Influence of warming temperatures on coregonine embryogenesis within and among species
Bibliographic record
Abstract
ABSTRACT The greatest known global response of lakes to climate change has been an increase in water temperatures. The responses of many lake fishes to warming water temperatures are projected to be inadequate to counter the speed and magnitude of climate change. We experimentally evaluated the responses of embryos from a group of cold, stenothermic fishes (Salmonidae Coregoninae) to increased incubation temperatures. Study groups included cisco ( Coregonus artedi ) from lakes Superior and Ontario (USA), and vendace ( C. albula ) and European whitefish ( C. lavaretus ) from Lake Southern Konnevesi (Finland). Embryos from artificial crossings were incubated at water temperatures of 2.0, 4.5, 7.0, and 9.0°C, and their responses were quantified for developmental and morphological traits. Embryo survival, incubation period, and length-at- hatch were inversely related to incubation temperature whereas yolk-sac volume increased with incubation temperature within study groups. However, varying magnitudes of responses among study groups suggested differential levels of developmental plasticity to climate change. Differential levels of parental effects indicate genetic diversity may enable all study groups to adapt to cope with some degree of changing environmental conditions. Our results suggest that the coregonines sampled within and among systems may have a wide range of embryo responses to warming incubation conditions.
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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".