Ethanol eDNA Reveals Unique Community Composition of Aquatic Macroinvertebrates Compared to Bulk Tissue Metabarcoding in a Biomonitoring Sampling Scheme
Why this work is in the frame
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Bibliographic record
Abstract
Freshwater ecosystems provide essential ecosystem services and support biodiversity; however, their water quality and biological communities are influenced by adjacent agricultural land use. Aquatic macroinvertebrates are commonly used as bioindicators of stream conditions in freshwater biomonitoring programs. Sorting benthic samples for molecular identification is a time-consuming process, and this study investigates the potential of ethanol-collected environmental DNA (eDNA) for metabarcoding macroinvertebrates, especially for common bioindicator groups. The objective of this study was to compare macroinvertebrate composition between paired bulk tissue and ethanol eDNA samples, as eDNA could provide a less time-consuming and non-destructive method of sampling macroinvertebrates. We collected benthic samples from streams in Ontario, Canada, and found that community composition varied greatly between sampling methods and that few taxa were shared between paired tissue and ethanol samples, suggesting that ethanol eDNA is not an acceptable substitute. It is unclear why we did not detect all the organisms that were preserved in the ethanol, or the origin of the DNA we did detect. Furthermore, we also detected no difference in community composition for bioindicator taxa due to surrounding land use or water chemistry, suggesting sites were similar in ecological condition.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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 it