Effects of permafrost thaw on vegetation productivity

When the permafrost thaws, it brings changes in soil hydrothermal conditions and nutrient levels, which can influence vegetation dynamics. The impact of permafrost degradation on vegetation growth with a warming climate and rising carbon dioxide levels remains unclear. This presentation synthesizes various ground observation records, satellite data, and multi-model multi-scenario data from Phase 6 of the Coupled Model Comparison Project to drive the machine learning models to investigate the contribution of deepening active layers to vegetation productivity at different growth stages and how these changes may vary under different shared socioeconomic pathways in the Northern Hemisphere. The results show that the machine learning model effectively simulates changes in permafrost active layer in the northern hemisphere. Currently, most permafrost in the northern Hemisphere show a positive correlation between active layer thickness (ALT) and vegetation gross primary productivity (GPP), with ALT explaining 8.5%-21.5% of the variation in permafrost GPP across the region. Tundra, temperate coniferous forests, and alpine grasslands are the most impacted vegetation types as the active layer thickens due to tundra degradation. However, in the future, ALT's contribution to GPP is expected to weaken further, especially under the high emission scenario SSP585. These findings help to improve our understanding of permafrost-vegetation feedbacks under the influence of climate change and human activities, and can be leveraged for optimizing simulations of carbon cycle processes in terrestrial ecosystems.