Testing the effectiveness of environmental <scp>DNA</scp> (<scp>eDNA</scp>) to quantify larval amphibian abundance
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
Abstract Environmental DNA (eDNA) monitoring is rapidly becoming an established approach for detecting the presence of aquatic organisms and may also be useful for indexing or estimating species abundance. However, the link between eDNA concentration and abundance of individuals (i.e., density or biomass) remains tenuous and may vary widely across species and environmental conditions. We investigated the relationship between eDNA concentration and abundance in two common and closely related amphibians in eastern North America, the wood frog ( Rana sylvatica ), and northern leopard frog ( R. pipiens ). We manipulated tadpole density in 80‐L mesocosms and documented the relationship between tadpole density and biomass and eDNA concentration through time. The two species differed in the amount of detectible genetic material produced, despite having comparable biomass. Concentration of eDNA increased with tadpole numbers and was primarily correlated with tadpole density in wood frogs and biomass in leopard frogs. eDNA degradation rates were rapid and comparable between species, with tadpoles becoming indetectable within 5 days post‐removal from the mesocosm, irrespective of tadpole density. Overall, our findings support that eDNA concentration has potential for tracking amphibian abundance in wetlands, but that indices of abundance are likely to be coarse and species‐specific calibration will be required. Future research should address how biotic and abiotic factors influence eDNA production, degradation, and recovery across species and through time before relying on eDNA for monitoring amphibian abundance in nature.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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