High‐volume plankton tow net sampling improves <scp>eDNA</scp> detection of invasive zebra mussels (<i>Dreissena polymorpha</i>) in recently infested lakes
Bibliographic record
Abstract
Abstract Aquatic invasive species are a serious and growing threat to biodiversity. Zebra and quagga mussels ( Dreissena polymorpha and D. rostriformis bugensis ) are freshwater invaders causing substantial ecological and economic damage across Europe and North America. Early detection of invasive mussels and other non‐indigenous species is increasingly needed to prevent their establishment and spread. Environmental DNA (eDNA) techniques potentially offer higher sensitivity monitoring tools to complement more conventional methods for surveying adult and juvenile mussels and veliger larvae. eDNA assays are typically performed on small‐volume (0.5–5 L) water samples that are concentrated by filtration prior to extraction and downstream processing. Sampling using a towed plankton net of a larger (64 μm) pore size can process orders of magnitude larger water volumes with the potential for increasing eDNA detection sensitivity. We compared the sensitivities of high‐volume plankton tow net water sampling to filter sampling in three recently infested lakes in Canada and Minnesota, USA. Paired filtration and tow net samples were analyzed for Dreissena DNA using an established quantitative polymerase chain reaction assay for the genus. Higher yields of Dreissena eDNA (more DNA copies) were recovered from plankton tow than from filtered samples in all 33 paired comparisons. In some cases, plankton tow samples were positive for Dreissena eDNA while lower‐volume filtering produced a false negative detection. Our results demonstrate the effectiveness of plankton tow net sampling for eDNA early detection of invasive mussels, a method that can be used exclusively or as a supplement to filter sampling. Our results further suggest that eDNA testing could be incorporated into monitoring programs that routinely use plankton tows for visual detection of invasive mollusk larvae, as well as other aquatic invasive and non‐invasive species ranging from plankton to metazoans, including many fish.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".