Seasonal lipid dynamics of four Arctic bivalves: Implications for their physiological capacities to cope with future changes in coastal ecosystems
Bibliographic record
Abstract
Abstract The Arctic is exposed to unprecedented warming, at least three times higher than the global average, which induces significant melting of the cryosphere. Freshwater inputs from melting glaciers will subsequently affect coastal primary production and organic matter quality. However, due to a lack of basic knowledge on the physiology of Arctic organisms, it remains difficult to understand how these future trophic changes will threaten the long‐term survival of benthic species in coastal habitats. This study aimed to gain new insights into the seasonal lipid dynamics of four dominant benthic bivalves (Astarte moerchi, Hiatella arctica, Musculus discors, and Mya truncata) collected before and after sea ice break‐up in a high‐Arctic fjord (Young Sound, NE Greenland). Total lipid content and fatty acid composition of digestive gland neutral lipids were analyzed to assess bivalve energy reserves while the fatty acid composition of gill polar lipids was determined as a biochemical indicator of interspecies variations in metabolic activity and temperature acclimation. Results showed a decrease in lipid reserves between May and August, suggesting that bivalves have only limited access to fresh organic matter until sea ice break‐up. The lack of seasonal variation in the fatty acid composition of neutral lipids, especially essential ω3 fatty acids, indicates that no fatty acid transfer from the digestive glands to the gonads occurs between May and August, and therefore, no reproductive investment takes place during this period. Large interspecies differences in gill fatty acid composition were observed, which appear to be related to differences in species life span and metabolic strategies. Such differences in gill fatty acid composition of polar lipids, which generally influence metabolic rates and energy needs, may imply that not all benthic species will be equally sensitive to future changes in primary production and organic matter quality in Arctic coastal habitats.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".