Spatial and temporal effects of drought on Chinese vegetation under different coverage levels

Sci Total Environ. 2020 May 10:716:137166. doi: 10.1016/j.scitotenv.2020.137166. Epub 2020 Feb 6.

Abstract

Land surface vegetation dynamics are strongly affected by drought. Thus, understanding the responses of vegetation to drought can inform measures to increase biome stability. In this study, the normalized difference vegetation index (NDVI) and the Palmer drought severity index (PDSI) were utilized to investigate the relationship between vegetation activity and drought across different drought regions and ecological community types from 1982 to 2015. Our results showed that the highest correlation between monthly NDVI and PDSI at different timescales (1-36 months) indicated the degree of drought impact on vegetation. There were diverse responses of vegetation to drought according to the drought features and climatic environment. The northern grassland, cropland, and desert ecosystems were strongly impacted by drought. These vegetation ecosystems had a low sensitivity to drought in southern China. Drought had the strongest impact on grassland in summer, which is the high frequency drought season. The most susceptible ecosystem types to drought were those with homogenous vegetation, especially under long-term drought conditions (such as the Inner Mongolia Plateau dominated by grassland). Under global warming, drought with high-temperature characteristics is expected to become more frequent and severe. Such drought could threaten the survival of plateau grassland, arid plain grassland, and rain-fed cropland, as high temperatures accelerate evaporation, leading to water deficit. However, moist forests showed little threat under normal drought. We suggest that future research should focus on vegetation activity in northern and southwestern China, where the vegetation shows the greatest sensitivity to drought.

Keywords: Climatic characteristics; Correlation analysis; MODIS; Meteorological; Vegetation activity.

MeSH terms

  • China
  • Droughts*
  • Forests
  • Rain