Assessments of genetic and reproductive health in Canada’s endangered Oregon Spotted Frog (Rana pretiosa)
Bibliographic record
Abstract
Zoological institutions are increasingly relied upon for ex situ management of species at risk, \nwith conservation breeding and reintroduction programs providing both assurance against \nextinction and a reliable source of offspring to reinforce wild population sizes. Ex situ efforts \nface many challenges, however. One often overlooked challenge is balancing genetic priorities, \nlike retaining genetic diversity and reducing inbreeding, with reproductive priorities, like mate \ncompatibility and reliable breeding, both of which are required for a successful program. Like \nmany amphibians, the Oregon Spotted Frog (Rana pretiosa) is highly threatened in its native \nhabitat and ongoing conservation breeding and reintroduction programs are experiencing \nlimited success; the genetic sustainability of these populations remains unassessed. In this \nstudy, I evaluated the genetic health of both zoo and wild populations of R. pretiosa in Canada \nand investigated some potential causes of the ongoing ex situ reproductive failures associated \nwith egg binding. I found that zoos have maintained stable genetic metrics relative to their wild \nsources, but ongoing collections from wild populations should be reassessed due to low genetic \ndiversity available therein. No clear causes of egg binding were elucidated but I found older \nfemale frogs (> 3 years old) who became egg bound generally had a higher body mass than \nconspecifics, while body mass did not differ in females becoming egg bound in their first \nbreeding season (2-3 years old). This suggests frogs should be monitored for egg binding and \nchanges in body condition differently depending on their age. Overall, there were no significant \ndifferences in genetic or reproductive health across the three zoo conservation breeding \npopulations, but scaled mass index was significantly lower in the zoo with larger holding tanks \nand less genetic management: a reminder of the importance of husbandry and environment in \nconservation breeding program outcomes. The costs and benefits of strict genetic management \nvs. a more communal breeding approach should be carefully considered in light of these results. \nAlong with more cohesion, communication is required between all involved institutions to have \nan effective impact on the conservation of Oregon Spotted Frogs in Canada, the \nrecommendations discussed here have applicability to amphibian ex situ programs worldwide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".