Evidence map›Paper›PMID 42814717›Full record

ArticlePloS one2026

Behavior of downstream swimming brown trout in accelerating and high flow velocity - Movement matters.

Falko Wagner, Ianina Kopecki, Jelger Elings, Ulf Enders, Andreas Lindig, Kathrin Maltzahn, Tom Roessger, Márcio S Roth, Mansour Royan, Jürgen Stamm and 1 more

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Falko WagnerInstitute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany.ORCID https://orcid.org/0000-0003-3926-9966
Ianina KopeckiSJE - Ecohydraulic Engineering GmbH, Stuttgart, Germany.ORCID https://orcid.org/0009-0002-4827-2032
Jelger ElingsDepartment of Fish Ecology and Evolution, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, Switzerland.
Ulf EndersInstitute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany.
Andreas LindigInstitute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany.
Kathrin MaltzahnInstitute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany.
Tom RoessgerInstitute of Hydraulic Engineering and Technical Hydromechanics (IWD), TUD Dresden University of Technology, Dresden, Germany.ORCID https://orcid.org/0009-0007-9203-7546
Márcio S RothInstitute of Hydraulic Engineering and Technical Hydromechanics (IWD), TUD Dresden University of Technology, Dresden, Germany.ORCID https://orcid.org/0000-0003-3181-7876
Mansour RoyanInstitute of Freshwater Ecology and Fish Biology (IGF) Jena, Jena, Germany.
Jürgen StammInstitute of Hydraulic Engineering and Technical Hydromechanics (IWD), TUD Dresden University of Technology, Dresden, Germany.
Stefan HoernerLaboratory of Geophysical and Industrial Flows (LEGI), Grenoble INP, CNRS, University Grenoble-Alpes, Saint-Martin-d'Hères, France.ORCID https://orcid.org/0000-0001-9167-4964

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies on active and sedated fish passing through turbines and pumps show different mortality and injury rates for both cases. Consequently, fish behavior appears to play a substantial role in these outcomes. However, direct behavioral observations in hydraulic machines using quantitative parameters to draw conclusions about the underlying mechanisms are hardly possible and remain understudied. In this study, we examined the behavior of adult brown trout (Salmo trutta) in an experimental flume under hydraulic conditions characterized by strong flow acceleration and high velocities, two key hydraulic features of turbine and pump intakes. Fish movement behavior was analyzed based on a quantitative approach to enable the analysis of swimming behavior even in flow velocities exceeding the sprint swimming speed of fish. The application of Hidden Markov Models (HMM) to analyze activity states and movement modes of fish from video tracking data demonstrated significant effects of the spatial velocity gradient (SVG) and flow velocity on fish behavior. Notably, SVG emerged as the primary trigger for avoidance reactions when exceeding a threshold of 0.31 msm. Fish exhibited distinct movement patterns under dark and daylight conditions, with more avoidance reactions in darkness. Whereas a considerable proportion of fish in daylight increased their swimming activity in the zone where flow velocity exceeded sprint swimming speed, in dark conditions no activity peak occurred in the same zone. The results illustrate how hydraulic conditions and light influence fish behavior. Integrating the behavioral rules identified in this study into numerical mortality‑risk models could substantially improve their predictive accuracy. This enhanced understanding can support the design and optimization of fish protection solutions at hydropower facilities and pumping stations.

Indexed as

Behavior, AnimalSwimmingTroutAccelerationAnimalsHidden Markov ModelsVideo Recording

Identifiers

PMID42814717
PMCPMC13626365

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.