Data from: Structural and compositional mismatch between captive and wild Atlantic salmon (Salmo salar) parrs gut microbiota highlights the relevance of integrating molecular ecology for management and conservation methods.
Bibliographic record
Abstract
Stocking methods are used in the Province of Quebec to restore Salmo salar populations. However, Atlantic salmon stocked juveniles show higher mortality rates than wild ones when introduced into nature. Hatchery environment, which greatly differs from the natural environment, is identified as the main driver of the phenotypic mismatch between captive and wild parrs. The latter is also suspected to impact the gut microbiota composition, which can be associated with essential metabolic functions for their host. We hypothesized that hatchery raised parrs potentially recruit gut microbial communities that are different from those recruited in the wild. This study evaluated the impacts of artificial rearing on gut microbiota composition in 0+ parrs meant for stocking in two distinct Canadian rivers: Rimouski and Malbaie (Quebec, Canada). Striking differences between hatchery and wild born parrs’ gut microbiota suggest that microbiota could be another factor that could impact their survival in the targeted river, since the microbiome is narrowly related to host physiology. For instance, major commensals belonging to Enterobacteriaceae and Clostridiacea from wild parrs’ gut microbiota were substituted in captive parrs by lactic acid bacteria from the Lactobacillaceae family. Overall, captive parrs host a generalist bacterial community whereas wild parrs’ microbiota is much more specialized. This is the very first study demonstrating extensive impact of captive rearing on intestinal microbiota composition in Atlantic salmon intended for wild population stocking. Our results strongly suggest the need to implement microbial ecology concepts into conservation management of endangered salmon stocks supplemented with hatchery reared parrs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".