Journal of Geographical Sciences

, Volume 28, Issue 11, pp 1611–1625 | Cite as

Modeling the spatio-temporal changes in land uses and its impacts on ecosystem services in Northeast China over 2000–2050

  • Tian Xia
  • Wenbin WuEmail author
  • Qingbo Zhou
  • Wenxia Tan
  • Peter H. Verburg
  • Peng Yang
  • Liming Ye


Land use and its dynamics have attracted considerable scientific attention for their significant ecological and socioeconomic implications. Many studies have investigated the past changes in land use, but efforts exploring the potential changes in land use and implications under future scenarios are still lacking. Here we simulate the future land use changes and their impacts on ecosystem services in Northeast China (NEC) over the period of 2000–2050 using the CLUE–S (Conversion of Land Use and its Effects at Small regional extent) model under the scenarios of ecological security (ESS), food security (FSS) and comprehensive development (CDS). The model was validated against remote sensing data in 2005. Overall, the accuracy of the CLUE–S model was evaluated at 82.5%. Obtained results show that future cropland changes mainly occur in the Songnen Plain and the Liaohe Plain, forest and grassland changes are concentrated in the southern Lesser Khingan Mountains and the western Changbai Mountains, while the Sanjiang Plain will witness major changes of the wetlands. Our results also show that even though CDS is defined based on the goals of the regional development plan, the ecological service value (ESV) under CDS is RMB 2656.18 billion in 2050. The ESV of CDS is lower compared with the other scenarios. Thus, CDS is not an optimum scenario for eco-environmental protection, especially for the wetlands, which should be given higher priority for future development. The issue of coordination is also critical in future development. The results can help to assist structural adjustments for agriculture and to guide policy interventions in NEC.


Northeast China land use spatio-temporal change scenario ecosystem service 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Barreto L, Schoorl J M, Kok K et al., 2013. Modelling potential landscape sediment delivery due to projected soybean expansion: A scenario study of the Balsas sub–basin, Cerrado, Maranhão state, Brazil. Journal of Environmental Management, 115: 270–277.CrossRefGoogle Scholar
  2. Bonilla–Moheno M, Aide T M, Clark M, 2012. The influence of socioeconomic, environmental, and demographic factors on municipality–scale land–cover change in Mexico. Regional Environmental Change, 12(3): 543–557.CrossRefGoogle Scholar
  3. Carpenter S R, Mooney H A, Agard J et al., 2009. Science for managing ecosystem services: Beyond the millennium ecosystem assessment. Proceedings of the National Academy of Sciences, 106(5): 1305–1312.CrossRefGoogle Scholar
  4. Chen C, Qian C, Deng A et al., 2012. Progressive and active adaptations of cropping system to climate change in Northeast China. European Journal of Agronomy, 38: 94–103.CrossRefGoogle Scholar
  5. Chen L, Wang J, Fu B et al., 2001. Land–use change in a small catchment of northern Loess Plateau, China. Agriculture, Ecosystems & Environment, 86(2): 163–172.CrossRefGoogle Scholar
  6. Costanza R, 1989. Model goodness of fit: A multiple resolution procedure. Ecological Modelling, 47(3/4): 199–215.CrossRefGoogle Scholar
  7. Costanza R, D’Arge R, de Groot R et al., 1997. The value of the world’s ecosystem services and natural capital. Nature, 387(6630): 253–260.CrossRefGoogle Scholar
  8. Costanza R, de Groot R, Sutton P et al., 2014. Changes in the global value of ecosystem services. Global Environmental Change, 26: 152–158.CrossRefGoogle Scholar
  9. David B L A C, 2007. Global scale climate–crop yield relationships and the impacts of recent warming. Environmental Research Letters, 2(1): 14002.CrossRefGoogle Scholar
  10. Duan P, Qin L, Wang Y et al., 2016. Spatial pattern characteristics of water footprint for maize production in Northeast China. Journal of the Science of Food and Agriculture, 96(2): 561–568.CrossRefGoogle Scholar
  11. Eitelberg D A, Vliet J, Verburg P H, 2015. A review of global potentially available cropland estimates and their consequences for model–based assessments. Global Change Biology, 21(3): 1236–1248.CrossRefGoogle Scholar
  12. Fu B, Zhang L, Xu Z et al., 2015. Ecosystem services in changing land use. Journal of Soils and Sediments, 15(4): 833–843.CrossRefGoogle Scholar
  13. Geoghegan J, Villar S C, Klepeis P et al., 2001. Modeling tropical deforestation in the southern Yucatán peninsular region: Comparing survey and satellite data. Agriculture, Ecosystems & Environment, 85(1–3): 25–46.CrossRefGoogle Scholar
  14. Jiang W, Chen Z, Lei X et al., 2016. Simulation of urban agglomeration ecosystem spatial distributions under different scenarios: A case study of the Changsha–Zhuzhou–Xiangtan urban agglomeration. Ecological Engineering, 88: 112–121.CrossRefGoogle Scholar
  15. Lambin E F, Meyfroidt P, 2011. Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences, 108(9): 3465–3472.CrossRefGoogle Scholar
  16. Letourneau A, Verburg P H, Stehfest E, 2012. A land–use systems approach to represent land–use dynamics at continental and global scales. Environmental Modelling & Software, 33: 61–79.CrossRefGoogle Scholar
  17. Li Z, Tang H, Yang P et al., 2012. Spatio–temporal responses of cropland phenophases to climate change in Northeast China. Journal of Geographical Sciences, 22(1): 29–45.CrossRefGoogle Scholar
  18. Liu J, Deng X, 2010. Progress of the research methodologies on the temporal and spatial process of LUCC. Chinese Science Bulletin, 55(14): 1354–1362.CrossRefGoogle Scholar
  19. Parry M, Arnell N, Hulme M et al., 1998. Adapting to the inevitable. Nature, 395: 741.CrossRefGoogle Scholar
  20. Roy P, Roy A, Joshi P et al., 2015. Development of decadal (1985–1995–2005) land use and land cover database for India. Remote Sensing, 7(3): 2401–2430.CrossRefGoogle Scholar
  21. Serneels S, Lambin E F, 2001. Proximate causes of land–use change in Narok District, Kenya: A spatial statistical model. Agriculture, Ecosystems & Environment, 85(1–3): 65–81.CrossRefGoogle Scholar
  22. Shearer A W, 2005. Approaching scenario–based studies: Three perceptions about the future and considerations for landscape planning. Environment and Planning B: Planning and Design, 32: 67–87.CrossRefGoogle Scholar
  23. Song W, Deng X, Yuan Y et al., 2015. Impacts of land–use change on valued ecosystem service in rapidly urbanized North China Plain. Ecological Modelling, 318: 245–253.CrossRefGoogle Scholar
  24. Stürck J, Schulp C J E, Verburg P H, 2015. Spatio–temporal dynamics of regulating ecosystem services in Europe: The role of past and future land use change. Applied Geography, 63: 121–135.CrossRefGoogle Scholar
  25. Tian L, 2015. Land use dynamics driven by rural industrialization and land finance in the peri–urban areas of China: The examples of Jiangyin and Shunde. Land Use Policy, 45: 117–127.CrossRefGoogle Scholar
  26. van Vliet J, Bregt A K, Hagen–Zanker A, 2011. Revisiting kappa to account for change in the accuracy assessment of land–use change models. Ecological Modelling, 222(8): 1367–1375.CrossRefGoogle Scholar
  27. van Vliet J, Hagen–Zanker A, Hurkens J et al., 2013. A fuzzy set approach to assess the predictive accuracy of land use simulations. Ecological Modelling, 261/262: 32–42.CrossRefGoogle Scholar
  28. Verburg P, Berkel D, Doorn A et al., 2010. Trajectories of land use change in Europe: A model–based exploration of rural futures. Landscape Ecology, 25(2): 217–232.CrossRefGoogle Scholar
  29. Verburg P H, Overmars K P, 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 Ecology, 24(9): 1167–1181.CrossRefGoogle Scholar
  30. Verburg P H, Rounsevell M D A, Veldkamp A, 2006. Scenario–based studies of future land use in Europe. Agriculture, Ecosystems & Environment, 114(1): 1–6.CrossRefGoogle Scholar
  31. Verburg P H, Soepboer W, Veldkamp A et al., 2002. Modeling the spatial dynamics of regional land use: The CLUE–S model. Environmental Management, 30(3): 391–405.CrossRefGoogle Scholar
  32. Wang M, Xiong Z, Yan X, 2015. Modeling the climatic effects of the land use/cover change in eastern China. Physics and Chemistry of the Earth, Parts A/B/C, 87/88: 97–107.Google Scholar
  33. Wang Z, Zhang B, Zhang S et al., 2006. Changes of land use and of ecosystem service values in Sanjiang Plain, Northeast China. Environmental Monitoring and Assessment, 112(1–3): 69–91.CrossRefGoogle Scholar
  34. Xia T, Wu W, Zhou Q et al., 2014. Spatio–temporal changes in the rice planting area and their relationship to climate change in Northeast China: A model–based analysis. Journal of Integrative Agriculture, 13(7): 1575–1585.CrossRefGoogle Scholar
  35. Xia T, Wu W, Zhou Q et al., 2016. Model–based analysis of spatio–temporal changes in land use in Northeast China. Journal of Geographical Sciences, 26(2): 171–187.CrossRefGoogle Scholar
  36. Xu G, Huang X, Zhong T et al., 2015. Assessment on the effect of city arable land protection under the implementation of China’s national general land use plan (2006–2020). Habitat International, 49: 466–473.CrossRefGoogle Scholar
  37. Ye L, Tang H, Zhu J et al., 2008. Spatial patterns and effects of soil organic carbon on grain productivity assessment in China. Soil Use and Management, 24(1): 80–91.CrossRefGoogle Scholar
  38. Ye L, Xiong W, Li Z et al., 2013. Climate change impact on China food security in 2050. Agronomy for Sustainable Development, 33(2): 363–374.CrossRefGoogle Scholar
  39. Zhang F, Tiyip T, Feng Z D et al., 2015. Spatio–temporal patterns of land use/cover changes over the past 20 years in the middle reaches of the Tarim River, Xinjiang, China. Land Degradation & Development, 26(3): 284–299.CrossRefGoogle Scholar
  40. Zhang X, Xiong Z, Zhang X et al., 2016. Using multi–model ensembles to improve the simulated effects of land use/cover change on temperature: A case study over Northeast China. Climate Dynamics, 46(3/4): 765–778.CrossRefGoogle Scholar
  41. Zhang Z, Wang X, Zhao X et al., 2014. A 2010 update of national land use/cover database of China at 1:100000 scale using medium spatial resolution satellite images. Remote Sensing of Environment, 149(149): 142–154.CrossRefGoogle Scholar

Copyright information

© Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Tian Xia
    • 1
    • 2
  • Wenbin Wu
    • 1
    Email author
  • Qingbo Zhou
    • 1
  • Wenxia Tan
    • 2
  • Peter H. Verburg
    • 3
  • Peng Yang
    • 1
  • Liming Ye
    • 4
    • 5
  1. 1.Key Laboratory of Agri-informatics, Ministry of Agriculture / Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina
  2. 2.Key Laboratory for Geographical Process Analysis & Simulation, Hubei Province / College of Urban & Environmental ScienceCentral China Normal UniversityWuhanChina
  3. 3.Institute for Environmental StudiesVU University AmsterdamAmsterdamThe Netherlands
  4. 4.CAAS-UGent Joint Laboratory of Global Change and Food Security / Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina
  5. 5.Department of Geology (WE13)Ghent UniversityGentBelgium

Personalised recommendations