Variability in competitive ability and mortality rates : the ability of transgenic coho salmon (Oncorhynchus kisutch) to survive in the wild
Bibliographic record
Abstract
into the field of transgenic research and the possibilities it provides for exploring aspects of animal behaviour and ecology.Through his guidance and support I was able to complete my degree and maintain the desire to continue my education in the field of scientific research.I would like to acknowledge my committee members, G. Eales, J' Hare and S' Mclachlan, for the time that they have committed to provide constructive comments at various stages of the development of this project.Their input has been verybeneficial' Many thanks to R. Devlin who provided me with the fish and research facilities so that I could carry out my experiments.In addition, he offered a great deal of support while I was conducting my research at west vancouver Lab.I am also very grateful to c' Biagi, who completed all PCR analysis required for this project.I would like to express my gratitude to friends and family who provided encouragement through all the trials and tribulations of conducting graduate work' This includes, of course, my parents, who I can always count on for constant support and motivation.'W.Kulzer, who always had time time for coffee, and my labmate T' Robb were always available with a sympathetic ear' Last of all, I would not have been able to complete this project without the support of my husband, J. Tymchuk.His help at all stages of this research was much appreciated' as was his ability to maintain my sense of humour through it all' Thank you' ABSTRACT Coho salmon (Oncorhynchus kisutch) have been genetically altered to produce growth hormone without regulatior¡ causing them to grow on average 1l times larger than control fish after one year of growth.This technology has important benefits for the aquaculture industry, but the environmental risk associated with the escape of transgenic fish into the wild is not known.To partially address this issue, I experimentally investigated how well transgenic salmon suwived under semi-natural conditions.If transgenic salmon retain their growth advantage under natural conditions, one can predictthat they must also be more effective at competing for food than wild salmon, and willing to suffer higher mortality rates while foraging.Two experiments were designed to test this hypothesis.The first tested the relative competitive ability of transgenic and control salmon using an unequal competitors ideal free distribution.A larger proportion of transgenic salmon were found at the high quantity food source, leading to the conclusion that they were more superior at securing higher quantity food resources.The second tested the relative mortality rates of transgenic and control salmon by providing them with the option to feed in the presence of a predator.There was no significant difference in mortality rates between the two groups.An individual-based population model was developed to examine the relative survival of transgenic fish in the natu¡al environment.Results from the model indicated that under certain environmental conditions, transgenic fish had survival rates equal to the wild type individuals.My preliminary results did not provide conclusive evidence that transgenic fish would be unable to survive in the wild indicates that care must be taken to insure these growth-enhanced individuals are not released into the environment.
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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 | 0.000 | 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 | 0.001 |
| 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".