Evaluation of methods for the collection and fertilization of burbot eggs from a wild stock for conservation aquaculture operations
Bibliographic record
Abstract
In the Kootenay River, British Columbia, Canada, burbot (Lota lota maculosa) numbers have diminished to near extirpation due to factors including physical changes to habitat and overfishing. Habitat restoration is currently underway but short-term recovery measures include the release of hatchery-reared burbot. Moyie Lake has been identified as a suitable brood source for a conservation aquaculture program but uncertainties remain regarding current population size, the feasibility of capturing broodstock and the ability to collect eggs from wild spawners. Specific objectives of our study were to: (i) develop a length at age key to provide a non-destructive means of population age structure identification, (ii) determine the location and general habitat characteristics of burbot spawning locations on Moyie Lake, (iii) provide a marked sample for future population estimation, and (iv) investigate the feasibility of collecting gametes for use in a conservation aquaculture program. A total of 181, 554, and 370 burbot were captured in 2009, 2010 and 2011, respectively. No significant relationship was established between length and age for burbot on Moyie Lake. Spawning burbot were observed over a number of different habitats, but high use areas consisted of steep banks dominated by a mix of gravel/boulder/cobble substrates. Mature burbot were reliably collected each year, and eggs from females were fertilized and transported to the hatchery. Egg survival was highly variable (range 0–98%) and resulted in an estimated 353 429, 3 032 143, and 3 970 283 eggs for use in the aquaculture program in 2009, 2010 and 2011, respectively. Results of this study demonstrate that gametes can be collected from adult burbot during spawning and eggs can be successfully fertilized in the field. Further methodological refinement aimed at improving egg fertilization and subsequent survival to the hatchery will be important as recovery moves forward.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".