Evidence and interpretation of non-linear recession behaviour in a periglacial cliff at Port Foster, Deception Island (South Shetlands, Antarctica)

Abstract. Cliff recession in periglacial coastal environments is highly sensitive to climate-driven changes in temperature, sea ice, and permafrost dynamics. While previous studies have predominantly relied on linear models to describe shoreline retreat, these methods often fail to capture the non-linear, episodic, and threshold-driven nature of coastal erosion in cold regions. Moreover, the scarcity of high-resolution, long-term datasets in polar regions, particularly in Antarctica, has limited the development of predictive models tailored to these dynamic systems. This study aims to improve the understanding of long-term cliff recession patterns in periglacial environments by applying advanced non-linear statistical modelling to a multitemporal dataset. Focusing on the coastal bluffs of Port Foster, Deception Island (South Shetlands, Antarctica), we examined geomorphological changes over a 66-year period (1956–2022), using a unique combination of historical aerial photographs and high-resolution satellite imagery. Photogrammetric pre-processing, orthorectification, and manual digitisation of reference lines were integrated into a transect-based statistical analysis framework. The study applied both linear and non-linear least squares regression models – quadratic and sigmoidal – to reconstruct spatial-temporal erosion trends, with uncertainty-weighted parameters incorporated into the estimation. Results reveal a distinct shift from quasi-stable to accelerated recession after 2000, particularly in areas exposed to dominant marine and thermal forcing. Linear models underestimated these trends, while sigmoidal logistic models more accurately identified inflection points in erosion rates. Maximum recession rates reached up to 5 m/year in the central bluff segment. The findings underscore the importance of integrating non-linear modelling into coastal monitoring and management frameworks, especially in vulnerable and data-scarce polar environments. This approach provides a more realistic understanding of periglacial coastal dynamics and highlights the critical need for adaptive strategies to address climate-induced instability near strategic infrastructure such as research stations.