Fish community shifts along a strong fluvial environmental gradient revealed by eDNA metabarcoding
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Large rivers and their estuaries are structurally complex and comprise a diversity of habitats supporting a rich biodiversity. As a result, identifying and monitoring fish communities using traditional methods in such systems may often be logistically challenging. Using the mitochondrial DNA 12S MiFish primers, we performed an eDNA metabarcoding analysis to assess the effect of spatial and environmental factors on the variation of the fish community structure along most of the St. Lawrence River/Estuary/Gulf (Québec Canada), a transect spanning 1300 km across a diversity of habitats from a fluviatile non‐tidal section to a marine environment. A total of 129 species were identified including freshwater and marine species. For the freshwater sectors, eDNA identified 80 species compared with the 85 species previously reported based on conventional sampling. eDNA also revealed similar species diversity and communities in the fluviatile section of the St. Lawrence River. Furthermore, our study improved current knowledge about the brackish and marine sections by describing community transition between freshwater and marine fish communities in association with a drastic shift in environmental conditions observed between the end of the fluvial estuary and the beginning of the middle (brackish) estuary. Altogether, this study exemplifies how eDNA metabarcoding is a powerful tool to document fish community shifts in large temperate lotic ecosystems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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