The soil water supply and atmospheric humidity conditions are crucial in controlling plants’ stomatal behavior and water use efficiency. When there is water stress caused by an increase in saturated water vapor pressure (VPD) and a decrease in soil water content (SWC), plants tend to close stomata to reduce water loss. This affects the gross primary productivity (GPP) and evapotranspiration (ET), subsequently leading to changes in water use efficiency (WUE) and carbon use efficiency (CUE) in plants. However, land–atmosphere interactions mean that water vapor in the atmosphere and soil moisture content causing water stress for plants are closely related. This study aims to compare and estimate the effects of VPD and SWC on the carbon cycle and water cycle for different plant functional types. Based on the fluxnet2015 dataset from around the world, the WUE and CUE of five plant functional types (PFTs) were estimated under varying levels of VPD and SWC. The results showed that high VPD and low SWC limit the stomatal conductance (Gs) and gross primary productivity (GPP) of plants. However, certain types of vegetation (crops, broad-leaved forests) could partially offset the negative effects of high VPD with higher SWC. Notably, higher SWC could even alleviate limitations and partially promote the increase in GPP and net primary production (NPP) with increasing VPD. WUE and CUE were directly affected by Gs and productivity. In general, the increase in VPD in the five PFTs was the dominant factor in changing WUE and CUE. The impact of SWC limitations on CUE was minimal, with an overall impact of only −0.05μmol/μmol on the four PFTs. However, the CUE of savanna plants changed differently from the other four PFTs. The rise in VPD dominated the changes in CUE, and there was an upward trend as SWC declined, indicating that the increase in VPD and decrease in SWC promote the increase in the CUE of savanna plants to some extent.

Under intensified global climate change and complex land use transitions, the Leaf Area Index (LAI) serves as a key ecological indicator to monitor vegetation responses to natural and anthropogenic factors. This study provided a comprehensive spatiotemporal diagnosis of the LAI and uniquely integrated remote sensing data with the Geodetector model to quantitatively assess both individual and interactive effects of natural and human drivers. Specifically, we analyzed LAI dynamics in the Jinsha River Basin from 2000 to 2023 using Sen’s Slope and Mann–Kendall tests, combined with Geodetector modeling to identify drivers and their interactions. Furthermore, ARIMA-based forecasting offered forward-looking insights to support land use planning and ecosystem resilience. Results revealed a fluctuating upward trend in LAI, with larger areas improving than degrading, and distinct seasonal and spatial patterns, with a notably higher LAI in southern regions. Elevation and temperature were the primary drivers, explaining 57% and 54% of spatial variation, respectively, with their combined effects further enhancing explanatory power. The future LAI trend appeared stable without significant changes. These findings demonstrated LAI’s utility for assessing land use change impacts and ecological sustainability, providing a scientific basis for land use optimization, ecological restoration, and sustainable regional development under the human–earth system framework.

To investigate the spatiotemporal characteristics of periphytic algae community structure and the Benthic Index of Biotic Integrity (B-IBI) in the Jinsha River, this study conducted two sampling surveys on periphytic algae and physicochemical factors at 15 representative sampling sites in November 2023 (dry season) and May 2024 (normal water period). Results showed that a total of 118 species of periphytic algae belonging to 59 genera and 7 phyla were detected, including 48 species from 5 phyla in the dry season of 2023 and 95 species from 6 phyla in the normal water period of 2024. Spatially, the distribution trends of total species richness and abundance of periphytic algae were basically consistent, both showing a gradually increasing trend from the downstream reservoir section of the Jinsha River to the upstream conservation section of the Yangtze River. Temporally, both the abundance and species richness of periphytic algae in the normal water period were higher than those in the dry season. Overall, the physicochemical indices of the Jinsha River water showed a decreasing trend from the reservoir areas to the river channels, with slightly higher values in the normal water period than in the dry season. Through parameter value distribution range analysis, discriminant ability analysis, and redundancy analysis of candidate parameters, the B-IBI index system for the study area was determined. The baseline values of the periphytic algae integrity index were 6.04 in the dry season of 2023 and 6.62 in the normal water period of 2024. The water ecological health status of the conservation section of the upper reaches of the Yangtze River is generally in a healthy state, and the overall water ecological health status gradually improves with the increase of the distance from the cascade reservoirs in the lower reaches of the Jinsha River.

The Yangtze River Basin is vital to China’s water security and flood management yet lacks a basin-wide quantitative assessment of long-term hydroclimatic changes. This study uses the high-resolution CMFD 2.0 dataset and the VIC model to evaluate spatiotemporal trends in precipitation and natural streamflow from 1951 to 2020. The results show a significant increase in annual precipitation in the upper basin (1.10 mm yr⁻¹, p < 0.05), particularly during the wet season, with spatially concentrated increases along the eastern Tibetan Plateau. The VIC model performed reliably across major stations, with NSE > 0.9 and PBIAS within ±10% during calibration. Natural streamflow trends are spatially heterogeneous: upper mainstream stations (e.g., Shigu, Panzhihua, Zhutuo) exhibit significant increases (6.25–14.58 m³/s per year), while lower stations remain stable or decline. Seasonally, wet-season streamflow increased in the upper basin, whereas dry-season streamflow decreased in the middle and lower reaches. At Yichang, natural simulations reveal growing seasonal extremes, with rising wet-season and declining dry-season flows (−19.06 m³/s yr⁻¹). Human interventions have partially offset these extremes. Since 1990, observed peak discharge at Yichang during the wet season has decreased by 10.04% compared to natural streamflow, while the dry-season minimum discharge has increased by 27.63%. This shows that large reservoirs help reduce flood peaks and increase low flows. These findings highlight the intensifying impacts of climate variability and human regulation on hydrological processes and provide a scientific basis for adaptive water resource management in large river basins.