ReviewScientific reports2025
Assessing the completeness and consistency of global-scale avian datasets.
Review in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The advancement of ecological research has increasingly focused on comparative methods and global-scale analyses. Birds are frequently selected for such studies for their widespread distribution and sensitivity to environmental changes. Given the need to integrate fragmented avian data, we aim to collect global-scale avian datasets and evaluate the completeness and consistency of them. We reviewed literature published in Springer Nature and American Association for the Advancement of Science (AAAS) from 2020 to 2024 and identified 90 articles with large-scale coverage and broad taxonomic representation. From these, we compiled 123 datasets covering environmental factors, avian traits, and ecosystem-level data. These were categorized into species-level and spatial data for completeness assessment, while consistency was evaluated across three modalities: species lists, nominal variables, and continuous variables. The database encompassed 12 distinct data types, including morphological, physiological, behavioural, and life-history traits, niche characteristics, evolutionary data, and environmental factors. Our assessment revealed that species distribution and abundance data were most frequently utilized in avian research worldwide. Both the species-level and spatial data exhibited high completeness. Continuous variables showed high consistency, whereas nominal variables and species lists exhibited moderate consistency with notable variability. Therefore, the supplementation of low-integrity data such as reproductive and behavioural datasets remains imperative. Systematic reconciliation between legacy and revised avian taxonomic inventories are critical for ensuring the consistency of data. We hope that the work can advance understanding of macroecology and providing guidance for global avian research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.