Phylogenetic diversity and the conservation biogeography of African primates
Bibliographic record
Abstract
Abstract Aim Phylogenetics has an important role in conservation biogeography. However, there are few data on the phylogenetic diversity of African primates. The phylogenetic diversity (PD) of a species is a measure of its taxonomic distinctness and can be estimated by looking at the phylogenetic relationships among taxa. Species‐specific metrics on PD can then be used to determine conservation priorities at various biogeographical scales. We used PD metrics to rank 55 African primate species according to their conservation priorities at the country level and within six African biogeographical regions. We also addressed the following question: are there differences in conservation rankings between the IUCN Red List and our PD metrics? Location Africa. Methods We created a consensus phylogeny for all African primate clades based on genetic studies. Analyses of species distributions were determined using presence / absence scores at two levels: country and biogeographical region. A node‐based method that standardizes for widespread taxa and endemicity was used to calculate PD indices. Hierarchical cluster analysis was used to convert one of the standardized, phylogenetic indices into three clusters that could be ranked and compared with the main IUCN conservation rankings of endangered, vulnerable, and lower risk. Results At the country and region levels, the top‐priority species in terms of PD are Pan paniscus , Macaca sylvanus , Arctocebus calabarensis , Gorilla beringei , Arctocebus aureus , Allenopithecus nigroviridis , Gorilla gorilla , Procolobus verus , Cercopithecus solatus , Cercocebus galeritus, Colobus angolensis , Theropithecus gelada , Galagoides zanzibaricus, Galagoides granti, and Procolobus (Piliocolobus) badius . Geographic rankings were highest for the Democratic Republic of the Congo (country level) and Central Africa (region level). Although there were no overall differences between IUCN conservation ranks and the PD rankings, there were significant differences between the two systems for vulnerable and endangered primate taxa. Main conclusions There are few ecological and behavioural data on populations of some of the African primates that represent the highest levels of phylogenetic diversity. Studies of primate taxa with high PD rankings should focus on identifying sites suitable for intensive studies of population densities, feeding ecology, and reproductive behaviour. We suggest that PD metrics can serve as an important, complementary data set in the IUCN ranking system for primates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".