Potential Impact of a Large-Scale Cascade Reservoir on the Spawning Conditions of Critical Species in the Yangtze River, China
Bibliographic record
Abstract
Dam building and reservoir operations alter the downstream hydrological regime, and as a result, affect the health of the river aquatic ecosystem, particularly for large-scale cascade reservoirs. This study investigated the impact of the Gezhouba Reservoir (GR) and the Three Gorges Reservoir (TGR) on the spawning conditions of two critical taxa, i.e., the endemic four major carps and the endangered Chinese sturgeon in the Yangtze River. We analyzed the flow, sediment, and thermal regime in these two taxa spawning seasons and compared their features between the predam and postdam periods. Our results revealed that the GR and the TGR had altered the frequency distributions of flow, sediment, and water temperature to different degrees, with the impact by the GR on the carps and Chinese sturgeon ranked as water temperature > flow, sediment > water temperature > flow, and the effect of the TGR on these two taxa were ordered as flow > water temperature, sediment > flow > water temperature. For the GR, the satisfying degree of the suitable flow and water temperature of the carps increased, whilst the suitable flow, sediment, and water temperature for the Chinese sturgeon decreased. These changes in TGR showed a significant ascending (descending) trend in the suitable flow (water temperature) for the carps, and a clear decreasing trend in the flow, sediment, and temperature for Chinese sturgeon. Both the TGR and the GR had negative impacts on the spawning of these two taxa in terms of the rising/falling flow characteristics.
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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 | 0.001 |
| 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".