Characterization of faecal and caecal microbiota of free-ranging black-tailed prairie dogs (<i>Cynomys ludovicianus</i>) using high-throughput sequencing of the V4 region of the 16S rRNA gene
Bibliographic record
Abstract
Abstract Black-tailed prairie dogs (Cynomys ludovicianus) are keystone species within their grassland ecosystems; their population stability affects a multitude of other species. The goals of this study were to explore, describe and compare the bacterial communities in caecal and hard faecal samples from free-ranging black-tailed prairie dogs (n = 36) from KS, USA, using high-throughput sequencing of the V4 region of the 16S rRNA gene and to compare sex and geographic locations. A total of 22 paired faecal and caecal samples were collected post-mortem from free-ranging black-tailed prairie dogs from 5 different geographical locations. The results revealed that the microbiota of both faecal and caecal samples were dominated by the phylum Firmicutes (genera belonging to the Clostridiales order). There was significantly greater richness in faecal compared with caecal samples. There were significant differences between the 5 different geographic regions (P < 0.001), specifically in the relative abundances of genera. There were differences in rare members of the microbiome between faecal samples from male and female prairie dogs but with no significant impact on overall community structure. This study provides novel data and expands our knowledge about the gastrointestinal microbiome composition of free-ranging black-tailed prairie dogs, which has potential to inform conservation efforts and improve their captive management.
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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 | 0.000 | 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) | 0.000 | 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".