Lifetime carryover of early partial migration behaviors in an estuarine-dependent fish under climate change
Bibliographic record
Abstract
Spatial structure within populations promotes population stability and resilience through asynchronous responses among population subcomponents (i.e., portfolio effect). In fishes, spatial structure frequently develops via early-life partial migration, leading to diversified nursery use. However, the portfolio effect depends on how adult recruitment from different nurseries exhibits asynchronous dynamics in response to climate variables, and whether nursery experiences carry over to adult demographics. For a three-decade span, we tested adult nursery recruitment and carryover effects associated with early-life partial migration in Hudson River striped bass. Early-life partial migration led to structured utilization of freshwater, brackish, and coastal nurseries, all of which recruited to the adult population. Adult recruitment from brackish nurseries increased with freshwater flow, while coastal nurseries produced more adults during severe winter years. First-year nursery experiences carried over to influence adult sex, but not growth. Most adult females utilized brackish nurseries in their first year, while adult males recruited from freshwater and brackish nurseries. Early-life partial migration led to diversified nursery use and influenced adult demographics, which buffered populations against perturbations.
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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 | 0.000 | 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".