Temperature and precipitation are the primary regulators of vegetation phenology in temperate zones. However, the relative contributions of each factor and their underlying combined effect on vegetation phenology are much less clear, especially for the grassland of the Tibetan Plateau To quantify the contribution of each factor and the potential interactions, we conducted redundancy analysis for grasslands spring phenology on the Tibetan Plateau during 2000–2017. Generally, the individual contribution of temperature and precipitation to grasslands spring phenology (the start of growing season (SOS)) was lower, despite a higher correlation coefficient, which further implied that these factors interact to affect the SOS. The contributions of temperature and precipitation to the grasslands spring phenology varied across space on the Tibetan Plateau, and these spatial heterogeneities can be mainly explained by the spatial gradient of long-term average precipitation during spring over 2000–2017. Specifically, the SOS for meadow was dominated by the mean temperature in spring (T_spring) in the eastern wetter ecoregion, with an individual contribution of 24.16% (p < 0.05), while it was strongly negatively correlated with the accumulated precipitation in spring (P_spring) in the western drier ecoregion. Spatially, a 10 mm increase in long-term average precipitation in spring resulted in an increase in the contribution of T_spring of 2.0% (p < 0.1) for meadow, while it caused a decrease in the contribution of P_spring of −0.3% (p < 0.05). Similarly, a higher contribution of P_spring for steppe was found in drier ecoregions. A spatial decrease in precipitation of 10 mm increased the contribution of P_spring of 1.4% (p < 0.05). Considering these impacts of precipitation on the relative contribution of warming and precipitation to the SOS, projected climate change would have a stronger impact on advancing SOS in a relatively moist environment compared to that of drier areas. Hence, these quantitative interactions and contributions must be included in current ecosystem models, mostly driven by indicators with the direct and the overall effect in response to projected climate warming.

Little attention has been paid to the impact of future urban expansion patterns on carbon emissions based on the existing urban pattern of a region. This study used the Central Guizhou Urban Agglomeration as the study area, and the relationships between regional urbanization and CO₂ emissions in the study area were analyzed based on historical data. Urban growth patterns were then simulated in four scenarios that focused on the next 15 years, and they were based on the cellular automaton model. In each different scenario, the CO₂ emissions were predicted, and some implications regarding the impact of those emissions were provided. The results showed that as urban land-use intensity increases, CO₂ emissions first increase then decrease; however, the rate of decline for CO₂ emissions is much slower than the rate at which it rises. Moreover, in the next 15 years, urban expansion will lead to a significant increase in CO₂ emissions. The CO₂ emissions were found to be lowest in the spatial agglomeration scenario and highest in the spatial dispersion scenario. The spatial agglomeration scenario was conducive to understanding how CO₂ emissions eventually peak; however, different cities in the study area should adopt different urban expansion patterns. These research results can provide a reference guide for the government with regard to urban planning.

Abandoned cropland is a widespread issue globally, with the impacts of utilizing abandoned cropland, such as grain production and carbon emissions, raising increasing concern. However, existing studies have largely overlooked the potential spillover effects on other regions through grain flows when increasing grain production in one region by utilizing abandoned cropland. Therefore, this study aimed to comprehensively estimate the impacts of using winter fallow fields (a typical seasonal abandoned cropland) on grain production and carbon emissions, particularly its neglected spillover impact. Focusing on Zhejiang province, this study used remote sensing techniques to identify winter fallow fields in 2018 and then assessed the impact of using those winter fallow fields on grain production based on grain yield data from the FAO, as well as its local and spillover impacts on carbon emissions based on the Greenhouse Gas Emission Factor method and a transportation carbon emission model. The results indicate the following: (1) The winter fallow fields in Zhejiang cover 5,161,000 hectares, accounting for 40.8% of the total cropland, with a notable prevalence in Jiaxing, Huzhou, Jinhua, and Quzhou. (2) Using winter fallow fields would increase grain production by 1,870,000 tons. (3) At the same time, local carbon emissions would rise by 261,000 tons if using winter fallow fields, but this would be paired with a reduction of 668,000 tons of carbon emissions from other regions (that is, a spillover impact), reflecting a net reduction (−447,000 tons) in overall emissions. In conclusion, using winter fallow fields can achieve a ‘win–win’ effect, increasing grain production while reducing carbon emissions. This study highlights that the spillover effects of using winter fallow fields on carbon emissions significantly surpass the localized impact, underscoring a critical aspect that has been traditionally undervalued, which should be paid more attention when policymakers formulate and implement cropland use policies. This study not only contributes to the academic discourse on sustainable land management but also serves as a practical guide for policymakers seeking to optimize agricultural productivity while curtailing the carbon footprint, thereby advancing towards a more secure and environmentally responsible food system.

Accompanied by China’s rapid economic growth, significant urban greening has occurred in Chinese cities, in particular in the urban core areas. In contrast, rapid urbanization and economic growth also led to a high probability of vegetation degradation in urban fringe regions. However, these significant spatial differences in urban greenness associated with economic growth in Chinese cities are not well understood. This study explored the spatiotemporal characteristics of the nighttime light (NTL) and annual maximum enhanced vegetation index (EVI_max) in urban areas from 2001 to 2020. A strong decoupling status between economic growth and urban greenness on the national scale was found. Overall, 49.15% of urban areas showed a decoupling status. Spatially, this percentage of urban areas with a decoupling status would significantly decrease when the long-term average NTL surpasses 51. Moreover, this significant threshold of decoupling status was found in 189 cities out of 344 (54.65%) in China. This threshold in each city showed significant spatial heterogeneity but can mostly be attributed to the gradient in the long-term average precipitation (P_mean) of each city during the period of 2001–2020. Specifically, a spatial increase in P_mean of 100 mm responded to a decrease in the threshold of 0.4 DN (p < 0.01). In contrast, there was no significant correlation between the threshold and the economic growth status of each city. Our results provide valuable insights for coordinating the development of urban greening and economic growth.