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Chinese Journal of Applied Ecology ›› 2019, Vol. 30 ›› Issue (12): 4099-4107.doi: 10.13287/j.1001-9332.201912.015

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Grassland vegetation phenology change and its response to climate changes in North China

QIN Ge-xia1, WU Jing1*, LI Chun-bin1, QIN An-ning2, NI Lu3, YAO Xiao-qiang1   

  1. 1College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China;
    2School of Mechanical Engineering, Suzhou University of Science and Technology, Suzhou 215000, Jiangsu, China;
    3Jinan City Sunshine 100 Middle School, Jinan 250022, China
  • Received:2019-03-22 Online:2019-12-15 Published:2019-12-15
  • Contact: * E-mail: wujing@gsau.edu.cn
  • Supported by:
    This work was supported by the Science and Technology Innovation Fund-Discipline Construction Fund Project of Gansu Agricultural University (GAU-XKJS-2018-207) and the National Natural Science Foundation of China (31760693)

Abstract: Understanding phenological change of grasslands has scientific significance to reveal their responses to global climate change. Based on the data of GIMMS NDVI 3g, climate data from 1983 to 2015 and digital elevation model (DEM), dynamic threshold method was used to extract the phenological information of northern grassland [the start of growth season (SOS), the end of growth season (EOS), and the length of growth season (LOS)]. We analyzed the temporal and spatial variation of phenology of grassland vegetation and the influence of climate on LOS. The results showed that 88.9% of SOS occurred from late March to late May (90-150 d), and 68.1% of pixels were advanced with a rate of -1.5-0 d·(32 a)-1. 79.7% of EOS occurred from early October to late October (270-300 d), with a delay rate of 0-1.5 d·(32 a)-1, accounting for 70.3% of the pixel number. LOS lasted for 100-140 days and became longer (73.7%), with a rate of 0-1.5 d·(32 a)-1. LOS was significantly positively correlated with temperature (R=0.628) and weakly negatively correlated with precipitation (R=-0.091). There was a significant spatial variation. The 2000 m line above sea level was recognized as the demarcation line. LOS had a weak positive correlation with altitude under 2000 m (R=0.235) and a significant negative correlation with altitude above 2000 m (R=-0.861). Above 3000 m altitude, LOS decreased by about 10 d for every 1000 m elevation.