Importance of parasites and their life cycle characteristics in determining the structure of a large marine food web
Bibliographic record
Abstract
1 Despite their documented effects on trophic interactions and community structure, parasites are rarely included in food web analyses. The transmission routes of most parasitic helminths follow closely the trophic relationships among their successive hosts and are thus embedded in food webs, in a way that may influence energy flow and the structure of the web. 2 We investigated the impact of parasitism on the food web structure of a New Zealand intertidal mudflat community. Different versions of the food web were analysed, one with no parasites, one with all parasite species and several other versions, each including a single parasite species. We measured key food web metrics such as food chain length, linkage density and proportions of top, intermediate and basal species. 3 The inclusion of all parasite species in the food web resulted in greatly increased mean and maximum food chain length, but had little impact on linkage density and realized connectance. The main change caused by introduction of parasites was the relegation of a number of species from top predators to intermediate status, although the addition of parasites as top predators left the actual ratio of predators to prey relatively unchanged. 4 When individual parasites were added to the food web, their effect on food web properties was generally minimal. However, one trematode species that affected several host species, because of its complex life cycle and low host specificity, produced food web properties similar to those in the web version including all parasite species. 5 The respective effect of individual parasite species was roughly proportional to the number of host species they affected, and thus the life cycle characteristics of parasites determine to a large extent their impact on food web structure. The next step would be to quantify how they affect energy flow through the web.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".