Typhoon-driven spatiotemporal dynamics of landslides and the implications on carbon fluxes in a subtropical montane forest

Long-term spatiotemporal mapping of landslides is crucial for understanding land surface dynamics and their impact on forest carbon fluxes. In a warming climate, clarifying how landslides interact with changing rainfall and typhoon extremes is critical for hazard assessment and regional forest carbon budgets. This study analyzed 33 years (1990–2022) of Landsat imagery and topography using machine learning (Random Forest) to map landslide dynamics in a 24,386-ha subtropical montane forest in Northeast Taiwan. We also quantified forest aboveground biomass (AGB) losses from landslides using temporally corresponding Landsat and lidar data. We observed pronounced interannual variability, with total landslide coverage ranging from 0.68 % to 3.19 %, and forest-to-landslide transitions driving annual AGB losses of 2–85 Gg yr⁻¹. Although landslide frequency, persistence, and reoccurrence declined exponentially over time, nearly half of affected sites failed repeatedly, indicating persistent spatial susceptibility. Elevation, slope, and aspect emerged as key topographic controls on landslide susceptibility. Extreme rainfall during typhoons, particularly daily maxima (r = 0.559, p = 0.004), was the most dominant driver, underscoring typhoons as primary drivers of disturbance and biomass loss, with AGB losses approximately 14-fold higher in extreme typhoon years than in quiet years. Post-landslide vegetation recovery exhibited a highly variable trajectory and plateaued at ∼63 % of pre-disturbance biomass within 25 years, based on a non-linear asymptotic model. Our analysis highlights that while vegetation recovery contributes to carbon uptake, its effectiveness is constrained by recurrent landslides driven by slope instability and frequent extreme rainfall. As climate change increases typhoon intensity and extreme rainfall frequency, landslide risks and associated carbon losses are expected to rise, while repeated landslides may further disrupt recovery and amplify uncertainty in future carbon dynamics. These findings underscore the need to integrate spatiotemporal disturbance–recovery interactions into global carbon cycle assessments, particularly in vulnerable, typhoon-prone mountain regions like East Asia.