Swimming activity and energetic costs of adult lake sturgeon during fishway passage
Bibliographic record
Abstract
Fish migrations through riverine systems can be energetically demanding, and the presence of fishways to facilitate upstream passage can add an additional energetic cost that may directly affect fitness. Successful fishway passage is a function of the ability of fish to select appropriate paths and swimming strategies that do not exceed their swimming capacity. Triaxial accelerometers were used to estimate the energetic expenditure of adult lake sturgeon (Acipenser fulvescens) swimming through a vertical slot fishway, to determine whether individual behaviour or path selection, resulting in differences in cumulative energy use, explain fishway passage success. Most individuals attempted to pass the fishway (n=30/44; 68%), although successful passage only occurred for a subset of those attempting (n=7/30; 23%). High-speed swimming was rarely observed during upstream passage through fishway basins, and was of short duration. Two turning basins delayed passage, subsequently resulting in a higher energetic cost. The rate at which energy was expended did not differ among successful and unsuccessful individuals, although successful sturgeon exhibited higher costs of transport (42.75 versus 25.85 J kg(-1) m(-1)). Energy expenditure metrics were not predictive of successful fishway passage, leading us to conclude that other endogenous or exogenous factors influence passage success. In a practical application of field measurements of energy expenditure, we demonstrate that fishway passage through a structure designed to facilitate migration does result in an energetic loss for lake sturgeon (3249-16,331 J kg(-1)), equivalent to individuals travelling 5.8-28.2 km in a lentic system.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".