Revealing subtle vegetation productivity dynamics in China via a reference-based framework

Vegetation productivity exhibits substantial spatiotemporal heterogeneity under the combined influence of climate change and anthropogenic disturbance. However, conventional long-term assessments focus on absolute changes, neglecting ecological heterogeneity and climatic confounding, thus limiting their utility for ecosystem management. From ecological and human activity perspectives, we established a reference-based framework using undisturbed ecosystems as ecological baselines, to detect subtle vegetation productivity dynamics across China between 2000 and 2020, capturing deviations between observed and reference productivity. The results showed that the RBRA significantly improved the detection of productivity declines, identifying a decline-affected area in China 39 percentage points larger than that of the CAA, particularly in temperate humid zones and northern regions with high human activity. By combining RBRA and CAA, four vegetation productivity change categories (sustained improvement, potential improvement, latent degradation, and sustained degradation) were identified. At the ecological zone level, the Tibetan Plateau emerged as the primary hotspot of relative decline (80.41%), while over 50% of the humid south-central region achieved sustained improvement. At the human activity zone level, high-intensity zones exhibited over 42% latent degradation, whereas low-intensity areas were dominated by sustained improvement (48–61%). Attribution analysis revealed that while climatic constraints remained the dominant drivers of vegetation productivity change, degradation risks driven by land-use change and economic expansion were more clearly captured by the RBRA framework, particularly in vulnerable and human-impacted regions. Overall, the reference-based framework enhances sensitivity to subtle vegetation change signals and provides a robust scientific basis for targeted conservation and adaptive ecosystem management.