A standardized dataset for conservation prioritization of songbirds to support CITES
Bibliographic record
Abstract
In this article we present a standardized dataset on 6659 songbirds (Passeriformes) highlighting information relevant to species conservation prioritization with a main focus to support the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Data were collected from both scientific and grey literature as well as several online databases. The data are structured into six knowledge categories: Conventions and Treaties, Human Use, Extinction Risk, Management Opportunities, Biological Information, and Intrinsic Values. The Conventions and Treaties category includes the listings for two international conventions, CITES and the Convention on the Conservation of Migratory Species of Wild Animals (CMS), as well as EU listings for the EU Wildlife Trade Regulations and the EU Birds Directive. The Human Use category contains information on both regulated trade collected from the CITES Trade Database and the United States' Law Enforcement Management Information System (LEMIS), and highly aggregated data on seizures which we obtained from TRAFFIC, the United Nations Office on Drugs and Crime (UNODC) and two data sources on traditional medicine. We also present, for the first time, the complete Songbirds in Trade Database (SiTDB), a trade database curated by taxon expert S. Bruslund based on expert knowledge, literature review, market surveys and sale announcements. Data on the types of human use, including traditional medicine are also provided. The knowledge area on Extinction Risk contains data on the species' IUCN Red List status, the Alliance for Zero Extinction Trigger Species status, site and population at the site, the species' IUCN Climate Change Vulnerability Assessment, and the listing of priority species at the Asian Songbird Crisis Summit. In the Management Opportunities category, we gathered data on ex-situ management from Species360 zoo holdings as well as species management plans from the European and North American Zoo Associations (EAZA and AZA, respectively). Biological Information includes data on body mass, clutch size, diet, availability of data from the IUCN Red List on habitat systems, extent of occurrence, generation length, migration pattern, distribution, and biological data from the Demographic Species Knowledge Index, number of occurrences recorded by the Global Biodiversity Information Facility (GBIF) as well as genomic data from the Bird 10 000K Genomes (B10K) project, Vertebrate Genome Project (VGP) and GenBank. Information on invasive species is also part of this knowledge area. The Intrinsic Value category refers to two measures of the species' intrinsic value, namely Ecological and Evolutionary Distinctiveness. In order to make these knowledge areas comparable, we standardized data following the taxonomy of the Handbook of the Birds of the World and Birdlife (Version 4, 2019). The data enable a broad spectrum of analyses and will be useful to scientists for further research and to policymakers, zoos and other conservation stakeholders for future prioritization decisions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.012 |
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".