Ecosystem heating experiment reveals sex-specific growth responses in fish
Bibliographic record
Abstract
Size-specific body growth responses to warming are common among animal taxa, but sex-specific responses are poorly known. Here we ask if body growth responses to warming are sex-dependent, and if such sex-specific responses vary with size and age. This was tested with sex-specific data of back-calculated individual growth trajectories, in European perch ( Perca fluviatilis) from a long-term whole-ecosystem warming experiment (6.3 °C above the surrounding sea). Warming led to both size- and sex-specific differences in growth responses. Warming had a consistent positive effect on body growth of females, but negative effects on male growth at size > 10 cm and age > 2 years. These sex-specific growth responses translate to an increased degree of female-biased sexual size dimorphism (in length-at-age) with warming. Although the exact temperature-mediated effects underlying differential growth responses could not be resolved, results imply global warming may have highly different effects during ontogeny of male and female perch. Such effects should be considered in climate warming scenarios concerning fish growth, population size-structure, and dynamics of aquatic food webs that include fish exhibiting sexual size dimorphism.
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 | 0.000 |
| 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".