The relationships between the thermocline and the catch rate of Thunnus albacares and Thunnus obesus in the high seas of the Indian Ocean
Notice bibliographique
Résumé
It can improve our understanding of their behavior characteristics to analyze and identify the relationships between the thermocline and the vertical distribution of yellowfin tuna and bigeye tuna.It also provides critical information for fisheries to enhance the catch rate of the targeting species,fisheries management and resource conservation.Yellowfin tuna and bigeye tuna seem to exhibit nearly opposite approaches to their shared environment.Yellowfin tuna spend their days making excursions from around the top of the thermocline,both up and downward.Their nights are spent near the surface,diving down into the emergent scattering layer to feed.Bigeye tuna swims upward from the cooler depths to stay with their food resources.The depth which bigeye tuna inhabited is usually greater than that of yellowfin tuna.The difference in temperature between the surface layer and waters below the thermocline may be limiting the vertical movements of the tropical tuna.The thermocline is a water column at which the rate of decrease of temperature with increase of depth is much greater compared with those of above and below.The thermocline limits the vertical distribution of yellowfin tuna and bigeye tuna,so their catch rates are affected by the thermocline.A survey on tuna fishing ground has been carried out aboard of the longliners,Huayuanyu No.18 and No.19 in the high seas of the Indian Ocean from September 15th to Dec.12th,2005.The actual measured environmental data of the fishing area were obtained using Submersible Data Logger XR-620,TDR(2050)(RBR Co., Canada) and SBE37SM(CTD,SeaBird Co.,USA),the depth and intensity of the thermocline could be estimated by these data,and combined with the catch data recorded everyday,the catch rates of yellowfin tuna and bigeye tuna in two different depth layers(the thermocline and the deep water layer) were calculated respectively.The relationships between the thermocline and catch rate of yellowfin tuna and bigeye tuna were analyzed.The results showed that:(1) for 60.9% and 60.0% of all the surveying days of Huayuanyu No.18 and No.19 respectively,the catch rate of yellowfin tuna was higher in the thermocline.The average catch rates of Huayuanyu No.18 in and below the thermocline were 18.22 inds per 1000 hooks and 6.04 inds per 1000 hooks respectively,and that of Huayuanyu No.19 were 2.22 inds per 1000 hooks and 1.31 inds per 1000 hooks respectively.The catch rate of yellowfin tuna was higher in the thermocline,by t-Test paired two sample for means, the overall average catch rate of yellowfin tuna in and below the thermocline showed significant difference(P=0.020.05).(2) for 69.6% and 100% of all the surveying days of Huayuanyu No.18 and No.19 respectively,the catch rate of bigeye tuna was higher below the thermocline,the average catch rates of Huayuanyu No.18 in and below the thermocline were 4.18 inds per 1000 hooks and 4.88 inds per 1000 hooks respectively,and those of Huayuanyu No.19 were 0.10 inds per 1000 hooks and 2.57 inds per 1000 hooks respectively.By t-Test paired two sample for means,the catch rates of bigeye tuna was higher below the thermocline,the overall average catch rates of bigeye tuna in and below the thermocline showed no significant difference(P=0.070.05),but for Huayuanyu No.19,the average catch rates of bigeye tuna in and below the thermocline showed significant difference(P=0.000.05).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».