Fish navigation of large dams emerges from their modulation of flow field experience

Authored by David L Smith, R Andrew Goodwin, Marcela Politano, Justin W Garvin, John M Nestler, Duncan Hay, James J Anderson, Larry J Weber, Eric Dimperio, Mark Timko

Date Published: 2014

DOI: 10.1073/pnas.1311874111

Sponsors: No sponsors listed

Platforms: MATLAB

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Navigating obstacles is innate to fish in rivers, but fragmentation of the world's rivers by more than 50,000 large dams threatens many of the fish migrations these waterways support. One limitation to mitigating the impacts of dams on fish is that we have a poor understanding of why some fish enter routes engineered for their safe travel around the dam but others pass through more dangerous routes. To understand fish movement through hydropower dam environments, we combine a computational fluid dynamics model of the flow field at a dam and a behavioral model in which simulated fish adjust swim orientation and speed to modulate their experience to water acceleration and pressure (depth). We fit the model to data on the passage of juvenile Pacific salmonids (Oncorhynchus spp.) at seven dams in the Columbia/Snake River system. Our findings from reproducing observed fish movement and passage patterns across 47 flow field conditions sampled over 14 y emphasize the role of experience and perception in the decision making of animals that can inform opportunities and limitations in living resources management and engineering design.

Tags

Migration behavior turbulence Movement ecology Columbia river-basin Brook trout Lateral-line Prey detection Salmon Acceleration