Integration of water replenishment and pollutant reduction to achieve ecological restoration goals based on sustainability of the lacustrine wetlands
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Successful wetland restoration is frequently constrained by the absence of persistent attention to the whole remedial process. The paper put forward a holistic method to restore the lacustrine wetland ecosystem. Yilong Lake wetland, one of the nine largest lakes of the Yun-Gui Plateau in China, was used as a case study. A modified (Pressure-State-Response) PSR model was presented to establish a comprehensive indicator system and to explain the ecological sustainability. Ecosystem sustainability and water quality were set as the general restoration target and the constraint restoration target, respectively, that makes the restoration goals not only contains the whole ecosystem but also the key individual parts. Two restoration goals (high and low) were set based on the cluster analysis of the historical data from 1952 to 2006. Different restoration levels give the decision makers and managers flexible options to restore the ecosystem based on the actual demand and practical capacity. Three restoration scenarios about the water replenishment and pollutant reduction were set to improve the ecological condition. The results showed that the integrated restoration measures according to water quantity and water quality can feasibly achieve the prescribed restoration levels. The paper gives the decision makers a holistic method to solve problems in lacustrine wetland restoration process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it