River- and Sex-Specific Annual Survival Rates of Mature Anadromous Alewife (Alosa pseudoharengus)
Bibliographic record
Abstract
During multiple annual spawning runs from 2013 to 2021, over 9,000 mature anadromous alewife (Alosa pseudoharengus A. Wilson, 1811) were monitored with passive integrated transponders (PITs) in four rivers of the Chignecto Isthmus, Bay of Fundy, Canada. A subsample of 384 individuals tagged during 2016–2019 were aged from 3 to 6 years (mean ± SD; 4.2 ± 0.7 years, n = 232, males; 4.5 ± 0.7 years, n = 152, females). Biotelemetry revealed that one unsexed individual survived seven years post tagging, possibly making it 10–13 years old. Return rates varied among the rivers, with the lowest rates in the most anthropogenically impacted river. Biotelemetry and ageing data were used to estimate apparent annual survival rates ranging from 0.25 to 0.50 depending on the river and the year. Based on capture-mark-recapture (CMR) analysis of biotelemetry data from the three less impacted rivers, the estimated overall annual survival was 0.396, total instantaneous mortality (Z) was 0.93, and future life expectancy from time of release was 1.08 years. Frequency distribution of ages 4–6 for alewife pooled from all four study rivers estimated a lower annual survival rate of 0.301, Z = 1.20, and a future life expectancy of 0.83 years. The biotelemetry detection rates were 0.89–0.98 but varied depending on the river and the year, with the lowest rates in one river during 2017-2018 possibly related to a malfunctioning tide gate preventing upstream fish passage and subsequent detection. Based on CMR, males had a higher survival rate compared to females, which translated into an overall mean survival increase of 0.05. Alewife survivorship in our study highlighted that a limited ecosystem-based management period is required to mitigate river connectivity and mortality issues to avoid loss of population cohorts and decrease the risk of extirpation.
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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 | 0.000 |
| 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".