Differences in spring green up date and climate sensitivities of forest and grassland ecosystems across China

The spring green up date (GUD) is highly sensitive to climate change and serves as a key indicator of ecosystem change. With the rapid advancement of satellite sensor technology, an increasing number of vegetation indices have been employed to derive GUD. Although these developments have broadened the avenues for obtaining GUD, they have also introduced retrieval uncertainties, resulting in discrepancies in analyses of its long-term trends and driving factors. In this study, the GUD for forests and grasslands was derived from both normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF), and the differences in GUD – as well as their sensitivities to dominant preseason climatic factors – were comparatively analyzed. We found that although forest and grassland GUDs across China advanced significantly from 2001 to 2023, the GUD derived from SIF (S_GUD) exhibited an even faster rate of advancement, particularly in forested areas. Preseason total precipitation (Ptot) and preseason mean temperature (Tmp) dominated the variation in forest GUD, whereas preseason total evaporation (Evap) and Ptot together governed grassland GUD; the resulting sensitivities displayed pronounced spatial heterogeneity. In addition, the magnitude and spatial continuity of S_GUD’s sensitivity to dominant preseason climatic factors were generally higher than those of GUD derived from NDVI (M_GUD), indicating that SIF captures vegetation responses to meteorological drivers more directly and sensitively. Our study quantified the distinct mechanisms by which forest and grassland GUDs – derived from NDVI and SIF – respond to climate change, thereby offering a valuable reference for subsequent quantitative phenological analyses and for predicting vegetation distributions under future climate scenarios.