Parasite‐induced alterations of host behaviour in a riverine fish: the effects of glochidia on host dispersal
Bibliographic record
Abstract
Summary Parasitic species can affect host behaviour in various ways. Freshwater mussels of the superfamilyUnionoidea have a glochidia larva that is parasitic on fish. Our aim was to evaluate whether fish exposed to glochidia have distinct behaviour that could affect the upstream dispersal of the parasite. Many freshwater mussels are highly endangered, and understanding the relationships with their hosts is important for their conservation. However, research on the behavioural effects of parasitism on fish host activity and/or the upstream dispersal of mussel larvae in nature has received little attention. Specifically, we examined a fish (the chub,Squalius cephalus) that hosts the larval stage of a freshwater bivalve (Anodonta anatina) and investigated alterations in host behaviour induced by the parasite. One laboratory and two field experiments were conducted using passive integrated transponder systems and radio‐telemetry. Infected fish were generally less active in the laboratory and, in the field, dispersed less far upstream. Moreover, radio‐telemetry revealed a habitat shift by the infected fish, which were found further from the riverbank. We suggest that behavioural changes in the fish that are induced by glochidia do not facilitate the long‐distance dispersal of the mussel but rather cause reductions in fish activity and slight habitat shifts. Possible consequences of such behavioural alterations are discussed.
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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".