Climate change and abundance cycles of two sympatric populations of smelt (<i>Osmerus mordax</i>) in the middle estuary of the St. Lawrence River, Canada
Bibliographic record
Abstract
Commercial catches of two ecologically distinct sympatric smelt (Osmerus mordax) populations segregated along the two shores of the St. Lawrence middle estuary exhibited inverse patterns with periodicities on the order of 30 years. The influence of water level in the St. Lawrence River and air temperature, chosen to reflect variations in hydrology and climate, differed markedly between the two populations. Analyses revealed that both water level and temperature were generally positively related with north-shore smelt landings and negatively related with south-shore smelt landings. For both populations, a number of significant climatic factors contributing to variance in smelt landings were lagged by one to three years relative to the year of landings, indicating that climatic variables influenced smelt recruitment. The contrasting role of hydroclimatic variables in driving these abundance cycles is likely related to differential exploitation of estuarine habitats; the south-shore population is associated with shallow shoal habitat, whereas the north-shore population is associated with deep channel habitat. The responses of the two smelt populations also reflect the fundamental ecological differences existing between shoal and channel habitats, indicating that future climate change may differentially affect other populations or species that are segregated between these two habitats.
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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 | 0.001 |
| 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".