Ecological immunology in a fluctuating environment: an integrative analysis of tree swallow nestling immune defense
Bibliographic record
Abstract
Evolutionary ecologists have long been interested by the link between different immune defenses and fitness. Given the importance of a proper immune defense for survival, it is important to understand how its numerous components are affected by environmental heterogeneity. Previous studies targeting this question have rarely considered more than two immune markers. In this study, we measured seven immune markers (response to phytohemagglutinin (PHA), hemolysis capacity, hemagglutination capacity, plasma bactericidal capacity, percentage of lymphocytes, percentage of heterophils, and percentage of eosinophils) in tree swallow (Tachycineta bicolor) nestlings raised in two types of agro-ecosystems of contrasted quality and over 2 years. First, we assessed the effect of environmental heterogeneity (spatial and temporal) on the strength and direction of correlations between immune measures. Second, we investigated the effect of an immune score integrating information from several immune markers on individual performance (including growth, mass at fledging and parasite burden). Both a multivariate and a pair-wise approach showed variation in relationships between immune measures across years and habitats. We also found a weak association between the integrated score of nestling immune function and individual performance, but only under certain environmental conditions. We conclude that the ecological context can strongly affect the interpretation of immune defenses in the wild. Given that spatiotemporal variations are likely to affect individual immune defenses, great caution should be used when generalizing conclusions to other study systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".