Population structure and genetic stock identification of the Lough Corrib brown trout
Bibliographic record
Abstract
Eurasian (brown) trout Salmo trutta populations are sensitive to alterations of their physical and natural environments (Elliott, 1994). The Lough Corrib catchment is renowned for its wild brown trout stock, which includes the long-lived, late maturing, piscivorous and highly prized ferox trout (Salmoferox). Over the past century, urban growth and associated discharges, arterial drainage, farming activities and agricultural run-off, introduction of alien species, among other factors, have all contributed to the alteration of the natural lake environment and, the loss and/or fragmentation of suitable spawning and nursery areas for brown trout. The lake has also been associated with an intensive hatchery stocking history, in particular between the mid-1960s and late 1970s. All of these factors, which are known to have an adverse effect on the demography and ecology of local populations, have contributed to fluctuations in brown trout productivity. Consequently, the health status, and long-term viability of trout populations spawning in the rivers comprising Lough Corrib’s catchment have been the focus of concern. To assess the status of contemporary Lough Corrib brown trout populations, in 2006, IFI commissioned a research project to examine the patterns and levels of population structuring and genetic diversity focusing on nine major rivers, which were part of the TAM (Tourism Angling Measure) river enhancement programme. The results of this project have been reported by Massa-Galluci et al.(2010). In 2012, the IFI commissioned QUB (Fish Population Genetics Research Group) to carry out a follow-up genetic study on the Lough Corrib brown trout with the aim of confirming the results of the initial survey, and to investigate possible changes in the genetic make-up of populations as a consequence of the changing environment. This new study is based on a new large-scale biological survey of Lough Corrib and its main tributary rivers and streams. A key distinction between the Massa-Galluci et al. (2010) and the 2012 survey is that, for the latter, the exact location of each lake adult brown trout is known in detail. Another relevant distinction of the present genetic study is that opportunistic historical archived tissue material (brown trout scales collected from IFI fish surveys in1974 and between 1994 and 1998) was also available for analyses. This archived material allows for a direct assessment of putative genetic changes among L. Corrib brown trout populations over a twenty years period. The results of this more comprehensive study are reported here.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".