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Wang, Xiaoyi; Wang, Tao; Liu, Dan; Guo, Hui; Huang, Huabing; Zhao, Yutong
Global change biology, November 2017, Volume: 23, Issue: 11Journal Article
South Asia experienced a weakening of summer monsoon circulation in the past several decades, resulting in rainfall decline in wet regions. In comparison with other tropical ecosystems, quantitative assessments of the extent and triggers of vegetation change are lacking in assessing climate‐change impacts over South Asia dominated by crops. Here, we use satellite‐based Normalized Difference Vegetation Index (NDVI) to quantify spatial–temporal changes in vegetation greenness, and find a widespread annual greening trend that stands in contrast to the weakening of summer monsoon circulation particularly over the last decade. We further show that moisture supply is the primary factor limiting vegetation activity during dry season or in dry region, and cloud cover or temperature would become increasingly important in wet region. Enhanced moisture conditions over dry region, coinciding with the decline in monsoon, are mainly responsible for the widespread greening trend. This result thereby cautions the use of a unified monsoon index to predict South Asia's vegetation dynamics. Current climate–carbon models in general correctly reproduce the dominant control of moisture in the temporal characteristics of vegetation productivity. But the model ensemble cannot exactly reproduce the spatial pattern of satellite‐based vegetation change mainly because of biases in climate simulations. The moisture‐induced greening over South Asia, which is likely to persist into the wetter future, has significant implications for regional carbon cycling and maintaining food security. Spatial distributions of GIMMS NDVI trends over the South Asia during the three periods: 1982–2014 (first row), 1982–2001 (second row), and 2002–2014 (third row). The trends are estimated on the annual (a, d, and g), wet season (b, e, and h), and dry season basis (c, f, and i), respectively. The inset panels show the pixels where NDVI trends are statistically significant at p < .05.
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