The Mediterranean mussel <i>Mytilus galloprovincialis</i>: responses to climate change scenarios as a function of the original habitat
Bibliographic record
Abstract
locally adapted to very distinct, widely separated sites in the Mediterranean Sea (Tunisia) and Atlantic Sea (Galicia, NW Spain) was evaluated in relation to key behavioural and eco-physiological parameters. Over the 2-month exposure to the experimental conditions, mussels were fed optimally to ensure that there are no synergistic interactions between climate change drivers and energetic status of the individuals. In general, regardless of origin (Atlantic or Mediterranean), the mussels were rather resilient to acidification for most of the parameters considered and they were able to grow in strongly acidified seawater through an increased feeding activity. However, shell strength decreased (40%) consistently in both mussel populations held in moderately and highly acidified seawater. The observed reduction in shell strength was not explained by slight alterations in organic matter, shell thickness or aragonite:calcite ratio. The combined effects of high acidification and warming on the key response of byssus strength caused a strong decline in mussel performance, although only in Galician mussels, in which the valve opening time decreased sharply as well as condition index (soft tissue state) and shell growth. By contrast, the observed negative effect of highly acidified scenario on the strength of Tunisian mussel shells was (partly but not totally) counterbalanced by the higher seawater temperature. Eco-physiological and behavioural interactions in mussels in relation to climate change are complex, and future scenarios for the ecology of the species and also the feasibility of cultivating them in Atlantic and Mediterranean zones are discussed.
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".