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Fish migration modeling and habitat assessment in a complex fluvial system
Shikang Liu1, Nan Wang1, Carlo Gualtieri2
1State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, China.
Journal of Environmental Management
|January 17, 2025
Summary
Hydrodynamic factors influence fish migration. This study found linear factors like velocity dominate straight river reaches, while nonlinear factors like temperature and vortex intensity are key in confluences, improving aquatic ecology insights.
Area of Science:
- Aquatic Ecology
- Ichthyology
- Environmental Fluid Dynamics
Background:
- Fish migration is crucial for aquatic ecosystems and is significantly influenced by hydrodynamic forces.
- Understanding these drivers is essential for effective conservation of fish populations, particularly in diverse riverine environments.
Purpose of the Study:
- To investigate the specific hydrodynamic drivers influencing the migration patterns of Gymnocypris przewalskii.
- To compare these drivers in a straight river reach (SR) versus a confluence reach (CR) within the Qinghai Lake region.
- To develop an improved framework for fish habitat assessment integrating linear and nonlinear predictive methods.
Main Methods:
- Utilized a 3D numerical model to simulate river hydrodynamics.
- Analyzed fish density field data to correlate with environmental factors.
- Employed four predictive models, including Random Forest, to assess the influence of thirteen hydrodynamic factors (e.g., water depth, velocity, temperature, turbulent kinetic energy, vortex intensity).
Main Results:
- In the SR, linear factors such as flow velocity and turbulent kinetic energy were the primary drivers of fish migration.
- In the CR, nonlinear factors including water temperature and vortex intensity were dominant.
- Fish migration patterns in CR were also significantly influenced by nonlinear factors.
- Random Forest models demonstrated higher precision in habitat assessment compared to traditional methods.
- Fish swimming ability was found to correlate with migration direction.
Conclusions:
- Hydrodynamic drivers of fish migration differ significantly between straight and confluence river reaches.
- Integrating fish swimming ability with habitat assessment methods enhances adaptability in complex fluvial systems.
- A novel workflow combining linear and nonlinear predictive methods offers improved fish habitat assessment and conservation strategies for diverse aquatic environments.
Keywords:
Fish migrationHabitat assessmentHydrodynamicsPopulation density analysisPredictive modelingRandom forestRiver confluenceMore Related Videos
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