Understanding the spatial and temporal evolution of ecosystem service values (ESVs) and their underlying drivers is essential for advancing ecological conservation and sustainable management in protected areas. The study area comprises ten national park system pilot areas in China, covering approximately 220,000 km² and encompassing environments ranging from tropical forests to alpine ecosystems. Using 1 km gridded data from the Spatial Distribution Dataset of Terrestrial Ecosystem Service Value in China for five observation years (2000, 2005, 2010, 2015, and 2020), we examined ESV dynamics, inter-service relationships, and their associated drivers through Mann–Kendall trend analysis, Spearman correlation analysis, partial least squares structural equation modeling (PLS-SEM), and Geodetector. Spatial trend analysis showed that, from 2000 to 2020, 58% of the total study area exhibited a decreasing ESV trend, 38% showed an increasing trend, and the remaining 4% remained stable; statistically significant decreases and increases accounted for 0.9% and 0.2% of the area, respectively. At the park level, ESVs increased in Three-River Source and Qilian Mountain but declined most markedly in Hainan Tropical Rainforest National Park. Positive associations among ecosystem services were more widespread than negative associations, although their spatial patterns differed among parks. Climatic, topographic, and socioeconomic variables showed service-specific associations with the estimated ESVs. Because policy implementation was not directly modeled, the analysis does not isolate the effects of national park designation or specific conservation measures. These findings can provide a national comparative baseline for monitoring ESV dynamics and may inform park-specific ecosystem service-oriented management strategies in China’s national parks.

Under the Yellow River Basin’s strategic imperative of ecological protection and high-quality development, the critical question is whether rapid urbanization’s population agglomeration and land expansion are genuinely aligned with-or increasingly decoupled from-underlying economic vitality. To address this, we construct a unified analytical framework that synchronously captures coupling coordination, decoupling trajectories, and land-use efficiency, operationalized through multi-source county-level panel data for the Jinan Metropolitan Area in lower Yellow River Basin across 2000, 2010, and 2020. Unlike conventional two-dimensional assessments, the framework distinguishes system coordination, evolutionary direction, and input–output performance while using harmonized nighttime light data to capture the spatial intensity of economic vitality. The results show that: (1) the mean county-level coordination grade increased from 4.76 to 5.32, although strong core–periphery disparities persisted; (2) the decoupling structure shifted from relative homogeneity to pronounced differentiation, and strongly decoupled counties accounted for 48% of all units by 2020; and (3) average efficiency rose from 0.25 to 0.39, but most counties remained below the efficiency frontier, producing a pattern of central agglomeration and peripheral dispersion. Cross-classification further identifies coordinated but inefficient, efficient but dysfunctional, and low-coordination–low-efficiency trajectories that cannot be detected using a single model. The framework therefore provides a transferable diagnostic tool for differentiated territorial planning in metropolitan regions undergoing rapid structural transformation.

Marine protected areas (MPAs) remain insufficient to meet global conservation ambitions. We overlaid four biodiversity-prioritization frameworks to map marine conservation priority zones (MCPZs), then intersected them with a published marine-wilderness layer to identify marine ecological expansion zones (MEEZs). The four sources contribute equally to a descriptive agreement score; the wilderness layer indicates low mapped cumulative human impact, not implementation cost. The global mapped MEEZ extent is 10,583,422.69 km². Within the 101 IHO sea areas used for scenario accounting, MEEZs cover 10,576,936.16 km² (2.91% of their summed area), and 16.92% overlaps effective 2026 protected-area (PA) polygons. Adding currently unprotected MEEZs to this PA-only baseline would raise coverage from 9.69% to 9.70%, 9.90%, and 12.11% under conservative, moderate, and ambitious scenarios, respectively. The largest absolute additions occur in the South Pacific, Southern, and North Pacific Seas; the largest within-sea percentage-point gains occur in the Beaufort, Chukchi, and Barents Seas. These candidates are a first-stage spatial screen, not a complete pathway to 30% protection; regional ecological, social, and governance assessment remains necessary.