Ecological niche specialization inferred from morphological variation and otolith strontium of Arctic charr <i>Salvelinus alpinus</i> L. found within open lake systems of southern Baffin Island, Nunavut, Canada
Bibliographic record
Abstract
The presence of two morphotypes of Arctic charr Salvelinus alpinus was confirmed via morphological variation and otolith strontium (Sr) within three open-lake systems of southern Baffin Island, Nunavut, Canada: Qinngu (LH001), Iqalugaarjuit Lake (PG082) and Qasigiat (PG015). Analysis of otolith Sr indicates that a component of each S. alpinus population within lakes LH001 and PG082 is migratory (large-maturing S. alpinus), whereas another component is lake-resident (small-maturing S. alpinus). Alternatively, small and large maturing S. alpinus may both inhabit tidal habitats during their lifetime in lake PG015. Three morphological characters were identified by principal factor analysis (PFA) as characters that were different between maturity groups for all lakes studied: eye diameter, pectoral fin length and pelvic fin length. As well, upper jaw length (LH001 and PG082) and fork depth (PG015) were identified in PFA as traits that differed between morphs. Univariate tests of morphological characters identified by PFA demonstrated maturity group differences with the exception of eye diameter in Lake PG015 and upper jaw length and pelvic fin length in lake LH001. No difference was found in the MANOVA test of upper and lower gill raker number between small-maturing and undeveloped fish within all lakes studied. Clear morphological variation observed between small-maturing and undeveloped fish in all three lakes of the study suggests ecological niche separation between morphotypes. This is the first documented case of lake-resident S. alpinus use of the tidal habitat in the presence of a migratory large-maturing morphotype.
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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 | 0.001 |
| 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".