Resistance of the cold-water coral Dendrophyllia cornigera to single and combined global change stressors
Bibliographic record
Abstract
Abstract Current knowledge of the consequences on global change in deep marine ecosystems is still limited, especially since environmental pressures do not act separately, and their potential interactions are mostly unknown. Cold-water corals (CWC) play a significant role in the deep sea, being ecosystem engineers supporting high biodiversity. However, global change may impact CWCs, compromising their integrity and survival. In this study, a nine-month aquaria experiment was conducted on the CWC Dendrophyllia cornigera from the NW Iberian Shelf (NE Atlantic Ocean). The aim was to assess the individual and combined effects of elevated temperature (12 vs. 15 °C), low pH (~ 7.99 vs. 7.69 pH T ) and low oxygen (~ 6.4 vs. 4.7 mL L −1 ), based on the IPCC RCP 8.5 scenario. During the experiment, coral survival, skeletal growth, tissue cover and respiration were monitored as response variables. No significant effects were found on any of the response variables for either individual or combined stressors, pointing to the resistance of D. cornigera to different global change scenarios. Such a physiological resistance may support D. cornigera persistence under future conditions where other CWCs with narrower tolerance ranges may face greater limitations. However, further research is needed to assess potential trade-offs to cope with environmental change, which might impact the long-term survival capacity of this species.
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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 | 0.001 | 0.000 |
| 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".