Competition overwhelms environment and genetic effects on growth rates of endangered white sturgeon from a conservation aquaculture program
Bibliographic record
Abstract
Improving the status of endangered species can be challenging because the efficacy of conservation actions is often uncertain. Conservation aquaculture has been the main recovery action for endangered white sturgeon ( Acipenser transmontanus) in the Transboundary Reach of the upper Columbia River. Using long-term mark-recapture data (2002–2018), we predicted variation in growth rates due to genetic, environmental, and competition effects to evaluate the efficacy of the aquaculture program. Environmental conditions (by season and country) and competition had the greatest effects on growth. Growth, length-at-age, weight-at-age, and condition factor were higher for fish residing in reservoir habitats (US) compared to those in riverine habitat (Canada). Growth declined over the study period but growth in length for larger fish remained higher in the US as fish > 100 cm fork length in Canada were not growing. Small differences in growth among families indicate that differences in genetics among parents spawned in the hatchery had negligible effects on growth in the wild. Our estimate of substantive negative density-dependent growth in Canada is important for management of conservation aquaculture for sturgeons.
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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 | 0.001 |
| 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) | 0.002 | 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".