Abstract: Exploring the spatiotemporal evolution and differentiation patterns of nature reserves provides valuable insights for strengthening China's nature reserve system. Using panel data on nature reserve coverage (NRC) across 31 provinces, this study employs kernel density estimation, the Dagum Gini coefficient decomposition method, and exploratory spatiotemporal data analysis (ESTDA) to investigate regional disparities and spatiotemporal interactions in the establishment of nature reserves among the four major regions-eastern, central, western, and northeastern China-across individual provinces. Results show that: (1) From 1985 to 2020, the NRC in China increased at an average rate of 0.35%·a^-1, showing a trend of "slow increase at a low level to rapid growth and to fluctuation at a high level". Spatially, the provincial distribution displayed a pattern of "high in the north and west, low in the south and east." (2) Both the overall disparities in nature reserve coverage and those within the four major regions showed a fluctuating yet declining trend toward stabilization, with inter-regional net worth differences identified as the main source of variation. (3) The development of nature reserves across provinces exhibited significant positive spatial autocorrelation. In terms of local spatial structure and dependency, the western and northeastern regions showed stronger fluctuations, whereas the central and eastern regions remained relatively stable. During the spatiotemporal transition of coverage rates, a certain degree of transfer inertia and strong spatial dependence were observed. Most provinces in the central and eastern regions consistently maintained low coverage levels, making them key areas constraining the overall improvement of China's nature reserve coverage. Therefore, future development strategies for nature reserves should focus on narrowing the regional development gap, prioritizing conservation priority assessments in ecologically critical areas of the central and eastern regions, and enhancing cross-regional coordination effects.