Distribution of American eels (Anguilla rostrata) and the influence of barriers in the Lake Champlain basin
Bibliographic record
Abstract
Freshwater eels ( Anguilla spp.) are experiencing significant population declines, particularly for species from temperate latitudes. These declines are attributed to overharvest, habitat degradation, and migration barriers such as dams. However, lack of information about eel distribution, habitat use, and ability to navigate in-stream barriers increases the challenge of managing eels. We investigated the distribution and abundance of eels in the Lake Champlain basin, where 2.7 million glass eels were stocked from 2005 to 2010, and focused on the influence of barriers pre- and post-stocking. Data were collated from a range of sources, from 1929 to 2024. Eels were recorded throughout Lake Champlain and its tributaries, including down to 90-m depth in the lake and distances up to 40 km upstream from the lake. Eels were rarely observed upstream of dams >10 m, and observations were reduced upstream of multiple dams, regardless of dam height. Stocked eels may be expanding the overall distribution of eels in the basin, with post-stocking observations from locations typically considered ‘impassable’. Inconsistency in data collection over space and time has left gaps in our understanding of eel distributions and creates uncertainty regarding accuracy of observed eel absences, issues which could be improved by future survey work. Our findings from the Lake Champlain basin can likely be extrapolated to the larger St Lawrence River basin, where stocking has also occurred, to identify research and management needs regarding the impacts of small dams in minor tributaries and large dams in major rivers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".