Downstream effects of the Three Gorges Dam on larval dispersal, spatial distribution, and growth of the four major Chinese carps call for reprioritizing conservation measures
Bibliographic record
Abstract
Larval drift and dispersal are critical processes that affect recruitment success for many riverine fishes. Hypolimnetic discharge from the Three Gorges Dam (TGD) lowers river temperature and reduces downstream nutrients, inducing distinct shifts in habitat conditions downstream of the dam. The inflow of major tributaries buffers these influences and creates physiochemical gradients according to the distance from the dam. We investigated the abundance, feeding, and growth of larvae of four major Chinese carps in three sections of the middle Yangtze River. Water temperature and transparency showed clear spatial gradients. Larvae in the river section closest to the dam tended to be lower in abundance and temporally delayed peak abundance and showed lower feeding intensity, poorer condition, and slower growth than those further from the dam. Our results demonstrate that physiochemical gradients influenced by the TGD have strong effects on abundance, feeding, and growth of the drifting larvae. We recommend that river sections farther from the TGD, particularly around the mouth of Poyang Lake, should become high-priority conservation areas to enhance protection of critical aquatic 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".