說明
資料紀錄
此資源sampling event的資料已發佈為達爾文核心集檔案(DwC-A),其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 17,731 筆紀錄。
亦存在 2 筆延伸集的資料表。延伸集中的紀錄補充核心集中紀錄的額外資訊。 每個延伸集資料表中資料筆數顯示如下。
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版本
以下的表格只顯示可公開存取資源的已發布版本。
如何引用
研究者應依照以下指示引用此資源。:
Swedish Meteorological and Hydrological Institute (2024). SHARK - Phyto- and Microzooplankton Data Collected by Imaging FlowCytobots (IFCB) in Swedish and Adjacent Waters
權利
研究者應尊重以下權利聲明。:
此資料的發布者及權利單位為 The Swedish Meteorological and Hydrological Institute。 To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.
GBIF 註冊
此資源已向GBIF註冊,並指定以下之GBIF UUID: a28ecb21-884c-4cc1-8e95-f0ec703609bd。 The Swedish Meteorological and Hydrological Institute 發佈此資源,並經由GBIF Sweden同意向GBIF註冊成為資料發佈者。
關鍵字
Samplingevent; Plankton
聯絡資訊
- 元數據提供者 ●
- 出處 ●
- 連絡人
- Data manager
地理涵蓋範圍
N/A
界定座標範圍 | 緯度南界 經度西界 [54.833, 5.804], 緯度北界 經度東界 [65.166, 23.821] |
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分類群涵蓋範圍
無相關描述
Kingdom | Chromista, Plantae, Protozoa, Bacteria |
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Phylum | Cyanobacteria, Myzozoa, Chlorophyta, Cercozoa, Cryptophyta, Euglenozoa, Bacillariophyta, Ochrophyta, Ciliophora |
Class | Dinophyceae, Chrysophyceae, Raphidophyceae, Cryptophyceae, Pyramimonadophyceae, Trebouxiophyceae, Oligotrichea, Dictyochophyceae, Euglenophyceae, Cyanophyceae, Chlorophyceae, Litostomatea, Thecofilosea, Ulvophyceae, Bacillariophyceae |
Order | Gonyaulacales, Ulotrichales, Thalassionematales, Gymnodiniales, Lithodesmiales, Eutreptiales, Coscinodiscales, Fragilariales, Dictyochales, Chaetocerotanae incertae sedis, Thalassiosirales, Cyclotrichiida, Pennales, Thoracosphaerales, Ebriales, Triceratiales, Choreotrichida, Oligotrichida, Chattonellales, Centrales, Dinophysales, Prorocentrales, Chromulinales, Rhizosoleniales, Chlorellales, Bacillariales, Chroococcales, Paraliales, Pyramimonadales, Tovelliales, Leptocylindrales, Pedinellales, Peridiniales, Hemiaulales, Amphidiniales, Cryptomonadales, Nostocales, Sphaeropleales, Licmophorales |
Family | Paraliaceae, Gymnodiniaceae, Fragilariaceae, Microcystaceae, Stephanodiscaceae, Tontoniidae, Dictyochaceae, Aphanizomenonaceae, Eutreptiaceae, Thalassiosiraceae, Thalassionemataceae, Dinophysaceae, Coscinodiscaceae, Triceratiaceae, Chattonellaceae, Actinomonadaceae, Metacylididae, Cladopyxidaceae, Protoperidiniaceae, Strombidiidae, Dinobryaceae, Chaetocerotaceae, Skeletonemaceae, Thoracosphaeraceae, Lithodesmiaceae, Leptocylindraceae, Pyramimonadaceae, Pyrocystaceae, Selenastraceae, Binucleariaceae, Ebriaceae, Polykrikaceae, Oxytoxaceae, Nodulariaceae, Oocystaceae, Lingulodiniaceae, Ceratiaceae, Prorocentraceae, Rhizosoleniaceae, Peridiniaceae, Licmophoraceae, Mesodiniidae, Gyrodiniaceae, Gonyaulacaceae, Hemiaulaceae, Kareniaceae, Warnowiaceae, Tovelliaceae, Scenedesmaceae, Heterocapsaceae, Amphidiniaceae, Bacillariaceae |
時間涵蓋範圍
起始日期 / 結束日期 | 2016-08-10 / 2024-12-15 |
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取樣方法
Sampling is performed either using shipboard flow through systems (i.e. FerryBox) where the Imaging FlowCytobot (IFCB) is connected as an addon, or at specific locations with the IFCB is submerged in-situ. Other deployment methods are possible. The IFCB uses flow cytometry technology and high-resolution images to detects particles in a water sample. Shapes in images are identified to best possible taxonomical levels using AI-assisted image analysis software. Volumes are estimated from the organism’s two-dimensional boundary.
研究範圍 | Data are collected within the following marine ecoregions: http://marineregions.org/mrgid/2401, http://marineregions.org/mrgid/2374, http://marineregions.org/mrgid/2379, http://marineregions.org/mrgid/2350 |
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方法步驟描述:
- The analysis follows the methods provided - Machine learning: Sosik, H. M. and Olson, R. J. (2007), Automated taxonomic classification of phytoplankton sampled with imaging-in-flow cytometry. Limnol. Oceanogr: Methods 5, 204–216. http://github.com/hsosik/ifcb-analysis - Quality control: Hayashi, K., Walton, J., Lie, A., Smith, J. and Kudela M. Using particle size distribution (PSD) to automate imaging flow cytobot (IFCB) data quality in coastal California, USA. In prep. http://github.com/kudelalab/PSD - Data processing: Anders Torstensson (2024). I 'R' FlowCytobot (iRfcb): Tools for Analyzing and Processing Data from the IFCB. R package version 0.3.10. https://doi.org/10.5281/zenodo.12533225. http://github.com/EuropeanIFCBGroup/iRfcb