Experimental assessment of the bioenergetic and behavioural differences between two morphologically distinct populations of Arctic char (Salvelinus alpinus)
Bibliographic record
Abstract
A common environment experiment was conducted to assess the magnitude of the difference in growth, consumption, activity rate, and spatial and temporal patterns of habitat use between morphologically different populations of Arctic char ( Salvelinus alpinus ) originating from two Norwegian lakes. These two lakes contrasted sharply in terms of surface area, depth, elevation, length of the winter period, and fish community structure (presence–absence of brown trout, Salmo trutta ). The experimental framework encompassed four littoral enclosures (average volume, 146 m3) stocked with char from either of the two populations with duplicated treatments. Char morphology was quantified with numerical image analysis, food consumption was estimated using caesium analysis (133Cs), and activity cost and patterns were determined using video cameras. Char populations were morphologically distinct and reacted differently in growth (1.9-fold difference between populations), food consumption (3-fold difference), and spatial activity patterns (20-fold difference) to the conditions prevailing in the enclosures. The results highlight that functional differences between morphologically distinct char may drive important differences in their bioenergetic and behavioural responses when exposed to similar environmental conditions. Such functional differences should be incorporated when developing habitat or trophic cascade models.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".