Host phenology, geographic range size and regional occurrence explain interspecific variation in damselfly–water mite associations
Bibliographic record
Abstract
In this study, we tested which host species’ characteristics explain the nature and level of parasitism for host damselfly (Coenagrionidae)–water mite (Arrenuridae) parasite associations. Prevalence and intensity of mite parasites, and mite species richness were examined in relation to geographic range size, regional occurrence, relative local abundance, phenology and body size of host damselfly species. A total of 7107 damselfly individuals were collected representing 16 species from 13 sites in southeastern Ontario and southwestern Quebec, Canada. Using comparative methods, differences in prevalence and intensity of parasitism could be predicted by a host species’ geographic range and phenology. Barcoding based on Cytochrome Oxidase I revealed 15 operational taxonomic units (OTUs) for mite species. The number of mite OTUs known to infest a given host species was explained by a host species’ regional occurrence. Our findings demonstrate the need to measure factors at several ecological scales in order to understand the breadth of evolutionary interactions with host–parasite associations and the selective ‘milieu’ for particular species of both hosts and parasites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".