{"id":8645,"date":"2023-07-21T11:01:09","date_gmt":"2023-07-21T11:01:09","guid":{"rendered":"https:\/\/komorebi.ai\/?page_id=8645"},"modified":"2024-01-04T09:44:04","modified_gmt":"2024-01-04T09:44:04","slug":"how-do-tuna-schools-associate-to-dfads","status":"publish","type":"page","link":"https:\/\/komorebi.ai\/en\/how-do-tuna-schools-associate-to-dfads\/","title":{"rendered":"How do tuna schools associate to dFADs?"},"content":{"rendered":"
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How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patterns<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Marine Ecology Progress Series, 2023<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This study uses Machine Learning to analyze data from echo-sounder buoys attached to Fish Aggregating Devices (dFADs) in tropical oceans, aiming to understand the behavioral patterns of tuna schools.<\/strong> \n

\nMetrics show that it takes between 25 and 43 days for tuna to first colonize dFADs, with longer times observed in the Pacific Ocean. Novel metrics, 'aggregation time' and 'disaggregation time', further revealed that the time taken for the tuna aggregation to depart from the dFADs is not significantly longer than the time taken to form. \n

\nThe study also discusses the implications of the results in the context of the 'ecological trap' hypothesis and proposes further analyses to utilize this data.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine Learning to analyze tuna behavior around Fish Aggregating Devices, providing insights to enhance sustainable fishing, marine biology research and conservation policies.<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Where does it apply?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The study on tuna behavior utilizing machine learning is applicable in commercial fishing<\/strong> for developing sustainable practices. \n

\nIt can assist marine biology research<\/strong> in understanding species dynamics. The findings can contribute to conservation efforts and policies<\/strong> pertaining to the use of Fish Aggregating Devices. \n

\nAdditionally, the success of this approach can also expand the use of AI and machine learning in computational biology and other biological data analysis areas.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Why does it matter?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This study matters as it provides crucial insights into the behavior of tuna schools in relation to Fish Aggregating Devices (dFADs), which are important resources in commercial fishing. \n

\nUnderstanding the aggregation and disaggregation times, as well as the colonization patterns of tuna can lead to more effective and sustainable fishing practices,<\/strong> potentially reducing overfishing and its negative ecological impacts. \n

\nFurthermore, the application of machine learning in this context showcases the potential of AI in enhancing marine biology studies and natural resource management.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patterns<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Marine Ecology Progress Series, 2023<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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V\u00edctor Gallego<\/a>, Alberto Torres<\/a>, David Gordo<\/a>, Manuel Navarro<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Other publications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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TUN-AI: Tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Assessing the effect of advertising expenditures upon sales. A Bayesian structural time series model<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Personalizing Text-to-Image Generation via Aesthetic Gradients<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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A Machine Learning method, TUN-AI, for accurate tuna biomass estimation, benefiting the fishing industry, fishery management organizations, and conservation efforts.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Accurate sales predictions based on advertising spend benefiting various industries in strategic advertising expenditure, budget allocation, and marketing campaign planning.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The study introduces Aesthetic Gradients for personalizing diffusion models, advancing user-interactive technology and impacting fields like digital art, design, and marketing.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tPredictive Analytics, Fisheries<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tAdvertising, Sales Forecasting<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

\u00bfC\u00f3mo se asocian los bancos de atunes con los dFADs? Marine Ecology Progress Series, 2023 Resumen Este estudio utiliza el aprendizaje autom\u00e1tico para analizar datos de boyas ecosonda fijadas a Dispositivos de Agregaci\u00f3n de Peces (dFAD) en oc\u00e9anos tropicales, con el objetivo de comprender los patrones de comportamiento de los bancos de atunes. Las m\u00e9tricas […]<\/p>","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"yoast_head":"\nHow do tuna schools associate to dFADs? - Komorebi AI<\/title>\n<meta name=\"description\" content=\"TUN-AI, a Machine Learning method, accurately estimates tuna biomass benefiting fishing industry, management organizations, and conservation.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/komorebi.ai\/en\/how-do-tuna-schools-associate-to-dfads\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How do tuna schools associate to dFADs? - Komorebi AI\" \/>\n<meta property=\"og:description\" content=\"TUN-AI, a Machine Learning method, accurately estimates tuna biomass benefiting fishing industry, management organizations, and conservation.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/komorebi.ai\/en\/how-do-tuna-schools-associate-to-dfads\/\" \/>\n<meta property=\"og:site_name\" content=\"Komorebi AI\" \/>\n<meta property=\"article:modified_time\" content=\"2024-01-04T09:44:04+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/komorebi.ai\/wp-content\/uploads\/2023\/07\/fishes-2-scaled.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/komorebi.ai\/es\/how-do-tuna-schools-associate-to-dfads\/\",\"url\":\"https:\/\/komorebi.ai\/es\/how-do-tuna-schools-associate-to-dfads\/\",\"name\":\"How do tuna schools associate to dFADs? 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