The potential of aquatic haematophagous, liquidosomatophagous and macrophagous leeches as a tool for iDNA characterisation
Bibliographic record
Abstract
Abstract Leeches play important roles in food webs due to their abundance, diversity and feeding habits. Studies using invertebrate-derived DNA (iDNA) extracted from leech gut contents to target vertebrate DNA have focused on the Indo-Pacific region and mainly leveraged the leech family Haemadipsidae, composed of haematophagous terrestrial leeches, while the aquatic haematophagous, liquidosomatophagous and macrophagous counterparts have largely been disregarded. While there is general knowledge regarding the taxonomic groups that leeches prefer to feed on, detailed taxonomic resolution is still missing and therefore, their potential use for monitoring animals is not known. In this study, 116 non-haemadipsid leeches belonging to 12 species and spanning the three feeding habits were collected in Mexico and Canada. We used DNA metabarcoding to investigate their diet and assess their potential use for vertebrate monitoring. We detected vertebrate taxa from five orders including fish, turtles and birds in the diet of the aquatic haematophagous leeches; eight invertebrate orders of annelids, arthropods and molluscs in the liquidosomatophagous leeches; and ten orders of invertebrates belonging to Arthropoda and Annelida, as well as one vertebrate and one parasitic nematode, in the macrophagous leeches. These results show the potential use of iDNA from the gut content of aquatic haematophagous leeches for retrieving vertebrate taxa, and from macrophagous and liquidosomatophagous counterparts for invertebrates. Our study provides information about the dietary range of the freshwater leeches and the non-haemadipsid terrestrial leech and proof-of-concept for the use of non-haemadipsid leeches for animal monitoring, expanding our knowledge of the use of iDNA from leech gut contents to North America.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".