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| Dataset Title: | [Hawaiian crustose coralline algae dissolved organic matter] - Fluorescent characteristics of the dissolved organic exudates of two species of crustose coralline algae in two water treatments and their effect on the microbial community cell count (Collaborative Research: Dissolved organic matter feedbacks in coral reef resilience: The genomic & geochemical basis for microbial modulation of algal phase shifts) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_783581) |
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Attributes {
s {
Water {
String bcodmo_name "treatment";
String description "Water treatment";
String long_name "Water";
String units "unitless";
}
Inhabitant {
String bcodmo_name "sample";
String description "Organism or control treatment";
String long_name "Inhabitant";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
String units "unitless";
}
Replicate {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 3;
String bcodmo_name "replicate";
String description "Replicate beaker";
String long_name "Replicate";
String units "unitless";
}
Timepoint {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 3;
String bcodmo_name "time_point";
String description "Time-lapse of data collection";
String long_name "Timepoint";
String units "unitless";
}
Hours {
Byte _FillValue 127;
String _Unsigned "false";
Byte actual_range 1, 8;
String bcodmo_name "time_elapsed";
String description "Hours of incubation";
String long_name "Hours";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
String units "hours";
}
Cells {
Float64 _FillValue NaN;
Float64 actual_range 13.64, 1141.92;
String bcodmo_name "abundance";
String description "number of cells measure by FCM";
String long_name "Cells";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "cells per microliter (cells uL-1)";
}
delta_Cells {
Float64 _FillValue NaN;
Float64 actual_range -94.86, 479.061225;
String bcodmo_name "abundance";
String description "change in cells from T0:TF";
String long_name "Delta Cells";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
String units "cells per microliter (cells uL-1)";
}
Surface_Area {
Float32 _FillValue NaN;
Float32 actual_range 16.603, 36.147;
String bcodmo_name "surface_area";
String description "sum surface area of cca in treatment";
String long_name "Surface Area";
String units "square centimeters (cm^2)";
}
Ultra_Violet_Humic_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0198831163049, 0.0545693486016;
String bcodmo_name "unknown";
String description "Coble Peak A (Ultra Violet Humic-like)";
String long_name "Ultra Violet Humic Like";
String units "Raman units of water (RU)";
}
Marine_Humic_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0222084940491, 0.056609340363;
String bcodmo_name "unknown";
String description "Coble Peak M (Marine Humic-like)";
String long_name "Marine Humic Like";
String units "Raman units of water (RU)";
}
Visible_Humic_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0199823279068, 0.0593025147738;
String bcodmo_name "unknown";
String description "Coble Peak C (Visible Humic-like)";
String long_name "Visible Humic Like";
String units "Raman units of water (RU)";
}
Tryptophan_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0166615440204, 0.0844118245414;
String bcodmo_name "unknown";
String description "Coble Peak T (Tryptophan-like)";
String long_name "Tryptophan Like";
String units "Raman units of water (RU)";
}
Tyrosine_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0197481729303, 0.06007038535;
String bcodmo_name "unknown";
String description "Coble Peak B (Tyrosine-like)";
String long_name "Tyrosine Like";
String units "Raman units of water (RU)";
}
Phenylalanine_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 0.0417268191721;
String bcodmo_name "unknown";
String description "Coble Peak F (Phenylalanine-like)";
String long_name "Phenylalanine Like";
String units "Raman units of water (RU)";
}
Fulvic_Acid_like {
Float64 _FillValue NaN;
Float64 actual_range 0.0096660756124, 0.0284126318272;
String bcodmo_name "unknown";
String description "Stedmon peak D (Fulvic acid like)";
String long_name "Fulvic Acid Like";
String units "Raman units of water (RU)";
}
DOC {
Float32 _FillValue NaN;
Float32 actual_range 131.47, 232.59;
String bcodmo_name "DOC";
String description "Dissolved Organic Carbon (DOC)";
String long_name "DOC";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGZZZX/";
String units "micromoles per liter (umol L-1)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
String acquisition_description
"The following sections contain methodology excerpts from Quinlain et al.
(2019) relevant to this dataset.
Crustose Coraline Algae Collection and Identification
Both Hydrolithon reinboldii and Porolithon onkodes were collected from Patch
Reef 42 (21.4785\\u02da, -157.8281\\u02da) in K\\u0101ne'ohe Bay, O'ahu, Hawai'i
on 4 May 2017. Porolithon onkodes is a common CCA species in the Pacific Ocean
that is often used for larval settlement experiments with coral species in
Australia (Heyward and Negri 1999). It is typically found in high light and
high flow environments, such as at the top of the patch reefs in
K\\u0101ne\\u2018ohe Bay. This species is characterized by its smooth surface
texture, and diagnostic depressions of trichosite fields. While there is a
recent paper showing that this species is a species complex globally
(Gabrielson et al., 2018), we retain the use of the name P. onkodes here to be
consistent with the published taxonomic monograph for CCA in Hawai\\u02bbi
(Adey et al., 1982). Hydrolithon reinboldii is also a common CCA species that
is found throughout the Pacific Ocean. It is known to facilitate coral larval
settlement (Harrington et al., 2004). This species often lives cryptically in
cracks in the reef or on the bottom of small pieces of calcium carbonate
rubble. It is characterized by slightly raised hemispherical single pore
conceptacles (400-600 \\u00b5m in diameter), and a patchy surface texture
referred to as tessellate (Adey et al., 1982).
Fragments of both species of CCA were trimmed using bone cutters to ensure
only a single plant was on each fragment. Each fragment still retained bare
calcium carbonate along with the individual species of CCA. To control for the
bare calcium carbonate, encrusted fragments of calcium carbonate were
similarly trimmed to remove any small CCA plants and epiphytes leaving only
the calcium carbonate rubble and endophytes. After fragmentation the specimens
were haphazardly placed into six containers and randomized within a 1300 L
flow through seawater bath to maintain all treatments at a stable temperature,
which was the same as those found in K\\u0101ne\\u2018ohe Bay. As there are
currently no studies on the effect of fragmentation on exudate production we
allowed the fragmented algae to recover for five days before starting the
exudation experiment. Flow through seawater baths were covered by shade cloth
to reduce natural irradiance to levels similar to those found at depth in
K\\u0101ne\\u2018ohe Bay where both species are naturally found. Both species
were exposed to the same light levels as to not bias by variation of abiotic
parameters.
Incubations and sample collection
Twenty-four 250 mL glass beakers were washed with 10% volumetric HCl, rinsed
with milliq-water and air-dried. At 07:30 on 9 May, 3 L of seawater (sand
filtered and collected from the Hawai\\u2018i Institute of Marine Biology flow-
through seawater system in K\\u0101ne'ohe Bay) was vacuum pre-filtered through
0.2\\u00b5m polyethersulfone filters (47 mm; Sterlitech) in a 500 mL
polysulfone graduated filter holder. Before water was aliquoted into the
beakers, samples for fluorescent DOM (fDOM), dissolved organic carbon (DOC),
and flow cytometry (FCM) were collected from the 500 mL polysulfone graduated
filter holder. Each beaker was filled and randomized within a 1300L flow
through seawater bath to maintain stable temperature between the treatments.
Each organism treatment beaker (water control, calcium carbonate control,
Hydrolithon reinboldii, or Porolithon onkodes) was filled with seawater
(filtered or unfiltered) and replicated (n = 3) for a total of 24 beakers (4
organismal treatments * 2 water treatments * 3 replicates). Filtered and
unfiltered treatments were designed to capture differences in sloughing
behavior between species. A Multiple trimmed fragments of each organism were
placed within their respective beakers so that the total surface area within
each replicate beaker was standardized to 20-30 square cm (25.57 \\u00b1 4.13
cm2). The incubation began at 9:00 and was halted at 17:00 to maintain only
exudates produced during the daylight hours. Surface area was digitally
determined at the end of the experiment by analyzing images to scale with
image-J (Schindelin, Arganda-Carreras, & Frise et al, 2012).
DOM samples were collected at the beginning of the experiment before
aliquoting the water at 9:00 and from each beaker at 17:00. DOM samples were
immediately filtered through a 0.2 \\u00b5m polyethersulfone filter (47 mm;
Sterlitech) in a 500 mL polysulfone graduated filter holder. Filtrate was
poured directly from polysulfone graduated filter holder into its respective
sample vial, Filtrate for fDOM samples were collected in acid washed,
combusted, triple sample-rinsed amber borosilicate vials with Teflon septa
caps and stored dark at 4\\u02daC until analysis for fDOM within 24 hours. DOC
was collected in acid washed, combusted, triple sample rinsed clear
borosilicate vials with Teflon septa caps and measured as non-purgeable
organic carbon via acidification, sparging and high temperature platinum
catalytic oxidation on a Shimadzu TOC-V at the UCSB DOM Analytical Lab
following the methods outlined by Carlson et al. (2010). Samples for flow
cytometry were collected by pipet (1 ml amended to a final concentration of
0.5% paraformaldehyde, mixed by inversion, snap frozen -80\\u00baC) at 9:00,
13:00, and 17:00.
Sample analysis
Flow Cytometry: Flow cytometry was used to measure total nucleic acid-stained
cell concentrations. Samples were thawed and 200 \\u00b5L were aliquoted into
u-bottomed 96-well autosampler plates and stained with 2 \\u00b5L of 100X SYBR
Green I stain (final concentration of 0.5X). Samples were analyzed on an
Attune Acoustic Focusing Cytometer with Autosampler Attachment (Life
Technologies, Eugene, OR, USA). Samples were run at a flow rate of 100 \\u00b5L
min-1 on standard sensitivity; 150 \\u03bcL of sample was aspirated, 75 \\u03bcL
was counted and data was collected only from the last 50 \\u03bcL (event rates
were empirically determined to be steady only after 25 \\u03bcL of continuous
sample injection per Nelson et al., 2015).
Fluorescence spectroscopy: Samples for fluorescence spectroscopy were measured
using an Horiba Aqualog scanning fluorometer following the methods of Nelson
et al. (2015), including scan time and resolution, spectral data processing,
inner filter correction, Raman unit standardization, blank subtraction and
PARAFAC modeling (Stedmon and Bro 2008; Lawaetz and Stedmon 2009; Kothawala et
al. 2013). Scans were processed using a Matlab (v2007b) script written and
specified by Nelson et al. (2015) and Quinlan et al., (2018; most recent
version available at DOI: 10.5281/zenodo/3479841), modified to additionally
capture the peak present at Excitation 240 nm and Emission 300 nm
(phenylalanine-like: Lakowicz 2010). Six modeled components were validated
using split half validation and outlier analysis (Quinlan et. al., 2018). All
PARAFAC components had similar excitation-emission maxima and strong
covariation among samples with previously identified fluorophores (Quinlan,
et. al., 2018); for subsequent analyses we examined established fluorescence
maxima from the literature (Coble 1996; Stedmon et al. 2003; Lakowicz 2010).";
String awards_0_award_nid "675030";
String awards_0_award_number "OCE-1538393";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1538393";
String awards_0_funder_name "NSF Division of Ocean Sciences";
String awards_0_funding_acronym "NSF OCE";
String awards_0_funding_source_nid "355";
String awards_0_program_manager "Michael E. Sieracki";
String awards_0_program_manager_nid "50446";
String cdm_data_type "Other";
String comment
"Hawaiian crustose coralline algae dissolved organic matter
PI: Craig E. Nelson (University of Hawaii)
Version date: 2019-12-06";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_type "institution";
String creator_url "https://www.bco-dmo.org/";
String data_source "extract_data_as_tsv version 2.3 19 Dec 2019";
String date_created "2019-12-05T20:02:09Z";
String date_modified "2019-12-06T20:31:52Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.783581.1";
String history
"2024-12-22T11:28:24Z (local files)
2024-12-22T11:28:24Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_783581.html";
String infoUrl "https://www.bco-dmo.org/dataset/783581";
String institution "BCO-DMO";
String instruments_0_acronym "Fluorometer";
String instruments_0_dataset_instrument_nid "783589";
String instruments_0_description "A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/113/";
String instruments_0_instrument_name "Fluorometer";
String instruments_0_instrument_nid "484";
String instruments_0_supplied_name "Horiba Aqualog scanning fluorometer";
String instruments_1_acronym "Shimadzu TOC-V";
String instruments_1_dataset_instrument_nid "783590";
String instruments_1_description "A Shimadzu TOC-V Analyzer measures DOC by high temperature combustion method.";
String instruments_1_instrument_external_identifier "http://onto.nerc.ac.uk/CAST/124";
String instruments_1_instrument_name "Shimadzu TOC-V Analyzer";
String instruments_1_instrument_nid "603";
String instruments_1_supplied_name "Shimadzu TOC-V Analyzer";
String instruments_2_acronym "FIA";
String instruments_2_dataset_instrument_nid "783588";
String instruments_2_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.";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB36/";
String instruments_2_instrument_name "Flow Injection Analyzer";
String instruments_2_instrument_nid "657";
String instruments_2_supplied_name "Seal Analytical Segmented Flow Injection AutoAnalyzer AA3HR";
String keywords "acid, area, bco, bco-dmo, biological, cells, chemical, commerce, data, dataset, delta, delta_Cells, department, dmo, doc, erddap, fulvic, Fulvic_Acid_like, hours, humic, inhabitant, like, management, marine, Marine_Humic_like, oceanography, office, phenylalanine, Phenylalanine_like, preliminary, replicate, surface, Surface_Area, timepoint, tryptophan, Tryptophan_like, tyrosine, Tyrosine_like, ultra, Ultra_Violet_Humic_like, violet, visible, Visible_Humic_like, water";
String license "https://www.bco-dmo.org/dataset/783581/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/783581";
String param_mapping "{'783581': {}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/783581/parameters";
String people_0_affiliation "University of Hawaii at Manoa";
String people_0_affiliation_acronym "SOEST";
String people_0_person_name "Craig E. Nelson";
String people_0_person_nid "51538";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of Hawaii at Manoa";
String people_1_affiliation_acronym "SOEST";
String people_1_person_name "Zachary A. Quinlan";
String people_1_person_nid "726344";
String people_1_role "Contact";
String people_1_role_type "related";
String people_2_affiliation "Woods Hole Oceanographic Institution";
String people_2_affiliation_acronym "WHOI BCO-DMO";
String people_2_person_name "Shannon Rauch";
String people_2_person_nid "51498";
String people_2_role "BCO-DMO Data Manager";
String people_2_role_type "related";
String project "Coral DOM2";
String projects_0_acronym "Coral DOM2";
String projects_0_description
"NSF award abstract:
Coral reef degradation, whether driven by overfishing, nutrient pollution, declining water quality, or other anthropogenic factors, is associated with a phase shift towards a reefs dominated by fleshy algae. In many cases managing and ameliorating these stressors does not lead to a return to coral dominance, and reefs languish in an algal-dominated state for years. Nearly a decade of research has demonstrated that trajectories toward increasing algal dominance are restructuring microbial community composition and metabolism; the investigators hypothesize that microbial processes facilitate the maintenance of algal dominance by metabolizing organic compounds released by algae thereby stressing corals through hypoxia and disease. The resilience of reefs to these phase shifts is a critical question in coral reef ecology, and managing reefs undergoing these community shifts requires developing an understanding of the role of microbial interactions in facilitating algal overgrowth and altering reef ecosystem function. The research proposed here will investigate the organics produced by algae, the microbes that metabolize the organics, and the impacts of these processes on coral health and growth. This research has implications for managing reef resilience to algal phase shifts by testing the differential resistance of coral-associated microbial communities to algae and defining thresholds of algal species cover which alter ecosystem biogeochemistry. This project provides mentoring across multiple career levels, linking underrepresented undergraduates, two graduate students, a postdoctoral researcher, and a beginning and established investigators.
This project will integrate dissolved organic matter (DOM) geochemistry, microbial genomics and ecosystem process measurements at ecologically-relevant spatial and temporal scales to test hypothetical mechanisms by which microbially-mediated feedbacks may facilitate the spread of fleshy algae on Pacific reef ecosystems. A key product of this research will be understanding how the composition of corals and algae on reefs interact synergistically with complex microbial communities to influence reef ecosystem resilience to algal phase shifts. Emerging molecular and biogeochemical methods will be use to investigate mechanisms of microbial-DOM interactions at multiple spatial and temporal scales. This project will leverage the background environmental data, laboratory facilities and field logistical resources of the Mo'orea Coral Reef Long Term Ecological Research Project in French Polynesia and contribute to the mission of that program of investigating coral reef resilience in the face of global change. The investigators will quantify bulk diel patterns of DOM production and characterize the composition of chromophoric components and both free and acid-hydrolyzable neutral monosaccharides and amino acids from varying benthic algae sources. The team will also characterize planktonic and coral-associated microbial community changes in taxonomic composition and gene expression caused by algal DOM amendments in on-site controlled environmental chambers using phylogenetics and metatranscriptomics, including tracking algal exudate utilization by specific microbial lineages. Field-deployed 100 liter tent mesocosms will be used to examine in situ diel patterns of coupled DOM production and consumption, microbial community genomics and ecosystem metabolism over representative benthic communities comprising combinations of algal and coral species. Together these experimental results will guide interpretation of field surveys of centimeter-scale spatial dynamics of planktonic and coral-associated microbial genomics and metabolism at zones of coral-algal interaction, including boundary layer dynamics of oxygen, bacteria and DOM using planar optodes, high-throughput flow cytometry and fluorescence spectroscopy.";
String projects_0_end_date "2018-11";
String projects_0_geolocation "Pacific Coral Reefs";
String projects_0_name "Collaborative Research: Dissolved organic matter feedbacks in coral reef resilience: The genomic & geochemical basis for microbial modulation of algal phase shifts";
String projects_0_project_nid "675025";
String projects_0_start_date "2015-12";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Fluorescent characteristics of the dissolved organic exudates of two species of crustose coralline algae (Hydrolithon reinboldii and Porolithon onkodes) in two water treatments (pre-filtered and unfiltered) and their effect on the microbial community cell count.";
String title "[Hawaiian crustose coralline algae dissolved organic matter] - Fluorescent characteristics of the dissolved organic exudates of two species of crustose coralline algae in two water treatments and their effect on the microbial community cell count (Collaborative Research: Dissolved organic matter feedbacks in coral reef resilience: The genomic & geochemical basis for microbial modulation of algal phase shifts)";
String version "1";
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.
Tabledap request URLs must be in the form
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For example,
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