Disentangling the effects of parasite infection and temperature on the aerobic swimming performance of pumpkinseed hosts
Bibliographic record
Abstract
Climate change is shifting the aerobic capacity of aquatic ectotherms, affecting their ability to move efficiently through their environment. Rising temperatures also alter host–parasite interactions, yet how these stressors interact to impact locomotion remains unclear. This is especially relevant for infections that disrupt streamlining and fin function, with implications for wild fish populations, aquaculture, and fisheries. Pumpkinseed sunfish ( Lepomis gibbosus (Linnaeus, 1758)), a popular recreational fishing species, are naturally co-infected with trematodes, forming rigid cysts on fins and body, and cestode tapeworms, infecting the liver and digestive tract. We tested whether pumpkinseed swimming performance is affected by drag from cysts by measuring critical swimming speed ( U crit ) and aerobic metabolic traits in naturally infected fish and fish treated to remove cestodes. Individuals with more cysts had lower U crit , maximum metabolic rate (MMR) and aerobic scope, likely due to increased drag. Next, we acclimated wild-caught, co-infected fish to 20, 25, and 30 °C and measured U crit and MMR. Warmer temperatures increased both metrics, and internal parasites were related to reduced MMR and U crit . Overall, infections can impair swimming by increasing drag and through physiological effects, but warming does not appear to exacerbate these effects in species not living near their thermal limits.
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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".