Antecedent Snowpack Conditions and Shifting Hydroclimatic Controls on Vegetation Productivity: Implications for Sustainable Watershed Management

Climate warming is altering seasonal snow regimes and vegetation phenology in cold regions, but the influence of snowmelt may extend well beyond spring thaw. We examined how snow-related associations with net primary productivity (NPP) changed across the growing season in the Naoli River Basin during 2014–2024. Monthly NPP was reconstructed using the Carnegie–Ames–Stanford Approach and evaluated against MODIS NPP. The growing season was divided into early (EGS), peak (PGS), and late (LGS) stages based on vegetation phenology. Generalized additive models identified contemporaneous, lagged, and cumulative associations of air temperature, precipitation, solar radiation, and snow water equivalent (SWE), while random forest and partial dependence analyses were used to compare driver importance and SWE–NPP responses. SWE showed antecedent associations, with AIC-selected April-referenced windows A0L4 (EGS; R2 = 0.23) and A0L3 (LGS; R2 = 0.24). Solar radiation remained the most important predictor, but its relative importance declined from 53.77% in the EGS to 42.56% in the LGS. SWE was more important than precipitation in the EGS (18.96% vs. 12.38%) and PGS (17.31% vs. 13.86%), whereas precipitation became more important in the LGS (19.75% vs. 15.13%). The SWE–NPP relationship also shifted from an overall declining response in the EGS to a nonlinear response in the PGS and a predominantly positive response in the LGS. These results highlight the value of considering antecedent snowpack conditions alongside growing-season climate in vegetation productivity monitoring, with implications for sustainable watershed management under climate change.