Potential vegetation greenness changes in the permafrost areas over the Tibetan Plateau under future climate warming

Permafrost degradation on the Tibetan Plateau is well-documented and expected to continue throughout this century. However, the impact of thawing permafrost on the greenness, distribution, composition, and resilience of vegetation in this region is not well understood. In this study, we combined a transient numerical permafrost model with machine learning algorithms to project the near-future thermal state of permafrost and vegetation greenness (represented by the Normalized Difference Vegetation Index [NDVI]) changes under two contrasting climate pathways (Shared Socioeconomic Pathway 1–2.6 [SSP1–2.6] and SSP5–8.5). Furthermore, we quantified the contribution of climatic and terrestrial variables to vegetation greenness evolution. By 2100, permafrost areas were expected to decrease by 20 ± 1 %, and 49 ± 1 % under the SSP1–2.6 and SSP5–8.5 scenarios, respectively, relative to the baseline period (2000–2018). Under the SSP1–2.6 scenarios, the mean annual ground temperature and active layer thickness were projected to experience stable fluctuations, while under the SSP5–8.5 scenarios, a significant increasing trend was anticipated. Satellite-based observations indicated an increasing trend of NDVI within the permafrost areas from 2000 to 2018 (0.01 per decade), mainly attributed to climatic factors. In the future, vegetation greenness in the permafrost areas is projected to increase under different climate scenarios, with varying degrees of change. This variation is primarily controlled by the surface air temperature, solar radiation and liquid water content at root zone during the growing season. Our modeling work provides a potential approach for investigating future vegetation greenness changes and offers more possibilities to improve understanding of the interaction between soil-vegetation-atmosphere in cold regions.