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Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem. [ABSTRACT FROM AUTHOR]

Net primary productivity (NPP) can indirectly reflect vegetation's capacity for CO 2 fixation, but its spatiotemporal dynamics are subject to alterations to some extent due to the influences of climate change and human activities. In this study, NPP is used as an indicator to investigate vegetarian carbon ability changes in the vital ecosystems of the Yangtze River Basin (YRB) in China. We also explored the NPP responses to climate change and human activities. We conducted a comprehensive analysis of the temporal dynamics and spatial variations in NPP within the YRB ecosystems from 2003 to 2020. Furthermore, we employed residual analysis to quantitatively assess the contributions of climate factors and human activities to NPP changes. The research findings are as follows: (1) Over the 18-year period, the average NPP within the basin amounted to 543.95 gC/m 2 , displaying a noticeable fluctuating upward trend with a growth rate of approximately 3.1 gC/m 2 ; (2) The areas exhibiting an increasing trend in NPP account for 82.55% of the total study area. Regions with relatively high stability in the basin covered 62.36% of the total area, while areas with low stability accounted for 2.22%, mainly situated in the Hengduan Mountains of the western Sichuan Plateau; (3) NPP improvement was jointly driven by human activities and climate change, with human activities contributing more significantly to NPP growth. Specifically, the contributions were 65.39% in total, with human activities contributing 59.28% and climate change contributing 40.01%. This study provides an objective assessment of the contributions of human activities and climate change to vegetation productivity, offering crucial insights for future ecosystem development and environmental planning. [ABSTRACT FROM AUTHOR]