Three Gorges Dam: Differential determinants and spatial-temporal effects of the change of snail density
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Résumé
Abstract BACKGROUND The abundance of Oncomelania hupensis snail can promote the transmission of schistosomiasis japonica. Snail distribution varies spatially and temporally in different geographical regions. Hence, we investigated differential drivers of snail density between the downstream and upstream areas of Three Gorges Dam (TGD), and spatial-temporal changes in snail abundance. METHODS We deployed the snail survey at 200 sites over 5 years to monitor a dynamic change in snail abundance within the Yangtze River basin. Corresponding variables that might affect snail abundance, such as Meteorology, vegetation, terrain, and economy, were collected from multiple data sources. We conducted the Bayesian spatial-temporal modeling framework to investigate the differential determinants and spatial-temporal effects of the change of snail density. RESULTS Obvious volatility for snail density was detected in the downstream area of TGD, whilst a small increment in the upstream area. For the downstream area of TGD, Snail density was positively associated with the average minimum temperature in January of the same year, annual normalized difference vegetation index of the previous year (NDVI), the 2nd quartile of average annual relative humidity of the previous year (RH), the 3rd quartile of RH, the 4th quartile of RH. Snail density was negatively associated with the average maximum temperature in July of the previous year, and annual night-time light of the previous year. An approximately inverted “U” curve of relative risk was detected among sites with a greater average annual ground surface temperature of the previous year. For the upstream area, snail density was positively associated with NDVI, the 2nd quartile of total precipitation of the previous year (Pre), the 3rd quartile of Pre, and the 4th quartile of Pre. Snail density was negatively associated with Slope. CONCLUSIONS Collectively, our study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation, and human activity were the main drivers affecting the snail abundance in the downstream area of TGD, while precipitation, slope, and vegetation were the main drivers affecting the upstream snail abundance. This evidence can assist the authorities to execute more precise strategies for snail investigation and control.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle