顾及时滞效应的西南地区植被NPP变化归因分析

随着社会经济的不断发展，近年来西南地区部分区域生态环境日益脆弱。研究气候变化和人类活动影响下植被净初级生产力（Net Primary Productivity，NPP）时空演变特征，可为监测区域植被生长状况及其对驱动因素的响应机制提供理论依据。该研究以2000－2020年MOIDS NPP数据为基础，结合气象、人口密度、夜间灯光和土地利用类型等数据，使用Theil-Sen Median趋势分析、多重共线性检验、多元回归分析、残差分析和偏相关分析等研究方法，分析2000－2020年西南地区及各地貌单元植被NPP时空变化特征及对气候变化和人类活动的响应特征。结果表明：1）2000－2020年，除青藏高原植被NPP、气候影响下的植被NPP预测值（Predicted Net Primary Productivity，NPPPre，）和人类活动影响下的植被NPP残差值（Residual Net Primary Productivity，NPPRes）呈微弱波动下降外，其余地貌单元植被NPP、NPPPre和NPPRes均呈较明显的波动上升趋势，其中，四川盆地植被NPP、NPPPre和NPPRes波动上升趋势尤为显著，上升斜率分别为7.14、3.72和3.44 g/(m2·a)。2）研究时段内西南地区气候变化对植被NPP上升的影响整体强于人类活动。气候变化影响下，西南地区约45.18%的区域植被NPP呈显著和极显著上升趋势，而人类活动影响下，该占比仅为18.55%。地貌单元上，气候变化和人类活动影响下，四川盆地植被NPP呈极显著上升和显著上升的比例最高，分别为69.42%和50.75%。3）西南地区整体及各地貌单元植被NPP变化主要受温度类因子的主导，相对湿度和大气压强对西南地区植被生长整体具有抑制作用。4）耕地转化为城镇用地是植被NPP下降的重要原因，而非耕地转化为耕地和非林地转化为林地是植被NPP上升的重要原因。整体上，西南地区植被NPP与人口密度和夜间灯光呈不显著相关关系。地貌单元上，四川盆地植被NPP与人口密度和夜间灯光的相关性最高，即四川盆地植被生长受人为活动的影响强于其他地貌单元。研究结果可为区域植被生长监测、生态环境质量评价和林业生态工程效益评估提供理论依据。

Attribution analysis of vegetation NPP variation in Southwest China considering time-lag effects

An ecosystem has been much more fragile against global warming in southwest China in recent years. Rapid and accurate monitoring of vegetation growth can greatly contribute to clarifying the response mechanism of vegetation growth to the driving factors. Therefore, it is very necessary to explore the spatiotemporal variation in the vegetation net primary productivity (NPP) under climate change and human activities. In this study, a systematic investigation was made to determine the spatiotemporal variation of vegetation NPP, and the effects of climate change and human activities on the regional and landform unit scales from 2000 to 2020. The moderate-resolution imaging spectroradiometer (MODIS) NPP was selected to combine with in situ meteorological data, population density, night-time light, and land use type datasets. Multiple mathematical models were also utilized, such as Theil-Sen Median trend, variance inflation factor, multivariate regression, residual and partial correlation analysis. Results showed that 1) there was an increasing fluctuation in the overall, predicted, and residual vegetation NPP over the past 21 years from 2000 to 2020, whereas, the Tibetan Plateau presented a relatively decrease trend. Among them, the vegetation NPP, predicted vegetation NPP, and residual vegetation NPP in the Sichuan Basin exhibited the most significant increasing trend, with a magnitude of 7.14, 3.72, and 3.44 g/(m2·a), respectively. 2) The impact of climate change on the vegetation NPP was higher than that of human activities during the study period. The areas with extremely significant and significant increases accounted for 45.18% and 18.55% of the study area, respectively, under the climate change and human activities. By contrast, the areas with extremely significant and significant increases in the predicted vegetation NPP and residual vegetation NPP in the Sichuan Basin accounted for the highest proportion in all landform units, with a magnitude of 69.42% and 50.75%, respectively. The vegetation NPP variation was dominated by the changes of temperature-like factors at the regional and landform unit scales. Specifically, the relative humidity and atmospheric pressure showed inhibitory effects on vegetation growth in southwest China. Correspondingly, the conversion of cultivated land to urban land can be an important reason for the decline of vegetation NPP, whereas, the conversion of non-cultivated land to the cultivated land and the non-forest land to forest land can be another important reason for the increase of vegetation NPP during the study period. There was an insignificant correlation of vegetation NPP with the population density and night-time light at the regional scale. Sichuan Basin exhibited the highest correlation of the vegetation NPP with population density and night-time light in all landform units at the landform unit scale. It infers that the vegetation growth in the Sichuan Basin was more associated with human activities than the rest landform units. The finding can provide a strong theoretical basis for the regional monitoring of the vegetation growth, quality assessment of the ecological environment, and benefit evaluation of forestry ecological engineering.