Thermal tolerance and survival are modulated by a natural gradient of infection in differentially acclimated hosts
Bibliographic record
Abstract
ABSTRACT Wild ectotherms are exposed to multiple stressors, including parasites, which can affect their responses to environmental change. Simultaneously, unprecedented warm temperatures are being recorded worldwide, increasing both the average and maximum temperatures experienced in nature. Understanding how ectotherms, such as fishes, will react to the combined stress of parasites and higher average temperatures can help predict the impact of extreme events such as heat waves on populations. The critical thermal method (CTM), which assesses upper (CT max ) and lower (CT min ) thermal tolerance, is often used in acclimated ectotherms to help predict their tolerance to various temperature scenarios. Yet, few studies have characterized the response of naturally infected fish to extreme temperature events or how acute thermal stress affects subsequent survival. We acclimated naturally infected pumpkinseed sunfish ( Lepomis gibbosus ), to four ecologically relevant temperatures (10, 15, 20 and 25°C) and one future warming scenario (30°C) for three weeks, before measuring CT max and CT min . We also assessed individual survival the week following CT max . Interestingly, trematode parasites causing black spot disease were negatively related to CT max , suggesting that heavily infected fish are less tolerant to acute warming. Moreover, fish infected with yellow grub parasites showed decreased survival in the days following CT max implying that the infection load has negative survival consequences on sunfish during extreme warming events. Our findings indicate that parasite infection and high prolonged average temperatures can affect fish thermal tolerance and survival, emphasizing the need to better understand the concomitant effects of stressors on health outcomes in wild populations. Summary statement This study shows that parasites influence thermal tolerance and survival of fish, suggesting that such stressors are important to increase the ecological relevance of thermal tolerance studies of wild 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 | 0.000 | 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".