Effects of Temperature upon Water Turnover in Fish Ponds in Northern Thailand
Notice bibliographique
Résumé
Fish culture in earthen ponds is an important source of income for farmers in northern Thailand. Water quality in ponds has strong impacts on fish production farmers’ return and is sensitive to weather and climate. Low levels of dissolved oxygen in fish ponds are major cause of mass mortality. Stratification with depth in ponds followed by rapid turnover or exchange of surface and bottom water can expose fish to dangerously low dissolved oxygen levels. The main purpose of this study was to observe the effects of weather on stratification and subsequent water turnover in fish ponds in northern Thailand, especially in the winter and rainy season, when stratification was expected to be most severe. Temperature and water quality measurements were made in fish ponds at 18 farms with depths ranged from 0.8-2.0 m and size of 0.16-0.64 ha. Measurements were made during January and May 2013. Fish farm pond sites were divided into two groups based on elevation above sea level: low (400 masl) and categorized into 3 types of farming: commercial, integrated and subsistence. In lower elevation sites, water turnover occurred at night between 22.00 and 02.00 in winter and between 18.00 and 02.00 in rainy season. At higher elevation, turnover occurred in ponds between 20.00 and 22.00 in winter and between 14.00 and 18.00 in rainy season. Turnover was slower in the lower elevation than in higher elevation zones and generally occurred earlier during the rainy season than in the winter. Mean DO in winter was significantly higher (p<0.05) than in rainy season, whilst water temperature and amount of ammonia-nitrogen during the rainy season was significantly higher (p<0.05) than in winter. Turnover improves distribution of dissolved oxygen through the water column and minimizes organic matter accumulation. Cloud cover during the rainy season may have contributed to limit oxygen production and thus may have significantly affect water quality in ponds. Fish farmers should consider more explicitly the role of temperature and cloud conditions when managing dissolved oxygen levels in their fish ponds. Therefore, efficient pond aeration or pond mixing strategies for reducing stratification still plays an important component for providing sound pond management in tilapia production ponds.
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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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».