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447 results for “Phytoplankton”
San Francisco Estuary Institute Phytoplankton eDNA and Toxin Monitoring, San Francisco Bay, CA, 2014-2023
From late 2014-present, San Francisco Estuary Institute has conducted molecular monitoring of phytoplankton in partnership with the US Geological Survey from several stations stretching from Rio Vista in the North Delta to the Lower South Bay, past the Dumbarton Bridge. These samples have been analyzed for 18S eDNA data in partnership with Timothy Otten at Bend Genetics, targeting the V7 region. The included dataset covers the 2014-2023 period, including data up to 2022, conducted with an Illumina MISEQ platform, and from 2022-2023 using a NEXTSEQ platform, which enabled much greater sampling depth. Two sets of taxonomic assignments are included in this data release, one using the Silva database, and the other using the PR2 database, two of the leading sources of phytoplankton taxonomic data aiding in assignments of OTUs to taxa. Raw sequence data will also be uploaded to NCBI for comparison. Data collection continues and this release will be updated as new time periods are added.
Interagency Ecological Program: Integrated Dataset of Phytoplankton Enumeration Data in the San Francisco Estuary, 1992-2024
Phytoplankton community composition is an important driver of zooplankton productivity and food supply for higher trophic levels in the San Francisco Estuary. Various monitoring surveys throughout the region collect phytoplankton enumeration data dating back to the 1990s. These include surveys from the CA Department of Water Resources (CADWR), CA Department of Fish and Wildlife (CDFW), the US Bureau of Reclamation (USBR), and the US Geological Survey (USGS). These surveys collect data via various sampling and laboratory methods which are not always directly comparable. This integrated dataset includes both enumeration counts and well-documented metadata to allow for informed decision-making in the integration of these data. It also standardizes taxonomic names between groups via a key list. Note that, in this dataset, we make conservative decisions about taxonomic resolution to ensure maximum compatibility between groups. For more detailed metadata and higher taxonomic resolution, refer to individual surveys’ publications or reach out to their primary contact.
Cascade Project at North Temperate Lakes LTER Core Data Phytoplankton 1984 - 2015
Data on epilimnetic phytoplankton from 1984-2015, determined by light microscopy from pooled Van Dorn samples at 100 percent, 50 percent, and 25 percent of surface irradiance. St. Amand (1990) and Cottingham (1996) describe the counting protocols in detail. Samples after 1995 were counted by Phycotech Inc. (http://www.phycotech.com). Sampling Frequency: varies; Number of sites: 5
St. Louis River Estuary Phytoplankton and Water Quality, 2022 - 2024
This data package supports the project Building a Collaborative Water Quality Monitoring Strategy for a Changing St. Louis River Estuary, funded by the National Estuarine Research Reserve System Science Collaborative. Led by the Lake Superior National Estuarine Research Reserve (LSNERR) and University of Minnesota’s Natural Resources Research Institute (NRRI) datasets include 2023–2024 water quality, phytoplankton, and winter dissolved oxygen observations from eight estuary “hotspot” locations. Sampling captured seasonal variability and cyanobacteria bloom events. All samples were collected using standardized field and laboratory protocols. Project details and associated products are available at: https://nerrssciencecollaborative.org/project/Ramage22. This dataset can be used to evaluate spatial and temporal patterns in water quality and phytoplankton dynamics, assess predictors of cyanobacterial blooms, and monitor winter under-ice hypoxia in the St. Louis River Estuary. It is well-suited for research on nutrient-bloom relationships, seasonal ecological shifts, and long-term monitoring strategy development.
Size-Fractionated Chlorophyll a, Primary Productivity, and Photosynthetic Physiological Parameters of Phytoplankton in the Cosmonaut Sea, Southern Ocean, During Summer 2022
This dataset provides vertical distribution profiles of size-fractionated phytoplankton parameters measured in the Cosmonaut Sea, a marginal ice zone in the Southern Ocean, during the austral summer of 2022. Sampling was conducted across multiple stations spanning latitudes from approximately 33°N to 60°N and longitudes from -62°E to -67°E, focusing on surface and subsurface waters up to depths of about 40 meters. The data capture key aspects of phytoplankton physiology and productivity in this dynamic polar environment, influenced by seasonal ice melt and nutrient availability. Parameters include chlorophyll a concentrations (Chl a), primary productivity indicators such as maximum photosynthetic rates (PBm), photosynthetic efficiency (α), saturation irradiance (Ek), and integrated gross primary productivity (IGPPeu), all differentiated by size fractions: net phytoplankton (>20 μm), nano- and pico-phytoplankton (<20 μm), and total community. Additional measurements encompass photosynthetically active radiation (PAR) and mixed layer depths, providing context for light and stratification effects on phytoplankton dynamics. Data were derived from in situ incubations and fluorometric analyses, with values reported for discrete depths at each station to highlight vertical gradients in biomass and photosynthetic performance. This completed dataset is particularly valuable for studies on polar marine ecosystems, carbon cycling, and climate-driven changes in phytoplankton communities, offering insights into how size-structured assemblages respond to environmental gradients in the Southern Ocean. It does not include taxonomic details beyond general phytoplankton groupings but emphasizes physiological metrics for modeling primary production in ice-influenced regions.
Time-series of high-frequency profiles of fluorescence-based phytoplankton spectral groups in Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2014-2025
Depth profiles of fluorescence-based phytoplankton biomass were sampled using a bbe Moldaenke FluoroProbe (Schwentinental, Germany) during 2014 to 2025 in five drinking water reservoirs in southwestern Virginia, USA. These reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of depth profiles of fluorescence-based phytoplankton biomass measured at the deepest site of each reservoir adjacent to the dam, except in Falling Creek Reservoir, where depth profiles were also taken at four upstream sites ranging from the riverine to the lacustrine zone during 2016-2019 and 2024-2025. Casts were taken approximately weekly from May-October and monthly from November-April. Casts were collected at Beaverdam and Falling Creek Reservoirs during all years (2014-2025); casts were collected at Carvins Cove Reservoir during 2014-2016, 2018-2023, and 2025; casts were collected at Spring Hollow Reservoir during 2014-2016 and 2019; and casts were collected at Gatewood Reservoir in 2015-2016. A sensor maintenance log and quality assurance/quality control analysis script accompanies the data package.
Plum Island LTER phytoplankton identification using HPLC and Chem Taxonomy along transects in the Plum Island Sound estuary, Massachusetts. (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-pie/404/4. The abstract below was extracted from the Level 0 data package and is included for context: Water column samples are collected along an estuarine salinity gradient as part of our monitoring surveys of the Parker River estuary each spring and late summer (typically high vs low freshwater input). Samples are filtered, and stored frozen for later pigment analyses by HPLC. Pigment data are then analyzed by CHEMTAX, calibrated to a matrix of pigment ratios based on taxonomy and enumeration of selected subsamples by microspcopy. Data are presented in terms of chlorophyll a concentrations partitionaed among the major phytoplankton groups as determined by CHEMTAX. For 2003-2006, sampling stations along the Plum Island Sound-Parker River were at fixed geographic locations at specific "Bends" in the river. In 2008, we began sampling the water column in salinity space rather than at specific geographic locations along the river. This sampling approach was adopted in order to follow particular water masses in this macrotidal estuary. In practical terms, it means that sampling locations, or stations, are not static. Therefore, we have mapped the 11 sampling locations (latitude and longitude are logged at each station) from each transect along the mainstem of the estuary, so each station may be placed along the river (to the nearest 0.5km) as well as in salinity space. We have also used the km marker to assign the sampling locations from each survey to one of four bounding boxes : the Sound (Plum Island Sound; EST-PR-SoundBND) which encompasses approximatly the first 9.5 km or the transect, with Okm at the mouth of the sound; the Lower Parker River (EST-PR-LowerParkerBND) , ~9.5 - 1
Phytoplankton, benthic algae, and associated environmental data from Lake Okeechobee, Florida, USA, August 2023 - November 2023
This data package contains phytoplankton, periphytometer, and environmental data collected from the South Florida Water Management District’s (SFWMD) Aquifer Storage and Recovery (ASR) monitoring sites and the Indian Prairie marsh during the 2023 rainy season. We collected phytoplankton from a surface water grab and benthic algae from artificial substrates (periphytometers) that were placed outside for three weeks. We also collected associated nutrient measurements and environmental data. Collections occurred twice from August to November 2023. Data were collected to better understand how phytoplankton and benthic algae differed in their responses to TN:TP ratios in a hypereutrophic lake known to have spatial differences in limiting nutrients. Data collection for this data package is complete.
North Temperate Lakes LTER: Phytoplankton - Trout Lake Area 1984 - 2006
Phytoplankton samples from the seven northern Wisconsin LTER lakes in the Trout Lake area (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes and bog lakes 27-02 [Crystal Bog], and 12-15 [Trout Bog]) are collected six times per year at the deep hole sampling station at the same time as our other limnological sampling is conducted. We use a peristaltic pump and tubing, collecting a separate sample from the epilimnion, metalimnion and hypolimnion for most of the lakes. For 27-2 Bog Lake, which is only 2m deep, we collect one 0-2m composite sample. The samples are preserved with Lugols iodine solution. We create a single hypsometrically pooled composite sample per lake from subsamples of the strata samples. The pooled samples are sent to PhycoTech, Inc., a private lab specializing in phytoplankton analysis, to be made into permanent slide mounts. The slide mounts, 3 slides per sample, are archived at the University of Wisconsin - Madison Zoology Museum Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentrations are then computed by mulitplying the average cell biovolume by the cell densities in the water sample. Note that one million cubicMicrometers of biovolume PerMilliliter of water are equal to a biovolume concentration of one cubicMillimeterPerMilliliter. Assuming a cell density equal to water, a cubicMillimeterPerMilliliter of biovolume conv
North Temperate Lakes LTER: Phytoplankton and Protoplankton 2000
Phytoplankton and Protoplankton collected in North Temparate Lakes Sampling Frequency: monthly Number of sites: 1. Graham JM, Kent AD, Lauster GH, Yannarell AC, Graham LE, Triplett EW. 2004. Seasonal dynamics of phytoplankton and planktonic protozoan communities in a north temperate humic lake: diversity in a dinoflagellate dominated system. Microbial Ecology. 48:528-540.
Cascade Project at North Temperate Lakes LTER: Phytoplankton 1984 - 1995
Data on epilimnetic phytoplankton from 1984-95, determined by light microscopy from pooled Van Dorn samples at 100percent, 50percent, and 25percent of surface irradiance. There have been 4 counters during this period, with the same counter from 1991-95. Standardization among counters is difficult, so I recommend sticking to the 1991-95 data if possible. Cottingham (1996) describes the counting protocols in detail. Sampling Frequency: varies Number of sites: 5
North Temperate Lakes LTER: Phytoplankton - Madison Lakes Area 1995 - current
Phytoplankton samples for the 4 southern Wisconsin LTER lakes (Mendota, Monona, Wingra, Fish) have been collected for analysis by LTER since 1995 (1996 Wingra, Fish) when the southern Wisconsin lakes were added to the North Temperate Lakes LTER project. Samples are collected as a composite whole-water sample and are preserved in gluteraldehyde. Composite sample depths are 0-8 meters for Lake Mendota (to conform to samples collected and analyzed since 1990 for a UW/DNR food web research study), and 0-2 meters for the other three lakes. A tube sampler is used for the 0-8 m Lake Mendota samples; samples for the other lakes are obtained by collecting water at 1-meter intervals using a Kemmerer water sampler and compositing the samples in a bucket. Samples are taken in the deep hole region of each lake at the same time and location as other limnological sampling. Phytoplankton samples are analyzed by PhycoTech, Inc., a private lab specializing in phytoplankton analyses (see data protocol for procedures). Samples for Wingra and Fish lakes are archived but not routinely counted. Permanent slide mounts (3 per sample) are prepared for all analyzed Mendota and Monona samples as well as 6 samples per year for Wingra and Fish; the slide mounts are archived at the University of Wisconsin - Madison Zoology Museum. Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentratio
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.
Nutrient amendment effects on phytoplankton, water chemistry, and cyanotoxins in the 2018 Large-Scale Mesocosm Experiment at the University of Kansas Field Station
This dataset includes water physicochemical parameters, phytoplankton community composition, and cyanobacteria metabolites collected during a 21-day nutrient amendment experiment conducted from 23 July to 13 August 2018 at the University of Kansas Biological Station, Lawrence, KS, United States (39.049674°N, 95.190777°W). The experiment was performed using 18 large-scale, closed-bottom fiberglass tanks (volume: 11,000 L; height: 1.25 m; diameter: 3 m). Three tanks served as ambient controls (CON), while the others received one of the following nutrient treatments: nitrogen only (280 µM) as either ammonium chloride (NH4) or sodium nitrate (NO3); nitrogen (280 µM) plus phosphorus (200 µM) as either ammonium chloride + dipotassium phosphate (NHP) or sodium nitrate + dipotassium phosphate (NOP); and phosphorus only (200 µM) as dipotassium phosphate (P). Each tank received an initial nutrient dose on Day 0.5, followed by weekly additions of 20% of the initial amendment to maintain treatment conditions. All data were quality controlled to correct basic errors and to remove measurements outside the manufacturer’s standard operational ranges.
Plum Island LTER phytoplankton identification using HPLC and Chem Taxonomy along transects in the Plum Island Sound estuary, Massachusetts. (Reformatted to a Darwin Core Archive)
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/338/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-pie/404/4. The abstract below was extracted from the Level 0 data package and is included for context: Water column samples are collected along an estuarine salinity gradient as part of our monitoring surveys of the Parker River estuary each spring and late summer (typically high vs low freshwater input). Samples are filtered, and stored frozen for later pigment analyses by HPLC. Pigment data are then analyzed by CHEMTAX, calibrated to a matrix of pigment ratios based on taxonomy and enumeration of selected subsamples by microspcopy. Data are presented in terms of chlorophyll a concentrations partitionaed among the major phytoplankton groups as determined by CHEMTAX. For 2003-2006, sampling stations along the Plum Island Sound-Parker River were at fixed geographic locations at specific "Bends" in the river. In 2008, we began sampling the water column in salinity space rather than at specific geographic locations along the river. This sampling approach was adopted in order to follow particular water masses in this macrotidal estuary. In practical terms, it means that sampling locations, or stations, are not static. Therefore, we have mapped the 11 sampling locations (latitude and longitude are logged at each station) from each transect along the mainstem of the estuary, so each station may be placed along the river (to the nearest 0.5km) as well as in salinity space. We have also used the km marker to assign the sampling locations from each survey to one of four bounding boxes : the Sound (Plum Island Sound; EST-PR-SoundBND) which encompasses approximatly the first 9
Continuous depth-integrated fluorometric phytoplankton measurements in Lake Bonney, McMurdo Dry Valleys, Antarctica (2013-2017)
Phytoplankton are key primary producers in the photic zones of permanently ice-covered lakes in Antarctica’s McMurdo Dry Valleys (MDV), playing a crucial role in regional carbon cycling. However, their seasonal dynamics remain poorly understood, particularly during winter, when the region is inaccessible to researchers. To address this gap, the Autonomous Lake Profiler and Samplers (ALPS) project, part of the McMurdo Dry Valleys Long Term Ecological Research (MCM LTER) program, deployed sensors and samplers to collect year-round data on phytoplankton dynamics. This data package provides continuous, depth-integrated fluorometric measurements of phytoplankton communities in Lake Bonney from 2013 to 2017. A submersible spectrofluorometer (bbe Moldaenke FluoroProbe) was used to quantify the vertical distribution of key algal classes – brown/mixed algae, green algae, and cryptophytes – within the deep photic zone of the lake’s eastern (21–24 m) and western (16–24 m) lobes. Lake Bonney serves as a year-round refugium for life in extreme environments, but rapid lake level rise over the past three decades has introduced new uncertainties regarding phytoplankton community dynamics. These data contribute to ongoing efforts to understand how environmental change influences microbial ecology in polar aquatic ecosystems.
Abundance, biovolume, and biomass of Synechococcus, eukaryote pico- and nano- phytoplankton, and heterotrophic bacteria from flow cytometry for water column bottle samples on NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic phytoplankton, eukaryotic pico- and nano- phytoplankton, and heterotrophic bacteria from discrete flow cytometry samples collected during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were collected and preserved from the water column at multiple depths using Niskin bottles on a CTD rosette system along the NES-LTER transect, and analyzed post cruise. Cells were identified and enumerated from the flow cytometry data files based on their scattering, SYBR (525 nm), phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals. Gating was completed manually in the Attune NXT software interface.
Phytoplankton growth and microzooplankton grazing rates from NES-LTER transect cruises, ongoing since 2018.
Phytoplankton growth and microzooplankton grazing rates were measured from incubation experiments using the dilution method in the framework of the Northeast U.S. Shelf Long-Term Ecological Research project. The data set includes plankton population dynamics rates obtained during 12 cruises from winter 2018 (EN608) to summer 2022 (EN687) along a north/south transect from Martha’s Vineyard to the shelf-break. Phytoplankton growth and microzooplankton grazing rates were measured for the total phytoplankton community (chl-a concentrations) and for size fractions (chl-a size fractionation) less than and greater than 10 µm. Phytoplankton growth and microzooplankton grazing rates, the first trophic interaction between primary producers and higher trophic levels, are essential parameters to assess the cycling and export of carbon in the ocean and to better understand marine food webs.
Global Phytoplankton Phenological Indices - 25km resolution
<p>Bloom phenology metrics calculated from OC-CCI v6.0 data at a spatial resolution of 25km. </p> <p>Metrics calculated using three approaches:</p> <ol> <li>Threshold method</li> <li>Cumulative Sum method</li> <li>Rate of Change method</li> </ol> <p> </p> <p><strong>Version 1.0:</strong></p> <ul> <li>Data from 1997 to 2022.</li> </ul> <p><strong>Version 1.1:</strong></p> <ul> <li>Data from 1997 to 2023.</li> </ul> <p> </p>
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