Competition constrains parasite adaptation to thermal heterogeneity
Bibliographic record
Abstract
Abstract Temporal thermal heterogeneity is expected to favour intermediate, generalist phenotypes that can maintain growth across a broad thermal range but have sub-optimal growth at any single temperature. Yet, thermal variation typically occurs in the presence of additional selection pressures which may interact to constrain adaptation to temperature. We propagated competing lytic viral parasites (bacteriophages, thermal specialist φ14–1 and thermal generalist φLUZ19) of Pseudomonas aeruginosa under fluctuating temperatures (37°C–42°C) in monoculture and in co-culture. Without competition, fluctuating temperatures resulted in intermediate thermal phenotypes in the phage φ14–1 and, in both phages, resulted in more variable evolutionary outcomes compared to static conditions. Selection from both fluctuating temperatures and competition accelerated thermal adaptation in the phage φ14–1. However, co-selection led to restricted thermal adaptation, lower genetic distance from ancestor, and fewer putative adaptive mutations in the phage φLUZ19. Our study highlights the potential for variable adaptive capacity in interacting communities amidst global climate change.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".