Data and code from: DNA metabarcoding reveals dietary divergence among sympatric swallows and flycatchers
Bibliographic record
Abstract
Aerial insectivore (AI) populations have been in steep decline in North America since the 1970s, with swallows, swifts, and nightjars declining more rapidly than flycatchers. As AI share a common diet of flying insects, reductions in insect abundance are likely one of the major factors driving population decline. Previous studies have shown major dietary differences between swallows and flycatchers; flycatchers have exhibited more diverse, generalist diets than swallows. However, no study has directly compared the diets of sympatric swallows and flycatchers using the same method of dietary analysis. To investigate these differences, we compared the diets of six AI species living in sympatry during the breeding season. We collected fecal samples from adult Riparia riparia (Bank Swallow), Hirundo rustica (Barn Swallow), Petrochelidon pyrrhonota (Cliff Swallow), Tachycineta bicolor (Tree Swallow), Empidonax alnorum (Alder Flycatcher), and E. minimus (Least Flycatcher). We used DNA metabarcoding to identify the taxonomic composition of invertebrates in the feces and compared the richness of genera by insect order, insect family, and dipteran family between all species. Through a Bray-Curtis distance-based redundancy analysis, we identified significant differences in dietary composition between bird species at all three levels; however, the greatest amount of dissimilarity is seen in the dipterans consumed. E. alnorum, E. minimus, H. rustica, and T. bicolor had broader, more generalist diets than P. pyrrhonota and R. riparia. By comparing the diets between multiple species living in sympatry, our study improves our understanding of a possible cause of disproportionate population declines observed among AI species.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.302 | 0.156 |
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".