John E. San Soucie, Yogesh Girdhar, Leah Johnson, Emily E. Peacock, Alexi Shalapyonok, Heidi M. Sosik
{"title":"时空主题建模揭示风暴驱动的平流和搅拌控制着开阔洋涡流中浮游生物群落的变化","authors":"John E. San Soucie, Yogesh Girdhar, Leah Johnson, Emily E. Peacock, Alexi Shalapyonok, Heidi M. Sosik","doi":"10.1029/2024JC020907","DOIUrl":null,"url":null,"abstract":"<p>Phytoplankton communities in the open ocean are high-dimensional, sparse, and spatiotemporally heterogeneous. The advent of automated imaging systems has enabled high-resolution observation of these communities, but the amounts of data and their statistical properties make analysis with traditional approaches challenging. Spatiotemporal topic models offer an unsupervised and interpretable approach to dimensionality reduction of sparse, high-dimensional categorical data. Here we use topic modeling to analyze neural-network-classified phytoplankton imagery taken in and around a retentive eddy during the 2021 North Atlantic EXport Processes in the Ocean from Remote Sensing (EXPORTS) field campaign. We investigate the role physical-biological interactions play in altering plankton community composition within the eddy. Analysis of a water mass mixing framework suggests that storm-driven surface advection and stirring were major drivers of the progression of the eddy plankton community away from a diatom bloom over the course of the cruise.</p>","PeriodicalId":54340,"journal":{"name":"Journal of Geophysical Research-Oceans","volume":"129 11","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JC020907","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal Topic Modeling Reveals Storm-Driven Advection and Stirring Control Plankton Community Variability in an Open Ocean Eddy\",\"authors\":\"John E. San Soucie, Yogesh Girdhar, Leah Johnson, Emily E. Peacock, Alexi Shalapyonok, Heidi M. Sosik\",\"doi\":\"10.1029/2024JC020907\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Phytoplankton communities in the open ocean are high-dimensional, sparse, and spatiotemporally heterogeneous. The advent of automated imaging systems has enabled high-resolution observation of these communities, but the amounts of data and their statistical properties make analysis with traditional approaches challenging. Spatiotemporal topic models offer an unsupervised and interpretable approach to dimensionality reduction of sparse, high-dimensional categorical data. Here we use topic modeling to analyze neural-network-classified phytoplankton imagery taken in and around a retentive eddy during the 2021 North Atlantic EXport Processes in the Ocean from Remote Sensing (EXPORTS) field campaign. We investigate the role physical-biological interactions play in altering plankton community composition within the eddy. Analysis of a water mass mixing framework suggests that storm-driven surface advection and stirring were major drivers of the progression of the eddy plankton community away from a diatom bloom over the course of the cruise.</p>\",\"PeriodicalId\":54340,\"journal\":{\"name\":\"Journal of Geophysical Research-Oceans\",\"volume\":\"129 11\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JC020907\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geophysical Research-Oceans\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2024JC020907\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OCEANOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research-Oceans","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024JC020907","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
Spatiotemporal Topic Modeling Reveals Storm-Driven Advection and Stirring Control Plankton Community Variability in an Open Ocean Eddy
Phytoplankton communities in the open ocean are high-dimensional, sparse, and spatiotemporally heterogeneous. The advent of automated imaging systems has enabled high-resolution observation of these communities, but the amounts of data and their statistical properties make analysis with traditional approaches challenging. Spatiotemporal topic models offer an unsupervised and interpretable approach to dimensionality reduction of sparse, high-dimensional categorical data. Here we use topic modeling to analyze neural-network-classified phytoplankton imagery taken in and around a retentive eddy during the 2021 North Atlantic EXport Processes in the Ocean from Remote Sensing (EXPORTS) field campaign. We investigate the role physical-biological interactions play in altering plankton community composition within the eddy. Analysis of a water mass mixing framework suggests that storm-driven surface advection and stirring were major drivers of the progression of the eddy plankton community away from a diatom bloom over the course of the cruise.