Introduction and synthesis: plant phylogeny and the origin of major biomes
Bibliographic record
Abstract
Phylogenetic trees based upon DNA sequence data, when calibrated with a dimension of time, allow inference of: (i) the pattern of accumulation of lineages through time; (ii) the time of origin of monophyletic groups; (iii) when lineages arrived in different geographical areas; (iv) the time of origin of biome-specific morphologies. This gives a powerful new view of the history of biomes that in many cases is not provided by the incomplete plant fossil record. Dated plant phylogenies for angiosperm families such as Leguminoaceae (Fabaceae), Melastomataceae sensu stricto, Annonaceae and Rhamnaceae indicate that long-distance, transoceanic dispersal has played an important role in shaping their distributions, and that this can obscure any effect of tectonic history, previously assumed to have been the major cause of their biogeographic patterns. Dispersal from other continents has also been important in the assembly of the Amazonian rainforest flora and the Australian flora. Comparison of dated biogeographic patterns of plants and animals suggests that recent long-distance dispersal might be more prevalent in plants, which has major implications for community assembly and coevolution. Dated plant phylogenies also reveal the role of past environmental changes on the evolution of lineages in species-rich biomes, and show that recent Plio-Pleistocene diversification has contributed substantially to their current species richness. Because of the critical role of fossils and morphological characters in assigning ages to nodes in phylogenetic trees, future studies must include careful morphological consideration of fossils and their extant relatives in a phylogenetic context. Ideal study systems will be based upon DNA sequence data from multiple loci and multiple fossil calibrations. This allows cross-validation both of age estimates from different loci, and from different fossil calibrations. For a more complete view of biome history, future studies should emphasize full taxon sampling in ecologically important groups, and should focus on geographical areas for which few species-level phylogenies are available, such as tropical Africa and Asia. These studies are urgent because understanding the history of biomes can both inform conservation decisions, and help predict the effects of future environmental changes at a time when biodiversity is being impacted on an unprecedented scale.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.121 | 0.030 |
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".