Multi‐decadal coastline dynamics in Suriname controlled by migrating subtidal mudbanks

For the development of climate-resilient coastal management strategies, which focus on challenges in the decades to come, it is critical to incorporate spatial and temporal variability of coastline changes. This is particularly true for the mud-dominated coastline of Suriname, part of the Guianas, where migrating subtidal mudbanks cause a cyclic instability of erosion and accretion of the coast that can be directly related to interbank and bank phases. The coastline hosts extensive mangrove forests, providing valuable ecosystem services to local communities. Recent studies on mudbank dynamics in Suriname predominantly focused on large-scale trends without accounting for local variability, or on local changes considering the dynamics of a single mudbank over relatively short time scales. Here we use a remote sensing approach, with sufficient spatial and temporal resolution and full spatial and temporal coverage, to quantify the influence of mudbank migration on spatiotemporal coastline dynamics along the entire coast of Suriname. We show that migration of six to eight subtidal mudbanks in front of the Suriname coast has a strong imprint on local coastline dynamics between 1986 and 2020, with an average 32 m/yr accretion during mudbank presence and 4 m/yr retreat of the coastline during mudbank absence. Yet, coastal erosion can still occur when mudbanks are present and coastal aggregation may happen in the absence of mudbanks, exemplifying local variability and thus suggesting the importance of other drivers of coastline changes. The novel remote sensing workflow allowed us to analyse local spatial and temporal variations in the magnitude and timing of expanding and retreating trajectories. Our results demonstrate that it is essential that all coastal behaviours, including changes that cannot be explained by the migration of mudbanks, are included in multi-decadal management frameworks that try to explain current variability, and predict future coastline changes in Suriname.