The impacts of urbanization on the bacterial communities of mountain chickadees (Poecile gambeli)
Bibliographic record
Abstract
Urbanization is a global process with numerous consequences on wildlife, including the amplification of certain infectious diseases. No studies have yet determined if this pattern exists across all detectable pathogenic bacteria, and few have investigated how bacterial communities change across urban to rural/native habitat gradients. We used whole-community sequencing of partial 16S rRNA gene amplicons to examine relationships between urban and rural bacterial communities found on Mountain Chickadee (Poecile gambeli) feathers and nests in Kamloops, British Columbia, Canada. Between urban and rural sites, we observed mostly similar abundances of major bacterial phyla, and dominant genera with pathogenic members, on both bird feathers and their nests. However, urban habitats tended to increase the richness of both bacterial communities and potential pathogens on birds, and accounted for some of the differences in bacterial occurrence between urban and rural environments. Similarities in bacterial communities between nests and their occupants indicated some degree of transmission occurred between them, or that shared environments result in similar community assemblages. We predicted habitat using potential pathogen occurrence with a 90% success rate for feather bacteria, and a 72.2% success rate for nest bacteria, indicating an influence of urban environments on potential pathogen presence. Our findings show that urban environments result in significant differences between urban and rural bacteria associated with Mountain Chickadees, with potential indications towards diverging disease dynamics across urban and rural gradients.
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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 | 0.001 | 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) | 0.001 | 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".