Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

Abstract

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.

The turning of ecological change in the Yellow River Basin

“…Temperature and precipitation are climate factors closely related to the growth of vegetation, and therefore indispensable for analysing vegetation response to climate change (He et al, 2015; Kong et al, 2017; Sun et al, 2021; Wang et al, 2011). In the context of global warming, temperature increased over the entire YRB (99.2% with a significant increase) from 1982 to 2015, by 0.045°C·a −1 on average.…”

“…It is worth noting that the regional average TP of the central YRB is 2003, and this TP will be used for subsequent regional average NDVI trend analysis. (He et al, 2015;Kong et al, 2017;Sun et al, 2021;Wang et al, 2011). In the context of global warming, temperature increased over the entire YRB (99.2% with a significant increase) from 1982 to 2015, by 0.045 CÁa À1 on average.…”

“…But previous studies often focused on the last four decades; and these studies concluded that the increase in temperature dominated the increase in the NDVI in the YRB (Toms & Lesperance, 2003; Wang et al, 2011). Some studies showed that while changes in vegetation cover are also affected by urbanization, the areas controlled by precipitation increased significantly in the recent past (Sun et al, 2021; Yuan et al, 2020). However, in the context of global climate change, vegetation cover has been changing in a complex way in recent decades, and the trend even reverses in some regions (Feng et al, 2021; Jiang et al, 2021; Wang et al, 2011).…”

Land Use and Climate Change Altered the Ecological Quality in the Luanhe River Basin

“…Sufficient precipitation provides moisture for soil and vegetation, which would improve plant growth and affect NDVI [83]. Sometimes, too much precipitation could inhibit it because insufficient sunshine would inhibit photosynthesis [84]. The vegetation in the upper reaches of LHRB showed an improvement over the past few years according to recent research; this is correlated with precipitation, which grassland is more sensitive to [85].…”

Temporal Variation of Soil Moisture and Its Influencing Factors in Karst Areas of Southwest China from 1982 to 2015

“…The NDVI dataset was derived from advanced very-high-resolution radiometer (AVHRR) global inventory modeling and mapping studies (GIMMS) NDVI3g.v1 (https: //ecocast.arc.nasa.gov/data/pub/gimms/3g.v1/, accessed on 4 October 2021), with a spatial resolution of 8 × 8 km [39], and the spatial resolution was resampled to 10 km. This is the most extended global vegetation dataset and is widely used in regional vegetation change research [40][41][42].…”