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A model for evaluation of sediment exposure and burial for freshwater mussels from heavy particle sedimentation

May 14, 2024

Freshwater mussels (Bivalvia: Unionida) are an ecologically important faunal group. Excessive sediments, both in suspended and deposited formats, are believed to have negative effects on survival of freshwater mussels. However, there is a lack of quantitative tools for assessing the impact of abrupt and excessive sedimentation on freshwater mussel habitats. This gap in knowledge poses challenges for construction planning that necessitates evaluating sedimentation effects on mussels. In this paper, we present a simple Lagrangian particle tracking (LPT) model designed to investigate the downstream distances from the sediment release point where mussels may face risks of sediment exposure and burial during episodic sedimentation events. We validated the model in predicting the deposition of sands ranging from 125 to 625μm">625μm in diameter within an open channel. Subsequently, we applied the LPT model to a representative stretch of mussel habitats in the lower Osage River, Missouri, USA. Implementing the LPT model using computational fluid dynamics analysis of river hydrodynamics, we investigated the downstream distances impacted by a hypothetical sedimentation event. The results indicate that the mussels within tens and hundreds of meters may be at risk of burial under low and high flow conditions, respectively. Mussels within hundreds and potentially thousands of meters may be at risks of sediment exposure under low and high flow conditions, respectively. The impacted distance is highly dependent on the sediment diameters and flow conditions. These results contribute valuable insights into the potential impacts of sedimentation on freshwater mussel habitats, aiding in informed decision-making for construction projects near these critical aquatic ecosystems.

Publication Year 2024
Title A model for evaluation of sediment exposure and burial for freshwater mussels from heavy particle sedimentation
DOI 10.1016/j.ecolmodel.2024.110751
Authors Binbin Wang, Brandon James Sansom, Wenyu Zhu, James L. Kunz, M. Christopher Barnhart, Henry Brown, Stephen E. McMurray, Andrew D Roberts, Christopher Shulse, Caleb Knerr, Kathleen Trauth, Jeffery Steevens, Baolin Deng
Publication Type Article
Publication Subtype Journal Article
Series Title Ecological Modelling
Index ID 70256049
Record Source USGS Publications Warehouse
USGS Organization Columbia Environmental Research Center
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