Conserving species' evolutionary potential and history: Opportunities under the <scp>Kunming–Montreal</scp> Global Biodiversity Framework
Bibliographic record
Abstract
Abstract Genetic diversity (GD) and phylogenetic diversity (PD) respectively represent species' evolutionary potential and history, and support most of the biodiversity benefits to humanity. Yet, these two biodiversity facets have been overlooked in previous biodiversity policies. As the Parties to the Convention on Biological Diversity (CBD) adopted the Kunming–Montreal Global Biodiversity Framework (GBF) in December 2022, we analyze how GD and PD are considered in this new framework and discuss how their incorporation in the GBF could strengthen their conservation. Although the inclusion of certain indicators could be elevated, both GD and PD are an integral part of the recently adopted GBF. This represents a significant improvement compared to the CBD strategic plan 2011–2020 and an unprecedented opportunity to bring species' evolutionary potential and history to the core of public biodiversity policies. We urge the scientific community to leverage this opportunity to actually improve the conservation of species' evolutionary potential and history.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".