Phylogenetic patterns of rarity in a regional species pool of tropical woody plants
Bibliographic record
Abstract
Abstract Aim Rarity, which is believed to influence extinction risk, can be defined in terms of local abundance, geographical range size and habitat breadth. Phylogenetic patterns in these attributes provide insight into the extent to which rarity and extinction risk are conserved during evolution and the potential for species‐level heritability. We evaluated phylogenetic signal (i.e., related species resembling each other more than species drawn at random) and evolutionary conservatism (similarity among related species exceeding that expected from a Brownian model of evolution) in three axes of rarity (local abundance, geographical range size and habitat breadth) among species in a regional pool of tropical woody plants. Location The Madidi region in Bolivia. Time period 2001–2010. Major taxa studied Lignophyta clade. Methods We used a network of 48 1‐ha forest plots and 442 0.1‐ha forest plots to measure local abundance and habitat breadth of 1,700+ woody plant species (from 100+ plant families). We estimated geographical range size from occurrence records of individual species across the Neotropics. We characterized overall phylogenetic patterns of rarity using Blomberg'sKand applied variance partitioning among taxonomic levels, as well as disparity analysis, to describe patterns of trait distribution at different depths in the phylogeny. Results We found phylogenetic signal, but not evolutionary conservatism, in the three axes of rarity. The variance in rarity among supra‐specific taxa, particularly families and genera, exceeded that calculated from random draws of species from the Madidi region. Phylogenetic signal, estimated by the proportion of variance among supra‐specific taxonomic levels, varied between 23 and 36% for local abundance and geographical range size, and between 9 and 10% for habitat breadth. Main conclusions The regional pool of woody plant species in Madidi exhibits phylogenetic signal in rarity that is consistent with biologically significant species‐level heritability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".