Exploited and excreting: parasite type affects host nutrient recycling
Bibliographic record
Abstract
Parasite-induced changes in the nutrient balance of hosts could alter the availability of nutrients in ecosystems by changing consumer-driven nutrient recycling. While these effects on host nutrient use are mediated by host physiology, they likely depend on characteristics of the parasite and host diet quality. We examined this possibility by measuring nutrient release rates of uninfected Daphnia and conspecifics infected by two microparasites (the bacterium Pasteuria ramosa and the microsporidium Hamiltosporidium tvaerminnensis) from daphnid hosts fed food that varied in phosphorus content. We found that infection type and diet affected host nutrient release rates, but the strength of these effects varied among parasite treatments. To improve our understanding of these effects, we examined whether two separate aspects of host exploitation (parasite-induced reductions in host fecundity and parasite load) could account for variation in Daphnia nutrient release, ingestion, and elemental ratios caused by our infection and diet treatments. Regardless of whether we compared individuals across infection type or diet treatment, Daphnia fecundity described variation in multiple aspects of host nutrient use better than infection, diet, or spore load. Our results suggest that parasite-induced changes in host nutrient use are both parasite and diet specific, and that host fecundity could be a useful parameter for predicting the magnitude and direction of these changes.
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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 | 0.000 | 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".