Large amounts of data accumulated in ecology and related environmental sciences arouses urgent need to explore useful patterns and information in it.Here we propose coclustering-based methods and a temperatures-photoperiod driven phenological model to explore spatio-temporal differentiation in long-term spring phenology in China.First,we created the first bloom date (FBD) dataset in China from 1979 to 2018 using the extended spring indices and China Meteorological Forcing Dataset.Then we analyzed the dataset using Bregman block average co-clustering algorithm with I-divergence (BBAC_I) and k-means algorithm.Such analysis delineated the spatially-continuous phenoregions in China for the first time.Results showed three spatial pattems of FBD in China and their temporal dynamics for 40 years (1979-2018).More specifically,overall late spring onsets occur in 1979-1996,in which areas located in Jiangxi,northern Xinjiang and middle Inner Mongolia experienced constant changing spring onsets.Overall increasingly earlier spring onsets occur in 1997-2012,in which areas located in Fujian,Hunan and eastern Heilongjiang experienced the most variable spring onsets.Stable early spring onsets over China occur after 2012.Results also showed 15 temporal patterns of spring phenology over the study period and their spatial delineation in China.More specifically,most areas in China have the same FBD category for 40 years while northern Guizhou,Hunan and southern Hubei have the same category in 1979-1997 and then fluctuate between different categories.Finally,our results have certain directive significance on the design of existing observational sites in Chinese Phenological Network.