Tracing aquatic resource contributions to Tree and Barn Swallow nestling diets across a cropland and wetland gradient
Bibliographic record
Abstract
The nutritional quality of nestling diets, influenced by parental prey selection, determines offspring health and development. In agricultural landscapes, nestling diets may be impacted by changes in prey availability from agricultural intensification. In 2020 and 2021, we compared landscape-level effects on nestling prey resources in two sympatric species of breeding aerial insectivores, Tree Swallow (Tachycineta bicolor) and Barn Swallow (Hirundo rustica). Our study was conducted across an agricultural crop and wetland gradient in Saskatchewan, Canada. Using hydrogen stable isotope analyses (δ²H) of nestling feathers, as an indicator of differential diet composition of terrestrial vs. aquatic-emergent insects, we hypothesized that Tree Swallows, as aquatic insect specialists, would have lower feather δ²H values indicative of more aquatic diets. We predicted that increasing annual-row crop and wetland cover around nests would differentially impact each species with Tree Swallows being more sensitive to landscape differences given known reliance on wetland-derived prey. Wetland waters and select aquatic and terrestrial insects showed high variation presumably due to seasonal stochastic evaporation requiring greater sampling effort. However, evidence of differential use of aquatic resources was consistently found between the two swallow species and between wet versus dry years. Lower average Tree Swallow nestling feather δ²H values suggested their diet was more reliant on aquatic-emergent prey, unrelated to the land use around the nest (at 500–2000 m). In contrast, Barn Swallows had higher average feather δ²H, which decreased with greater standing water cover in proximity of the nest (< 500 m), suggesting more terrestrial diets with opportunistic use of aquatic-emergent prey resources. For both species, we found no effect of crop cover extent on the isotopic indicator of prey source. These results contribute to the growing body of evidence that multiple species of aerial insectivores rely on aquatic insect resources regardless of local agricultural land use. Our results highlight the importance of conservation of small, interspersed wetlands, especially in intensive cropland-dominated landscapes, to benefit multiple species of aerial insectivores.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.000 |
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".