Abstract
Salt marshes are vital estuarine ecosystems that have experienced significant global declines due to sediment dynamics and rising sea levels. Monitoring the dynamics of these habitats is crucial for elucidating the mechanisms driving such changes. This study investigates the spatiotemporal dynamics of salt marshes on JiuDuan Shoal, the largest uninhabited island in the Changjiang Estuary, from 2002 to 2022. Utilizing advanced machine learning techniques, we analyzed a comprehensive dataset comprising Landsat imagery, hydro-sediment measurements, and localized sea level rise data. The results reveal that salt marshes on JiuDuan Shoal underwent substantial seaward expansion, averaging 3.66 km2/yr, with vertical accretion rates of 0.15 m/yr. Conversely, bare flats shifted from slight deposition (0.01 m/yr from 2002 to 2014) to erosion (0.07 m/yr from 2014 to 2022). Spatial analyses identified distinct expansion patterns, with the Upper Shoal extending northwestward and the Middle-Lower Shoal expanding southwestward. Notably, enhanced tidal currents facilitated continued sediment deposition despite a more than 70 % decline in fluvial sediment discharge. The hydrodynamic changes from the Deep Waterway Project contribute to the observed spatial variability in salt marsh dynamics. Additionally, the invasion of Spartina alterniflora has accelerated the seaward marsh expansion. By elucidating the interplay between hydrodynamic changes and salt marsh resilience, our findings provide crucial insights for conservation strategies to safeguard coastal habitats in the face of ongoing environmental challenges.
| Original language | English |
|---|---|
| Article number | 114052 |
| Journal | Ecological Indicators |
| Volume | 178 |
| DOIs | |
| State | Published - Sep 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 14 Life Below Water
Keywords
- Machine learning
- Salt marsh
- Sea level rise
- Sediment transport
- Wetland dynamics
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