The digital economy is an important driving force for promoting national economic growth and achieving high-quality economic transformation, and is a key force in achieving the sustainable development goals (SDGs). This paper measures the digital economy development level of 30 provinces in China from 2013 to 2021 utilizing the entropy of weighting approach, and in order to further reveal its intrinsic laws and differences, it uses three-dimensional kernel density analysis, the Dagum Gini coefficient, spatial autocorrelation analysis, and cold hot spot analysis to explore the spatial and temporal evolution characteristics of the digital economy and its regional imbalance. The empirical results show that ① China’s digital economy has been steadily increasing, spatially showing the characteristics of gradual decrease from east to west and from coast to inland, with obvious spatial agglomeration characteristics and an increasing trend. ② There are obvious regional imbalances in the digital economy, with the southeast coastal region leading significantly. ③ The overall regional differences are large but reduced, mainly from intra-regional differences, the and inter-regional contribution is low. The research in this paper provides data support for revealing the spatial and temporal evolution characteristics of digital economic development and provides new path support for the balanced development of China’s regional digital economy.

Terrestrial gross primary productivity (GPP) is the major carbon input to the terrestrial ecosystem. The Yangtze River Basin (YRB) holds a key role in shaping China’s economic and social progress, as well as in ecological and environmental protection. However, how the GPP in the YRB responds to the climate factors remain unclear. In this research, we applied the Vegetation Photosynthesis Model (VPM) GPP data to explore the spatial and temporal variations of GPP in the YRB during 2000–2018. Based on the China Meteorological Forcing Dataset (CMFD), the partial least squares regression (PLSR) method was employed to identify the GPP responses to changes in precipitation, temperature, and shortwave radiation between 2000 and 2018. The findings showed that the long-term average of GPP in the YRB was 1153.5 ± 472.4 g C m⁻² yr⁻¹ between 2000 and 2018. The GPP of the Han River Basin, the Yibin-Yichang section of the Yangtze River mainstream, and the Poyang Lake Basin were relatively high, while the GPP of the Jinsha River Basin above Shigu and the Taihu Lake Basin were relatively low. A significant upward trend in GPP was observed over the 19-year period, with an annual increase rate of 8.86 g C m⁻² yr⁻¹ per year. The GPP of the Poyang Lake Basin and Jialing River Basin grew much faster than other water resource regions. Savannas and forests also had relatively higher GPP rate of increase compared to other vegetation types. The relative contributions of precipitation, temperature, and shortwave radiation to GPP variations in the YRB were 13.85 ± 13.86%, 58.87 ± 9.79%, and 27.07 ± 15.92%, respectively. Our results indicated that temperature was the main climatic driver on the changes of GPP in the YRB. This study contributes to an in-depth understanding of the variations and climate-impacting factors of vegetation productivity in the YRB.

Vapor pressure deficit (VPD) and soil moisture (SM) are the two main parameters related to ecosystem water stresses. They are tightly coupled through land–atmosphere interactions and have large impacts on terrestrial ecosystems and global water and carbon cycles. However, the coupling characteristics between the two have not been thoroughly studied, particularly in the context of climate warming. In this study, based on remote sensing and reanalysis datasets, spatial and temporal variations in the VPD and SM and their correlation coefficients in the growing season in China from 1982 to 2018 were evaluated. Then, the probabilities of compound water stress (high VPD and low SM) were investigated under three scenarios based on a copula analysis. The results show that, over the 37 years, the VPD significantly increased during the growing season, while the SM significantly decreased. The coupling relationship between the VPD and SM was relatively weak in extreme arid and arid regions. In contrast, this relationship was stronger in semi-arid and semi-humid regions, where the probabilities of compound water stress were significantly higher (p < 0.05). The probabilities of compound water stress (high VPD and low SM) were significantly higher than the probabilities when the VPD and SM were independent, and this difference increased with the severity of the water stress in the same region. The obtained results can be further applied to improve Earth system models and formulate agricultural irrigation schemes.