The high-quality development in the Yunnan–Guizhou region (YGR) is a significant support for the high-quality development of China. It will help shape a new pattern of regional coordinated development. Referring to a Beautiful China and the United Nations Sustainable Development Goals (SDGs) evaluation indexes, we built an evaluation index system that puts the high-quality development at its heart. This system includes the resource load, economic development, ecological environment protection, and social progress. Taking 25 prefecture-level cities of the YGR as study subjects, the authors used the entropy weight–TOPSIS model to evaluate high-quality development and evolution. Then, the authors used the Geographical Detector (GD) method and a Geographic-Weighted Regression (GWR) model to analyze factors and mechanisms of the evolution of high-quality development. The results suggest that the changes of urban built-up area, per capita GDP, total foreign trade value, tourism revenue, and total investment of fixed assets investment are the primary factors of spatial differentiation of this evolution. The influence and direction of each factor are different in different periods, with apparent spatio-temporal heterogeneity. From 2005 to 2018, the synergistic effect of changes in total foreign trade value and tourism revenue is the leading force in shaping the evolution pattern. The high-quality development of the YGR generally presents the spatial pattern of “central Yunnan–central Guizhou core dual drive”, “high in east and low in west”, and the evolution speed presents a development characteristic of “low speed–relatively high speed–high speed”. The research can provide a reference for high-quality and precise development and decision-making in the YGR.

This study aims to assess the current status of green agricultural development and its influencing factors in Lincang City, a national innovation demonstration zone for sustainable development; it also seeks to enhance the potential and competitiveness of green agricultural development in underdeveloped border areas. To achieve this, an evaluation index system is constructed encompassing six dimensions. Using a coupled coordination and obstacle degree approach, this study explores the spatiotemporal differences in the level of green agricultural and sustainable development, as well as the power, coupled coordination degree, and factors that negatively impact green agricultural development in Lincang City from 2010 to 2019. The Liang-Kleeman information flow method is applied to uncover the key information flow factors that influence the coupled coordination degree in each county and district of Lincang City. The results reveal several insights: First, the comprehensive score of sustainable green agricultural development increased from 0.4405 to 0.5975 during the study period. Second, the coupling coordination degree of green agricultural development was relatively low, fluctuating between 0.1821 and 0.2816. Overall, the development has shifted from severe imbalance to mild imbalance. Third, the obstacle degree increased by 3.75%. From a systemic perspective, the “resource conservation” layer had the highest barrier level, with the maximum value being observed in Yun County at 25.5%. Further analysis of the indicators reveals that the use of outdated water-saving irrigation techniques has resulted in low irrigation efficiency and excessive water resource waste. This is the main cause of the high barrier levels in terms of water-saving irrigation intensity and effective irrigation area. Moreover, the excessive use of chemical pesticides to enhance vegetable production has contributed to high barrier levels for achieving yields of pollution-free vegetable production per unit area. Finally, the information flow values of the factors influencing the coordinated and harmonious development of green agriculture exhibit significant regional heterogeneity among counties and districts. The highest information flow value for the area of drought- and flood-resistant crop cultivation is in Zhengkang County at 1.86. Based on these results, local government departments and decision-makers should focus on promoting comprehensive improvements in the level of green agricultural development. It is crucial to tailor measures to the specific needs of each county to address the shortcomings in green agricultural development. Additionally, efforts should be made to strengthen the innovation-driven chain of green agricultural development, including production, processing and sales. Enhancing the green agricultural development system is essential for long-term progress.

Fewer studies on ecological security (ES) in border areas limit the synergistic development of border areas in the context of rapid globalization. The study of ES in border areas of southwest China can enrich the evaluation methods, summarize the knowledge related to ES in border areas, and provide references for similar areas in the world. Therefore, twenty-five international border counties in Yunnan Province were selected to establish a system to evaluate ES; an entropy weight TOPSIS model was used to evaluate the changes in ES from 2004 to 2019. Then, an obstacle degree model was used to diagnose the factors affecting ES. The state of ES was predicted by a gray prediction model (GM) (1,1) in 2025 and 2030. The results show that an improving ES situation presented a spatial distribution pattern of high to low from the southwest to the west and east. Various factors, including fixed assets investment, per-capita fiscal revenue, per-capita GDP, food production, and water regulation, created obstacles to a desirable ES in the study area. Although the ES of border areas will maintain an upward trend under the existing development model, the number of counties that will reach a secure state of ES in 2025 and 2030 is predicted to only be 1 and 2, respectively.

Context: Under global climate change and intensified human activities, the Yangtze River Basin (YZRB) and Yellow River Basin (YRB) face escalating challenges to ecosystem services (ESs), including water scarcity and biodiversity loss. Understanding ES dynamics is essential for sustainable landscape management. Objectives: This study aimed to (1) predict spatiotemporal changes in land cover and ESs from 2030 to 2100 under SSP1–2.6, SSP3–7.0, and SSP5–8.5 scenarios, and (2) quantify pixel-scale ES trade-offs/synergies and their driving factors. Methods: An integrated SSP–LUH2–PLUS–InVEST/CS framework was developed, combining climate scenarios, land use simulations, and ES assessments. The framework was applied to both basins to project future land cover changes and quantify ES responses under varying radiative forcing scenarios. Results: Forests expanded notably in the YZRB under SSP1–2.6 and SSP3–7.0, largely replacing grasslands and croplands, whereas grasslands remained in the YRB. Water yield (WY), soil conservation (SC), and habitat quality (HQ) improved the most under SSP1–2.6, whereas carbon sequestration (CS) peaked under SSP5–8.5. Synergies prevailed among WY–SC, CS–SC, and SC–HQ across all scenarios, whereas CS–HQ shifts to trade-offs under SSP5–8.5. ES interactions were scenario-dependent, with precipitation, temperature, potential evapotranspiration, land cover, and elevation as key drivers, shifting from land use-driven under low emissions to climate-driven under high emissions. Conclusions: Future ES management in the YZRB and YRB should adopt scenario-specific strategies, optimizing land use under low-emission pathways and applying climate-adaptive interventions under high-emission scenarios to sustain ES provision.

Gauge-measured precipitation data have long been recognized to underestimate actual precipitation due to wind-induced error, trace precipitation, and wetting loss, which affects the spatial and temporal characteristics of precipitation. In this study, we examined spatial and temporal differences in wet and dry spell indices based on original (Po) and corrected (Pc) precipitation data and their correlations with large-scale circulation indices (LSCIs) in Southwest China during 1961–2019. The main conclusions were: (1) Pc-based trends in wet/dry spell indices were generally more pronounced than Po-based. Specifically, when Pc-based, more stations had significant changes in the MWS, MLWS, MPWS, PWS95, FWW, FDW, MDS, MLDS, NLDS, and DDS95 indices, while fewer had significant changes in the NWS, NDS, FDD, and FWD indices. (2) Spearman’s results showed that more LSCIs were significantly related to the Pc-based wet/dry spell indices than Po-based. Po-based and Pc-based MWS, Po-based MDS, and Pc-based NLDS were significantly related to the most LSCIs. Therefore, taking them as examples, wavelet transform coherence (WTC) and partial wavelet coherence (PWC) were used to explore the coherence with LSCIs. WTC results showed South Asian Summer Monsoon Index (SASMI) + Po-based MWS, Arctic Oscillation (AO) + Po-based MDS, SASMI + Pc-based MWS, Asia Polar Vortex Intensity Index (APVI) + Pc-based NLDS exhibited the most obvious periodic resonance with main resonance periods of 2.13~7.8 year, 2.19~10.41 year, 2.13~12.13 year, 2.75~18.56 year, respectively. Since WTC may arbitrarily ignore the interaction between LSCIs, PWC is adopted for further analysis. PWC results showed the coherence of AO +Po-based MDS significantly increased after eliminating the Nino Eastern Pacific index (NEP) influence, with the main resonance period of 6.56~18.56 year. This study clearly demonstrated that corrected precipitation data should be used to improve the accuracy of drought assessments, climate models, eco-hydrological models, etc.