The biology and feeding ecology of <scp>Arctic charr</scp> in the <scp>Kerguelen Islands</scp>
Bibliographic record
Abstract
Subsequent to their introduction in the 1950s, Arctic charr Salvelinus alpinus have been able to establish a self-sustaining population that has adapted to the unique conditions of the sub-Antarctic Kerguelen Islands. Here, 48 individuals (198-415 mm) were caught with gillnets and their basic biology and feeding ecology were examined using stable isotope analysis. The Lac des Fougères population split use of littoral and pelagic resources evenly, although larger fish relied more heavily on littoral production and appear to follow the size-dependent life history habitat template seen in many Scandinavian lakes where smaller sized individuals occupy the pelagic zone and larger individuals dominate the littoral habitat. In Kerguelen, Arctic charr mature at the same ages (5.6 years) as Arctic charr in both sub-Arctic and Arctic lakes. Although mortality was average in comparison to comparator sub-Arctic lakes, it was high in comparison to Arctic lakes. Maximal age (>7+) was at the lower end of the range typically seen in sub-Arctic lakes. Although they inhabit a resource-poor environment, Kerguelen Arctic charr showed no evidence of cannibalism. Thus, while Arctic charr can survive and reproduce in the relatively unproductive Kerguelen lake environments, survival and growth nevertheless appear to be traded off against survival and longevity. The uniqueness of the population location and the recency of its introduction suggest that further monitoring of the population has the potential to yield valuable insights into both the adaptability of the species and its likely responses to ongoing large-scale environmental change as represented by climate change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".