Scaling effects of temperature on parasitism from individuals to populations
Bibliographic record
Abstract
) remains a major knowledge gap. We conducted a literature review and identified 24 host-parasite systems that had information on the temperature dependence of parasitism at both individual host and host population levels: 13 vector-borne systems and 11 environmentally transmitted systems. We found a strong positive correlation between the thermal optima of individual- and population-level parasitism, although several of the environmentally transmitted systems exhibited thermal optima >5°C apart between individual and population levels. Parasitism thermal optima were close to vector performance thermal optima in vector-borne systems but not hosts in environmentally transmitted systems, suggesting these thermal mismatches may be more common in certain types of host-parasite systems. We also adapted and simulated simple models for both types of transmission modes and found the same pattern across the two modes: thermal optima were more strongly correlated across scales when there were more traits linking individual- to population-level processes. Generally, our results suggest that information on the temperature dependence, and specifically the thermal optimum, at either the individual or population level should provide a useful-although not quantitatively exact-baseline for predicting temperature dependence at the other level, especially in vector-borne parasite systems. Environmentally transmitted parasitism may operate by a different set of rules, in which temperature dependence is decoupled in some systems, requiring the need for trait-based studies of temperature dependence at individual and population levels.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".