Links between marine and gut bacterial communities and diet in thick-billed murres «(Uria lomvia)»
Bibliographic record
Abstract
The use of diet generalizations for the study of an animal population facilitates sampling efforts and drawing conclusions from the collected data. However, using average values does not take into consideration the fact that a population is composed of individuals who may have different feeding behaviours. Individual prey specialization occurs in many animals and, particularly, in many seabirds. The study of this phenomenon is of importance for the understanding various aspects of the life history of these animals. This thesis contributes to the current knowledge of an Arctic seabird, the thick-billed murre (Uria lomvia) by investigating the interactions with bacteria that could determine the way these birds consume nutrients and accumulate mercury (Hg).Seabirds are often used to monitor contaminant levels in the ocean because they integrate exposure signals over large areas and bring that signal back to a central location, their colonies, where they can be easily sampled. Individual prey specialization should be taken into consideration when using wildlife as monitors, given that diet plays an important role on the concentrations and type of contaminants that are accumulated by wildlife. We studied Hg accumulation patterns in an Arctic food web from Coats Island (Canada) comprised of invertebrates and fish that are common prey of the thick-billed murre. We characterized this food web using stable isotope signatures as proxy measurements of trophic level (δ15N), Hg methylation (δ34S), and carbon source (δ13C). δ34S can be used as an indicator of the activity of sulfate-reducing bacteria, the main Hg methylators. δ34S better explained Hg levels than the more widely used δ15N when used individually and improved the correlation of δ15N with Hg when the two ratios were combined. As diet can affect the composition of the gut microbiome, it is expected that the bacteria inhabiting the intestines of prey specialists will vary with differential diets. Males and females also present variating feeding habits which could potentially change their gut bacterial communities. We present the first description of the gut microbiome of the thick-billed murre. Diet categories were associated with variation in the gut microbiome. The bacteria that dominate the microbial community may be aiding their host to better metabolize the nutrients of their specialized diet. Differences in bacterial diversity were also found between males and females which can be explained by the variation in feeding times by sex that occurs at the studied colony.
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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 | 0.000 | 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) | 0.001 | 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".