How temperature‐induced variation in musculoskeletal anatomy affects escape performance and survival of zebrafish (<i>Danio rerio</i>)
Bibliographic record
Abstract
Fishes are particularly sensitive to the effects of environmental conditions during early development, which can significantly impact adult morphology, performance, and survival. Previous research has highlighted the sensitivity of fishes to the effects of temperature during early development on vertebral number and muscle composition, which are both important determinants of an individual's swimming performance. In this study, we investigated the effect of developmental temperature on vertebral and muscle variation, and the subsequent effect of any variation on burst swimming performance in zebrafish (Danio rerio). Following development at a range of temperatures, all individuals were shifted to and maintained at a common temperature before startle responses were recorded and individuals were analyzed for either vertebral number or muscle composition. Our results indicate that developmental temperature does not significantly affect muscle composition, but can affect an individual's vertebral number, and that individuals with more vertebrae achieved greater displacement and velocities during C-start performance. To determine the ecological importance of this vertebral variation and to identify the potential selective factors behind it, we exposed populations of zebrafish with various vertebral numbers to native predators, needlenose garfish (Xenentodon cancila). We found that only caudal vertebral number was related to survival, and that survivors had the same caudal vertebral number across developmental temperatures. Overall, this work highlights the importance of including variation in musculoskeletal anatomy when investigating what is driving selection in fishes. J. Exp. Zool. 325A:25-40, 2016. © 2015 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".