Imperilled phylogenetic endemism of Malagasy lemuriformes
Bibliographic record
Abstract
Abstract Aim To highlight where in Madagascar the phylogenetically and spatially rare lemur species at risk of extinction are concentrated. Location Madagascar. Methods Phylogenetic endemism (PE) is a combined measure for apportioning a phylogenetic tree across a landscape used to identify those geographical locations that contain spatially rare phylogenetic diversity (Rosauer et al., 2009). We present a simple extension (imperilled phylogenetic endemism) that scales this phylogenetic diversity by the probability of its loss to extinction. We apply these measures to a composite phylogeny of all confirmed Malagasy lemuriform species using International Union for Conservation of Nature (IUCN) extent of occurrence and threat status data. Results We find that, because nonimperilled species are scattered about the lemuriform tree, interior branches of the tree are still quite secure: this also means that areas of high phylogenetic endemism for Madagascar lemuriformes are often the same areas as those of high imperilled PE (IPE), as both are heavily weighted by branches nearer the tips. However, although the North of Madagascar holds the largest amount of spatially rare evolutionary history using both PE and IPE, there are additional pockets of imperilled history in the south and west. Main Conclusions Correlations of endemism and threat status with phylogenetic isolation are modest across lemurs and so are not substitutable conservation values. They might best be integrated on the landscape using IPE. As illustrated here, IPE successfully highlights areas containing species which are at once threatened with extinction and that are phylogenetically and spatially rare.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".