Shedding new light on old species identifications: morphological and genetic evidence suggest a need for conservation status review of the critically endangered bat, Saccolaimus saccolaimus
Bibliographic record
Abstract
Information based on the accurate identification of species is a vital component for achieving successful outcomes of biodiversity conservation and management. It is difficult to manage species that are poorly known or that are misidentified with other similar species. This is particularly problematic for rare and threatened species. Species that are listed under endangered species classification schemes need to be identified accurately and categorised correctly so that conservation efforts are appropriately allocated. In Australia, the emballonurid Saccolaimus saccolaimus is currently listed as ‘Critically Endangered’. On the basis of new observations and existing museum specimens, we used a combination of genetic (mitochondrial DNA sequence) and morphological (pelage characteristics, dig III : phalanx I length ratio, inter-upper canine distance) analyses to identify six new geographic records for S. saccolaimus, comprising ~100 individuals. Our analyses also suggested that there are likely to be more records in museum collections misidentified as S. flaviventris specimens. The external morphological similarities to S. flaviventris were addressed and genetic, morphological and echolocation analyses were used in an attempt to provide diagnostic characters that can be used to readily identify the two species in the field. We recommend genetic testing of all museum specimens of Australian Saccolaimus to clarify species’ distributions and provide data for reassessing the conservation status for both S. saccolaimus and S. flaviventris. Museum curators, taxonomists and wildlife managers need to be aware of potential species misidentifications, both in the field and laboratory. Misidentifications that result in misclassification of both threatened and non-threatened species can have significant implications.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".