Seasonal Redistribution of Immune Function in a Migrant Shorebird: Annual‐Cycle Effects Override Adjustments to Thermal Regime
Bibliographic record
Abstract
Throughout the annual cycle, demands on competing physiological systems change, and animals must allocate resources to maximize fitness. Immune function is one such system and is important for survival. Yet detailed empirical data tracking immune function over the entire annual cycle are lacking for most wild animals. We measured constitutive immune indices once a month for a year on captive red knots (Calidris canutus). We also examined temperature as an environmental contributor to immune variation by manipulating ambient temperature to vary energy expenditure. To identify relationships among immune indices, we performed principal-component analysis. We found significant repeatability in immune indices over the annual cycle and covariation of immune indices within and among individuals. This covariation suggests immune strategies as individual traits among individuals and the use of different immune strategies during different annual-cycle stages within individuals. Over the annual cycle, both higher-cost phagocyte-based immunity and lower-cost lymphocyte-based immunity were high during mass change, but there was a clear shift toward lower-cost lymphocyte-based immunity during peak molt. Experimental manipulation of temperature had little effect on annual variation in immune function. This suggests that other environmental factors, such as food availability and disease, should also be examined in the future.
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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".