Integrating Dam-Induced Effects into a Bayesian eDNA-Hydrodynamic Model to Improve Fish Monitoring in Regulated...

Area of Science:

• Environmental Science
• Ecology
• Hydrology

Background:

• Dam-induced hydrological changes significantly impact riverine biodiversity.
• Environmental DNA (eDNA) is a promising tool for non-invasive biodiversity monitoring.
• Existing eDNA studies often neglect dam-related flow and sediment alterations, limiting accuracy in regulated rivers.

Purpose of the Study:

• To develop and validate a Bayesian framework integrating hydrodynamic modeling with eDNA characteristics.
• To explicitly incorporate dam-induced effects on eDNA transport and fate.
• To enhance the accuracy of biodiversity assessments in dam-regulated rivers.

Main Methods:

• Developed a Bayesian framework combining fish eDNA properties, hydrodynamic modeling, and species distribution modeling.
• Incorporated dam-specific effects on eDNA particle size (≤30 μm) and sedimentation velocities.
• Analyzed eDNA settling velocities in dam-influenced versus non-dammed river sections.

Main Results:

• Fish eDNA-adsorbing particles were predominantly small (≤30 μm), with sedimentation velocities ranging from 0.001 to 0.403 mm/s.
• Mean eDNA settling velocities were higher in dam-influenced (0.073 mm/s) compared to non-dammed (0.041 mm/s) sections.
• The integrated Bayesian model improved spatial prediction accuracy for fish genera by 18.3-22.9% compared to conventional models.

Conclusions:

• The developed framework provides a process-based approach to address eDNA transport uncertainties in regulated rivers.
• Probabilistically incorporating hydraulic effects enhances the ecological reliability of eDNA monitoring.
• This approach supports effective conservation strategies for biodiversity under anthropogenic flow alterations.