Distinct intestinal microbial communities of two sympatric anadromous Arctic salmonids and the effects of migration and feeding
Bibliographic record
Abstract
Although intestinal microbial communities from anadromous Arctic char (Salvelinus alpinus (Linnaeus, 1758)) in Kitikmeot, Nunavut, Canada, differ depending on the timing and location of capture, determinants of gut microbiota in other wild Arctic salmonids are largely unknown. Using high-throughput 16S rRNA gene sequence data, we compared intestinal microbiota from Arctic char to those from a related and sympatric salmonid, lake whitefish (Coregonus clupeaformis (Mitchill, 1818)). Shifts in lake whitefish gut microbial community composition were observed between brackish water and freshwater, similar to impacts of salinity reported previously for Arctic char. Despite these similarities, gut community profiles for the two salmonids differed, with whitefish having higher diversities and increased proportions of taxa affiliated with potential pathogens. Geography seemed to have a greater impact on freshwater whitefish gut microbiota than on corresponding Arctic char. Additionally, microbiota diversity was significantly more affected by feeding behavior in whitefish compared with sympatric Arctic char. As sampled whitefish were at their northern range limits and grew slowly, we speculate that they, and their microbial consortia, could be more vulnerable to certain abiotic and biotic factors than Arctic char, which are well adapted to conditions found in these high latitude environments and have the most northern distribution of any freshwater fish.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".