The timing of spring warming shapes reproductive effort in a warm-water fish: the role of mismatches between hepatic and gonadal processes
Bibliographic record
Abstract
Temperate zone winters are experiencing greater rates of warming relative to other seasons and latitudinal regions globally. Spring-spawning fishes native to northern environments rely on both increasing temperature and lengthening photoperiod to cue reproduction and may thus be particularly sensitive to rapid warming earlier in the year while day lengths remain short. We investigated the reproductive response of pumpkinseed sunfish (Lepomis gibbosus) to spring warming commencing at a range of day lengths (9–15 hours), corresponding to various calendar days (10 January – 22 May). In both the laboratory and field, both male and female fish that experienced early warming while day lengths were <11 hours (1) failed to initiate reproductive preparation in the liver before gonad development began and (2) had reduced reproductive allocation. Analysis of published data on temperate fishes suggested that liver development prior to gonad development is widespread across warm-, cool-, and cold-water thermal guilds, though the precise phenology of liver relative to gonad development appears to vary widely among species. Together, our results point toward dampened reproductive preparation as a novel mechanism mediating reduced reproductive output in both warm- and cool-water fish following earlier spring warming.
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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 | 0.000 |
| 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) | 0.001 | 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".