Congruence of Fish Community Diversity and Composition Estimates Using Water and Sediment (Benthic Surface and Trapped Suspended Solids) Based Environmental <scp>DNA</scp> in a Recently Restored Creek
Bibliographic record
Abstract
ABSTRACT Environmental DNA (eDNA) metabarcoding is increasingly paired with electrofishing efforts for aquatic biomonitoring and it has been shown that aquatic eDNA and electrofishing can be complementary when used together. Sedimentary eDNA is also used when monitoring rivers but is infrequently paired with electrofishing. Additionally, the utility of capturing eDNA from suspended solids as an alternative sampling medium in freshwater systems has not been explored. In this study, we used a common universal 12S metabarcoding assay for fishes on three different eDNA sampling media (water, benthic surface sediments, and trapped suspended solids) to determine which most similarly estimated fish community diversity with paired electrofishing efforts in a recently restored creek in Guelph, Ontario, Canada. A mock community comprised of DNA extracts from fish inhabiting the system was used as a positive control for species detection. Estimates of species richness were most comparable between electrofishing and trapped suspended solids though water samples estimated the greatest overall species richness. However, all three eDNA sampling media were found to generate estimates of community diversity that were more similar to each other than they were to estimates from electrofishing. Differences in community diversity were associated most strongly with collection method, weakly with sampling site, and were not associated with sampling period. Additionally, an indicator species analysis revealed that the taxa discriminating between the eDNA and electrofishing methods were all taxa that could not be amplified from the mock community. These findings suggest that the dissimilarity in diversity and indicator species observed between eDNA and electrofishing sampling methods is being primarily driven by methodological limitations relating to primer specificity and resolution.
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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 | 0.000 | 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 | 0.002 |
| 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 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".