Modeling life history changes in inner Bay of Fundy Atlantic salmon to test hypotheses for population decline
Bibliographic record
Abstract
Inner Bay of Fundy Atlantic salmon are an endangered species at imminent risk of extinction. When assessing populations at risk, important questions to be asked are: "What changed, when and why?". To answer the first two of these questions I present a population model used to estimate the changes in mortality this population has experienced over a 42 year period. Input consisted of measures or estimates of abundance for different life stages from 1954 to 2005. I then estimated a suite of life history parameters, including yearly estimates of at-sea mortality for the years 1963 to 2004, inclusive. At-sea mortality was estimated to vary from ~78% to ~99% over this period. Linear regression techniques were subsequently used to test for significant relationships between yearly at-sea mortality rates and eighty-two indices related to five proposed hypotheses for decline. Five indices showed significant regressions (p-value < 0.05 and R² > 0.30, hypotheses: ecological community shifts and interactions with farmed and hatchery salmon, indices: grey seal population, aquaculture (number of market fish, cage sites and yearly production) and cormorant population) but due to the nature of those individual datasets there was the potential for spurious correlations. More important were the 77 indices representing the remaining two hypotheses (changes in environmental conditions, fisheries) that showed highly non-significant regressions which contributed to the 'hypothesis reduction' of the threats to iBoF populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".