Global change and premature hatching of aquatic embryos
Bibliographic record
Abstract
Anthropogenically induced changes to the natural world are increasingly exposing organisms to stimuli and stress beyond that to which they are adapted. In aquatic systems, it is thought that certain life stages are more vulnerable than others, with embryos being flagged as highly susceptible to environmental stressors. Interestingly, evidence from across a wide range of taxa suggests that aquatic embryos can hatch prematurely, potentially as an adaptive response to external stressors, despite the potential for individual costs linked with underdeveloped behavioural and/or physiological functions. However, surprisingly little research has investigated the prevalence, causes and consequences of premature hatching, and no compilation of the literature exists. Here, we review what is known about premature hatching in aquatic embryos and discuss how this phenomenon is likely to become exacerbated with anthropogenically induced global change. Specifically, we (1) review the mechanisms of hatching, including triggers for premature hatching in experimental and natural systems; (2) discuss the potential implications of premature hatching at different levels of biological organisation from individuals to ecosystems; and (3) outline knowledge gaps and future research directions for understanding the drivers and consequences of premature hatching. We found evidence that aquatic embryos can hatch prematurely in response to a broad range of abiotic (i.e. temperature, oxygen, toxicants, light, pH, salinity) and biotic (i.e. predators, pathogens) stressors. We also provide empirical evidence that premature hatching appears to be a common response to rapid thermal ramping across fish species. We argue that premature hatching represents a fascinating yet untapped area of study, and the phenomenon may provide some additional resilience to aquatic communities in the face of ongoing global change.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".