Warmer springs may lead to more frequent spawning in lake sturgeon
Bibliographic record
Abstract
Environmental variation and life history influence reproductive behavior in fishes. Many iteroparous fishes, like lake sturgeon, may transition between spawning and non-spawning states among years in response to recent spawning history, sex, and environmental variation leading to variation in interannual spawning intervals, with strong implications for conservation and management. We combined three capture–mark–recapture datasets to jointly estimate interannual spawning state transitions in lake sturgeon of the lower Niagara River between 2011 and 2020, where temperature drives strong interannual environmental variation. Our Bayesian multi-state capture–mark–recapture model suggested interannual spawning state transitions were best explained by sex-specific responses to water temperatures during the previous spring. With higher spring temperatures, males were less likely to delay spawning, while females were more likely to re-engage in spawning after delaying. Our model thus suggests that both sexes shorten intervals between spawning years in response to warming. Conservation and management of lake sturgeon in the lower Niagara River should account for the link between spawning behavior and environmental temperature, underscoring the need to address similar questions in other long-lived imperiled taxa.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".