You are how you eat: stable isotopes unravel the feeding mode-trophic position relationship in trematode parasites
Bibliographic record
Abstract
Stable isotopes have been sporadically used over the last two decades to characterise host-parasite trophic relationships. The main reason for this scarcity is the lack of an obvious pattern in the nitrogen stable isotope values ( δ 15 N) of parasites in comparison to their host tissues, which would be key to understand any host-parasite system dynamics. To circumvent this, we focused on a single snail host, Zeacumantus subcarinatus, and three of its trematode parasites. We used stable isotopes to investigate each host-trematode trophic relationship and shed light on the mechanisms utilised by the parasite to reroute its hosts’ biomass. All our trematodes were found to be 15 N-enriched compared to their host, with their δ 15 N values strongly related to their feeding behaviours: passive vs active. It was possible to ‘rank’ these parasite species and assess their ‘relative’ trophic position using δ 15 N values. We also demonstrated that including a broader range of samples (e.g. host food and faeces, multiple parasite life stages) helped understand the metabolic mechanisms used by the various participants, and that using carbon stable isotope values and C:N ratios allowed to identify an important lipid requirement of these trematode parasites. Finally, we show how critical it is to not ignore parasitic infections as they can have a great influence on their host’s trophic position.
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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 | 0.001 |
| 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".