Nutrients (phosphate and nitrite+nitrate) from daily sampling at the Santa Monica Pier (SMP), Santa Monica Bay, CA from 2018 to 2019

Website: https://www.bco-dmo.org/dataset/883916
Data Type: Other Field Results
Version: 1
Version Date: 2022-11-17

Project
» Protistan, prokaryotic, and viral processes at the San Pedro Ocean Time-series (SPOT)
ContributorsAffiliationRole
Caron, DavidUniversity of Southern California (USC)Principal Investigator
Hu, Sarah K.University of Southern California (USC)Scientist
Ollison, Gerid A.University of Southern California (USC)Scientist
York, Amber D.Woods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
This dataset contains nutrients (phosphate and nitrite+nitrate) from daily sampling at the Santa Monica Pier (SMP) from 2018 to 2019. These data were published in Ollison et al (2022). These data were collected as part of a study of high frequency (daily) changes in relative abundance dynamics of the metabolically active protistan community were followed via expressed 18S V4 rRNA genes (RNA) throughout two algal blooms during the spring of 2018 and 2019 in Santa Monica Bay (central Southern California Bight) to examine the environmental factors that influence protistan community dynamics during algal blooms.


Coverage

Spatial Extent: Lat:34.009 Lon:-118.497
Temporal Extent: 2018-03-26 - 2019-05-05

Methods & Sampling

Blooms were targeted in Santa Monica Bay during spring 2018 and 2019 using local meteorological information to anticipate coastal upwelling events (Figure S1, Ollison et al., 2022). Sampling from the Santa Monica Pier (SMP) was conducted daily at 0900 (PST/PDT) from the same location and orientation on the SMP from the 16th through the 30th in April 2018 (15 days), and in 2019 from the 13th April through 6th May (22 days; no sample was collected on the 14th April 2019). Sampling periods are henceforth referred to as 2018 and 2019, respectively.

An RBR Concerto (https://rbr-global.com) was deployed in surface water for 15 minutes at the time of each sample collection to obtain temperature, conductivity, chlorophyll a fluorescence, and dissolved oxygen concentrations (See "Related Dataset" section for CTD data). A 20 µm mesh plankton net was drift towed from the pier (15 min), and samples were examined via light microscopy to identify the dominant planktonic taxa and their relative abundances.

Surface water for 18S rRNA sequencing (see Related Datasets section), nutrient analyses, cell counts, extracted chlorophyll concentrations, and domoic acid concentrations was collected via bucket toss from the pier; an extended funnel was used to gently fill a single acid-washed-3x-rinsed 20 L carboy per established lab protocol (https://www.protocols.io/view/sample-collection-from-the-field-for-downstream-mo-hisb4ee). The carboy was protected from the light and immediately transported approximately 300 meters to the Heal the Bay Aquarium located at the SMP for sample processing.

Samples for nitrite + nitrate and phosphate were measured from 0.02 μm filtered seawater via flow injection analysis on a Quickchem 8500 at the Marine Science Institute Analytical Lab, UCSB (See supplemental files for metadata about these analyses).


Data Processing Description

BCO-DMO Data Manager Processing Notes:
* Data from source files nutrients_2018_metadata.txt, nutrients_2019_metadata.txt were imported into the BCO-DMO data system and concatenated into one data table.
* blank column heading named "location" to be consistant with related datasets.
* date format converted to ISO8601 format


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Supplemental Files

File
Nutrient Analysis Metadata 2018
filename: nutrients_2018_metadata.txt
(Plain Text, 364 bytes)
MD5:6d3291fcb7bc12098f84c14e68eb2b7a
Analysis metadata from the "FIA Nutrient Analysis Results" conducted by the Marine Science Institute Analytical Lab, UCSB in 2018.
Nutrient Analysis Metadata 2019
filename: nutrients_2019_metadata.txt
(Plain Text, 351 bytes)
MD5:2c7b29bdde6b8d579d69991350a8e32d
Analysis metadata from the "FIA Nutrient Analysis Results" conducted by the Marine Science Institute Analytical Lab, UCSB in 2019.

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Related Publications

Hu, S. (2017). Sample collection from the field for downstream molecular analysis - microbial eukaryote-focused v1. Protocols.io. doi:10.17504/protocols.io.hisb4ee
Methods
Kim, H.-J., Miller, A. J., McGowan, J., & Carter, M. L. (2009). Coastal phytoplankton blooms in the Southern California Bight. Progress in Oceanography, 82(2), 137–147. https://doi.org/10.1016/j.pocean.2009.05.002
Methods
Ollison, G. A., Hu, S. K., Hopper, J. V., Stewart, B. P., Smith, J., Beatty, J. L., Rink, L. K., & Caron, D. A. (2022). Daily dynamics of contrasting spring algal blooms in Santa Monica Bay (central Southern California Bight). Environmental Microbiology. Portico. https://doi.org/10.1111/1462-2920.16137
Results
Seubert, E. L., Gellene, A. G., Howard, M. D. A., Connell, P., Ragan, M., Jones, B. H., Runyan, J., & Caron, D. A. (2013). Seasonal and annual dynamics of harmful algae and algal toxins revealed through weekly monitoring at two coastal ocean sites off southern California, USA. Environmental Science and Pollution Research, 20(10), 6878–6895. https://doi.org/10.1007/s11356-012-1420-0 https://doi.org/10.1007/S11356-012-1420-0
Methods

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Related Datasets

IsRelatedTo
Caron, D., Ollison, G. A., Hu, S. K. (2022) CTD data from daily sampling at the Santa Monica Pier (SMP), Santa Monica Bay, CA from 2018 to 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-11-17 http://lod.bco-dmo.org/id/dataset/883908 [view at BCO-DMO]
Relationship Description: Data collected as part of targeted sampling of blooms in the Santa Monica Bay during spring 2018 and 2019.
Caron, D., Ollison, G. A., Hu, S. K. (2022) Sampling information and sequence accessions for 18S-V4 sequences from surface water collected at the Santa Monica Pier (SMP) Santa Monica Bay, CA from 2018 to 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-11-17 http://lod.bco-dmo.org/id/dataset/883924 [view at BCO-DMO]
Relationship Description: Data from the same samples collected as part of targeted sampling of blooms in the Santa Monica Bay during spring 2018 and 2019.

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Parameters

ParameterDescriptionUnits
Project

Associated project

unitless
Date

Date sampled

unitless
Location

Location of sampling (e.g. Surface, st.3, SPOT= San Pedro Ocean Time-series)

unitless
Sample_ID

Sample Identification number

unitless
Phosphate

Phosphate concentration

micromolar (uM)
Nitrite_plus_nitrate

Nitrite+nitrate concentration

micromolar (uM)


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Instruments

Dataset-specific Instrument Name
Quickchem 8500
Generic Instrument Name
Flow Injection Analyzer
Generic Instrument Description
An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques.


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Project Information

Protistan, prokaryotic, and viral processes at the San Pedro Ocean Time-series (SPOT)

Coverage: San Pedro Channel off the coast of Los Angeles


Planktonic marine microbial communities consist of a diverse collection of bacteria, archaea, viruses, protists (phytoplankton and protozoa) and small animals (metazoan). Collectively, these species are responsible for virtually all marine pelagic primary production where they form the basis of food webs and carry out a large fraction of respiratory processes. Microbial interactions include the traditional role of predation, but recent research recognizes the importance of parasitism, symbiosis and viral infection. Characterizing the response of pelagic microbial communities and processes to environmental influences is fundamental to understanding and modeling carbon flow and energy utilization in the ocean, but very few studies have attempted to study all of these assemblages in the same study. This project is comprised of long-term (monthly) and short-term (daily) sampling at the San Pedro Ocean Time-series (SPOT) site. Analysis of the resulting datasets investigates co-occurrence patterns of microbial taxa (e.g. protist-virus and protist-prokaryote interactions, both positive and negative) indicating which species consistently co-occur and potentially interact, followed by examination gene expression to help define the underlying mechanisms. This study augments 20 years of baseline studies of microbial abundance, diversity, rates at the site, and will enable detection of low-frequency changes in composition and potential ecological interactions among microbes, and their responses to changing environmental forcing factors. These responses have important consequences for higher trophic levels and ocean-atmosphere feedbacks. The broader impacts of this project include training graduate and undergraduate students, providing local high school student with summer lab experiences, and PI presentations at local K-12 schools, museums, aquaria and informal learning centers in the region. Additionally, the PIs advise at the local, county and state level regarding coastal marine water quality.

This research project is unique in that it is a holistic study (including all microbes from viruses to small metazoa) of microbial species diversity and ecological activities, carried out at the SPOT site off the coast of southern California. In studying all microbes simultaneously, this work aims to identify important ecological interactions among microbial species, and identify the basis(es) for those interactions. This research involves (1) extensive analyses of prokaryote (archaean and bacterial) and eukaryote (protistan and micro-metazoan) diversity via the sequencing of marker genes, (2) studies of whole-community gene expression by eukaryotes and prokaryotes in order to identify key functional characteristics of microorganismal groups and the detection of active viral infections, and (3) metagenomic analysis of viruses and bacteria to aid interpretation of transcriptomic analyses using genome-encoded information. The project includes exploratory metatranscriptomic analysis of poorly-understood aphotic and hypoxic-zone protists, to examine their stratification, functions and hypothesized prokaryotic symbioses.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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