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54 results for “phytoplankton bloom”
Dataset: Environmental drivers of under-ice phytoplankton bloom dynamics in the Arctic Ocean
<p>This dataset is linked to this manuscript entitled "Environmental drivers of under-ice phytoplankton bloom dynamics in the Arctic Ocean" published in Elementa: Science of the Anthropocene (<a href="http://doi.org/10.1525/elementa.430">http://doi.org/10.1525/elementa.430</a>). Please find the abstract below:</p> <p>The decline of sea-ice thickness, area, and volume due to the transition from multi-year to first-year sea ice improves the under-ice light environment for pelagic Arctic ecosystems. One unexpected and direct consequence of this transition, the proliferation of under-ice phytoplankton blooms (UIBs), challenges the paradigm that waters beneath the ice pack harbor little planktonic life. Little is known about the diversity and spatial distribution of UIBs in the Arctic Ocean, or the environmental drivers behind their timing, magnitude, and species composition. Here, we compiled a unique and comprehensive dataset from seven major research projects in the Arctic Ocean (11 expeditions, covering the spring sea-ice-covered period to summer ice-free conditions) to identify the environmental drivers responsible for initiating and shaping the magnitude and assemblage structure of UIBs. The temporal dynamics behind UIB formation related to the ways that snow and sea-ice conditions impact the under-ice light field. In particular, the onset of snowmelt significantly increased under-ice light availability (> 0.1–0.2 mol photons m<sup>–2</sup> d<sup>–1</sup>), marking the concomitant termination of the sea-ice algal bloom and initiation of UIBs. At the pan-Arctic scale, bloom magnitude (expressed as maximum chlorophyll <em>a </em>concentration) was predicted best by winter water Si(OH)<sub>4</sub> and PO<sub>4</sub><sup>3–</sup> concentrations, as well as Si(OH)<sub>4</sub>:NO<sub>3</sub><sup>–</sup> and PO<sub>4</sub><sup>3–</sup>:NO<sub>3</sub><sup>–</sup><sub> </sub>drawdown ratios, but not NO<sub>3</sub><sup>–</sup> concentration. Two main phytoplankton assemblages dominated UIBs (diatoms or <em>Phaeocystis</em>), driven primarily by the winter nitrate:silicate (NO<sub>3</sub><sup>–</sup>:Si(OH)<sub>4</sub>) ratio and the under-ice light climate. <em>Phaeocystis</em> co-dominated in low Si(OH)<sub>4</sub> (i.e., NO<sub>3</sub>:Si(OH)<sub>4</sub> molar ratios > 1) waters, while diatoms contributed the bulk of UIB biomass when Si(OH)<sub>4</sub> was high (i.e., NO<sub>3</sub>:Si(OH)<sub>4</sub> molar ratios < 1). The implications of such differences in UIB composition could have important ramifications for Arctic biogeochemical cycles, and ultimately impact carbon flow to higher trophic levels and the deep ocean.</p>
Plumes and Blooms: phytoplankton pigment concentration
The data set provided here is a curated collection of phytoplankton pigment observations collected from the discrete seawater bottle samples by the Plumes and Blooms program (PnB). The curated data set was used to determine the dominant seasonal to multi-decadal patterns and forcings of phytoplankton groups in the Santa Barbara Channel, CA. The data included here encompass the PnB cruises since Nov 2005.
Plumes and Blooms: Curated oceanographic and phytoplankton pigment observations
These data come from the Plumes and Blooms project (PnB), which has conducted approximately monthly 1-day oceanographic cruises since August 1996. The data included here encompass all PnB cruises from August 1996 through December 2018. Data are two data tables: one table includes conductivity-temperature-depth profiles (CTD) and derived physical parameters, the other table includes discrete seawater samples for various biological and biogeochemical parameters. Details are available in Catlett et al., in prep. References: Catlett, D., D. A. Siegel, R. D. Simons, N. Guillocheau, F. Henderikx-Freitas, C. S. Thomas.2021. Diagnosing seasonal to multi-decadal phytoplankton group dynamics in a highly productive coastal ecosystem, Progress in Oceanography. 197. https://doi.org/10.1016/j.pocean.2021.102637.
Image-derived indicators of phytoplankton community responses to Pseudo-nitzschia blooms
<p>Data associated with the manuscript "Image-derived indicators of phytoplankton community responses to <em>Pseudo-nitzschia</em> blooms" submitted to the journal <em>Harmful Algae</em>. There is an additional R script that calculates an interaction metric as described in the paper. </p>
Figure 9. Dipole eddy evolution from August 7 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 9. Dipole eddy evolution from August 7 to August 9, 2018 in the suspended matter field from OLCI Sentinel-3A data for August 7 (a) and August 8, 2018 (b) and MSI Sentinel-2B data for August 9, 2008 (c) according Krayushkin et al. (2018).
Figure 5 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 5. Spatial variations of optical, physical, chemical, and biological parameters along the coast of the Sambia Peninsula and the Curonian Spit. The yellow background corresponds to warm waters in eddies, the blue background corresponds to cold waters, and the grey background corresponds to waters outside eddies.
Figure 4 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 4. Photosynthetic active radiation attenuation coefficient (Kd) and inverse Secchi depth (D, circles) vs. turbidity and inverse Secchi depth (squares) at stations with cyanobacteria blooms (green symbols), under the influenced of cold water stations (blue symbols) and under the influenced of warm water stations (black symbols), respectively. Turbidity is given in units according to the turbidity standard for Formazine (Formazin Turbidity Unit, ftu).
Figure 3 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 3. Sea surface temperature (a) and chlorophyll a concentration (b) on August 22 (11:30 UTC), and sea surface temperature (c) on August 23, 2018 (12:10 UTC), all from MODIS-Aqua satellite data; (d) fragment of optical satellite image (red, green, blue composite) derived from the Ocean and Land Color Instrument (OLCI) on Sentinel-3A satellite from August 23, 2018 (9:25 UTС); (e) temperature (˚C) and salinity (f) transects along the northern coast of the Sambia Peninsula and Curonian Spit on August 23, 2018.
Figure 7 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 7. Vertical distribution of chlorophyll a concentration along the coastal area of the Sambia Peninsula on August 22, 2018.
Figure 8 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 8. Fragments of optical satellite images derived from OLCI Sentinel-2 on May 3, 2019 (a) and August 28, 2022 (b).
Figure 2 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 2. Study area and locations of station in the southeastern Baltic Sea (а) Conditional symbols: Yellow circles correspond to the stations conducted on August 22, 2018. Red circles correspond to the stations conducted on August 23, 2018. White circle is Wastewater Treatment Plant (WTP) on the northern coast of Sambia Peninsula. Amber Mining Plant (AC) is indicated as an asterisk on the western coast.
Figure 1 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 1. Phytoplankton patches on the surface of the southern Baltic Sea. Fragment of a color-synthesized image of the Baltic Sea surface in the visible range from OLCI-Sentinel-3 satellite scanner data of June 27, 2018.
Figure 6 in Influence of circulation processes on cyanobacteria bloom and phytoplankton succession in the Baltic Sea coastal area
Figure 6. Phytoplankton biomass contribution in the upper 1 m layer (station 16 and 24 – integrated samples over euphotic depth).
Phytoplankton blooms in the Southern Ocean in high vs. low sea ice years
<p>Processing files and relevant datasets for Schlosser & Strutton (2025), 'Phytoplankton blooms in the Southern Ocean in high vs. low sea ice years', published in Elementa. Available here: <span>https://doi.org/10.1525/elementa.2024.00055</span></p>
Widespread changes in Southern Ocean phytoplankton blooms linked to climate drivers
<p>Bloom phenology metrics calculated from OC-CCI v6.0 data. Dataset forms part of a publication in Nature Climate Change.</p>
Non-Targeted Metabolomics of a Phytoplankton Bloom in the California Current Ecosystem 1706
<p>Non-Targeted LC-MS/MS based Metabolomics of SPE (PPL) extracts of a Phytoplankton Bloom in the California Current Ecosystem 1706</p>
Model output associated with Bucciarelli et al. "Western Indian subantarctic phytoplankton blooms fertilized by iron-enriched Agulhas water"
<p> Annual mean sea surface elevation (zeta), surface chlorophyll (chl), surface DFE (fe0), 500 m DFE (fe500), surface salinity (salt0) and 500 m salinity (salt500) from CROCO PISCES ocean model for two simulations (reference ASAP2 and NAM without Fe sources along African margins).This is associated with publication: Bucciarelli et al. "Iron-enriched Agulhas waters fertilise the Indian Subantarctic Zone"</p>
Model output dataset for Ardyna et al. (2022) Wildfire aerosol deposition likely amplified a summertime Arctic phytoplankton bloom
<p>Daily July and August 2014 aerosol optical depth (AODVIS) and nitrogen deposition (NDEP) output from simulations using Community Earth System Model. Data owner: Diana Bernstein (diana.bernstein@usm.edu).</p>
Data from: Nutrient sources, phytoplankton blooms, and hypoxia along the Chinese coast in the East China Sea: Insight from summer 2014
<p>This dataset contains data collected onboard the <em>R/V Ocean Researcher I</em> during the summer of 2014 (August 20–31) East China Sea described in the paper: "C.-C. Chen, W.-C. Chou, and C.-C. Hung (2024). Nutrient sources, phytoplankton blooms, and hypoxia along the Chinese coast in the East China Sea: Insight from summer 2014, Marine Pollution Bulletin (accepted on July 4 2024)".</p>
Coastal phytoplankton blooms expand and intensify in the 21st century:data and code
<p>This repository contains the relevant dataset and code for the paper <strong>Coastal phytoplankton blooms expand and intensify in the 21st century.</strong></p> <p>We generated a satellite-based dataset of phytoplankton bloom occurrence to characterize the spatial and temporal patterns of algal blooms in coastal oceans globally. The dataset was derived using global, 1-km resolution daily observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Aqua satellite, and all 0.76 million images acquired by this satellite mission between 2003 and 2020 were used. </p> <p>Please refer to the README file in code_examples.rar file for more detailed information.</p>
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International Brain Laboratory public data
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OpenNeuro
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