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301 results for “bloom”
Cascade Project at North Temperate Lakes LTER – Daily Bloom Data for Whole Lake Experiments 2011 - 2019
Daily measurements of algal bloom variables (chlorophyll, phycocyanin fluorescence, dissolved oxygen, and pH) from the surface waters of Paul, Peter, and Tuesday lakes from mid-May to early September for the years 2011 to 2019, excluding 2012 and 2017. In some years, Peter (2013-2015, 2019) and Tuesday (2013-2015) lakes had inorganic nitrogen and phosphorus added to them daily to cause algal blooms while Paul Lake served as an unmanipulated reference.
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.
Harmful algal bloom and aquatic weeds data from the Sacramento-San Joaquin Delta, collected to evaluate the impact of the 2021 Temporary Urgency Change Order and Emergency Drought Barrier
Condition 8 of the June 2021 Temporary Urgency Change Order for the Central Valley Project (CVP) and State Water Project (SWP) requires a special study of harmful algal blooms (HABs) in the Sacramento–San Joaquin Delta (Delta) and the spread of submersed aquatic vegetation (SAV), and floating aquatic vegetation (FAV), also referred to as “aquatic weeds”. A report on the study was submitted to the State Water Resources Control Board on June 1, 2022. This data package contains all publicly available data used in the report, including visual cyanobacteria reports, cyanotoxin data, water quality, nutrients, flow/hydrodynamics, chlorophyll-a concentrations, temperature, coverage of SAV and FAV, use of herbicides, and human populations. Many of these data were derived from other datasets, though some were collected specifically for this study
Shifts in Bacterioplankton During Cyanobacterial Blooms Reflect Bloom Toxicity and lake Trophic State, OR 2019-2020
Harmful cyanobacterial blooms (cyanoHABs) typically occur in human-impacted eutrophic lakes suffering from nutrient pollution, but they also occur in lakes spanning the trophic and disturbance gradients. CyanoHABs change the bacterioplankton community structure with increases in specific cyanobacteria strains, as well as shifts in heterotrophic taxa. Bacterioplankton community shifts during cyanoHABs can be somewhat predictable but have been only studied in a limited number of lakes, most highly productive and in developed watersheds. The Cascade Mountains (USA) offer an unique area to study cyanotoxin variation and shifts in bacterioplankton composition across a productivity gradient in lakes with documented cyanoHABs but removed from most development. We explored associations of bacterioplankton communities with cyanoHABs and toxins within a season, as well as across lakes and years via physicochemical metrics, passive toxin samplers and 16S rRNA gene sequencing. The data set is a compilation of physicochemical, meteorological, biological as well as physical lake characteristics and sampling information. Water temperature was tracked continuously within a season for the three lakes while single point measurements of water temperature were taken for the other lakes in the spatial (n= 29) and intra-annual subset (n =12). Daily air temperature, precipitation and aerosol optical depth were extracted from the PRISM Gridded Climate data. Nutrient concentrations were measured for all lakes and analyzed for nitrogen and phosphorus via colorimetry in a flow analyzer. Chlorophyll-a concentrations were measured from filter samples via fluorimetry. Microcystin concentrations from grab and SPATT samples were analyzed via an ELISA kit for Microcystin-LR. Bacterioplankton diversity metrics were calculated from the processed 16S rRNA sequences along with the relative abundance of potentially toxigenic cyanobacteria. Bacterioplankton composition was and can be derived from the raw
Unravelling winter diatom blooms in temperate lakes using high frequency data and ecological modeling
<p>This repository contains the dataset and the R script of the lake ecological model linked to the following publication:</p> <p>Article title: Unravelling winter diatom blooms in temperate lakes using high frequency data and ecological modeling</p> <p>Journal title: Water Research</p> <p>Article Number: 116681</p> <p>Abstract: In temperate lakes, it is generally assumed that light rather than temperature constrains phytoplankton growth in winter. Rapid winter warming and increasing observations of winter blooms warrant more investigation of these controls. We investigated the mechanisms regulating a massive winter diatom bloom in a temperate lake. High frequency data and process-based lake modeling demonstrated that phytoplankton growth in winter was dually controlled by light and temperature, rather than by light alone. Water temperature played a further indirect role in initiating the bloom through ice-thaw, which increased light exposure. The bloom was ultimately terminated by silicon limitation and sedimentation. These mechanisms differ from those typically responsible for spring diatom blooms and contributed to the high peak biomass. Our findings show that phytoplankton growth in winter is more sensitive to temperature, and consequently to climate change, than previously assumed. This has implications for nutrient cycling and seasonal succession of lake phytoplankton communities. The present study exemplifies the strength in integrating data analysis with different temporal resolutions and lake modeling. The new lake ecological model serves as an effective tool in analyzing and predicting winter phytoplankton dynamics for temperate lakes.</p>
Ground-truthing of satellite imagery to track harmful algal blooms in Pigeon Lake, Alberta, Canada 2017-2022
This data was collected to create a calibrated model that would enable the use of satellite imagery to track harmful algal blooms by using chlorophyll a estimates as a proxy for cyanobacteria in the lake. Samples from Pigeon Lake were collected on the same day that the Sentinel-2 satellite would pass over the lake. These samples were analyzed for different algal pigments and enumerated to genus level to ensure that the satellite imagery was of cyanobacteria rather than different algal groups. An algorithm was developed which we termed the three band index (TBI) that best matched with the cholorophyll a from the in situ samples. This model was used on satellite imagery from 2017-2022 of Pigeon Lake to get chlorophyll a estimates for every 20 x 20 pixel of each image of the lake. This pixel data was used to determine different bloom metrics like the intensity, the area (extent) and severity.
Nutrient Inputs in Mesocosms of an Oligotrophic Lake Fail to Sustain an Algal Bloom, Lake George, NY, 2019
Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems, and their frequency in oligotrophic lakes—previously thought resistant to such blooms due to their low nutrient levels—has been increasing. This challenges the traditional view that nutrient loading, a major driver of HABs, is less relevant in low-nutrient systems. To investigate whether nutrient enrichment plays a role in HAB development in oligotrophic lakes, we used in-lake mesocosms to assess the effects of varying nitrogen and phosphorus levels on pelagic communities over a 4-week period. The experiment utilized 20 mesocosms (~2,000 L each), with varying phosphorus (P) and nitrogen (N) concentrations, all maintaining a 30:1 N:P ratio, representing ten distinct nutrient levels (235:8 µg/L [control], 600:20 µg/L, 1200:40 µg/L, 1800:60 µg/L, 2400:80 µg/L, 3000:100 µg/L, 3600:120 µg/L, 4200:140 µg/L, 4800:160 µg/L, and 5400:180 µg/L). Nutrients were added twice a week (Tuesdays and Fridays) to sustain the concentrations, with two replicates for each of the ten treatments, totaling 20 experimental units. Water samples were collected to assess water chemistry at two points during the experiment (days 12 and 26). The water chemistry variables measured included total phosphorus (TP), total dissolved phosphorus (TDP), dissolved reactive phosphorus (DRP), total nitrogen (TN), nitrate, nitrite, ammonium, and chlorophyll a. Phytoplankton abundance and abiotic conditions (dissolved oxygen, temperature, pH, and turbidity) were monitored on days 5, 7, 10, 13, 17, 19, 21. Grab samples were also collected on day 12 and 26 to identify phytoplankton species/abundance and zooplankton abundance. In this experiment, nutrient additions enhanced the fluorescence of chlorophyll a (indicative of total phytoplankton) and phycocyanin (a proxy for cyanobacteria), these increases plateaued at low nutrient levels and were transient. Phytoplankton species identification and enumeration revealed no significant changes
Harmful Algal Bloom Monitoring in the Southern Sacramento-San Joaquin Delta
The Department of Water Resources (DWR) North Central Region Office (NCRO) Water Quality Evaluation Section (WQES) and the Division of Operations and Maintenance (O&M) provide technical expertise and program support for regulatory compliance, water operations, emergency response, and environmental restoration. Harmful Algal Blooms (HABs) are large overgrowths of algae in eutrophic marine or freshwater ecosystems that degrade beneficial uses of water resources, from aesthetics to habitat quality to human consumption. The Sacramento-San Joaquin Delta has observed an increasing number of HABs, especially in the South Delta. These HABs have been composed primarily of cyanobacteria, or blue-green algae (BGA). The most prevalent HAB producing cyanobacteria in recent years is the freshwater species Microcystis aeruginosa - a known producer of toxins called microcystins. Microcystins negatively affect the health of aquatic and terrestrial organisms alike, including humans and their pets. In late 2017, the Central Valley Water Resources Control Board (CVWRCB) issues a Section 401 Water Quality Certification for the DWR South Delta Temporary Barriers Projects. This certification required DWR to develop a dataset of surface Microcystis Visual Index (MVI) values during standard water quality station visits. In addition to the MVI, requirements for DWR to collect water samples for phytoplankton enumeration and cyanotoxin analysis began in 2019 and 2022, respectively. Together these data help DWR and CVWRCB to understand the distribution and composition of the algal community in the South Delta and to evaluate the species that contribute to HABs. As a separate project, DWR O&M collects cyanotoxin and taste and odor samples at Clifton Court Forebay and the Harvey O. Banks Pumping Plant to ensure that the water exported from the Delta is safe for use. This dataset provides an ongoing collection of taste and odor and cyanotoxin analysis beginning in 2009 and 2012, respectively.
Harmful algal bloom monitoring data near Frenchman Bay from 2004-2022
The Community Environmental Health Lab at the MDI Biological Laboratories has monitored phytoplankton and water quality in Frenchman Bay for the past few decades. Our goal was to understand how climate change and local changes in anthropogenic activity, including cruise ship activity, have altered the water quality and phytoplankton dynamics in the bay. This data provides information on target harmful algae bloom species as well as a few measures of phytoplankton biodiversity. Our data were collected by a variety of field technicians and citizen scientists who perform weekly sampling throughout the year at Bar Harbor town pier and during the summer months at the MDIBL pier and cruise ship anchorages.
California Harmful Algal Bloom Monitoring and Alert Program Data (Darwin Core Archive format)
The Harmful Algal Bloom Monitoring and Alert Program (HABMAP) was formed in 2008 and provides updates on current algal blooms and facilitates information exchange among scientists, federal and state managers, and the general public in California. A major component of this program is regional HAB monitoring with support from the Southern California Coastal Ocean Observing System (SCCOOS) and the Central and Northern California Ocean Observing System (CeNCOOS). Water samples and net tows are collected once per week at piers to monitor for HAB species, the neurotoxin domoic acid, and water quality data including temperature, chlorophyll-a, and nutrients. The sampling stations represented in this dataset include Santa Cruz Wharf, Monterey Wharf, Cal Poly Pier, Stearns Wharf, Santa Monica Pier, Newport Beach Pier, and Scripps Pier. These data are consolidated and reformatted into Darwin Core Archive (DwC-A) format from the level 1 site-specific datasets hosted on the SCCOOS ERDDAP server: (https://erddap.sccoos.org/erddap/tabledap/index.html?page=1).
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>
Dataset of E. huxleyi blooms: spatio-temporal distribution and their impact on high-latitudinal marine environments (1998-2016)
<p>Dataset of coccolithophore blooms in polar seas of the Northern Hemisphere, viz. the North, Labrador (with adjacent North Atlantic open waters), Norwegian, Barents, Greenland and Bering seas are presented for the period 1998-2016. Seas are divided into 4 regions, for each of them continuous data series (as 8-days composites) are published, including information about bloom spatial masks, coccolith concentration, particulate inorganic carbon content and CO<sub>2</sub> partial pressure in water increment driven by coccolithophores.</p> <p>Datasets are published as NetCDF files with full metadata/descriptions and with GDAL support.</p> <p>Additional information (regions configuration, data access instructions) is provided alongside the data.</p> <p>Naming convention is: <strong>niersc_cocco_<version of dataset>_<region>_<start date>_<end date>.nc</strong></p>
Harmfull algae bloom monitoring program dataset; ERDDAP, ERA5 and ONI datasets; and R script for multicriteria analisys in Santa Catarina coastal zone, Brazil.
<p>Project Harmful Algae Bloom (HAB) Monitoring Network in Santa Catarina, Brazil - Database and R script with data analysis. This project was funded by the Foundation for Research Support of the State of Santa Catarina – FAPESC and generated a database combining a HAB monitoring dataset with oceanographic (from ERDDAP) and climatic (from ERA5 and ONI) data which was submitted to multicriteria analysis using R. The HAB monitoring dataset was obtained from Cidasc/SC State Government (http://www.cidasc.sc.gov.br/defesasanitariaanimal/monitoramento-de-algas-nocivas/) and contains results of phytoplankton counts in water samples and toxin levels in shellfish samples obtained from 39 points located in shellfish farms distributed along the SC coastline. Oceanographic data were obtained from the ERDDAP/NOAA website (https://coastwatch.pfeg.noaa.gov/erddap/index.html), including the variables mean chlorophyll concentration (mg.m-3) and mean sea surface temperature (ºC); Climate data were obtained from Copernicus/ERA5 (https://cds.climate.copernicus.eu/) including the variables mean air temperature (ºC), mean pressure (Pasc.), mean cloud cover (%), mean precipitation (kg.m-2), radiation (Einsteins.m-2.day-1), mean U wind (m.s-1), and mean V wind (m.s-1).; Oceanic Niño Index (ONI) data were obtained from the NOAA website (https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php); The R script involves a pre-processing routine aimed at summarizing and integrating all datasets and the subsequent data analyses carried out to evidence temporal patterns related to different type of algal blooms. Detailed methods will be provided in a scientific article.</p>
Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 2)
<p>The dataset contains:</p> <p>i. the meteorological forcing, hydrological boundary condition and chlorophyll-a files used as an input</p> <p>ii. the model output and skill produced</p> <p>for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 2)</p>
Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 1)
<p>The dataset contains:</p> <p>i. the meteorological forcing, hydrological boundary condition and chlorophyll-a files used as an input</p> <p>ii. the model output and skill produced</p> <p>for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 1)</p>
Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 3)
<p>The dataset contains:</p> <p>i. the meteorological forcing, hydrological boundary condition and chlorophyll-a files used as an input</p> <p>ii. the model output and skill produced</p> <p>for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 3)</p>
Plumes and Blooms: Microbial eukaryote diversity and composition
These are amplicon sequencing data collected during Plumes and Blooms (PnB) cruises conducted from March, 2011, through September, 2014. The V9 hypervariable region of the 18S rRNA gene derived from microbial eukaryotic communities was amplified and sequenced from 345 discrete seawater samples. Sample collection and laboratory methods are described in Catlett et al. 2020 and Catlett et al. in review. Bioinformatic and data manipulation methods follow those employed in Catlett et al. in review. The data are provided in two tables: one includes amplicon sequence variant (ASV) sequences and relative sequence abundances for each sampling event, and the other includes ASV taxonomy predictions for each ASV sequence. References: Catlett, D., P. G. Matson, C. A. Carlson, E. G. Wilbanks, D. A. Siegel, and M. D. Iglesias‐Rodriguez. 2020. Evaluation of accuracy and precision in an amplicon sequencing workflow for marine protist communities. Limnol. Oceanogr.: Methods. 18(1): 20-40. https://doi.org/10.1002/lom3.10343. Catlett, D., D. A. Siegel, P. G. Matson, E. K. Wear, C. A. Carlson, T. S. Lankiewicz, and M. D. Iglesias‐Rodriguez. In review. Integrating phytoplankton pigment and DNA meta-barcoding observations to determine phytoplankton community composition in the coastal ocean. Limnol. Oceanogr.
Lake Superior cyanobacterial bloom reports, 2012 - present
Lake Superior is a cold, oligotrophic lake. It is the largest freshwater lake in the world by surface area and the largest of the Laurentian Great Lakes with binational (United States and Canada) and multi-state (Michigan, Wisconsin, Minnesota) borders. Lake Superior is a globally important freshwater resource. Beginning in 2012, researchers and resource managers began receiving reports of cyanobacterial blooms in the western arm of the Lake. Cyanobacterial blooms have been reported nearly every year since. The purpose of this dataset is to collect observations of cyanobacterial blooms for Lake Superior and connecting waters, document patterns in their occurrence, and provide insights into their causes. For this dataset, a cyanobacterial bloom is defined as an aggregation of cyanobacterial biomass in some or all of the water column, which may lead to the occurrence of surface scums or subsurface maximums. This dataset relies on observations, data, photographs, and insights from a wide range of agency staff and individual members of the public with key input from participants in the Lake Superior Algal Bloom and Nutrient Subgroup collaboration. This dataset only includes reported blooms, and likely doesn’t include all actual bloom events. Additionally, there may be more than one report for a single bloom event, depending on its size. For example, in 2018 there was a widespread bloom event which resulted in numerous reports. Interpretation of this dataset should incorporate these nuances. Observations in the dataset were assigned one of four verification statuses to communicate the level of certainty in the cyanobacterial bloom event. Additional information on taxonomy and/or toxin analyses can be made available upon request.
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