JG000455
14	H Haberl, K H Erb, F Krausmann, W Loibl, N Schulz, H Weisz (2001). Changes in ecosystem processes induced by land use: human appropriation of aboveground NPP and its influence on standing crop in Austria. Global Biogeochem Cycles, 15(4): 929–942 https://doi.org/10.1029/2000GB001280
15	C He, N Okada, Q Zhang, P Shi, J Li (2008). Modelling dynamic urban expansion processes incorporating a potential model with cellular automata. Landsc Urban Plan, 86(1): 79–91 https://doi.org/10.1016/j.landurbplan.2007.12.010
16	K Hilferink, P Rietveld (1999). Land use scanner: an integrated GIS based model for long term projections of land use in urban and rural areas. J Geogr Syst, 1(2): 155–177 https://doi.org/10.1007/s101090050010
17	L Jiang, X Cui, X Xu, Y Jiang, M Rounsevell, D Murray-Rust, YH Liu(2013) A simple global food system model. Agricultural Economics, (in press)
18	J D Kline, A Moses, G J Lettman, D L Azuma (2007). Modeling forest and range land development in rural locations, with examples from eastern Oregon. Landsc Urban Plan, 80(3): 320–332 https://doi.org/10.1016/j.landurbplan.2006.10.017
19	F Krausmann (2001). Land use and industrial modernization: an empirical analysis of human influence on the functioning of ecosystems in Austria 1830–1995. Land Use Policy, 18(1): 17–26 https://doi.org/10.1016/S0264-8377(00)00042-9
20	F Krausmann, H Haberl, N B Schulz, K H Erb, E Darge, V Gaube (2003). Land use change and socio-economic metabolism in Austria—part I: driving forces of land-use change: 1950–1995. Land Use Policy, 20(1): 1–20 https://doi.org/10.1016/S0264-8377(02)00048-0
21	G Kruseman, R Ruben, H Hengsdijk, M van Ittersum (1995). Farm household modeling for estimating the effectiveness of price instruments in land use policy. Neth J Agric Sci, 43: 111–123
22	A Kuyvenhoven, R Ruben, G Kruseman (1995). Options for sustainable agricultural systems and policy instruments to reach them. In: Eco-regional Approaches for Sustainable Land Use and Food Production, 12–16 December 1994, ISNAR. Kluwer Academic Publishers,187–212
23	E F Lambin, M D A Rounsevell, H J Geist (2000). Are agricultural land-use models able to predict changes in land-use intensity? Agric Ecosyst Environ, 82(1–3): 321–331 https://doi.org/10.1016/S0167-8809(00)00235-8
24	X Lee, M Goulden, D Hollinger, A Barr, TA Black, G Bohrer, R Bracho, B Drake, A Goldstein, L Gu, G Katul, T Kolb, BE Law, H Margolis, T Meyers, R Monson, W Munger, R Oren, Tha Paw U K, AD Richardson, HP Schmid, R Staebler, S Wofsy, L Zhao (2011). Observed increase in local cooling effect of deforestation at higher latitudes. Nature, 4790: 384–387 doi:10.1038/nature10588
25	G Lin, S Ho (2003). China’s land resources and land-use change: insights from the 1996 land survey. Land Use Policy, 20(2): 87–107 https://doi.org/10.1016/S0264-8377(03)00007-3
26	J Liu, J Diamond (2005). China’s environment in a globalizing world. Nature, 435(7046): 1179–1186 https://doi.org/10.1038/4351179a pmid: 15988514
27	J Liu, Z Zhang, X Xu (2009). Spatial patterns and driving forces of land use change in China in the early 21st century. Acta Geogr Sin, 64(12): 1411–1420
28	J F Mas, H Puig, J L Palacio, A Sosa-Lo’pez (2004). Modelling deforestation using GIS and artificial neural networks. Environ Model Softw, 19(5): 461–471 https://doi.org/10.1016/S1364-8152(03)00161-0
29	R Moss, J Edmonds, K Hibbard, M R Manning, S K Rose, D P van Vuuren, T R Carter, S Emori, M Kainuma, T Kram, G A Meehl, J F B Mitchell, N Nakicenovic, K Riahi, S J Smith, R J Stouffer, A M Thomson, J P Weyant, T J Wilbanks (2010). The nest generation of scenarios for climate change research and assessment. Nature, 463(7282): 747–756 https://doi.org/10.1038/nature08823
30	R Muetzelfeldt, J Massheder (2003). The Simile visual modelling environment. Eur J Agron, 18(3–4): 345–358 https://doi.org/10.1016/S1161-0301(02)00112-0
31	K P Overmars, P H Verburg, T Veldkamp (2007). Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model. Land Use Policy, 24(3): 584–599 https://doi.org/10.1016/j.landusepol.2005.09.008
32	F W T Penning de Vries, H van Keulen, R Rabbinge (1995). Natural resources and limits to food production in 2040. In: Eco-regional Approaches for Sustainable Land Use and Food Production, 12–16 December 1994. Kluwer Academic Publishers, 65–87
33	B C Pijanowski, K T Alexandridis, D Müller (2006). Modelling urbanization patterns in two diverse regions of the world. J Land Use Sci, 1(2–4): 83–108 https://doi.org/10.1080/17474230601058310
34	B C Pijanowski, S H Gage, D T Long, W E Cooper (2000). A land transformation model for the Saginaw Baywatershed. In: J Sanderson, L D Harris, eds. Landscape Ecology: A Top Down Approach. Boca Raton: Lewis Publishing, 708pp
35	R G Pontius Jr, J D Cornell, C A S Hall (2001). Modeling the spatial pattern of land-use change with GEOMOD2: application and validation. Agric Ecosyst Environ, 85(1–3): 191–203 https://doi.org/10.1016/S0167-8809(01)00183-9
36	S Pourebrahim, M Hadipour, Bin M Mokhtar (2011). Integration of spatial suitability analysis for land use planning in coastal areas; case of Kuala Langat District, Selangor, Malaysia. Landsc Urban Plan, 101(1): 84–97 https://doi.org/10.1016/j.landurbplan.2011.01.007
37	R Rabbinge, H C van Latesteijn (1992). Long-term options for land use in the European Community. Agric Syst, 40(1–3): 195–210 https://doi.org/10.1016/0308-521X(92)90021-F
38	R R Rindfuss, B Entwisle, S J Walsh, L An, N Badenoch, D G Brown, P Deadman, T P Evans, J Fox, J Geoghegan, M Gutmann, M Kelly, M Linderman, J Liu, G P Malanson, C F Mena, J P Messina, E F Moran, D C Parker, W Parton, P Prasartkul, D T Robinson, Y Sawangdee, L K Vanwey, P H Verburg (2008). Land use change: complexity and comparisons. J Land Use Sci, 3(1): 1–10 https://doi.org/10.1080/17474230802047955 pmid: 20354590
39	C J E Schulp, G J Nabuurs, P H Verburg (2008). Future carbon sequestration in Europe—effects of land use change. Agric Ecosyst Environ, 127(3–4): 251–264 https://doi.org/10.1016/j.agee.2008.04.010
40	B S Soares-Filho, D C Nepstad, L M Curran, G C Cerqueira, R A Garcia, C A Ramos, E Voll, A McDonald, P Lefebvre, P Schlesinger (2006). Modelling conservation in the Amazon basin. Nature, 440(7083): 520–523 https://doi.org/10.1038/nature04389 pmid: 16554817
41	T L Sohl, K L Sayler, M A Drummond, T R Loveland (2007). The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling. J Land Use Sci, 2(2): 103–126 https://doi.org/10.1080/17474230701218202
42	F Tao, M Yokozawa, Z Zhang (2009). Modelling the impacts of weather and climate variability on crop productivity over a large area: a new process-based model development, optimization, and uncertainties analysis. Agric Meteorol, 149(5): 831–850 https://doi.org/10.1016/j.agrformet.2008.11.004
43	C Tebaldi, D B Lobell (2008). Towards probabilistic projections of climate change impacts on global crop yields. Geophys Res Lett, 35(8): L08705 https://doi.org/10.1029/2008GL033423
44	F V Tongeren (2008). Agricultural Policy Design and Implementation: A Synthesis. OECD Food, Agriculture and Fisheries Working Papers, 7: doi:10.1787/243786286663
45	F V Tongeren, H V Meijl, Y Surry (2001). Global models applied to agricultural and trade policies: a review and assessment. Agric Econ, 26(2): 149–172 https://doi.org/10.1111/j.1574-0862.2001.tb00060.x
46	B L Turner 2nd, E F Lambin, A Reenberg (2007). The emergence of land change science for global environmental change and sustainability. Proc Natl Acad Sci USA, 104(52): 20666–20671 https://doi.org/10.1073/pnas.0704119104 pmid: 18093934
47	A Veldkamp, L O Fresco (1996). CLUE-CR: an integrated multi-scale model to simulate land use change scenarios in Costa Rica. Ecol Modell, 91(1–3): 231–248 https://doi.org/10.1016/0304-3800(95)00158-1
48	P H Verburg, B Eickhout, H V Meijl (2008). A multi-scale, multi-model approach for analyzing the future dynamics of European land use. Ann Reg Sci, 42(1): 57–77 https://doi.org/10.1007/s00168-007-0136-4
49	P H Verburg, K P Overmars (2009). Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model. Landscape Ecol, 24(9): 1167–1181 https://doi.org/10.1007/s10980-009-9355-7
50	P H Verburg, P P Schot, M J Dijst, A Veldkamp (2004). Land use change modelling: current practice and research priorities. Geol J, 61: 309–324
51	P H Verburg, C J E Schulp, N Witte, A Veldkamp (2006). Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agric Ecosyst Environ, 114(1): 39–56 https://doi.org/10.1016/j.agee.2005.11.024
52	P H Verburg, W Soepboer, A Veldkamp, R Limpiada, V Espaldon, S S Mastura (2002). Modeling the spatial dynamics of regional land use: the CLUE-S model. Environ Manage, 30(3): 391–405 https://doi.org/10.1007/s00267-002-2630-x pmid: 12148073
53	P H Verburg, J van de Steeg, A Veldkamp, L Willemen (2009). From land cover change to land function dynamics: a major challenge to improve land characterization. J Environ Manage, 90(3): 1327–1335 https://doi.org/10.1016/j.jenvman.2008.08.005 pmid: 18809242
54	P H Verburg, G H J de Koning, K Kok, A Veldkamp, J Bouma (1999). A spatial explicit allocation procedure for modeling the pattern of land use change based upon actual land use. Ecol Modell, 116(1): 45–61 https://doi.org/10.1016/S0304-3800(98)00156-2
55	P H Verburg, K H Erb, O Mertz, G Espindola (2013) Land System Science: between global challenges and local realities. Current Opinion in Environmental Sustainability, 5(5): 433–437
56	W B Wu, P Yang, H J Tang (2007). Regional variability of efects of land use system on soil properties. Scientia Agricultura Sinica, 2007, 40(8): 1697–1702
57	X Xu, Q Gao, Y H Liu, J A Wang, Y Zhang (2009). Coupling a land use model and an ecosystem model for a crop-pasture zone. Ecol Modell, 220(19): 2503–2511 https://doi.org/10.1016/j.ecolmodel.2009.04.043

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