Ocean acidification increases susceptibility to sub-zero air temperatures in ecosystem engineers and limits poleward range shifts
Bibliographic record
Abstract
Ongoing climate change has caused rapidly increasing temperatures and an unprecedented decline in seawater pH, known as ocean acidification. Increasing temperatures are redistributing species toward higher and cooler latitudes that are most affected by ocean acidification. While the persistence of intertidal species in cold environments is related to their capacity to resist sub-zero air temperatures, studies have never considered the interacting impacts of ocean acidification and freeze stress on species survival and distribution. Here, a full-factorial experiment was used to study whether ocean acidification increases mortality in subtidal Mytilus trossulus and subtidal M . galloprovincialis , and intertidal M. trossulus following sub-zero air temperature exposure. We examined physiological processes behind variation in freeze tolerance using 1 H NMR metabolomics, analyses of fatty acids, and amino acid composition. We show that low pH conditions (pH = 7.5) significantly decrease freeze tolerance in both intertidal and subtidal populations of Mytilus spp. Under current day pH conditions (pH = 7.9), intertidal M. trossulus was more freeze tolerant than subtidal M. trossulus and subtidal M. galloprovincialis . Conversely, under low pH conditions, subtidal M. trossulus was more freeze tolerant than the other mussel categories. Differences in the concentration of various metabolites (cryoprotectants) or in the composition of amino acids and fatty acids could not explain the decrease in survival. These results suggest that ocean acidification can offset the poleward range expansions facilitated by warming and that reduced freeze tolerance could result in a range contraction if temperatures become lethal at the equatorward edge.
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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 | 0.000 | 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".