As a vital indicator for measuring the coupled carbon–water cycle of an ecosystem, water use efficiency (WUE) can also reflect the adaptive capacity of plants in different ecosystems. Located in Southwest China, the Li River Basin has a representative karst landform, and the uneven rainfall in the region leads to severe water shortage. In this study, we analyzed the spatial–temporal transformation characteristics of the WUE of the basin and its relationship with different influencing factors from 2001 to 2020 based on a correlation analysis and trend analysis. The main conclusions are as follows: (1) The average value of WUE in the Li River Basin was 1.8251 gC· mm⁻¹·m⁻², and it kept decreasing at a rate of 0.0072 gC· mm⁻¹·m⁻²·a⁻¹ in the past 20 years. With respect to the spatial distribution of the multi-year average of WUE, it exhibits a gradual increasing trend from west to east. (2) Between gross primary productivity (GPP) and evapotranspiration (ET), it was found that ET was the primary influencing factor of WUE. Precipitation was positively correlated with WUE in the Li River Basin, accounting for 67.22% of the total area of the basin. The air temperature was negatively correlated with WUE, and the area was negatively correlated with WUE, accounting for 92.67% of the basin area. (3) The normalized difference vegetation index (NDVI) and leaf area index (LAI) were negatively correlated with WUE, and the proportions of negatively correlated areas to the total area of the basin were similar; both were between 60 and 70%. The growth of vegetation inhibited the increase in WUE in the basin to a certain extent. Regarding Vapor Pressure Deficit (VPD), the proportions of positive and negative correlation areas with WUE were similar, accounting for 49.58% and 50.42%, respectively. (4) The occurrence of drought events and the enhancement in its degree led to a continuous increase in WUE in the basin; for different land cover types, the correlation of the standardized precipitation evapotranspiration index (SPEI) was in the following order from strongest to weakest: grassland > cropland > forest > shrubland.

To explore the spatiotemporal evolution of extreme temperature events in Guangxi (1940–2023), reveal regional response mechanisms, and assess future trends of persistence under climate warming, a multi-scale analysis was conducted using ERA5 reanalysis data. Methodologies included RH tests for homogeneity correction, collaborative kriging for data optimisation, Mann–Kendall tests for trend and abrupt change detection, Morlet wavelet analysis for cyclic pattern identification, Exploratory Spatio-Temporal Data Analysis (ESTDA) for spatial heterogeneity quantification, and Rescaled Range (R/S) analysis to calculate Hurst indices for future persistence assessment. Results showed the following: (1) The ERA5 dataset exhibited high applicability in Guangxi (R = 0.9989, RMSE = 1.9492 °C), supporting robust evidence of continuous warming—warm indices (e.g., SU25, TX90p) increased significantly (SU25 at 0.2044 d/10a), while cold indices (e.g., TN10p, FD0) declined (TN10p at −0.0519 d/10a); abrupt changes of cold indices were concentrated in 1942–1950, with warm indices accelerating post-2000 and TXx exhibited the highest warming rate (0.23 °C/decade). (2) Extreme temperature indices displayed a primary 19–21-year oscillation cycle (dominant in warm indices) and a secondary 13-year cycle (prominent in cold indices). (3) Spatial heterogeneity featured northwest–southeast cold–heat inversion, coastal–inland intensity gradients, and latitudinal zonation of extreme indices; ESTDA revealed intensified polarisation, with warm indices clustering in low-latitude regions (e.g., Baise) and cold indices declining homogeneously in mountainous areas (e.g., Guilin), indicating an irreversible transition to a warming steady state. (4) R/S analysis indicated all indices had Hurst indices of 0.65–0.92, reflecting persistent future trends consistent with historical evolution, with warm indices (e.g., TNn, SU25) showing stronger persistence (H > 0.85). This work clarifies the spatial polarisation mechanism and future persistence of extreme temperature dynamics in Guangxi, providing a multi-scale scientific basis for disaster early warning and adaptation planning in climate-sensitive karst-monsoon regions.

In this study, the hydrochemistry-runoff method and remote sensing estimation method were used to calculate the karst carbon sink flux (KCSF) and the forest vegetation carbon sequestration flux (FVCSF) in Darongjiang (DRJ) and Lingqu (LQ) watersheds. The results show the following: (1) The KCSF in DRJ and LQ watersheds is 238.43 × 10⁵ t·y⁻¹ and 353.44 × 10⁵ t·y⁻¹, respectively. Influenced by changes in flow rate, the two watersheds both show that their KCSF is higher in the rainy season than in the dry season. (2) The FVCSF in DRJ and LQ watersheds was 680.78 × 10⁷ t·y⁻¹ and 229.63 × 10⁷ t·y⁻¹, respectively. Through comparison, it can be seen that the FVCSF is much higher than the KCSF in both watersheds, but the FVCSF and the KCSF are at the same order of magnitude. (3) Through further analysis of the influence factors on the FVCSF and the KCSF, we found that the highest values of FVCSF are mainly distributed around Kitten Mountain on the upper reach and along the LQ watershed. That may be because most of the upper reach areas are mountainous forestland, and the strong weathering of rocks in the LQ watershed promotes the development of forest vegetation carbon sequestration. Therefore, it can be inferred that there is a certain synergistic effect between the karst carbon sink (KCS) and the forest vegetation carbon sequestration (FVCS) in the study area, and such a synergistic effect is caused by rock weathering.

Under the global dual-carbon goals, assessing regional solar potential is vital for the energy transition. This study evaluates solar resource potential and spatiotemporal redistribution risks in Guangxi, China, using ECMWF ERA5 and CMIP6 multi-scenario data. We develop an interactive spatiotemporal regression model by integrating optimal parameter geographic detectors with geographically weighted regression to quantify drivers' synergistic effects. Key findings: (1) solar resources exhibit strong path dependency, with the highest growth rate occurring under the medium-emission scenario due to the atmospheric purification effect.; (2) dominant drivers shift with scenarios: topography (low emissions), cloud-aerosol interactions (medium), and multi-factor synergy (high); and (3) The resource center migrates from the southwestern coast to the northeastern interior, with rising spatial-instability risks. This work supports optimized solar deployment and regional energy transition in Guangxi.

The karst ecologically fragile region of northern Guangxi faces dual pressures from wetland shrinkage and landscape functional degradation driven by rapid urbanisation. The mechanisms governing its multi-scale landscape pattern evolution and the dominance of disturbances require urgent clarification. This study integrates land use data from 1980 to 2020, employing ArcGIS 10.8 analysis, Fragstats landscape indices, and optimal parameter geographic detectors to construct a ‘pattern-process-driver’ interpretative framework in northern Guangxi. It quantitatively reveals the evolution characteristics and driving mechanisms of wetland landscape patterns in northern Guangxi, thereby optimising wetland ecological conservation pathways. Results indicate the following: (1) Between 1980 and 2020, total wetland area decreased by 65.58 km², exhibiting a ‘structural substitution’ trend characterised by natural wetland decline and artificial wetland expansion. (2) Wetland landscape patterns exhibited intensified fragmentation and increased structural complexity. (3) Wetland evolution was primarily driven by annual mean temperature, GDP, and annual mean precipitation, reflecting a composite mechanism characterised by climate dominance, economic pressure, and policy failure. Specifically, the increase in temperature is the main reason for the decrease in natural wetlands, while economic growth dominates the expansion of artificial wetlands. This study provides scientific basis for karst wetland ecological restoration and differentiated territorial spatial planning, offering reference for ecological and environmental governance in karst watersheds.

In this study, the spatial and temporal evolution characteristics and driving mechanism of land use and landscape pattern in northern Guangxi from 1980 to 2020 were systematically analyzed by using ArcGIS 10.8, Fragstats 4.2 and PLUS models, and the land use structure and landscape pattern under different development scenarios in 2030 were simulated and predicted. The results show that: (1) Between 1980 and 2020, the areas of cropland, forest, and grassland in the northern Guangxi decreased by 307, 140, and 68 km ² , respectively. While the area of built-up land increased by about 444 km ² . The land use structure is characterized by ‘bidirectional succession and increased artificialization’. (2) The overall landscape pattern showed a trend of ‘increased fragmentation and decreased connectivity’, and the self-regulation ability of ecological landscape was weakened. (3) The driving analysis shows that land use change is driven by both socio-economic and natural environmental factors, among which population driving factors are dominant. (4) The results of multi-scenario simulation show that the ecological protection scenario can achieve the most compact landscape structure, the highest connectivity and aggregation, which is the optimal path for regional sustainable development. The results of this study can provide scientific basis and theoretical support for the optimal allocation of landscape space and the restoration and reconstruction of ecosystem in northern Guangxi.