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

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.

History and review of the habitat suitability criteria curve in applied aquatic ecology

“…The existing format for HSC's using only two hydraulic variables (average velocity and depth) and one general variable (cover) equally weighted and multiplied together to form a single index per discharge is a very restrictive format for describing a biological process as complex as aquatic habitat selection. We recommend a strategy parallel to the successful modelling approach used to develop design guidelines for downstream passage of emigrating juvenile salmon in the Pacific Northwest of the USA (Goodwin et al, ): Use or develop a modelling framework such as the Eulerian‐Lagrangian‐Agent Method (ELAM—Goodwin et al, ) to efficiently integrate computational fluid dynamics modelling (Eulerian component), descriptions of the movement paths and locations of individual tagged fish (Lagrangian component), and a representation of fish cognition (agent component). Build a strong mathematical and conceptual foundation for the habitat modelling framework similar to that developed for the movement model (e.g., Nestler et al, ; Nestler, Goodwin, Smith, & Anderson, ). Structure the agent component so that the modelled fish behaviour can be related to capabilities of the fish mechanosensory system (Nestler et al, ) and principles of fluvial geomorphology (Nestler et al, ) to ensure model fidelity to fish biology and physical habitat structure. For example, Nestler et al () evaluated 38 candidate hydraulic variables in their creation of defensible juvenile salmon movement rules. Confirm the performance of habitat models (equivalent to HSC curves) at different sites, times, and species as were used to confirm juvenile salmon movement rules (e.g., Weber, Goodwin, Li, & Nestler, ). Confirm the performance of the habitat summary variable (equivalent to WUA) to forecast population responses to flow at different sites, times, and species. …”

“…Shear, turbulence, velocity gradient, water acceleration, or any of a large number of different hydraulic variables could have been considered in the development of HSC curves to better explain the distribution of aquatic organisms. For example, velocity gradient was found to be a critical hydraulic variable for understanding the swim path selection of emigrating juvenile salmon at dams (Goodwin et al, ; Haro, Odeh, Noreika, & Castro‐Santos, ; Kemp, Gessel, & Williams, ; Nestler, Goodwin, Smith, Anderson, & Li, ) and may also be important for habitat selection. This omission is understandable during the initial development of HSC curves because neither measurement nor simulation tools were sufficiently sophisticated for use in more comprehensive habitat studies.…”

An Overview of Multi-Dimensional Models of the Sacramento–San Joaquin Delta

“…At the other end of the spectrum, one could imagine carrying out large-eddy simulation (LES) (c.f., Sotiropoulos 2015) to model the very detailed structure of flows at the proposed north Delta intakes. In this case, individual-based models of fish behavior (Goodwin et al 2014) could be combined with highresolution LES results to examine how interactions of flow and behavior would affect entrainment of out-migrating juvenile salmon. The fact that only relatively short periods of time (a few days) would need to be modeled makes this computationally feasible.…”

Integrating Fish Bioenergetics and Volitional Movement in Water Quality and Hydrodynamic Models

“…A simple demonstration of smart and dumb particle movement was shown for isothermal conditions in Brownlee Reservoir on the Snake River system. Further development of fish volitional models have also involved looking at detailed fish interaction with physical structures such as at dams (Goodwin et al 2014). …”