Trophic niche partitioning of dominant North‐Atlantic krill species, <i>Meganyctiphanes norvegica</i>, <i>Thysanoessa inermis</i>, and <i>T. raschii</i>
Bibliographic record
Abstract
Abstract Different krill species have a pivotal position in many marine food webs by both preying upon several trophic levels and being forage species for consumers. Within these food webs, different krill species coexist, though it remains unclear what mechanisms allow for the coexistence, for instance, of northern krill species in subarctic environments. Here, we hypothesize that the stable coexistence of sympatric krill species is based on trophic niche partitioning related to seasonal trade‐offs between their respective food preferences, their energy needs, and prey availability. To test our hypothesis, we analyzed the diets, feeding selectivity, and lipid composition of three coexisting northern krill species (Meganyctiphanes norvegica, Thysanoessa inermis, and Thysanoessa raschii) throughout 1 yr using a multimarker approach. We assessed lipid classes, fatty acids, and stable isotope signatures of krill and potential food sources (27 groups, from phytoplankton to lipid‐rich copepods) to elucidate seasonal variation of niche utilization. Results revealed strong trophic niche separation occurring at a very fine trophic scale (species level) throughout the year. The three krill species showed different degrees of food specialization rather than being purely opportunistic as classically proposed. Feeding on copepod prey was important to accumulate energy reserves for overwintering and subsequent rebuilding of energy reserves. Energy reserve utilization might reduce potential competition for the limited available resources, especially under low food 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 | 0.000 | 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".