Trophic ecology and nutritional status of northern shrimp in Canada’s sub-Arctic
Bibliographic record
Abstract
In the Northwest Atlantic Ocean, northern shrimp (Pandalus borealis) play key ecological roles as mid-trophic level consumers and as prey to higher-trophic level predators, including commercial fish species. However, the effects of changing environmental conditions and biological processes on trophic interactions in sub-Arctic ecosystems, particularly on lipid storage and nutrient transfer from intermediate to high trophic levels, remain unclear. Biochemical tracer methods (i.e., fatty acids and stable isotopes) were employed to study the trophic ecology and stage-specific nutritional condition of P. borealis across different spatial and seasonal scales. Trophic markers indicated significant contributions from both diatoms and zooplankton to the diet of P. borealis and highlighted the adaptability of this species to opportunistic feeding strategies based on sinking phytodetritus. Our results revealed a strong seasonality in the lipid composition of P. borealis, with lipid dynamics being highly influenced by environmental conditions and resource availability. The primary lipid classes in P. borealis were storage triacylglycerols, accounting for over 50% of lipids observed, followed by membrane phospholipids. Eggs from ovigerous females exhibited the highest concentrations of total lipids and essential fatty acids, such as omega-3 fatty acids, underscoring the important ecological role of eggs in sub-Arctic food webs by providing high-quality lipid sources. Additionally, our findings indicated an increase in the total lipid content of shrimp eggs from spring to summer, suggesting that the early stages of P. borealis are vulnerable to changes in the timing of seasonal primary production, when females store large reserves of energy-rich lipids. This study highlights the large seasonal and temporal variability in the nutritional status of P. borealis and underlines the importance of understanding lipid dynamics in assessing the resilience of populations to environmental changes.
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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 | 0.001 |
| 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".