Insights on the evolutionary origin of Detarioideae, a clade of ecologically dominant tropical African trees
Bibliographic record
Abstract
African tropical forests are generally considered less diverse than their Neotropical and Asian counterparts. By contrast, the Detarioideae is much more diverse in Africa than in South America and Asia. To better understand the evolution of this contrasting diversity pattern, we investigated the biogeographical and ecological origin of this subfamily, testing whether they originated in dry biomes surrounding the Tethys Seaway as currently hypothesized for many groups of Leguminosae. We constructed the largest time-calibrated phylogeny for the subfamily to date, reconstructed ancestral states for geography and biome/habitat, estimated diversification and extinction rates, and evaluated biome/habitat and geographic shifts in Detarioideae. The ancestral habitat of Detarioideae is postulated to be a primary forest (terra firme) originated in Africa-South America, in the early Palaeocene, after which several biome/habitat and geographic shifts occurred. The origin of Detarioideae is older than previous estimates, which postulated a dry (succulent) biome origin according to the Tethys Seaway hypothesis, and instead we reveal a post Gondwana and terra firme origin for this early branching clade of legumes. Detarioideae include some of the most dominant trees in evergreen forests and have likely played a pivotal role in shaping continental African forest diversity.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".