Grassland Phenology in Different Eco-Geographic Regions over the Tibetan Plateau
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Grassland Phenology in Different Eco-Geographic Regions over the Tibetan Plateau

Authors: Jiahua Zhang, Qing Chang, Fengmei Yao

Abstract:

Studying on the response of vegetation phenology to climate change at different temporal and spatial scales is important for understanding and predicting future terrestrial ecosystem dynamics and the adaptation of ecosystems to global change. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset and climate data were used to analyze the dynamics of grassland phenology as well as their correlation with climatic factors in different eco-geographic regions and elevation units across the Tibetan Plateau. The results showed that during 2003–2012, the start of the grassland greening season (SOS) appeared later while the end of the growing season (EOS) appeared earlier following the plateau’s precipitation and heat gradients from southeast to northwest. The multi-year mean value of SOS showed differences between various eco-geographic regions and was significantly impacted by average elevation and regional average precipitation during spring. Regional mean differences for EOS were mainly regulated by mean temperature during autumn. Changes in trends of SOS in the central and eastern eco-geographic regions were coupled to the mean temperature during spring, advancing by about 7d/°C. However, in the two southwestern eco-geographic regions, SOS was delayed significantly due to the impact of spring precipitation. The results also showed that the SOS occurred later with increasing elevation, as expected, with a delay rate of 0.66 d/100m. For 2003–2012, SOS showed an advancing trend in low-elevation areas, but a delayed trend in high-elevation areas, while EOS was delayed in low-elevation areas, but advanced in high-elevation areas. Grassland SOS and EOS changes may be influenced by a variety of other environmental factors in each eco-geographic region.

Keywords: Grassland, phenology, MODIS, eco-geographic regions, elevation, climatic factors, Tibetan Plateau.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1108364

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References:


[1] H. Lieth, Phenology and seasonality modeling. Springer Springer-Verlag, New York, 1974.
[2] F. M. Chmielewski, T. Rötzer, “Response of tree phenology to climate change across Europe,” Agricultural and Forest Meteorology, vol.108, pp., 101-112, Mar. 2001.
[3] J. Peñuelas, and I. Filella, “Responses to a warming world,” Science,vol. 294, pp.793-795, Oct. 2001.
[4] R. B. Myneni, C. Keeling, C. Tucker, G. Asrar, and R. Nemani, “Increased plant growth in the northern high latitudes from 1981 to 1991,” Nature, vol. 386, pp. 698-702, April 1997.
[5] X. Zhang, M. A .Friedl, C. B. Schaaf, A. H. Strahler, J. C. Hodges, F. Gao, B. C. Reed, and A. Huete, “Monitoring vegetation phenology using MODIS,” Remote sensing of Environment, vol. 84, pp. 471-475, Mar. 2003.
[6] Y. Julien, and J. Sobrino, “Global land surface phenology trends from GIMMS database,” International Journal of Remote Sensing, vol. 30, pp. 3495-3513, July 2009.
[7] S.J. Jeong, C. H. Ho, H.J. Gim, and M.E. Brown, “Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008,” Global Change Biology, vol. 17, pp. 2385-2399, July 2011.
[8] S. Piao, J. Fang, L. Zhou, P. Ciais, and B. Zhu, “Variations in satellite-derived phenology in China's temperate vegetation,” Global Change Biology, vol.12, pp. 672-685, March 2006.
[9] H. Yu, E. Luedeling, and J. Xu, “Winter and spring warming result in delayed spring phenology on the Tibetan Plateau,” Proceedings of the National Academy of Sciences, vol. 107, pp. 22151-22156, May 2010.
[10] L. Liu, L. Liu, and Y. Hu, “Response of spring phenology to climate change across Tibetan Plateau,” In: Remote Sensing, Environment and Transportation Engineering (RSETE), 2nd International Conference on, IEEE, 2012, pp. 1-4.
[11] M. Ding, Y. Zhang, X. Sun, L. Liu, Z. Wang, and W. Bai, “Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009,” Chinese Science Bulletin, vol.58, pp. 396-405, Jan. 2013.
[12] G. Zhang, Y. Zhang, J. Dong, and X. Xiao, “Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011,” Proceedings of the National Academy of Sciences, vol. 110, pp. 4309-4314, Mar. 2013.
[13] M. Shen, “Spring phenology was not consistently related to winter warming on the Tibetan Plateau,” Proceedings of the National Academy of Sciences, vol. 108, E91-E92, May 2011.
[14] M. Shen, Z. Sun, S. Wang, G. Zhang, W. Kong, A. Chen, and S. Piao, “No evidence of continuously advanced green-up dates in the Tibetan Plateau over the last decade,” Proceedings of the National Academy of Sciences, vol.110, E2329-E2329, June 2013.
[15] Z. Jin, Q. Zhuang, J. S. He, T. Luo, and Y. Shi, “Phenology shift from 1989 to 2008 on the Tibetan Plateau: an analysis with a process-based soil physical model and remote sensing data,” Climatic Change, vol.117, DOI 10.1007/s10584-013-0722-7, Apr. 2013.
[16] C. Song, S. You, L. Ke,G. Liu, and X. Zhong, “Spatio-temporal variation of vegetation phenology in the Northern Tibetan Plateau as detected by MODIS remote sensing,” Chinese Journal of Plant Ecology, vol. 35, pp.853-863, Aug. 2011.
[17] S. Wu, Q. Yang, and D. Zheng, “Delineation of eco-geographic regional system of China,” Journal of Geographical Sciences, vol. 13, pp. 309-315, July 2003.
[18] J. Chen, P. Jönsson, M. Tamura, Z. Gu, B. Matsushita, and L. Eklundh, “A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter,” Remote Sensing of Environment, vol.91, pp. 332-344, June 2004.
[19] L. Zhou, C.J. Tucker, R.K. Kaufmann, D. Slayback, N.V. Shabanov, and R.B. Myneni, “Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999,”Journal of Geophysical Research: Atmospheres (1984–2012), vol. 106, pp. 20069-20083, Sep. 2001.
[20] S. Piao, J. Fang, L. Zhou, Q. Guo, M. Henderson, W. Ji, Y. Li, and S. Tao, “Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999”. Journal of Geophysical Research: Atmospheres, vol. 108, doi: 10.1029/2002JD 002848, July 2003.
[21] J. Bian, A. Li, M. Song, L. Ma, and J. Jiang, “Reconstruction of NDVI time-series datasets of MODIS based on Savitzky-Golay filter.” Journal of Remote Sensing, vol. 14, pp. 725-741, Apr. 2010.
[22] P. Jönsson and L. Eklundh, “TIMESAT—A program for analyzing time-series of satellite sensor data,” Computers & Geosciences, vol. 30, pp. 833-845, May 2004.
[23] B. Zhang, J. Cao, Y. Bai, X. Zhou, Z. Ning, S. Yang, and L. Hu, “Effects of rainfall amount and frequency on vegetation growth in a Tibetan alpine meadow,” Climatic Change, vol. 118, pp. 197-212, May 2013.
[24] D.T. Tingey, D.L. Phillips, and M.G. Johnson, “Elevated CO2 and conifer roots: effects on growth, life span and turnover.” New Phytologist, vol. 147, pp. 87-103, March 2000.
[25] J.H. Zhang, Eco-environmental and Meteorological Disaster Remote Sensing in Northern Tibet Region of China, Beijing: Meteorological Press, June 2007.