Abstract
The grasslands in arid and semi-arid regions rely heavily on the use of rain, thus, improving rain use efficiency (RUE) is essential for securing sustainable development of grassland ecosystems in these areas with limited rainfall. In this study, the spatial and temporal variabilities of RUE for grassland ecosystems over Northwestern China during 1982–2013 were analyzed using the normalized difference vegetation index (NDVI) and precipitation data. Results showed that: (1) Although grassland area has decreased gradually over the past 30 years, the NDVI in most areas showed that the vegetation was gradually restored; (2) The trends of RUE increased in the east of Northwestern China and decreased in the west of Northwestern China. However, the trends of RUE for the high-coverage grasslands (vs. low-coverage grassland) increased (decreased) significantly over the past 30 years. (3) The RUE for the grasslands was positively correlated with air temperature, while it was negatively correlated with the change of annual mean precipitation in northwestern China. Moreover, the obvious RUE increasing trends were found in the vegetation restoration areas, while the RUE decreasing trends appeared in the vegetation degradation areas. This study will be helpful for understanding the impacts of climate change on securing the sustainable development of grassland ecosystems in arid and semi-arid regions.
Highlights
Vegetation is an important part of a terrestrial ecosystem and plays an important role in global climate change [1,2]
Based on the time series normalized difference vegetation index (NDVI) data and meteorological data, this study aims to explore the temporal and spatial variations of rain use efficiency (RUE) and its response to the vegetation restoration/degradation in Northwestern China
It can be found that the lower RUE values appeared in the vegetation degradation areas, while the higher RUE values can be found in the vegetation restoration areas (Figure 2a)
Summary
Vegetation is an important part of a terrestrial ecosystem and plays an important role in global climate change [1,2]. The normalized difference vegetation index (NDVI) is a simple graphical indicator to monitor the change in vegetation by using remote sensing measurements [3] It has been widely used in such large-scale vegetation dynamic monitoring such as global or continental studies. Eastman et al [4] used the seasonal trend analysis (STA) procedure to determine that over half (56.30%) of land surfaces were found to exhibit significant trends, and the NDVI in the green season was balanced by decreases in the brown season. These areas were found primarily in grassland and shrubland regions. Laidler et al [5] explored the relationship between the NDVI and percent-vegetation covers in a tundra environment, where variations in soil moisture, exposed soil, and gravel till
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