Grassland Phenology in Different Eco-Geographic Regions over the Tibetan Plateau
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.
[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.
[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.
@article{"International Journal of Earth, Energy and Environmental Sciences:70715", author = "Jiahua Zhang and Qing Chang and Fengmei Yao", title = "Grassland Phenology in Different Eco-Geographic Regions over the Tibetan Plateau", 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.", volume = "9", number = "11", pages = "1293-6", }
