A complete and dynamic tree of birds
Bibliographic record
Abstract
We present a complete, time-scaled, evolutionary tree of the world's bird species. This tree unites phylogenetic estimates for 9,239 species from 262 studies published between 1990 and 2024, using the Open Tree synthesis algorithm. The remaining species are placed in the tree based on curated taxonomic information. The tips of this complete tree are aligned to the species in the Clements Taxonomy used by eBird and other resources, and cross-mapped to other taxonomic systems including the Open Tree of Life (Open Tree), National Center for Biotechnology Information, and Global Biodiversity Information Facility. The total number of named bird species varies between 10,824 and 11,017 across the taxonomy versions we applied (v2021, v2022, and v2023). We share complete trees for each taxonomy version. The procedure, software, and data stores we used to generate this tree are public and reproducible. The tree presented here is Aves 1.3 and can be easily updated with new phylogenetic information as new estimates are published. We demonstrate the types of large-scale analyses this data resource enables by linking geographic data with the phylogeny to calculate the regional phylogenetic diversity of birds across the world. We will release updated versions of the phylogenetic synthesis and taxonomic translation tables annually. The procedure we describe here can be applied to developing complete phylogenetic estimates for any taxonomic group of interest.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".