Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing, 100101, China.
Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, 72 Wenhua Road, Shenhe District, Shenyang, 110016, China.
Int J Biometeorol. 2019 Apr;63(4):523-533. doi: 10.1007/s00484-019-01683-4. Epub 2019 Feb 7.
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).
本研究采用地理探测器和地理加权回归(GWR)方法,调查了中国区域绿化的气候决定因素,以及特定区域气候决定因素与植被之间的空间变化相关性。分析基于归一化差异植被指数(NDVI)和从 652 个中国气象站插值的气候决定因素。研究期(1982-2013 年)分为两个阶段(T1-T2),前一阶段是由 NDVI 的累积异常确定的转折点之前,后一阶段是转折点之后。然后根据与中国在两个时期相同的 NDVI 变化趋势,选择了三个典型区域(R1-R3)。降水是中国 NDVI 的主要气候因素,而温度对绿色度的影响随着从 T1 到 T2 的变暖而增加。在相对干旱的地区(R1),与 T1 相比,T2 降水的影响进一步加强。同时,在相对湿润的地区(R2),T2 最低温度的影响也比 T1 有所增加,成为主要的气候决定因素。除了区域差异外,通过比较气候决定因素的 GWR 归一化系数来研究空间变异性;这表明每个区域内都存在显著的空间异质性。在降水主导地区(R1 和 R3)也存在温度影响区,其中降水影响区从 T1 扩大到 T2。此外,NDVI 动态与气候可变性之间的回归系数揭示了区域分化和空间变异性之间的关系。例如,在相对干旱地区(R1),降水速率的增加可以缓解由于较高的变暖速率对绿色度的不利影响。