Strong restructuration of skin microbiota during captivity challenges ex-situ conservation of amphibians
Bibliographic record
Abstract
In response to the current worldwide amphibian extinction crisis, conservation instances have encouraged the establishment of ex-situ collections for endangered species. The resulting assurance populations are managed under strict biosecure protocols, often involving artificial cycles of temperature and humidity to induce active and overwintering phases, which likely affect the bacterial symbionts living on the amphibian skin. However, the skin microbiota is an important first line of defense against pathogens that can cause amphibian declines, such as the chytrid Batrachochytrium dendrobatidis (Bd). Determining whether current husbandry practices for assurance populations might deplete amphibians from their symbionts is therefore essential to conservation success. Here, we characterize the effect of the transitions from the wild to captivity, and between aquatic and overwintering phases, on the skin microbiota of two newt species. While our results confirm differential selectivity of skin microbiota between species, they underscore that captivity and phase-shifts similarly affect their community structure. More specifically, the translocation ex-situ is associated with rapid impoverishment, decrease in alpha diversity and strong species turnover of bacterial communities. Shifts between active and overwintering phases also cause changes in the diversity and composition of the microbiota, and on the prevalence of Bd-inhibitory phylotypes. Altogether, our results suggest that current husbandry practices strongly restructure the amphibian skin microbiota. Although it remains to be determined whether these changes are reversible or have deleterious effects on their hosts, we discuss methods to limit microbial diversity loss ex-situ and emphasize the importance of integrating bacterial communities to applied amphibian conservation.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".