State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Donggang West Rd. 318, Lanzhou, 730000, China.
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Donggang West Rd. 318, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
Environ Res. 2024 Jun 1;250:118450. doi: 10.1016/j.envres.2024.118450. Epub 2024 Feb 13.
Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.
评估气候变化和人类活动的相对重要性对于制定区域土地利用的可持续管理政策至关重要。本研究利用多个遥感数据集，包括 CHIRPS（气候危害组红外降水与台站数据）降水、MODIS 地表温度（LST）、增强型植被指数（EVI）、潜在蒸散量（PET）、土壤湿度（SM）、WorldPop 和夜间灯光数据，来研究 2000 年至 2022 年期间气候变化（CC）和区域人类活动（HA）对印度东部植被动态的影响。利用非参数统计方法，即 Mann-Kendall 和 Sen 斜率估计器，评估气候和人为因素的相对影响。降水和 LST 的显著空间和海拔依赖性变化是明显的。高海拔地区的年平均气温升高（0.22°C/年，p<0.05），冬季降水减少，而过去二十年，西孟加拉邦的北部和西南部地区年平均降水增加（17.3mm/年，p<0.05），且有轻微降温趋势。温度和降水趋势共同影响 EVI 分布。虽然 LST 和 EVI 之间存在负空间相关，但降水与 EVI 之间的关系是正相关且更强（R=0.83，p<0.05）。相关的水文气候参数是 EVI 的主要驱动因素，西南地区的 PET 导致 SM 明显降低。CC 和 HA 对 EVI 的相对重要性也存在空间差异。在加尔各答主要城市群附近，并且得到夜间灯光和人口密度数据的证实，植被覆盖的变化非常明显地受到 HA 的控制（87%）。相比之下，在该州北部海拔较高的地区以及东南部，CC 成为 EVI 的主要驱动因素（70-85%）。我们的研究结果为整个州的脆弱社会水文气候系统的未来可持续性提供了政策参考。
