Environmental <scp>DNA</scp> in lake sediment reveals biogeography of native genetic diversity
Bibliographic record
Abstract
Understanding the historical distributions of species is vital to the conservation and restoration of native species, yet such information is often qualitative. We show that the paleolimnological history of threatened freshwater fishes can be reconstructed using species‐diagnostic markers amplified from environmental DNA deposited in lake sediments (lake sed DNA ). This method was validated through the detection of lake sed DNA from non‐native trout (Yellowstone cutthroat trout, Oncorhynchus clarkii bouvieri ), which corroborated historical records of human‐mediated introductions. We also discovered native trout (westslope cutthroat trout, Oncorhynchus clarkii lewisi ) lake sed DNA that predated human‐mediated introductions of freshwater fishes in a watershed with high topographical relief. This unexpected result revealed that the westslope population was of native origin and requires immediate conservation protection. Our findings demonstrate that lake sed DNA can be used to determine the colonization history of freshwater fishes and the structure of ecosystems, aiding in the identification of native ranges, novel native diversity, and introductions of non‐native species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".