Snail-trematode dynamics in central Alberta wetlands: A longitudinal survey of infections and interactions
Bibliographic record
Abstract
Abstract Previous research has shown that host diversity and heterogeneity promote parasite abundance and heterogeneity by creating additional niches for parasites to occupy. Central Alberta, Canada, sees a diverse array of native and migratory species each year. A previous snail–trematode survey conducted at six lakes in central Alberta from 2013-2015 uncovered 79 trematode species. However, analyses suggested that additional species remained to be uncovered. To build on this baseline, we conducted further snail–trematode collections from 2019 to 2022 at eight reclaimed wetland sites in various stages of reclamation, along with one established lake in Alberta. Across the nine sites, we collected 22,397 snails, of which 1,981 were infected with digenean trematodes. We also documented broader biodiversity at these sites using traditional survey techniques. Through DNA barcoding, we identified 74 trematode species infecting five snail species. Among these were 23 trematode species not previously reported in central Alberta and nine putative novel species. In addition, we observed several previously unreported snail–trematode interactions. While trematode richness did not vary significantly with the wetland reclamation stage, host identity did influence richness: Physa gyrina hosted significantly more trematode species than Planorbella trivolvis . When combined with data from the earlier survey, sample completeness analyses indicate that we captured 100% of the dominant species and 99% of the typical species, but only 63% of the overall species diversity in central Alberta. These findings underscore that trematode diversity in central Alberta remains underestimated and highlight the continued value of long-term and host-inclusive sampling efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".