Decoupling anthropogenic and climate impacts on vegetation dynamics in China's Huaihe River Basin using geodetector

Understanding the spatiotemporal dynamics of vegetation under the coupled influence of climatic and anthropogenic drivers is crucial for ecological governance at the river basin scale. This study focuses on the Huaihe River Basin (HRB) in China, a climate-sensitive region spanning both northern and southern climatic zones. Previous studies have often overlooked the inherent temporal and spatial autocorrelation in NDVI time series within this region, which may lead to overestimation or underestimation of vegetation trends, as well as misidentification of spurious trends as statistically significant. To address spatial and temporal autocorrelation challenges, we developed a novel hybrid framework combining Univariate Stationary First-order Gaussian Autoregressive (AR1) modeling with spatial autocorrelation analysis (Moran's I index), enabling robust detection of vegetation trends, stability evaluation, and clustering characteristics. Combined with Geodetector, we quantified the impacts of climatic extremes, land use change, and urbanization on NDVI patterns(2000-2022). Key findings reveal: (1) A significant greening trend with mean annual NDVI increase of 0.00152 yr⁻¹ (p < 0.05), demonstrating basin-wide ecological improvement; (2) Spatially divergent patterns where 42.89% of the basin show significant NDVI growth, contrasted by 9.54% degradation areas. Notably, 47.57% exhibits non-significant increases, emphasizing the necessity of temporal autocorrelation correction in trend detection; (3) Geodetector analysis identifies land use type as the dominant spatial heterogeneity driver (q = 0.35-0.42), while extreme climatic events (particularly the 2000-2001 mega-drought) govern temporal anomalies. Urban expansion reduced vegetation cover, except near water bodies where NDVI remained stable. Interaction analysis revealed nonlinear synergies between anthropogenic activities (e.g., GDP, population) and climatic factors, emphasizing the need for adaptive policies in transitional ecosystems. These findings advocate for tiered management strategies incorporating climate-adaptive zoning, emphasizing riparian corridor conservation and dynamic land-use optimization to balance ecological restoration with urban development. This work offers a replicable framework for regional-scale ecological assessments.