Investigating long-term drought trends is of great importance in coping with the adverse effects of global warming. However, little attention has been focused on studying the detailed spatial variability and attribution of drought variation in China. In this study, we first generated a 1 km resolution monthly climate dataset for the period 1901–2100 across China using the delta spatial downscaling method to assess the variability of the Standardized Precipitation Evaporation Index (SPEI). We then developed a simple approach to quantifying the contributions of water supply (precipitation) and demand (potential evapotranspiration, PET) on SPEI variability, according to the meaning of the differentiating SPEI equation. The results indicated that the delta framework could accurately downscale and correct low-spatial-resolution monthly temperatures and precipitation from the Climatic Research Unit and general circulation models (GCMs). Of the 27 GCMs analyzed, the BNU-ESM, CESM1-CAM5, and GFDL-ESM2M were found to be the most accurate in modeling future temperatures and precipitation. We also found that, compared with the past (1901–2017), the climate in the future (2018–2100) will tend toward significant droughts, although both periods showed a high spatial heterogeneity across China. Moreover, the proportion of areas with significantly decreasing SPEI trends was far greater than the proportion of those with increasing trends in most cases, especially for northwestern and northern China. Finally, the proposed approach to quantifying precipitation and PET contributions performed well according to logical evaluations. The percentage contributions of precipitation and PET on SPEI variability varied with study periods, representative concentration pathway scenarios, trend directions, and geographic spaces. In the past, PET contributions for significant downward trends and precipitation contributions for significantly upward trends accounted for 95% and 72%, while their future contributions were 57 ± 22%–149 ± 20% and 95 ± 27%–190 ± 58%, respectively. Overall, our results provide detailed insights for planning flexible adaptation and mitigation strategies to cope with the adverse effects of climate drought across China.

The vegetation response to climatic factors is a hot topic in global change research. However, research on vegetation in Shule River Basin, which is a typical arid region in northwest China, is still limited, especially at micro scale. On the basis of Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data and daily meteorological data, employing panel data models and other mathematical models, the aim of this paper is to reveal the interactive relationship between vegetation variation and climatic factors in Shule River Basin. Results show that there is a widespread greening trend in the whole basin during 2000–2015, and 80.28% of greening areas (areas with vegetation improvement) are distributed over upstream region, but the maximum vegetation variation appears in downstream area. The effects of climate change on NDVI lag about half to one month. The parameters estimated using panel data models indicate that precipitation and accumulated temperature have positive contribution to NDVI. With every 1-mm increase in rainfall, NDVI increases by around 0.223‰ in upstream area and 0.6‰ in downstream area. With every 1-°C increase in accumulated temperature, NDVI increases by around 0.241‰ in upstream area and 0.174‰ in downstream area. Responses of NDVI to climatic factors are more sensitive when these factors are limiting than when they are not limiting. NDVI variation has performance in two seasonal and inter-annual directions, and the range of seasonal change is far more than that of inter-annual change. The inverted U-shaped curve of the variable intercepts reflects the seasonal change. Our results might provide some scientific basis for the comprehensive basin management.

As global climate change has a large effect on the structure and function of vegetation, it is very important to understand how forests in climate transition regions respond to climate change. The present study investigates the net primary productivity (NPP) of two planted forests (Robinia pseudoacacia and Pinus tabulaeformis) and one natural forest (Quercus wutaishanica) from 1951–2100 using the LPJ-GUESS model in the Shaanxi province of China, which is a typical transition region from humid to dry climates. We found that: (1) Future annual precipitation and mean temperature exhibited nonsignificant and significant increasing trend in the region, respectively, indicating a drier climate in future; (2) although precipitation would increase in the dry area and decrease in the humid area, the NPP of each species in the dry area would be lower than that of the humid area, possibly because increasing temperature and CO₂ concentration could restrain forest growth in dry areas and promote forest growth in humid areas; (3) of the three species, P. tabulaeformis forest exhibited the highest average NPP and R. pseudoacacia forest exhibited the highest NPP trend in both dry and humid areas, indicating these planted species may be adaptable to future climate change. Our results provide novel insights into the potential response of forest productivity to a changing climate in the transition region from humid to dry climates.

Purpose: This paper aims to analyze the internal relationships and tendency of residential energy consumption, income and carbon emissions. Design/methodology/approach: Taking 30 provinces of China as the analysis unit and dividing them into two types of urban and rural consumer groups, the panel data model was built. In addition, panel unit root test, panel cointegration test and panel Granger causality test were also used. Findings: The results showed that there are long-run equilibrium relationships between the three variables, which show the regular tendency in the spatial process. The elasticity coefficients of residential energy consumption and CO₂ emissions vary across the three regions and decline continuously from the western to central and eastern regions. In addition, geographic location is also an important factor on the energy consumption and CO₂ emissions in residential sector. Originality/value: This paper provides some points for policies on cutting energy use and pollution in residential sector.

The ecological functions of vegetation play a significant role in improving human well-being. However, previous studies on ecological functions have only used semi-empirical models, which do not include physiological mechanisms and therefore do not accurately estimate the ecological functions of vegetation under scenarios of future climate change. To address this problem, a process-based dynamic vegetation model (LPJ-GUESS) was used to simulate the ecological functions of vegetation under different climate change scenarios in the Loess Plateau (LP), a typical ecologically fragile area in China. The simulated ecological functions were the carbon stock function (CS), soil conservation function (SC), and the water conservation function (WC). The results showed that: (1) Compared with 2001–2020, the proportion of area by shrub and grass vegetation that was predicted to transform into forest accounted for more than 1% of the area in the LP under the SSP119 scenario and 3% of the area in the LP under the SSP585 scenario during 2081–2100, respectively. (2) Compared with 2001–2020, the CS would decrease in the central and south-eastern regions, the SC would decrease in the western regions, and the WC would decrease in the Qilian, Wushaoling, Xinglong and Liupan Mountains during 2081–2100. (3) The relationships and the corresponding regions between the ecological functions of the vegetation and the corresponding regions in the LP would change significantly under climate change from 2001–2020 to 2081–2100.These results indicate that a process-based dynamic vegetation model can capture the changes in the carbon and water fluxes under changes in the climate and CO₂ concentration. It can also capture the vegetation succession, changes in ecological functions, and the transformation of functional relationships, which provide information that is conducive to the management and restoration of vegetation on the LP. This study supplies a novel perspective for vegetation management and high-quality development in other ecologically fragile regions worldwide.