A mesocosm comparison of laboratory‐based and on‐site eDNA solutions for detection and quantification of striped bass (Morone saxatilis) in marine ecosystems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental effects monitoring in marine ecosystems are challenging, particularly in dynamic macrotidal settings like the Bay of Fundy. Environmental DNA provides a useful tool for determining species presence in such challenging places to access and sample. Moreover, recent studies showing a link between eDNA concentration and fish density/biomass reveal the great promise for eDNA tools to improve biodiversity assessments in marine environments. Three mesocosm experiments were conducted to assess the accuracy and precision of a hand-held point-of-need (PoN) tool for quantitative polymerase chain reaction (qPCR) assay for eDNA detection of striped bass (Morone saxatilis) versus conventional laboratory-based eDNA techniques. The first of these experiments determined that striped bass eDNA was reliably detected using either of the laboratory-based or PoN platforms, with some variation observed in the estimates of eDNA concentrations derived from each. Next, a time series experiment established that eDNA in water samples collected within a 24-hour period of exposure to striped bass was reliably and consistently detectable with either platform. Our final experiment found that the relationship between eDNA concentrations and manipulated striped bass stocking densities was significant and positive based on results from each of the laboratory-based or PoN platforms. Our results validate and advance eDNA approaches towards environmental monitoring efforts and demonstrate the potential for real-time eDNA tools to quantify and identify the spatial and temporal distribution of species-at-risk in an open ocean environment.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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