A review of an electric weir and fishway in a Great Lakes tributary from conception to termination
Bibliographic record
Abstract
A successful management plan requires clear goals and a process for evaluation. Without them, managers risk operational shifts in which continuous changes disguised as improvements may have little beneficial effect. The conception, design, and operation of an electric barrier and fishway on the Pere Marquette River of Lake Michigan serve as an illustration. The Great Lakes Fishery Commission operated an electric weir to stop migration of adult sea lampreys (Petromyzon marinus) and a fishway to provide upstream passage of rainbow trout (Oncorhynchus mykiss) during 2000–2009. The weir and fishway were successful in blocking some of the annual spawning run of sea lampreys (trapped an annual average of 439 sea lampreys) and it allowed passage of rainbow trout (an annual average of 6,091). Even with success that yielded an estimated density of 0.03 adult female sea lampreys per 100 m2 of larval habitat upstream of the weir, lampricide treatments continued because the weir still allowed establishment of substantial densities of larval sea lampreys. Our evaluation suggests that an in-stream barrier must approach 100% blockage of sea lampreys to eliminate large recruitment events. The failure of the weir to reduce lampricide treatments was due to an informally defined purpose and measures for success at the onset, the complexity of electric weir systems (and the operational problems created by such intricacy), and lack of recognition of the reduction in larval sea lamprey recruitment needed to succeed. Control of sea lampreys in the Pere Marquette River could have benefited from an adaptive management approach.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".