Does What Goes up Also Come Down? Using a Recruitment Model to Balance Alewife Nutrient Import and Export
Bibliographic record
Abstract
Abstract Migrating adult Alewives Alosa pseudoharengus are a source of marine-derived nutrients on the East Coast of North America, importing nitrogen and phosphorus into freshwater habitats. Juvenile migrants subsequently transport freshwater-derived nutrients into the ocean. We developed a deterministic model to explore the theoretical nutrient dynamics of Alewife migrations at differing spawner abundances. Net nutrient balance was calculated relative to these abundances along the spawner–recruit curve. The ecological consequences of these subsidies in a particular watershed depend on the magnitude of adult escapement relative to the habitat's carrying capacity for juveniles. At low escapement levels and assuming complete habitat access, the number of recruits produced per spawner was high and juvenile nutrient export dominated. At high escapement levels, fewer recruits were produced per spawner because recruitment is density dependent. As a result, adult nutrient import dominated. At varying levels of freshwater productivity and fisheries mortality for upstream spawners, this trend remained the same while the magnitude of the endpoints changed. Productivity level was the major determinant of export, while fisheries mortality had the strongest effect on adult import. The dynamics of this nutrient trade-off are important for managers to consider as a recovering population will likely shift from net export to net import as escapement increases. This transition will be sensitive to both harvest rates and to fish passage efficacy at dams and other barriers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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 teacher head, 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".