Impacts of river flow and thermal regimes on fish-growth dynamics during early life history
Bibliographic record
Abstract
Growth during early life stages is critical to fish population persistence. Few studies explore how river discharge and thermal regimes impact growth dynamics of young-of-the-year (YOY) fishes. We used otolith biochronologies and generalised additive mixed models to partition the effects of age, individual, river, temperature, discharge, and variance in discharge on daily growth rates of YOY fishes with an opportunistic life-history strategy: Galaxias vulgaris and Gobiomorphus breviceps. Growth of both species increased with temperature. Galaxias growth decreased with discharge, while Gobiomorphus growth increased with lowered discharge but only to a point (ca. 1/3 of median discharge), after which growth plateaued. Floods had a strong negative effect on YOY growth. Our study systems and species had different characteristics to those that formed the basis of the Riverscape Recruitment Synthesis Model (RRSM) and may explain why our results were only partially consistent with flow predictions for opportunistic species of the RRSM. Further, Galaxias growth was a negative function of high-frequency, daily variation in flow, and we present testable hypotheses to explain this result.
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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 | 0.001 | 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".