This paper comprehensively used three methods to explore the global and local impact mechanism of socioeconomic on ecosystem services value in Beijing-Tianjin-Hebei region, which included principal component analysis (PAC), ordinary least square (OLS) and geographic weighted regression (GWR). The results suggested that, the primary industry related factors were the main socioeconomic factors, while factors such as the second industry, the third industry, the fiscal revenue and so on, had little effect on it. Socioeconomic factors can affect or change the value of ecosystem services to a certain extent. The comprehensive factor of primary industry had a negative effect, and the negative effect of the total population factor was weaker than the comprehensive factor, meanwhile, the effect of the simplification factor of the primary industry was positive or negative. The local model of a PCA-GWR can better solve the spatial non-stationarity of the dependent and the independent variables, and the local model was better than the global model of OLS and PCA-OLS. A standard GWR model can be further improved to reflect the local differences of the impact mechanism in more detail.

Vegetation plays an important role in the hydrological cycle, carbon storage and regional climate. It provides multiple ecosystem services, regulates ecosystem structure and promotes the sustainable and stable development of the earth’s ecosystem. Under the interference of the ever-changing environment, vegetation vulnerability is increasingly evident. This study focuses on Yunnan Province, China, where we analyze the spatiotemporal dynamics of NDVI at both provincial and municipal scales. Utilizing methods such as geographical detectors, time-lag analysis, and residual analysis, we identify key drivers of NDVI changes in Yunnan. From 2001 to 2023, the multi-year average NDVI in Yunnan decreases spatially from southwest to southeast, with the annual maximum NDVI increasing at a rate of 0.025 per decade. Qujing City exhibits the fastest NDVI growth, while Diqing City shows the slowest. Vegetation degradation is primarily concentrated in central Yunnan. The NDVI in Yunnan demonstrates significant spatial heterogeneity, influenced by a combination of climatic, topographic, and anthropogenic factors. The interaction between land use type and precipitation is identified as a key driver, explaining over 50% of the spatial distribution of NDVI. Approximately 83% and 82% of vegetated areas in Yunnan exhibit delayed responses to precipitation and temperature changes, respectively. Notably, 73% of the NDVI increase and 7% of the NDVI decrease in Yunnan were jointly affected by climate change and human activities, and positive contributions from these factors cover 92% and 90% of the area, respectively. The impact of human activities on vegetation is mainly positive, although urbanization in central Yunnan significantly inhibits NDVI. By elucidating key mechanisms, this work fosters balanced vegetation–environment synergies in Yunnan and supports the building of ecological safeguards in China.

Soil and water conservation measures (SWCM) are increasingly adopted to combat erosion and enhance carbon sequestration, yet their net effects on soil organic carbon (SOC) pools, particularly the balance between active and stable fractions, remain contentious, especially along complex hillslope terrains. To address this, we conducted a slope-position-resolved investigation across nine runoff plots under diverse SWCM (cropland and forestland) in the Danjiangkou Reservoir's Hujia Mountain watershed, analyzing SOC fractions and carbon management index (CMI) across two growth seasons. Our findings challenge the view that all SWCM uniformly promote carbon accumulation: only Stone step and Natural forest increased total SOC (by 0.10 and 0.95 g·kg-1, respectively), whereas upper-slope cropland measures suffered substantial losses (up to -2.74 g·kg-1). Structural analysis revealed that recalcitrant carbon constituted the majority (77%–83%) of the SOC pool, with active carbon (17%–24%) driving short-term fluctuations, suggesting that carbon pool stability depends more on fraction composition than total stock changes. Critically, the coupling between carbon fractions and nutrients exhibited strong slope-position dependency: total phosphorus consistently facilitated carbon accumulation, total potassium became progressively more positively associated downslope, while total nitrogen remained decoupled from carbon dynamics. Forestland systems provided greater carbon pool stability, whereas cropland showed higher responsiveness in CMI. We conclude that effective carbon management in reservoir watersheds must move beyond land-use type alone and adopt slope-specific strategies that consider both carbon fraction dynamics and nutrient interactions, offering a mechanistic basis for optimizing SWCM under China's dual-carbon strategy.

Meteorological factors are one of the natural factors, which affect ecosystem services value (ESV). Influence of meteorological factors was studied in Beijing-Tianjin-Hebei region using ordinary least square (OLS) with geographical weighted regression (GWR). The main aim of this study was to reveal the differences in the influence mechanism at the global and local levels. The main meteorological factors influencing ESV were temperature and precipitation, followed by humidity. Days with annual daily precipitation≥0.1mm, annual minimum precipitation and annual average relative humidity were three important meteorological factors. Annual temperature range, annual minimum precipitation, days with annual daily precipitation≥0.1mm, in particular, the last one had an obvious positive effect. The positive and negative effects of annual average relative humidity were coexisting, and the negative effect was the main. It was obvious that the spatial distribution characteristics of the local influence mechanism. The local model of GWR can better solve the spatial non-stationarity of the dependent and independent variables, thus it was better than the global model of OLS. The results also provide detailed field information on the different effects of meteorological factors at different locations.

Meteorological factors are one of the natural factors, which affect ecosystem services value(ESV). Influence of meteorological factors was studied in Beijing-Tianjin-Hebei region using odinary least square (OLS) with geographical weighted regression (GWR). The main aim of this study was to reveal the differences in the influence mechanism at the global and local levels. The main meteorological factors influencing ESV were temperature and precipitation, followed by humidity. Days with annual daily precipitation≥0.1mm, annual minimum precipitation and annual average relative humidity were three important meteorological factors. Annual temperature range, annual minimum precipitation, days with annual daily precipitation≥0.1mm, in particular, the last one had an obvious positive effect. The positive and negative effects of annual average relative humidity were coexisting, and the negative effect was the main. It was obvious that the spatial distribution characteristics of the local influence mechanism. The local model of GWR can better solve the spatial non-stationarity of the dependent and independent variables, thus it was better than the global model of OLS. The results also provide detailed field information on the different effects of meteorological factors at different locations.