Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history
Bibliographic record
Abstract
Phylogenetic information is increasingly being used to understand the assembly of biological communities and ecological processes. However, commonly used metrics of phylogenetic diversity (PD) do not incorporate information on the relative abundances of individuals within a community. In this study, we develop three indices of PD that explicitly consider species abundances. First, we present a metric of phylogenetic-abundance evenness that evaluates the relationship between the abundance and the distribution of terminal branch lengths. Second, we calculate an index of hierarchical imbalance of abundances at the clade level encapsulating the distribution of individuals across the nodes in the phylogeny. Third, we develop an index of abundance-weighted evolutionary distinctiveness and generate an entropic index of phylogenetic diversity that captures both information on evolutionary distances and phylogenetic tree topology, and also serves as a basis to evaluate species conservation value. These metrics offer measures of phylogenetic diversity incorporating different community attributes. We compare these new metrics to existing ones, and use them to explore diversity patterns in a typical California annual grassland plant community at the Jasper Ridge biological preserve.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".