Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes
Why this work is in the frame
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Bibliographic record
Abstract
Accurately identifying the species present in an ecosystem is vital to lake managers and successful bioassessment programs. This is particularly important when monitoring cyanobacteria, as numerous taxa produce toxins and can have major negative impacts on aquatic ecosystems. Increasingly, DNA-based techniques such as metabarcoding are being used for measuring aquatic biodiversity, as they could accelerate processing time, decrease costs and reduce some of the biases associated with traditional light microscopy. Despite the continuing use of traditional microscopy and the growing use of DNA metabarcoding to identify cyanobacteria assemblages, methodological comparisons between the two approaches have rarely been reported from a wide suite of lake types. Here, we compare planktonic cyanobacteria assemblages generated by inverted light microscopy and DNA metabarcoding from a 379-lake dataset spanning a longitudinal and trophic gradient. We found moderate levels of congruence between methods at the broadest taxonomic levels (i.e., Order, RV=0.40, p < 0.0001). This comparison revealed distinct cyanobacteria communities from lakes of different trophic states, with Microcystis, Aphanizomenon and Dolichospermum dominating with both methods in eutrophic and hypereutrophic sites. This finding supports the use of either method when monitoring eutrophication in lake surface waters. The biggest difference between the two methods was the detection of picocyanobacteria, which are typically underestimated by light microscopy. This reveals that the communities generated by each method currently are complementary as opposed to identical and promotes a combined-method strategy when monitoring a range of trophic systems. For example, microscopy can provide measures of cyanobacteria biomass, which are critical data in managing lakes. Going forward, we believe that molecular genetic methods will be increasingly adopted as reference databases are routinely updated with more representative sequences and will improve as cyanobacteria taxonomy is resolved with the increase in available genetic information.
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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 | 0.002 |
| 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