A complete and dynamic tree of birds
Bibliographic record
Abstract
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 (NCBI), and Global Biodiversity Information Facility (GBIF). 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 v1.2 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. Significance statement Birds are charismatic - well loved, and highly studied. Many new phylogenies elucidating avian birds evolutionary relationships are published every year. We have united phylogenetic estimates from hundreds of studies to create a complete evolutionary tree of all birds. While a variety of resources aggregate huge collections of trait, behavior and location data for birds, previously the barriers to linking data between these data resources and bird evolutionary history have limited the opportunities to do exciting large scale analyses. We have bridged that gap, and developed a system that allows us to easily update our understanding of bird evolution as new estimates are generated. We share a workflow and the software needed to create a complete evolutionary tree for any group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".