Abstract
The method for surface modelling of land cover scenarios (SMLCS) has been improved to simulate the scenarios of land cover in Eurasia. On the basis of the observation monthly climatic data observed from 2127 weather stations in Eurasia during 1981–2010, the climatic scenarios data of RCP26, RCP45 and RCP85 scenarios released by CMIP5, and the land cover current data of Eurasia in 2010, the land cover scenarios of Eurasia were respectively simulated. The results show that most land cover types would generally have similar changing trends in the future, but with some difference in different periods under the three scenarios of RCP26, RCP45 and RCP85. Deciduous needleleaf forest, mixed forest, shrub land, wetlands and snow and ice would generally decrease in Eurasia during 2010–2100. Snow and ice would have the fastest decreasing rate that would decrease by 37.42% on average. Shrub land would have the slowest decreasing rate that would decrease by 5.65% on average. Water bodies would have the fastest increasing rate that would increase by 28.78% on average. Barren or sparsely vegetated land would have the slowest increasing rate that would increase by 0.76%. Moreover, the simulated results show that climate change would directly impact on land cover change in Eurasia.
Similar content being viewed by others
References
Adams R M, Fleming R A, Chang C C et al., 1995. A reassessment of the economic effects of global climate change on U.S. agriculture. Climatic Change, 30(2): 147–167.
Alcamo J, Kreileman G J J, Krol M S et al., 1994. Modeling the global society-biosphere-climate system: Part 1: Model description and testing. Water Air & Soil Pollution, 76(1/2): 1–35.
Bai W Q, Zhang Y M, Yan J Z, 2005. Simulation of land use dynamics in the upper reaches of the Dadu River. Geographical Research, 24(2): 206–212. (in Chinese)
Clarke K, Hoppen S, Gaydos L, 1997. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment & Planning B Planning & Design, 24(2): 247–261.
Fan Z M, Li J Y, Yue T X, 2013. Land-cover changes of biome transition zones in Loess Plateau of China. Ecological Modelling, 252: 129–140.
Fan Z M, Li J Y, Yue T X et al., 2015. Scenarios of land cover in karst area of southwestern China. Environmental Earth Sciences, 74(8): 6407–6420.
Fan Z M, Yue T X, Liu J Y et al., 2005. Spatial and temporal distribution of land cover scenarios in China. Acta Geographica Sinica, 60(6): 941–952. (in Chinese)
Fan Z M, Zhang X, Jing Li et al., 2013. Land-cover changes of national nature reserves in China. Journal of Geographical Sciences, 23(2): 258–270.
Fischer G, Ermoliev Y M, Keyzer M A et al., 1996. Simulating the socio-economic and biogeographical driving forces of land-use and land cover change: The IIASA land-use change model. IIASA Working Paper, WP-96-010.
Gao Z Q, Yi W, 2012. Land use change in China and analysis of its driving forces using CLUE-S and Dinamica EGO model. Chinese Society of Agricultural Engineering, 28(16): 208–216. (in Chinese)
Gregorio A D, Jansen L J M, 2001. Land cover classification system (LCCS): Classification concepts and user manual for software version 1.0. FAO.
Guo Y F, Yu X B, Jiang L G et al., 2012. Scenarios analysis of land use change based on CLUE model in Jiangxi Province by 2030. Geographical Research, 31(6): 1016–1028. (in Chinese)
He C Y, Chen J, Shi P J et al., 2002. Study on the spatial dynamic city model based on CA (Cellular Automata) model. Progress in Geography, 21(2): 188–119. (in Chinese)
Holdridge L R, 1947. Determination of world plant formations from simple climate data. Science, 105(2727): 367.
Holdridge L R, 1967. Life Zone Ecology. Libros Y Materiales Educativos.
Holdridge L R, Grenke W C, Hatheway W H et al., 1971. Forest Environments in Tropical Life Zones. Oxford: Pergamon Press.
Ichinose T, Otsubo K, 2003. Temporal structure of land use change in Asia. Journal of Global Environment Engineering, 9: 41–51.
Lauenroth W K, Urban D L, Coffin D P et al., 1993. Modeling vegetation structure-ecosystem process interactions across sites and ecosystems. Ecological Modelling, 67(1): 49–80.
Li J, Fan Z M, Yue T X, 2014. Spatio-temporal simulation of land cover scenarios in southwestern of China. Acta Ecologica Sinica, 34(12): 3266–3275. (in Chinese)
Li X, Yu L, Sohl T et al., 2016. A cellular automata downscaling based 1 km global land use datasets (2010–2100). Science Bulletin, 61(21): 1651–1661.
Turner B L I, Skole D L, Sanderson S et al., 1995. Land-use and land-cover change, Science/research plan. Global Change Report, 43: 669–679.
Veldkamp A, Fresco L O, 1996. CLUE: A conceptual model to study the conversion of land use and its effects. Ecological Modelling, 85(2): 253–270.
Verburg P H, 2000. Exploring the spatial and temporal dynamics of land use with special reference to China. Wageningen University.
Verburg P H, Schot P P, Dijst M J et al., 2004. Land use change modeling: Current practice and research priorities. GeoJournal, 61(4): 309–324.
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.
Verburg P H, Veldkamp A, Fresco L O, 1999. Simulation of changes in the spatial pattern of land use in China. Applied Geography, 19(3): 211–233.
Vuuren D P V, Edmonds J, Kainuma M et al., 2011. The representative concentration pathways: An overview. Climatic Change, 109(1/2): 5.
Wu F, 2002. Calibration of stochastic cellular automata: The application to rural-urban land conversions. International Journal of Geographical Information Systems, 16(8): 795–818.
Wu F, Webster C J, 1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment & Planning B Planning & Design, 25(1): 103–126.
Yue T X, 2010. Surface Modeling: High Accuracy and High Speed Methods. Boca Raton: CRC Press.
Yue T, Fan Z, Chen C et al., 2011. Surface modelling of global terrestrial ecosystems under three climate change scenarios. Ecological Modelling, 222(14): 2342–2361.
Yue T X, Fan Z M, Liu J Y, 2005. Changes of major terrestrial ecosystems in China since 1960. Global and Planetary Change, 48: 287–302.
Yue T X, Fan Z M, Liu J Y et al., 2006. Scenarios of major terrestrial ecosystems in China. Ecological Modelling, 199: 363–376.
Yue T X, Fan Z M, Liu J Y, 2007. Scenarios of land cover in China. Global and Planetary Change, 55(4): 317–342.
Yue T X, Wang Y A, Liu J Y et al., 2005. Surface modelling of human population distribution in China. Ecological Modelling, 181(4): 461–478.
Yue T X, Zhao N, Douglas Ramsey R et al., 2013. Climate change trend in China, with improved accuracy. Climatic Change, 120: 137–151.
Yue T X, Zhao N, Fan Z M et al., 2016. CMIP5 downscaling and its uncertainty in China. Global and Planetary Change, 146: 30–37.
Yue T X, Zhao N, Yang H et al., 2013. A multi-grid method of high accuracy surface modeling and its validation. Transaction in GIS, 17(6): 943–952.
Zhang R, Huang C Q, Zhan X et al., 2016. Development and validation of the global surface type data product from S-NPP VIIRS. Remote Sensing Letters, 7: 1, 51–60.
Zhang X S, 1993. A vegetation-climate classification system for global change studies in China. Quaternary Sciences, 13(2): 157–169. (in Chinese)
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation: National Key R&D Program of China, No.2017YFA0603702, No.2018YFC0507200; National Natural Science Foundation of China, No.41421001, No.41271406; Innovation Project of LREIS, No.O88RA600YA
Author: Fan Zemeng, PhD, specialized in ecological modelling and system simulation.
Rights and permissions
About this article
Cite this article
Fan, Z., Bai, R. & Yue, T. Scenarios of land cover in Eurasia under climate change. J. Geogr. Sci. 30, 3–17 (2020). https://doi.org/10.1007/s11442-020-1711-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11442-020-1711-1