|Identifying hydro-geomorphological conditions for state shifts from bare tidal flats to vegetated tidal marshes|Wang, C.; Smolders, S.; Callaghan, D.P.; van Belzen, J.; Bouma, T.J.; Hu, Z.; Wen, Q.; Temmerman, S. (2020). Identifying hydro-geomorphological conditions for state shifts from bare tidal flats to vegetated tidal marshes. Remote Sens. 12(14): 2316. https://hdl.handle.net/10.3390/rs12142316
pending shift; stable ecosystem states; marsh formation; intertidal flats; LIDAR
|Auteurs|| || Top |
- Wang, C., meer
- Smolders, S., meer
- Callaghan, D.P.
- van Belzen, J., meer
High-lying vegetated marshes and low-lying bare mudflats have been suggested to be two stable states in intertidal ecosystems. Being able to identify the conditions enabling the shifts between these two stable states is of great importance for ecosystem management in general and the restoration of tidal marsh ecosystems in particular. However, the number of studies investigating the conditions for state shifts from bare mudflats to vegetated marshes remains relatively low. We developed a GIS approach to identify the locations of expected shifts from bare intertidal flats to vegetated marshes along a large estuary (Western Scheldt estuary, SW Netherlands), by analyzing the interactions between spatial patterns of vegetation biomass, elevation, tidal currents, and wind waves. We analyzed false-color aerial images for locating marshes, LIDAR-based digital elevation models, and spatial model simulations of tidal currents and wind waves at the whole estuary scale (~326 km²). Our results demonstrate that: (1) Bimodality in vegetation biomass and intertidal elevation co-occur; (2) the tidal currents and wind waves change abruptly at the transitions between the low-elevation bare state and high-elevation vegetated state. These findings suggest that biogeomorphic feedback between vegetation growth, currents, waves, and sediment dynamics causes the state shifts from bare mudflats to vegetated marshes. Our findings are translated into a GIS approach (logistic regression) to identify the locations of shifts from bare to vegetated states during the studied period based on spatial patterns of elevation, current, and wave orbital velocities. This GIS approach can provide a scientific basis for the management and restoration of tidal marshes.