Success of two methods for long distance transport and fertilization of Bull Trout
Bibliographic record
Abstract
ABSTRACT Objective The use of captive breeding programs for the conservation of freshwater fishes, be it for research or reintroduction, is becoming more common. Interspecific differences in rearing ecology make applying common rearing techniques difficult for threatened species. This becomes increasingly difficult for species in remote areas, as accessing fish for hatchery propagation can take longer. Bull Trout Salvelinus confluentus has recently been listed as threatened in Alberta and is garnering greater consideration for artificial propagation. Currently, there are no active hatchery programs for Bull Trout, and historically, very few attempts have occurred with limited success. The goal of this research was to establish a laboratory population of Bull Trout and compare the effectiveness of delayed and same day fertilization when transporting gametes or embryos over large distances. Methods Here, eggs were either fertilized in the field prior to transport (field) or 1 d after transport (green). Both treatments were collected from Smith-Dorrien Creek, Alberta, and transported to Winnipeg, Manitoba, by airplane (approximately 1,300 km). Differences between treatments were tested using a binomial generalized linear model. Results Fertilization rates were similar and high (>99%) for both treatments, and our model did not detect a significant treatment effect. Although a significant treatment effect was not observed, the green treatment had 10% lower survival over the duration of the experiment. The greatest mortality rates were observed at the swim-up stage in both treatments. Conclusions Both methods had similar fertilization rates and high survival to the fry stage (green = 36% and field = 46%). The results suggest that both methods are viable options when transporting Bull Trout gametes or embryos long distances for species recovery and research purposes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".