Northern shrimp from multiple origins show similar sensitivity to global change drivers, but different cellular energetic capacity
Bibliographic record
Abstract
Species with a wide distribution can experience significant regional variation in environmental conditions, to which they can acclimatize or adapt. Consequently, the geographic origin of an organism can influence its responses to environmental changes, and therefore its sensitivity to combined global change drivers. This study aimed at determining the physiological responses of the northern shrimp, Pandalus borealis, at different levels of biological organization and from four different geographic origins, exposed to elevated temperature and low pH to define its sensitivity to future ocean warming and acidification. Shrimp sampled within the northwest Atlantic were exposed for 30 days to combinations of three temperature (2, 6 or 10°C) and two pH levels (7.75 or 7.40). Survival, metabolic rates, whole-organism aerobic performance and cellular energetic capacity were assessed at the end of the exposure. Our results show that shrimp survival was negatively affected by temperature above 6°C and low pH, regardless of their origin. Additionally, shrimp from different origins show overall similar whole-organism performances: aerobic scope increasing with increasing temperature and decreasing with decreasing pH. Finally, the stability of aerobic metabolism appears to be related to cellular adjustments specific to shrimp origin. Our results show that the level of intraspecific variation differs among levels of biological organization: different cellular capacities lead to similar individual performances. Thus, the sensitivity of the northern shrimp to ocean warming and acidification is overall comparable among origins. Nonetheless, shrimp vulnerability to predicted global change scenarios for 2100 could differ among origins owing to different regional environmental conditions.
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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".