Using otolith microchemistry to reconstruct habitat use of<scp>A</scp>merican eels<i><scp>A</scp>nguilla rostrata</i>in the<scp>S</scp>t.<scp>L</scp>awrence<scp>R</scp>iver–<scp>L</scp>ake<scp>O</scp>ntario system
Bibliographic record
Abstract
Abstract Catadromy among freshwater eels is increasingly recognised as being facultative, with some individuals carrying out growth exclusively in brackish or coastal marine waters, or switching between brackish or marine waters and freshwater habitats. In an attempt to reconstruct habitat use of yellow‐stage American eels in a large river‐lake ecosystem, trace element line scans were obtained, using LA ‐ ICP ‐ MS , from the otoliths of 110 eels sampled at various locations throughout the St. Lawrence River–Lake Ontario ( SLRLO ) system. Elemental profiles for strontium (Sr), barium (Ba), manganese (Mn) and magnesium (Mg) enabled us to distinguish three chemical signatures that appear to represent three distinct habitats within the SLRLO . Of these, one was shown to likely correspond to the brackish estuary (high strontium values). The other two signatures, characterised by low strontium but variable concentrations of barium and manganese, may correspond to habitats within the main‐stem St. Lawrence River and one or more of its tributaries. Most (78%) of the switches among habitats occurred within the first four years after recruitment suggesting an increasing likelihood for eels to maintain residence in one habitat as they grow older. This suggests that tributaries may provide important habitats for American eels during the first several years after recruiting to the SLRLO . In addition, our results suggest that a small proportion American eels in the SLRLO can undertake movements on the order of at least 200 km during the early growth stage. This information has important implications for the management and conservation of this species in the system.
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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 | 0.000 | 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".