Fine‐scale environmental heterogeneity shapes fluvial fish communities as revealed by eDNA metabarcoding
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Conservation of freshwater biodiversity requires being able to track the presence and abundance of entire fish communities. However, studying fish community composition within rivers remains a technical challenge because of high spatial and temporal physico‐chemical variability, anthropic activities and connections with other river catchments, which may all contribute to important variations in local ecology and communities. Here, we used environmental DNA metabarcoding to document spatial variation in fish communities at a small geographic scale in a large river system. The study was conducted in the Contrecoeur sector (5.5 km long and approximately 1–1.5 km wide) of the St. Lawrence River (Québec, Canada), where two water masses with different physico‐chemical properties, known as "brown waters" and "green waters," flow in parallel with limited admixing. Water samples were collected during two consecutive days at 53 stations located in both water masses. Using universal PCR MiFish 12S primers, Illumina MiSeq sequencing, and the Barque ( www.github.com/enormandeau/barque ) eDNA analysis software developed by our group, a total of 67 fish species were detected. PERMANOVA and redundancy analyses (RDA) performed on relative read abundance revealed that each water mass comprised distinct communities that depended on turbidity, depth, and to a lesser extent on the upstream versus downstream position along the study area. eDNA metabarcoding results were compared with those of traditional surveys conducted previously in the sector and up to 40 km upstream of it. As previously reported, higher species diversity was detected by eDNA and with substantially lower sampling effort. Our results represent one of the few studies documenting the potential of eDNA metabarcoding to investigate small‐scale variation in 2D spatial patterns of distribution of whole fish communities associated with habitat characteristics within a lotic system.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.010 |
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