Immune profiles vary seasonally, but are not significantly related to migration distance or natal dispersal, in a migratory songbird
Bibliographic record
Abstract
A central tenet of ecoimmunology is that an organism's environment shapes its optimal investment in immunity. For example, the benefits of acquired (relatively pathogen specific) versus innate (nonspecific) immune defenses are thought to vary with the risk of encountering familiar versus unfamiliar pathogens. Because pathogen communities vary geographically, individuals that travel farther during seasonal migration or natal dispersal are predicted to have higher exposure to novel pathogens, and lower exposure to familiar pathogens, potentially favoring investment in innate immunity. During the breeding season, migratory animals' exposure to familiar pathogens should increase, potentially favoring investment in acquired immunity. We hypothesized that song sparrows Melospiza melodia adjust their constitutive immune profiles in response to risk of encountering novel versus familiar pathogens. We predicted that individuals migrating longer distances (inferred from stable hydrogen isotope analysis of claws) and less philopatric individuals (inferred from microsatellite assignment testing) would rely more heavily on acquired than innate defenses. We also predicted that reliance on acquired defenses would increase throughout the early breeding season. Consistent with trade-offs between acquired and innate defenses, levels of immunoglobulin Y (acquired) varied negatively with macrophage phagocytosis activity (innate). Levels of acquired relative to innate immunity did not vary significantly with migration distance or philopatry, but increased throughout the early breeding season. Macrophage phagocytosis was not significantly repeatable between years. Song sparrows appear to shift from innate defenses immediately after migration to acquired defenses with increasing time at the breeding grounds. These patterns highlight the plasticity of constitutive immune defenses in migratory animals.
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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 | 0.001 | 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".