Assessing Distribution of Migratory Fishes and Connectivity following Complete and Partial Dam Removals in a North Carolina River
Bibliographic record
Abstract
Abstract Fish, especially migratory species, are assumed to benefit from dam removals that restore connectivity and access to upstream habitat, but few studies have evaluated this assumption. Therefore, we assessed the movement of migratory fishes in the springs of 2008 through 2010 and surveyed available habitat in the Little River, North Carolina, a tributary to the Neuse River, after three complete dam removals and one partial (notched) dam removal. We tagged migratory fishes with PIT tags at a resistance-board weir located at a dam removal site (river kilometer [rkm] 3.7) and followed their movements with an array of PIT antennas. The river-wide distribution of fish following removals varied by species. For example, 24–31% of anadromous American Shad Alosa sapidissima, 45–49% of resident Gizzard Shad Dorosoma cepedianum, and 4–11% of nonnative Flathead Catfish Pylodictis olivaris passed the dam removal site at rkm 56 in 2009 and 2010. No preremoval data were available for comparison, but reach connectivity appeared to increase as tagged individuals passed former dam sites and certain individuals moved extensively both upstream and downstream. However, 17–28% did not pass the partially removed dam at rkm 7.9, while 20–39% of those that passed remained downstream for more than a day before migrating upstream. Gizzard Shad required the deepest water to pass this notched structure, followed by American Shad then Flathead Catfish. Fish that passed the notched dam accessed more complex habitat (e.g., available substrate size-classes) in the middle and upper reaches. The results provide strong support for efforts to restore currently inaccessible habitat through complete removal of derelict dams. Received August 23, 2013; accepted June 18, 2014
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".