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1. Quantifying Postfire Aeolian Sediment Transport Using Rare Earth Element Tracers

   https://doi.org/10.1002/2017JG004284  

   Dukes, David; Gonzales, Howell B.; Ravi, Sujith; Grandstaff, David E.; Van Pelt, R. Scott; Li, Junran; Wang, Guan; Sankey, Joel B. (January 2018, Journal of Geophysical Research: Biogeosciences)
2. Dense vegetation hinders sediment transport toward saltmarsh interiors

   https://doi.org/10.1002/lol2.10436  

   Gourgue, Olivier; Belliard, Jean‐Philippe; Xu, Yiyang; Kleinhans, Maarten G; Fagherazzi, Sergio; Temmerman, Stijn (December 2024, Limnology and Oceanography Letters)

   Abstract To save saltmarshes and their valuable ecosystem services from sea level rise, it is crucial to understand their natural ability to gain elevation by sediment accretion. In that context, a widely accepted paradigm is that dense vegetation favors sediment accretion and hence saltmarsh resilience to sea level rise. Here, however, we reveal how dense vegetation can inhibit sediment accretion on saltmarsh platforms. Using a process‐based modeling approach to simulate biogeomorphic development of typical saltmarsh landscapes, we identify two key mechanisms by which vegetation hinders sediment transport from tidal channels toward saltmarsh interiors. First, vegetation concentrates tidal flow and sediment transport inside channels, reducing sediment supply to platforms. Second, vegetation enhances sediment deposition near channels, limiting sediment availability for platform interiors. Our findings suggest that the resilience of saltmarshes to sea level rise may be more limited than previously thought. 

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3. Aeolian sediment in El Paso, Texas: Elevated desert sand deposition rates and dust concentrations, enhanced by drought and urban sources

   https://doi.org/10.1016/j.atmosenv.2025.121029  

   Gill, Thomas E; Rivas, Jose A; Walsh, Elizabeth J (March 2025, Atmospheric Environment)
4. On the development of a magnetic susceptibility‐based tracer for aeolian sediment transport research

   https://doi.org/10.1002/esp.4536  

   Ravi, Sujith; Gonzales, Howell B.; Buynevich, Ilya V.; Li, Junran; Sankey, Joel B.; Dukes, David; Wang, Guan (November 2018, Earth Surface Processes and Landforms)
5. A New Approach to Account for Species‐Specific Sand Capture by Plants in an Aeolian Sediment Transport and Coastal Dune Building Model

   https://doi.org/10.1029/2024JF007867  

   Laporte‐Fauret, Quentin; Wengrove, Meagan; Ruggiero, Peter; Hacker, Sally D; Cohn, Nicholas; Zarnetske, Phoebe L; Piercy, Candice D (December 2024, Journal of Geophysical Research: Earth Surface)

   Vegetation plays a crucial role in coastal dune building. Species‐specific plant characteristics can modulate sediment transport and dune shape, but this factor is absent in most dune building numerical models. Here, we develop a new approach to implement species‐specific vegetation characteristics into a process‐based aeolian sediment transport model. Using a three‐step approach, we incorporated the morphological differences of three dune grass species dominant in the US Pacific Northwest coast (European beachgrassAmmophila arenaria, American beachgrassA. breviligulata, and American dune grassLeymus mollis) into the model AeoLiS. First, we projected the tiller frontal area of each grass species onto a high resolution grid and then re‐scaled the grid to account for the associated vegetation cover for each species. Next, we calibrated the bed shear stress in the numerical model to replicate the actual sand capture efficiency of each species, as measured in a previously published wind tunnel experiment. Simulations were then performed to model sand bedform development within the grass canopies with the same shoot densities for all species and with more realistic average field densities. The species‐specific model shows a significant improvement over the standard model by (a) accurately simulating the sand capture efficiency from the wind tunnel experiment for the grass species and (b) simulating bedform morphology representative of each species' characteristic bedform morphology using realistic field vegetation density. This novel approach to dune modeling will improve spatial and temporal predictions of dune morphologic development and coastal vulnerability under local vegetation conditions and variations in sand delivery. 

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