Vegetation recovery following retrogressive thaw slumps across northern tundra regions

nature climate change Article https://doi.org/10.1038/s41558-026-02603-2 Vegetation recovery following retrogressive thaw slumps across northern tundra regions Received: 28 January 2025 Accepted: 26 February 2026 Zhuoxuan Xia 1,2,3, Lin Liu 1 , Ingmar Nitze 4, Nina Nesterova 4,5, Jurjen Van der Sluijs 6, Xiaofan Zhu7, Tonghua Wu 7, Ksenia Ermokhina Emma C. Hall 3, Rustam Khairullin9, Artem Khomutov 8 & Mark J. Lara , 8 2,3 Published online: xx xx xxxx Check for updates Warming permafrost is driving widespread terrain destabilization and collapse through retrogressive thaw slumps, stripping vegetation and releasing soil carbon. Despite increasing thaw slump disturbances in permafrost regions, the time and patterns of vegetation recovery remain uncertain. Here we estimate surface greenness recovery times and compositional changes following disturbances across northern tundra regions, using data from remote sensing imagery. Our findings reveal that low-stature vegetation recolonizes barren terrain in low-Arctic sites within a decade, followed by erect shrubs, resulting in greener surface than undisturbed areas. In contrast, vegetation recovery in high-Arctic and high-elevation sites requires over 30 years. Greenness recovery time (τ, years) varies widely but can be accurately predicted by a power-law function (1.35 × (GPP)−1.68, P < 0.05) based on solar-induced chlorophyll fluorescence-derived ecosystem gross primary productivity (GPP, kgC m−2 yr−1). We present a regionally scalable framework to quantify surface greenness recovery times and reveal divergent vegetation succession pathways following permafrost disturbances across tundra regions. Recent observations across Arctic and alpine regions reveal substantial greening and browning trends in response to disturbances, such as retrogressive thaw slumps (RTS)1,2 in ice-rich permafrost regions3. Over recent decades, RTS activity has increased dramatically4–6, with a 60-fold rise observed on Banks Island in the Canadian High Arctic from 1984 to 20157 and a threefold expansion on the Qinghai–Tibet Plateau between 2016 and 20228. RTS occur throughout the Northern Hemisphere permafrost regions9,10, eroding plant structures (including roots and aboveground biomass), mobilizing previously thawed sediments and soil organic carbon, thereby reducing ecosystem carbon sequestration and increasing microbial decomposition11–16. Nonetheless, RTS can stabilize once ground ice is depleted or insulated by sediments17,18, allowing vegetation succession (gradual process of change in the composition of plant communities over time) to recolonize disturbed areas19, increasing carbon sequestration. However, the stabilized RTS can re-activate within their disturbed boundaries when a deeper thaw occurs or when ground ice is re-exposed. Consequently, these RTS are considered chronic mass-wasting sites with long-term polycyclic activity (decades to centuries), resulting in complex morphologies and heterogeneous plant compositions20–22. Indeed, the close relationship between plant community composition and the stage of stabilization is well-known and recorded as chronosequences Department of Earth and Environmental Sciences, The Chinese University of Hong Kong, Hong Kong, China. 2Department of Plant Biology, University of Illinois Urbana–Champaign, Urbana, IL, USA. 3Department of Geography and Geographic Information Science, University of Illinois Urbana–Champaign, Urbana, IL, USA. 4Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany. 5Institute of Geosciences, University of Potsdam, Potsdam, Germany. 6Northwest Territories Centre for Geomatics, Government of Northwest Territories, Yellowknife, Northwest Territories, Canada. 7Cryosphere Research Station on the Qinghai–Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China. 8Earth Cryosphere Institute, Tyumen Scientific Centre SB RAS, Tyumen, Russia. 9b.geos, Korneuburg, Austria. e-mail: ; 1 Nature Climate Change Article https://doi.org/10.1038/s41558-026-02603-2 TL NT CQ 0.4 NDVI NDVI 0.6 20 40 Years since last RTS disturbance MD 80 –10 0 40 –10 70 0 10 TL CR PP 0.6 MD 0 10 20 30 40 5 10 50 60 HI –0.10 –0.05 WB –5 EB TP sh Ere ct 0.4 15 WQ n tio ta ge ve re atu YP 0.6 0 Years since last RTS disturbance CQ st wLo Years since last RTS disturbance WB 0.2 0 10 20 30 Years since last RTS disturbance EB Bare ground 40 YP NDVI 0.1 Continous permafrost 0.75 0.2 NDVI 20 Years since last RTS disturbance WQ NT 0.8 NDVI 10 Years since last RTS disturbance rub s 0 NDVI 0.2 0.4 0.4 NDVI NDVI 0.8 0.6 Discontinous permafrost Sporadic permafrost 0.50 Isolated permafrost Confidence interval 0.25 0 20 40 Years since last RTS disturbance –10 0 10 20 40 Years since last RTS disturbance 50 Fig. 1 | Time series of NDVI and the associated changes in PFT cover for each ecosystem. Coloured dots and grey plus symbols represent mean NDVI values for each RTS subpart, segmented by identified breakpoints (indicated by vertical lines). PFT cover is visualized using a ternary diagram showing the proportions of low-stature vegetation, erect shrubs and bare ground. Each dot (RTS subpart) is colour-coded on the basis of its PFT classification. The RTS subparts that lack vegetation surveys are shown in plus symbols. Black lines represent best-fit NDVI piecewise trends, with the grey bands representing the 95% confidence intervals. The red triangles on the map indicate the locations of four validation sites, including CR, PP, HI and TP. The basemap shows the circumpolar permafrost extent map. Basemap data from the US National Snow and Ice Data Center/World Data Center for Glaciology61. for several RTS field sites18,23–25, yet to date there is limited information for the Northern Hemisphere as a whole about any regional differences of vegetation recovery in terms of timing, composition and succession. Vegetation greenness can be assessed across large regions using multidecadal satellite-derived normalized difference vegetation index (NDVI) data3,26–28, which serve as an effective proxy for plant productivity. For instance, in Siberian boreal forests, MODIS-derived NDVI indicated greenness recovery (that is, same levels of landscape greenness) 13 years after wildfire disturbance29. Similarly, in Alaskan tundra dominated by lichens, mosses and dwarf shrubs, NDVI values of burned areas returned to undisturbed levels within 10 years, closely corresponding with the recovery time of functional plant diversity30. The growing availability of high-resolution satellite imagery has enhanced NDVI-based assessments, enabling precise detection and monitoring of regional vegetation change trajectories. Vegetation recovery patterns following RTS dis (...truncated)