Spatiotemporal vegetation changes serve as a key indicator of regional ecological environmental quality and provide crucial guidance for developing strategies for regional ecological protection and sustainable development. Currently, vegetation change studies in the Yangtze River Basin primarily rely on the Normalized Difference Vegetation Index (NDVI). However, the NDVI is susceptible to atmospheric and soil conditions and exhibits saturation phenomena in areas with high vegetation coverage. In contrast, the kernel NDVI (kNDVI) demonstrates significant advantages in suppressing background noise and improving saturation thresholds through nonlinear kernel transformation, thereby enhancing sensitivity to vegetation changes. To elucidate the spatiotemporal characteristics and driving mechanisms of vegetation changes in the Yangtze River Basin, this study constructed a temporal kNDVI using MOD09GA data from 2000 to 2022. Considering sectional heterogeneity, rather than analyzing the entire region as a whole as in previous studies, this research examined spatiotemporal evolution characteristics by sections using four statistical metrics. Subsequently, Partial Least Squares Path Modeling (PLSPM) was innovatively introduced to quantitatively analyze the influence mechanisms of topographic, climatic, pedological, and socioeconomic factors. Compared to traditional correlation analysis and the geographical detector method, PLSPM, as a theoretically driven statistical method, can simultaneously process path relationships among multiple latent variables, effectively revealing the intensity and pathways of driving factors’ influences, while providing more credible and interpretable explanations for kNDVI variation mechanisms. Results indicate that the overall kNDVI in the Yangtze River Basin exhibited an upward trend, with the midstream demonstrating the most significant improvement with minimal interannual fluctuations, the upstream displaying an east-increasing and west-stable spatial pattern, and the downstream demonstrating coexisting improvement and degradation characteristics, with these trends expected to persist. Driving mechanism analysis reveals that the upstream was predominantly influenced by the climatic factor, the midstream was dominated by terrain, and the downstream displayed terrain–soil coupling effects. Based on these findings, it is recommended that the upstream focus on enhancing vegetation adaptation management to climate change, the midstream need to coordinate the relationship between topography and human activities, and the downstream should concentrate on controlling the negative impacts of urban expansion on vegetation.

Understanding regional precipitation extreme responses to global warming is critical for climate adaptation planning, yet threshold behaviors and dry‐wet anomaly asymmetries remain poorly characterized at provincial scales. This study quantifies drought and wet‐anomaly frequency evolution across four warming levels (1.5°C, 2.0°C, 3.0°C, 4.0°C) in Shandong Province, China, over the period 1979–2100 (relative to a 1979–2008 baseline), using high‐resolution (0.1°) downscaled CMIP6 data from 19 climate models under multiple emission scenarios (SSP2‐4.5 and SSP5‐8.5). We apply the Standardized Precipitation Index and the Intensity‐Area‐Duration framework to characterize compound event severity. Results reveal systematic dry‐wet asymmetry: dry‐anomaly frequency (SPI‐12 ≤ −1.0) declines 43.5%–51.8% from its 6.5% baseline, while wet‐anomaly frequency (SPI‐12 ≥ +1.0) increases from its 6.4% baseline by 82.3% at 1.5°C to 232.7% at 4.0°C. The historical 0.81:1 dry‐wet anomaly ratio collapses to 0.50:1 at 4.0°C, creating unprecedented wet‐anomaly‐dominated conditions. Notably, the largest single‐step increment in wet‐anomaly frequency (+4.1 percentage points from 3.0°C to 4.0°C) is approximately double the preceding 2.0 to 3.0°C increment (+2.1 pp), a pattern consistent with published process studies linking high‐warming regimes to reorganized convective systems, soil moisture saturation thresholds, and positive wetness‐evaporation feedbacks—though these mechanisms are not directly tested and formal statistical tests do not confirm significant nonlinear acceleration at α = 0.05. Spatial analysis reveals remarkable uniformity in wet‐anomaly amplification, with increases of +22–37 percentage points in northwestern and central plains. The Intensity‐Area‐Duration framework demonstrates that compound event severity escalates dramatically, with the severity index reaching 43.9 ± 35.1 at 4.0°C—a + 307% increase from 1.5°C—driven by event durations extending to 38.3 months. Scenario comparison reveals pathway divergence at 2040–2060; limiting warming to approximately 3.0°C avoids progression to the highest warming level examined and substantially constrains wet‐anomaly frequency escalation in the latter half of the century. These findings underscore the importance of near‐term mitigation and highlight strong warming‐level dependence in regional wet‐anomaly responses.