Shades of grey: Coat-colour dependent effect of urbanization on the bacterial microbiome of a wild mammal
Bibliographic record
Abstract
Abstract Background Host-associated microbiota can be fundamental to the ecology of their host and may even help wildlife species colonize novel niches or cope with rapid environmental change. Urbanization is a globally replicated form of severe environmental change which we can leverage to better understand wildlife microbiomes. Does the colonization of separate cities result in parallel changes in the intestinal microbiome of wildlife, and if so, does within-city habitat heterogeneity matter? Using 16S rRNA gene amplicon sequencing, we quantified the effect of urbanization on the microbiome of eastern grey squirrels ( Sciurus carolinensis ). Eastern grey squirrels are ubiquitous in both rural and urban environments throughout their native range, across which they display an apparent coat colour polymorphism (agouti, black, intermediate). Results Grey squirrel microbiomes differed between rural and city environments; however, comparable variation was explained by habitat heterogeneity within cities. Our analyses suggest that operational taxonomic unit (OTU) community structure was more strongly influenced by local environmental conditions (rural and city forests versus human built habitats) than urbanization of the broader landscape (city versus rural). Many of the bacterial genera identified as characterizing the microbiomes of built-environment squirrels are though to specialize on host-derived products and have been linked in previous research to low fibre diets. However, despite an effect of urbanization at fine spatial scales, phylogenetic patterns in the microbiome were coat colour phenotype dependent. City and built environment agouti squirrels displayed greater phylogenetic beta-dispersion than those in rural or forest environments, and null modelling results indicated that the phylogenetic structure of urban agouti squirrels did not differ greatly from stochastic phylogenetic expectations. Conclusions Habitat heterogeneity at fine spatial scales affects host-associated microbiomes, however, we found little evidence that this pattern was the result of similar selective pressures acting on the microbiome within environments. Further, this result, those of phylogeny-independent analyses, and patterns of beta-dispersion lead us to suggest that microbiota dispersal and ecological drift are integral to shaping the inter-environmental differences we observed. These patterns were partly mediated by squirrel coat colour phenotype, and therefore putatively, host physiology. Given a well-known urban cline in squirrel coat colour melanism, grey squirrels provide an ideal free-living system with which to study how host genetics mediate environment x microbiome interactions.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".