Trophic niche segregation among native whitefish and invasive vendace in a north Norwegian lake system
Bibliographic record
Abstract
Abstract Introductions and invasions of non‐native species alter nutrient cycling and trophic dynamics resulting in significant ecological disturbance. Stable isotope data were used to test for evidence of invader‐induced trophic niche differences in a north Norwegian lake system differentially dominated by native European whitefish (Coregonus lavaretus) morphotypes and invasive vendace (Coregonus albula). Aspects of both realised trophic niche position and trophic niche width were affected by the invader, with the effects varying by whitefish morphotype. Densely rakered pelagic whitefish demonstrated a relatively lower reliance on pelagic resources in the presence of the invader and the isotopic niche size was relatively larger in conjunction with the broadening of the prey base. Within the benthic‐dwelling sparsely rakered whitefish morphotype, the trophic impacts of invading vendace were size‐dependent, with larger individuals experiencing niche compression. Smaller sparsely rakered whitefish increased, contrary to our hypothesis, reliance on pelagic‐based energy in the face of invasion. Our findings demonstrate that the trophic ecology of invaded systems can differ in multiple and subtle ways that have consequences for community‐ and ecosystem‐level energy flows, which if persisting over time are likely to have implications for the recruitment, growth and reproductive rate of the native fishes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 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".