Decoding the impact of environmental shifts on snail density dynamics in the Yangtze River basin: a 26-year study
Bibliographic record
Abstract
BACKGROUND: With the intensification of climate change and human engineering activities, environmental changes have affected schistosome-transmitting snails. This study explored the influence of environmental changes on the evolution of snail populations. METHODS: Data from annual snail surveys and related factors such as hydrology, temperature, vegetation, etc., on nine bottomlands from 1997 to 2022 were collected retrospectively from multiple sources. Interpretable machine learning and the Bayesian spatial-temporal model assessed the relationship between environmental change and snail density. RESULTS: ). Since operation of the Three Gorges Dam (TGD) began in 2003, the duration of bottomland flooding decreased from 122 days (1997-2003) to 57 days (2003-2012) and then rebounded in 2012-2022, which was noticeable in the Anhui Section. The ground surface temperature and night light index of the bottomlands increased from 1997 to 2022. After adjusting for confounding factors (e.g. rainfall, temperature, and vegetation), the relative risk (RR) of increased snail density rose with flooding duration of between 20 and 100 days but decreased with flooding duration of > 100 days. Snail density showed an "L"-shaped relationship with the night light index, and the RR of increased snail density was lower at a higher night light index. Compared with bottomlands in the first quartile cluster of ground surface temperature, bottomlands in the second, third, and fourth quartile clusters of ground surface temperature had higher snail density RR values of 1.271 (95% CI 1.082-1.493), 1.302 (95% CI 1.146-1.480), and 1.278 (1.048, 1.559), respectively. CONCLUSIONS: The TGD lowered the water level and flooding duration, which were not conducive to snail population growth. However, over time, the inhibitory effect of the TGD on snails may have been weakening, especially in areas far from the TGD. In recent years, the rebound of snail density may have been related to the rise in water levels and the change in the microenvironment. Establishing an efficient monitoring and response system is crucial for precisely controlling snails.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".