Data from: Rainy springs linked to poor nestling growth in a declining avian aerial insectivore (Tachycineta bicolor)
Bibliographic record
Abstract
As species shift their ranges and phenology to cope with climate change, many are left without a ready supply of their preferred food source during critical life stages. Food shortages are often assumed to be driven by reduced total food abundance, but here we propose that climate change may cause short-term food shortages for foraging specialists without affecting overall food availability. We frame this hypothesis around the special case of birds that forage on flying insects for whom effects mediated by their shared food resource have been proposed to cause avian aerial insectivores’ decline worldwide. Flying insects are inactive during cold, wet, or windy conditions, effectively reducing food availability to zero even if insect abundance remains otherwise unchanged. Using long-term monitoring data from a declining population of tree swallows (Tachycineta bicolor), we show that nestlings’ body mass declined substantially from 1977 to 2017. In 2017, nestlings had lower body mass if it rained during the preceding three days, though females increased provisioning rates, potentially in an attempt to compensate. Adult body mass, particularly that of the males, has also declined over the long-term study. Mean rainfall during the nestling period has increased 9.3±0.3 mm/decade, potentially explaining declining nestling body mass and population declines. Therefore, we suggest that reduced food availability, distinct from food abundance, may be an important and previously overlooked consequence of climate change, which could be affecting populations of species that specialize on foraging on flying insects.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".