Acta Geographica Sinica ›› 2014, Vol. 69 ›› Issue (1): 15-30.doi: 10.11821/dlxb201401002

Previous Articles     Next Articles

Spatial-temporal dynamics of grassland coverage and its response to climate change in China during 1982-2010

ZHOU Wei1, GANG Chengcheng1, LI Jianlong1, ZHANG Chaobin1, MU Shaojie1, SUN Zhenguo2   

  1. 1. School of Life Science, Nanjing University, Nanjing 210093, China;
    2. College of Animal Sciences, Nanjing Agricultural University, Nanjing 210095, China
  • Received:2013-09-10 Revised:2013-10-20 Online:2014-01-20 Published:2014-01-20
  • Contact: 李建龙(1962-),教授,
  • Supported by:
    The National Basic Research Program of China, No.2010CB950702; APN Project ARCP 2013-16NMY-Li; National Natural Science Foundation of China, No.40871012; No.J1103512; No.J1210026; National High Technology Research and Development Program of China, No.2007AA10Z231; The Public Sector Linkages Program supported by Aus AID, No.64828

Abstract: Global climate warming has led to significant vegetation changes in the past half century. Grassland in China, most of which is sensitive to climatic change and ecologically fragile region, undergoes a process of prominent warming and drying. It is necessary to investigate the response of grassland to the climatic variations (temperature and precipitation) for a better understanding of the accumulated consequence of climate change. Vegetation coverage, as an important indicator for evaluating grassland ecosystem condition, is used to monitor grassland change. GIMMS NDVI from 1982 to 2006 and MODIS NDVI from 2001 to 2010 were adopted and integrated in this study to extract the time series of grassland coverage, and to analyze its spatial pattern and changes. The response of grassland coverage to climatic variations at annual and monthly time scales was analyzed using temperature and precipitation time series at Chinese meteorological stations from 1982 to 2010. During the 29 years, the national annual surface air temperature increased with an annual rate of 0.04℃, while national precipitation decreased with an annual rate of -0.39 mm with the exception of Northwest China. Grassland coverage distribution increased from northwest to southeast across China. During 1982-2010, the mean national grassland coverage was 34% but exhibited apparent spatial heterogeneity being highest (61.4%) in slope grasslands and lowest (17.1%) in desert areas. There was a slight increase of the grassland coverage over the study period with an annual rate of 0.17%. Regionally, the largest increase in the grassland area was observed in Northwest China and Tibetan Plateau. The increase in slope grassland areas was as high as 0.27% per year, while in the plain grassland and meadow, the grassland coverage increase was the lowest (being 0.11% per year and 0.1% per year, respectively). Across China, the grass coverage with extremely significant (P<0.01) and significant (P<0.05) area increases accounted for 46.03% and 11% of the total grassland area, respectively, while those with extremely significant and significant decrease were only 4.1% and 3.24% , respectively. At the annual time scale, there were no significant correlations between grassland coverage and annual temperature and precipitation for the total grassland area. However, the grass coverage was mainly affected by temperature in alpine and sub-alpine grassland, alpine and sub-alpine meadow, slope grassland and meadow, while grass coverage in desert grassland and plain grassland was mainly affected by precipitation. At the monthly time-scale, there are significant correlations between grass coverage with both temperature and precipitation, indicating that the grass coverage is mainly affected by seasonal fluctuations of the hydrothermal factors. Additionally, there is obvious time lag-effect between grass growth and climate factors for each grassland type: the highest correlations are observed between the grass coverage and temperature and precipitation of the preceding month.

Key words: grassland coverage, temperature, precipitation, spatial-temporal dynamics, correlation, time lag effect