Persistence of a southern Atlantic salmon population: diversity of natal origins from otolith elemental and Sr isotopic signatures
Bibliographic record
Abstract
We investigated the use of Sr:Ca, Ba:Ca, and87Sr:86Sr ratios as natural tags for determining the natal origins of juvenile and adult Atlantic salmon (Salmo salar) from 12 tributaries in the Adour basin (southwestern France) and estimated homing on a tributary scale. Geochemical signatures from core regions of the otolith were also used to identify fish from hatchery or naturally spawned sources. Quadratic discriminant function analysis (QDFA) was on average 80% successful at classifying juveniles according to their natal rivers. Adults of unknown natal origin were assigned to their natal rivers using the juvenile fingerprints from QDFA approach. Only 18 adults originated from streams not included in the juvenile database. Although most of the adults showed a marked homing instinct, homing was not perfect, and some wild fish strayed into non-natal spawning areas. Returns of hatchery-reared fish as adult spawners represented 10% of the total sampled fish. Allocation of fish to natal tributaries or hatcheries illustrated the abundance and relative contributions of natal sources, important for the recovery of Atlantic salmon in this area.
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 | 0.001 | 0.001 |
| 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".