Influence of tree shape and evolutionary time‐scale on phylogenetic diversity metrics
Bibliographic record
Abstract
During the last decades, describing, analysing and understanding the phylogenetic structure of species assemblages has been a central theme in both community ecology and macro‐ecology. Among the wide variety of phylogenetic structure metrics, three have been predominant in the literature: Faith's phylogenetic diversity (PD Faith ), which represents the sum of the branch lengths of the phylogenetic tree linking all species of a particular assemblage, the mean pairwise distance between all species in an assemblage (MPD) and the pairwise distance between the closest relatives in an assemblage (MNTD). Comparisons between studies using one or several of these metrics are difficult because there has been no comprehensive evaluation of the phylogenetic properties each metric captures. In particular it is unknown how PD Faith relates to MDP and MNTD. Consequently, it is possible that apparently opposing patterns in different studies might simply reflect differences in metric properties. Here, we aim to fill this gap by comparing these metrics using simulations and empirical data. We first used simulation experiments to test the influence of community structure and size on the mismatch between metrics whilst varying the shape and size of the phylogenetic tree of the species pool. Second we investigated the mismatch between metrics for two empirical datasets (gut microbes and global carnivoran assemblages). We show that MNTD and PD Faith provide similar information on phylogenetic structure, and respond similarly to variation in species richness and assemblage structure. However, MPD demonstrate a very different behaviour, and is highly sensitive to deep branching structure. We suggest that by combining complementary metrics that are sensitive to processes operating at different phylogenetic depths (i.e. MPD and MNTD or PD Faith ) we can obtain a better understanding of assemblage structure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".