Characterization of skin- and intestine microbial communities in migrating high Arctic lake whitefish and cisco
Bibliographic record
Abstract
Abstract At high latitudes, lake whitefish ( Coregonus clupeaformis ) and others in the closely related Coregonus species complex (CSC), including cisco ( C. autumnalis and C. sardinella ), can be diadromous, seasonally transitioning between freshwater lakes and the Arctic Ocean. CSC skin- and intestine microbiomes were collected, facilitated by Inuit fishers at sites on and around King William Island, Nunavut, at the northern range limits of lake whitefish. Community composition was explored using 16S rRNA gene sequencing, with significant differences in microbiota dispersions depending on fishing site salinity for lake whitefish intestine and skin, as well as cisco skin. Overall, lake whitefish intestine communities appeared more variable than cisco and had higher Shannon diversity, suggesting that lake whitefish and their microbiomes could be more susceptible to environmental stress possibly leading to dysbiosis. Although cisco condition was similar among distinct seasonal habitats, the higher average lake whitefish condition in freshwater rivers suggests that fishing these diadromous whitefish in estuaries may be optimal from a sustainable fishery perspective. Taken together, the impact of changing habitats on fish condition and different microbial composition may inform new approaches to CSC health in fisheries and aquaculture, in addition to being relevant for northern Indigenous peoples with subsistence and economic interests in these resources.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".