Langbiangia, a new genus of Gesneriaceae endemic to Langbiang Plateau, southern Vietnam and a taxonomic endeavor to achieve key targets of the post-2020 global biodiversity framework
Bibliographic record
Abstract
Situated in the southern end of the Annamite Mountain Range, Langbiang Plateau is a major biodiversity hotspot of southern Vietnam known for high species diversity and endemicity. To achieve effective conservation, parts of the plateau were designated as the Langbiang Biosphere Reserve, an UNESCO World Network aiming to improve relationships between inhabitants and their environments. Amongst the rich endemic flora of the plateau are three gesneriads ascribed to Primulina, a calciphilous genus with high species diversity in the vast limestone karsts stretching from southern China to northern Vietnam. However, a recent phylogenetic study questioned the generic placement of the Langbiang Primulina, corroborating with observations on the geographical distribution, habitat preference, and phyllotaxy of the three species. Based on phylogenetic analyses of nuclear ITS and plastid trnL-F DNA sequences of a comprehensive sampling covering nearly all genera of the Old World Gesneriaceae, we demonstrate that the three Langbiang Primulina species form a fully supported clade distantly related to other Primulina. As this clade is biogeographically, ecologically, morphologically, and phylogenetically distinct worthy of generic recognition, we propose to name it Langbiangia gen. nov. to highlight the rich and unique biodiversity of the Langbiang Plateau. By means of this taxonomic endeavor, we are hoping to raise the conservation awareness of this biodiversity heritage of southern Vietnam and promote the importance of Langbiang Biosphere Reserve that is crucial for achieving action-oriented global targets of the post-2020 global biodiversity framework (GBF) of the UN Convention on Biological Diversity (CBD)-effective conservation and management of at least 30% of biodiverse terrestrial, inland water, and costal and marine areas by 2030-that has been agreed at the COP15 in Montréal in December 2022.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".