Advertisement

Journal of Arid Land

, Volume 10, Issue 6, pp 850–863 | Cite as

Seasonal differences in climatic controls of vegetation growth in the Beijing–Tianjin Sand Source Region of China

  • Lishan ShanEmail author
  • Xiang Yu
  • Lingxiao Sun
  • Bin He
  • Haiyan Wang
  • Tingting Xie
Article
  • 44 Downloads

Abstract

Launched in 2002, the Beiing–Tianjin Sand Source Control Project (BTSSCP) is an ecological restoration project intended to prevent desertification in China. Evidence from multiple sources has confirmed increases in vegetation growth in the BTSSCP region since the initiation of this project. Precipitation and essential climate variable-soil moisture (ECV-SM) conditions are typically considered to be the main drivers of vegetation growth in this region. Although many studies have investigated the inter-annual variations of vegetation growth, few concerns have been focused on the annual and seasonal variations of vegetation growth and their climatic drivers, which are crucial for understanding the relationships among the climate, vegetation, and human activities at the regional scale. Based on the normalized difference vegetation index (NDVI) derived from MODIS and the corresponding climatic data, we explored the responses of vegetation growth to climatic factors at annual and seasonal scales in the BTSSCP region during the period 2000–2014. Over the study region as a whole, NDVI generally increased from 2000 to 2014, at a rate of 0.002/a. Vegetation growth is stimulated mainly by the elevated temperature in spring, whereas precipitation is the leading driver of summer greening. In autumn, positive effects of both temperature and precipitation on vegetation growth were observed. The warming in spring promotes vegetation growth but reduces ECV-SM. Summer greening has a strong cooling effect on land surface temperature. These results indicate that the ecological and environmental consequences of ecological restoration projects should be comprehensively evaluated.

Keywords

vegetation growth climatic drivers seasonal variation ecological engineering interaction Beiing–Tianjin Sand Source Controlling Project (BTSSCP) NDVI 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (31560135, 41361100), the Discipline Construction Fund Project of Gansu Agricultural University (GAU-XKJS-2018-104, GAU-XKJS-2018-108) and the Gansu Science and Technology Support Program (1604FKCA088). The authors are very grateful to the anonymous reviewers and editors for their critical review and comments which helped to improve and clarify the manuscript.

References

  1. Bao A Y, Bao G, Guo L, et al. 2009. Evaluation on vegetation net primary productivity using MODIS data in Inner Mongolia. Proceedings Volume 7490, PIAGENG 2009: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 749006. [2009-07-10]. International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), Zhangjiajie, China.CrossRefGoogle Scholar
  2. Batra N, Islam S, Venturini V, et al. 2006. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains. Remote Sensing of Environment, 103(1): 1–15.CrossRefGoogle Scholar
  3. Beguería S, Vicenteserrano S M, Angulomartínez M. 2010. A multiscalar global drought dataset: the SPEIbase: a new gridded product for the analysis of drought variability and impacts. Bulletin of the American Meteorological Society, 91(10): 1351–1356.CrossRefGoogle Scholar
  4. Beguería S, Vicenteserrano S M, Reig F, et al. 2014. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology, 34(10): 3001–3023.CrossRefGoogle Scholar
  5. Cao S X. 2011. Impact of China’s large-scale ecological restoration program on the environment and society in arid and semiarid areas of China: achievements, problems, synthesis, and applications. Critical Reviews in Environmental Science and Technology, 41(4): 317–335.CrossRefGoogle Scholar
  6. Cao S X, Chen L, Shankman D, et al. 2011. Excessive reliance on afforestation in China’s arid and semi-arid regions: Lessons in ecological restoration. Earth-Science Reviews, 104(4): 240–245.CrossRefGoogle Scholar
  7. Dorigo W, de Jeu R, Chung D, et al. 2012. Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture. Geophysical Research Letter, 39(18): 18405.CrossRefGoogle Scholar
  8. Feng X M, Fu B J, Piao S L, et al. 2016. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nature Climate Change, 6(11): 1019–1022.CrossRefGoogle Scholar
  9. Forzieri G, Alkama R, Miralles D G, et al. 2017. Satellites reveal contrasting responses of regional climate to the widespread greening of Earth. Science, 356(6343): 1180–1184.CrossRefGoogle Scholar
  10. Ge Q S, Wang H J, Rutishauser T, et al. 2015. Phenological response to climate change in China: a meta-analysis. Global Change Biology, 21(1): 265–274.CrossRefGoogle Scholar
  11. Gong Z, Kawamura K, Ishikawa N, et al. 2015. MODIS normalized difference vegetation index (NDVI) and vegetation phenology dynamics in the Inner Mongolia grassland. Solid Earth, 6(3): 1185–1194.CrossRefGoogle Scholar
  12. He B, Chen A F, Jiang W G, et al. 2017. The response of vegetation growth to shifts in trend of temperature in China. Journal of Geographical Sciences, 27(7): 801–816.CrossRefGoogle Scholar
  13. Hu Y L, Zeng D H, Fan Z P, et al. 2008. Changes in ecosystem carbon stocks following grassland afforestation of semiarid sandy soil in the southeastern Keerqin Sandy Lands, China. Journal of Arid Environments, 72(12): 2193–2200.CrossRefGoogle Scholar
  14. Hutchinson M F. 1995. Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems, 9(4): 385–403.CrossRefGoogle Scholar
  15. Jiang B, Liang S L, Yuan W P. 2015. Observational evidence for impacts of vegetation change on local surface climate over northern China using the Granger causality test. Journal of Geophysical Research Biogeosciences, 120(1): 1–12.CrossRefGoogle Scholar
  16. Li X S, Wang H Y, Wang J Y, et al. 2015. Land degradation dynamic in the first decade of twenty-first century in the Beijing–Tianjin dust and sandstorm source region. Environmental Earth Sciences, 74(5): 4317–4325.CrossRefGoogle Scholar
  17. Li Y, Zhao M S, Motesharrei S, et al. 2015. Local cooling and warming effects of forests based on satellite observations. Nature Communications, 6: 6603.CrossRefGoogle Scholar
  18. Liu J H, Wu J J, Wu Z T, et al. 2013. Response of NDVI dynamics to precipitation in the Beijing–Tianjin sandstorm source region. International Journal of Remote Sensing, 34(15): 5331–5350.CrossRefGoogle Scholar
  19. Liu J Y, Kuang W H, Zhang Z X, et al. 2014. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. Journal of Geographical Sciences, 24(2): 195–210.CrossRefGoogle Scholar
  20. Liu X P, Zhang W J, Cao J S, et al. 2013. Carbon storages in plantation ecosystems in sand source areas of north Beijing, China. PloS ONE, 8(12): e82208.CrossRefGoogle Scholar
  21. Liu X R, Dong Y S, Ren J Q, et al. 2010. Drivers of soil net nitrogen mineralization in the temperate grasslands in Inner Mongolia, China. Nutrient Cycling in Agroecosystems, 87(1): 59–69.CrossRefGoogle Scholar
  22. Liu Y Y, Parinussa R M, Dorigo W A, et al. 2011. Developing an improved soil moisture dataset by blending passive and active microwave satellite–based retrievals. Hydrology and Earth System Sciences, 15(2): 425–436.CrossRefGoogle Scholar
  23. Ma T, Zhou C H. 2012. Climate-associated changes in spring plant phenology in China. International Journal of Biometeorology, 56(2): 269–275.CrossRefGoogle Scholar
  24. Miao L J, Luan Y B, Luo X Z, et al. 2013. Analysis of the phenology in the Mongolian Plateau by inter-comparison of global vegetation datasets. Remote Sensing, 5(10): 5193–5208.CrossRefGoogle Scholar
  25. Mitchell J M, Dzerdzeevskü B, Flohn H, et al. 1966. Climatic change. WMO Technical Note 79 (WMO-No. 195/TP. 100). Geneva: World Meteorological Organization.Google Scholar
  26. Mohammat A, Wang X H, Xu X T, et al. 2013. Drought and spring cooling induced recent decrease in vegetation growth in Inner Asia. Agricultural and Forest Meteorology, 178–179: 21–30.CrossRefGoogle Scholar
  27. Mu Q Z, Zhao M S, Running S W. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8): 1781–1800.CrossRefGoogle Scholar
  28. Peng S S, Chen A P, Xu L, et al. 2011. Recent change of vegetation growth trend in China. Environmental Research Letters, 6(4): 044027.CrossRefGoogle Scholar
  29. Peng S S, Piao S L, Zeng Z Z, et al. 2014. Afforestation in China cools local land surface temperature. Proceedings of the National Academy of Sciences of the United States of America, 111(8): 2915–2919.CrossRefGoogle Scholar
  30. Qin Y B, Xin Z B, Yi Y, et al. 2012. Spatiotemporal variation of sandstorm and its response to vegetation restoration in Beijing–Tianjin sandstorm source area. Transactions of the Chinese Society of Agricultural Engineering, 28: 196–204. (in Chinese)Google Scholar
  31. Rishmawi K, Prince S D, Xue Y K. 2016. Vegetation responses to climate variability in the northern arid to sub-humid zones of sub-Saharan Africa. Remote Sensing, 8(11): 910, doi: 10.3390/rs8110910.CrossRefGoogle Scholar
  32. Shan N, Shi Z J, Yang X H, et al. 2015. Spatiotemporal trends of reference evapotranspiration and its driving factors in the Beijing–Tianjin Sand Source Control Project Region, China. Agricultural and Forest Meteorology, 200(15): 322–333.CrossRefGoogle Scholar
  33. Shen M G, Piao S L, Jeong S J, et al. 2015. Evaporative cooling over the Tibetan Plateau induced by vegetation growth. Proceedings of the National Academy of Sciences of the United States of America, 112(30): 9299–9304.CrossRefGoogle Scholar
  34. Swenson S, Wahr J. 2006. Post-processing removal of correlated errors in GRACE data. Geophysical Research Letters, 33(8): L08402.Google Scholar
  35. Tang Q H, Zhang X J, Tang Y. 2013. Anthropogenic impacts on mass change in North China. Geophysical Research Letters, 40(15): 3924–3928.CrossRefGoogle Scholar
  36. Tian H J, Cao C X, Chen W, et al. 2015. Response of vegetation activity dynamic to climatic change and ecological restoration programs in Inner Mongolia from 2000 to 2012. Ecological Engineering, 82(4): 276–289.CrossRefGoogle Scholar
  37. Velpuri N M, Senay G B, Singh R K, et al. 2013. A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: Using point and gridded FLUXNET and water balance ET. Remote Sensing of Environment, 139(4): 35–49.CrossRefGoogle Scholar
  38. Vicenteserrano S M, Beguería S, Lópezmoreno J I. 2010. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate, 23(7): 1696–1718.CrossRefGoogle Scholar
  39. Wolf S, Keenan T F, Fisher J B, et al. 2016. Warm spring reduced carbon cycle impact of the 2012 US summer drought. Proceedings of the National Academy of Science of the United States of America, 113(21): 5880–5885.CrossRefGoogle Scholar
  40. Wu J J, Zhao L, Zheng Y T, et al. 2012. Regional differences in the relationship between climatic factors, vegetation, land surface conditions, and dust weather in China’s Beijing–Tianjin Sand Source Region. Natural Hazards, 62(1): 31–44.CrossRefGoogle Scholar
  41. Wu Z T, Wu J J, Liu J H, et al. 2013. Increasing terrestrial vegetation activity of ecological restoration program in the Beijing–Tianjin Sand Source Region of China. Ecological Engineering, 52(52): 37–50.CrossRefGoogle Scholar
  42. Wu Z T, Wu J J, He B, et al. 2014. Drought offset ecological restoration program-induced increase in vegetation activity in the Beijing–Tianjin Sand Source Region, China. Environmental Science & Technology, 48(20): 12108–12117.CrossRefGoogle Scholar
  43. Xu L, Myneni R B, Iii F S C, et al. 2013. Temperature and vegetation seasonality diminishment over northern lands. Nature Climate Change, 3(6): 581–586.CrossRefGoogle Scholar
  44. Yang Y T, Long D, Guan H D, et al. 2015. GRACE satellite observed hydrological controls on interannual and seasonal variability in surface greenness over mainland Australia. Journal of Geophysical Research Biogeosciences, 119(12): 2245–2260.CrossRefGoogle Scholar
  45. Yu F F, Price K P, Ellis J, et al. 2003. Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sensing of Environment, 87(1): 42–54.CrossRefGoogle Scholar
  46. Zeng X H, Zhang W J, Cao J S, et al. 2014. Changes in soil organic carbon, nitrogen, phosphorus, and bulk density after afforestation of the “Beijing–Tianjin Sandstorm Source Control” program in China. Catena, 118: 186–194.CrossRefGoogle Scholar
  47. Zhang G L, Dong J W, Xiao X M, et al. 2012. Effectiveness of ecological restoration projects in Horqin Sandy Land, China based on SPOT-VGT NDVI data. Ecological Engineering, 38(1): 20–29.CrossRefGoogle Scholar

Copyright information

© Xinjiang Institute of Ecology and Geography, the Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Lishan Shan
    • 1
    Email author
  • Xiang Yu
    • 2
  • Lingxiao Sun
    • 3
  • Bin He
    • 4
  • Haiyan Wang
    • 4
  • Tingting Xie
    • 1
  1. 1.College of ForestryGansu Agricultural UniversityLanzhouChina
  2. 2.Chinese Academy of ForestryBeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina

Personalised recommendations