Modeling migratory energetics of Connecticut River American shad (Alosa sapidissima): implications for the conservation of an iteroparous anadromous fish
Bibliographic record
Abstract
We present a simulation model in which individual adult migrant American shad ( Alosa sapidissima ) ascend the Connecticut River and spawn, and survivors return to the marine environment. Our approach synthesizes bioenergetics, reproductive biology, and behavior to estimate the effects of migratory distance and delays incurred at dams on spawning success and survival. We quantified both the magnitude of effects and the consequences of uncertainty in the estimates of input variables. Behavior, physiology, and energetics strongly affected both the distribution of spawning effort and survival to the marine environment. Delays to both upstream and downstream movements had dramatic effects on spawning success, determining total fecundity and spatial extent of spawning. Delays, combined with cues for migratory reversal, also determined the likelihood of survival. Spawning was concentrated in the immediate vicinity of dams and increased with greater migratory distance and delays to downstream migration. More research is needed on reproductive biology, behavior, energetics, and barrier effects to adequately understand the interplay of the various components of this model; it does provide a framework, however, that suggests that provision of upstream passage at dams in the absence of expeditious downstream passage may increase spawning success — but at the expense of reduced iteroparity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".