Grassland Coverage Inter-Annual Variations and Its Coupling Relation with Hydrothermal Factors in China

Abstract

Global inventory modeling and mapping studies (GIMMS) and normalized difference vegetation index (NDVI), from 1982 to 2010, were used to simulate the grass coverage and analyze its spatial pattern and changes. The response of grass coverage to climatic variations at annual and monthly time scales was analyzed (during the 29 years, the nationwide annual temperature increased with a mean rate of 0.04 °C/year and precipitation decreased with a mean rate of −0.39 mm/year; however, in northwest China, precipitation increased). Grass coverage distribution had increased from northwest to southeast across China. During 1982–2010, the mean nationwide grass coverage was 34%, but exhibited apparent spatial heterogeneity being the highest (61.4%) in slope grasslands and the lowest (17.1%) in desert grasslands. There was a slight increase in the grass coverage over the study period with a rate of 0.17% per year. Regionally, the largest increase of grass coverage was observed in northwest China and Tibetan Plateau. Increase in slope grasslands coverage was as high as 0.27% per year, while in the plain grasslands and meadows, the grass coverage increase was the lowest (being 0.11% per year and 0.1% per year, respectively). Across China, the grass coverage with extremely significant increase (P < 0.01) and significant increase (P < 0.05) accounted for 46.03% and 11% of the total grassland area, respectively, while those with extremely significant and significant decrease accounted for only 4.1% and 3.24%, respectively. At the annual time scale, there are no significant correlations between grass coverage and annual mean temperature and precipitation for the total grassland area. However, the grass coverage was somewhat 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 more 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 more affected by seasonal fluctuations of hydrothermal conditions. Additionally, there is one-month time-lag effect between grass coverage and climate factors for each grassland types, and the correlations are the highest between the current months’ grass coverage and the former one month’s temperature and precipitation.