Effects of agricultural intensification and temperature on immune response to phytohemagglutinin in Tree Swallows (<i>Tachycineta bicolor</i>)
Bibliographic record
Abstract
Lower immune response usually translates into lower fitness. Environmental quality can play a key role in shaping immune responses in the wild, as it influences both resource availability and costly maintenance functions. The aim of this study is to evaluate the effect of habitat quality on proinflammatory response to phytohemagglutinin (PHA) in Tree Swallows (Tachycineta bicolor (Vieillot, 1808)) under contrasting agricultural practices. Specifically, we tested the hypothesis that lower quality habitat (intensive agricultural practices and low temperature) negatively impairs immune responses. To do so, we compared the response to PHA of adult female and nestling Tree Swallows nesting in intensive vs. nonintensive agricultural landscapes over 3 years (2008–2010). In accordance with our predictions, we found that habitat quality affected adult female responses to PHA. The response of adult females was significantly higher in nonintensive agricultural areas than in intensive ones. The level of agricultural intensity, however, had no influence on the response to PHA of nestlings. Our results suggest that female adults can buffer the negative impact of a low-quality habitat on their nestlings. Furthermore, our results suggest that under limiting conditions, individuals may have to trade between immunity and other functions such as parental effort.
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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".