Hatchery Rearing of Lake Sturgeon to Age 1 Prior to Stocking: A Path Forward for Species Recovery in the Upper Nelson River, Manitoba, Canada
Bibliographic record
Abstract
Abstract The release of hatchery-reared age-0 Lake Sturgeon Acipenser fulvescens has proven sufficient to re-establish mid-latitude populations, but there was minimal evidence of poststocking survival in the functionally extirpated population of the upper Nelson River, Manitoba, until the practice of rearing fish to age 1 in the hatchery began in 2007. After 5 years of poststocking monitoring (2012–2016), mark–recapture data sets have yielded important information regarding survival, dispersal shortly after stocking, post-establishment movement and emigration, and growth, clarifying a path forward for Lake Sturgeon recovery initiatives in this system. Based on Cormack–Jolly–Seber models, mean cohort-specific apparent survival (i.e., consolidated survival and retention of fish within the reach) for Lake Sturgeon reared to age 1 in the hatchery from the time of stocking until the period of post-first-winter recapture in the wild (predominantly at age 2) was estimated to range from 0.08 (95% CI = 0.06–0.11) to 0.49 (95% CI = 0.41–0.56); dispersal occurring shortly after stocking was identified as at least partially influential. In the years after poststocking establishment (i.e., age 2 and older), apparent survival of the fish that established in the primary reach was estimated at 0.99–1.00, indicative of negligible mortality and negligible emigration. The stocked Lake Sturgeon exhibited growth patterns similar to (or even outpacing) those of wild populations occupying comparable habitats in Manitoba. Moreover, data indicate that growth trajectories set early in life persist throughout the juvenile stage. The results of upper Nelson River poststocking monitoring provide quantitative support for a stocking strategy predicated on rearing Lake Sturgeon over winter in the hatchery followed by release at age 1 during spring, thus striking a balance between high poststocking survival and moderate hatchery rearing costs.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".