Climatic determinants impacting the distribution of greenness in China: regional differentiation and spatial variability
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This study investigated climatic determinants for regional greenness in China and spatially variable correlations between climatic determinants and vegetation in specific regions using the geographical detector and geographically weighted regression (GWR) methodologies. The analyses were based on normalized difference vegetation index (NDVI) and interpolations of climatic determinants from 652 Chinese meteorological stations. The study period (1982–2013) was divided into two stages (T1–T2) before and after the inflection year identified by the accumulative anomaly of NDVI. Three typical regions (R1–R3) were then selected according to the same NDVI variation trend as China in the two periods. Precipitation was the dominant climatic factor of NDVI in China, and the effect of temperature on greenness increased with warming from T1 to T2. In a relatively arid region (R1), the effect of precipitation in T2 was further strengthened compared to T1. Meanwhile, the effect of minimum temperature in T2 also increased compared with T1 in a relatively humid region (R2), becoming the major climatic determinant. In addition to the regional differentiation, spatial variability was investigated by comparing normalized coefficients of GWR for climatic determinants; this showed significant spatial heterogeneity within each region. Temperature impact areas also existed within precipitation-dominated regions (R1 and R3), where areas of precipitation impact expanded from T1 to T2. Furthermore, regression coefficients between NDVI dynamics and climate variability revealed relationships between regional differentiation and spatial variability. For example, the increasing precipitation rate could mediate the adverse impacts on greenness caused by the higher warming rate in relatively arid regions (R1).
KeywordsGreenness NDVI Climatic determinants Spatial variability Regional variations China
This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 41671098 and 41530749), the National Key R&D Program of China (2018YFC1508801), and the “Strategic Priority Research Program” of the Chinese Academy of Sciences (Grant Nos. XDA20020202 and XDA19040304).
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