Genetic variation in responses to a settlement cue and elevated temperature in the reef-building coral Acropora millepora
Bibliographic record
Abstract
Reef-building corals are threatened by increasing sea surface temperatures resulting from global climate change. Whether corals can adapt to increasing temperatures over the course of generations will depend in part on heritable variation in thermal physiology and dispersal potential, which may serve as the raw material for natural selection. To investigate whether such variation exists in coral populations, and build a framework for identifying the coral-specific genetic factors involved, we performed controlled crosses between 3 genetically distinct colonies of the branching coral Acropora millepora. We compared the families of larvae (which in this species naturally lack symbionts) for several physiological traits, and observed between-family differences in nearly every case. Using larvae cultured at standard and elevated temperatures, we measured the developmental decrease in protein content and the expression of candidate heat response genes. We used an in vivo assay for mitochondrial enzyme activity to evaluate the metabolic response to temperature changes in individual larvae. We also compared the responsiveness of larvae from different families to a natural settlement cue to gain insights into long-range dispersal potential. Partitioning the components of total phenotypic variance confirmed the existence of additive genetic effects for settlement rates and βγ-crystallin expression, while variance in mitochondrial Q10 and the expression of actin and Hsp16 were driven by non-additive effects. The phenotypic variance observed among the small number of families analyzed here suggests the existence of considerable heritable variation in natural coral populations, which supports the possibility of effective adaptive responses to climate change.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".