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Record W4412603653 · doi:10.1186/s40317-025-00420-6

The performance of 76 kHz positional acoustic telemetry is challenged by acoustic conditions in the tailrace of a hydroelectric dam

2025· article· en· W4412603653 on OpenAlex
Christopher Hill, Antóin M. O’Sullivan, R. Allen Curry, Tommi Linnansaari, Philip M. Harrison

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnimal Biotelemetry · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTelemetryBiotelemetryHydroelectricityBiologyAcousticsBioacousticsOceanographyFisheryMarine engineeringTelecommunicationsEcologyEngineeringGeologyPhysics

Abstract

fetched live from OpenAlex

Background: Positional acoustic telemetry permits high-resolution (2D and 3D) tracking of tagged fish based on the speed of sound and time at which acoustic signals are detected at independent receivers. Such positional data has important implications for understanding fish behavior in hydropower tailraces, where movement and fishway passage may be influenced by complex hydraulic conditions. However, environmental features common to these settings-such as rocks, vegetation, bubbles, and suspended particles-can reflect, scatter, or absorb acoustic signals, contributing to spatial and temporal variation in positioning error. Therefore, validating system performance in tailrace environments is important for study design and interpretation. We evaluated the performance of a 76 kHz positional acoustic telemetry system (LOTEK MAP) in the tailrace (0-500 m downstream) of a large (672 MW generating capacity) hydroelectric dam, an environment characterized by reflective surfaces, complex hydraulics, and ambient noise from power generation. Methods: , position estimates/total transmissions) for six stationary transmitters centered within two hydrophone arrays installed 0-150 m and 200-500 m downstream from the power station. Further, we used generalized linear models to explore how accuracy and position efficiency varied as a function of transmitter location, power station discharge (which represented variation in the acoustic environment at each hydrophone), and the number of receivers that contributed to position estimates. Results: , 0-150 m downstream) yielded no positional data. Performance improved marginally for the second array (i.e., 200-500 m downstream), but position efficiency was ultimately low (1%), variable across transmitter locations, and negatively correlated with discharge. When position estimates were obtained, positional accuracy was moderate (overall mean = 3 ± 3 m) and increased with the number of contributing receivers, but also varied in direction and magnitude as a function of transmitter location and discharge conditions. Conclusions: Performance of the telemetry system was limited by environmental conditions that influenced signal propagation at complex spatial and temporal scales and would ultimately challenge the interpretation of positional data for free-swimming fish in the tailrace. The telemetry system is likely not suitable for studies that require frequent and reliable positions in hydropower dam tailrace environments. Supplementary Information: The online version contains supplementary material available at 10.1186/s40317-025-00420-6.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.230
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it