How pathogens affect the marine habitat use and migration of sea trout (<i>Salmo trutta</i>) in two Norwegian fjord systems
Bibliographic record
Abstract
Wild fish are confronting changing pathogen dynamics arising from anthropogenic disturbance and climate change. Pathogens can influence animal behaviour and life histories, yet there are little such data from fish in the high north where pathogen dynamics may differ from comparatively southern regions. We aimed to compare the pathogen communities of 160 wild anadromous brown trout in two fjords in northern Norway and to determine whether pathogens influenced area use or return to spawn. Application of high-throughput qPCR detected 11 of the 46 pathogens screened for; most frequently encountered were Ichthyobodo spp., Flavobacterium psychrophilum and Candidatus Branchiomonas cysticola. The rate of returning to freshwater during the spawning season was significantly lower for the Skjerstadfjord fish. Piscichlamydia salmonis and F. psychrophilum were indicator species for the Skjerstadfjord and pathogen communities in the two fjords differed according to perMANOVA. Individual length, Fulton's condition factor and the time between first and last detection of the fish were not related to the presence of pathogens ordinated using non-metric multidimensional scaling (NMDS). However, there was evidence that pathogen load was correlated with the expression of smoltification genes, which are upregulated by salmonids in freshwater. Correspondingly, percentage of time in freshwater after release was longer for fish with greater pathogen burdens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".