[Low-pH springs: foraminifera boron isotopes] - Isotopes (d11B, 87Sr/86Sr, d18O, d13C), elemental concentrations (B, Mg, Ca), and carbon content collected from the foraminifera Ammonia parkinsoniana and sediments in Celestun Lagoon, Yucatan, Mexico in June 2009 and May 2015 (Calcification in low saturation seawater: What can we learn from organisms in the proximity of low pH; undersaturated submarine springs)

This dataset includes isotopes (δ11B, 87Sr/86Sr, δ18O, δ13C), elemental concentrations (B, Mg, Ca), and carbon content collected from the foraminifera Ammonia parkinsoniana and sediments in Celestun Lagoon, Yucatan, Mexico in June 2009 and May 2015. Sediment cores were taken with push corers and piston corers. Sampling site were distributed unevenly along a transect along the lagoon. These data were collected to investigate the influence of low-pH groundwater-seawater mixing on the boron isotope pH proxy.

cdm_data_type = Other
VARIABLES:
date (date)
site (unitless)
latitude (degrees_north)
longitude (Long, degrees_east)
distance (kilometers (km))
core (unitless)
depth (m)
MgCa (millimol per mole (mmol/mol))
MgCa_2sd (millimol per mole (mmol/mol))
BCa (micromol per mole (umol/mol))
BCa_2sd (micromol per mole (umol/mol))
d11B (per mil (0/00))
d11B_2sd (per mil (0/00))
d18O (per mil (0/00))
d13C (per mil (0/00))
Sr8786 (unitless)
Sr8786_2sd (unitless)
d13C_om (per mil (0/00))
d13C_om_2sd (per mil (0/00))
om_content (percent (%))
om_content_2sd (percent (%))


[Low-pH springs: water samples] - Measured and calculated geochemistry values and uncertainty for water samples taken from the water column of Celestun Lagoon, Yucatan, Mexico in May of 2015 (Calcification in low saturation seawater: What can we learn from organisms in the proximity of low pH; undersaturated submarine springs)

Measured and calculated geochemistry values and uncertainty for water samples taken from the water column of Celestun Lagoon, Yucatan, Mexico in May of 2015.

This dataset was collected in coordination with the following study (See "Related Datasets" section):

Isotopes (δ11B, 87Sr/86Sr, δ18O, δ13C), elemental concentrations (B, Mg, Ca), and carbon content were collected from the foraminifera Ammonia parkinsoniana and sediments in Celestun Lagoon, Yucatan, Mexico in June 2009 and May 2015. Sediment cores were taken with push corers and piston corers. Sampling site were distributed unevenly along a transect along the lagoon. These data were collected to investigate the influence of low-pH groundwater-seawater mixing on the boron isotope pH proxy.

cdm_data_type = Other
VARIABLES:
site (unitless)
latitude (degrees_north)
longitude (Long, degrees_east)
distance (kilometers (km))
region (unitless)
date (unitless)
time_local (Time, unitless)
ISO_DateTime_UTC (unitless)
tide (unitless)
sample (unitless)
temperature (degrees Celsius)
salinity (practical salinity units (PSU))
pH (total scale)
DIC (micromoles per kilogram (umol/kg))
DIC_2sd (micromoles per kilogram (umol/kg))
TA (micromoles per kilogram (umol/kg))
... (40 more variables)


[M. jannaschii high/low H2: isotopes and fractionation factors] - Carbon isotopic compositions and fractionation factors of M. jannaschii in high and low hydrogen (H2) environments (Bioenergetic influences upon carbon flow in alkaliphilic sulfate-reducing microbial populations with relevance to the subsurface biosphere at the Lost City Hydrothermal Field)

Carbon isotopic compositions and fractionation factors of amino acids and squalenoid lipids in  Methanocaldococcus jannaschii in high and low hydrogen (H2) environments.

cdm_data_type = Other
VARIABLES:
Experiment (unitless)
Culture_ID (unitless)
d13C_ppt_Ala (D13 C Ppt Ala, parts per thousand (ppt))
d13C_ppt_Gly (D13 C PPT GLY, parts per thousand (ppt))
d13C_ppt_Thr (D13 C PPT THR, parts per thousand (ppt))
d13C_ppt_Ser (D13 C Ppt Ser, parts per thousand (ppt))
d13C_ppt_Val (D13 C Ppt Val, parts per thousand (ppt))
d13C_ppt_Leu (D13 C Ppt Leu, parts per thousand (ppt))
d13C_ppt_Iso (D13 C Ppt Iso, parts per thousand (ppt))
d13C_ppt_Pro (D13 C Ppt Pro, parts per thousand (ppt))
d13C_ppt_Glu (D13 C Ppt Glu, parts per thousand (ppt))
d13C_ppt_Phe (D13 C Ppt Phe, parts per thousand (ppt))
Weighted_Avg_d13C_THAA_ppt (Weighted Avg D13 C THAA Ppt, parts per thousand (ppt))
d13C_ppt_Sq_3 (D13 C PPT SQ 3, parts per thousand (ppt))
d13C_ppt_Sq_4 (D13 C PPT SQ 4, parts per thousand (ppt))
d13C_ppt_Sq_5 (D13 C PPT SQ 5, parts per thousand (ppt))
d13C_ppt_Sq_6 (D13 C PPT SQ 6, parts per thousand (ppt))
Weighted_Avg_ppt_d13C_Sq (Weighted Avg Ppt D13 C Sq, parts per thousand (ppt))
DIC_mM_To (DIC M M To, milliMolar (mM))
DIC_mM_Tf (DIC M M Tf, milliMolar (mM))
TFAA_uM_To (TFAA U M To, microMolar (uM))
TFAA_uM_Tf (TFAA U M Tf, microMolar (uM))
THAA_uM_To (THAA U M To, microMolar (uM))
THAA_uM_Tf (THAA U M Tf, microMolar (uM))
Fractionation_factor_ppt_eCO2_CH4 (Fractionation Factor Ppt E CO2 CH4, parts per thousand (ppt))
Fractionation_factor_ppt_eCO2_B (Fractionation Factor Ppt E CO2 B, parts per thousand (ppt))
Fractionation_factor_ppt_eCO2_AA (Fractionation Factor Ppt E CO2 AA, parts per thousand (ppt))
Fractionation_factor_ppt_eCO2_squalenoids (Fractionation Factor Ppt E CO2 Squalenoids, parts per thousand (ppt))


[macroalgal and coral cover] - Macroalgal and coral cover by species at 4x5 m plots, Panama, 1984-2010 (EPac Corals projects I-VII) (Ecological Effects of the 1982/83 El Nino-Associated Disturbance to Eastern Pacific Coral Reefs)

Macroalgal and coral cover surveys were conducted at the Uva Island coral reef (7o48\u201950.43\u201dN, 81o45\u201932.41\u201dW), Gulf of Chiriqu\u00ed, Panama from 1984 to 2010.

cdm_data_type = Other
VARIABLES:
year (unitless)
latitude (degrees_north)
longitude (degrees_east)
month (unitless)
plot (unitless)
benthic_cover (unitless)
area (pixels)


[Macroalgal biodiversity experiment: coral growth and tissue mortality data] - Coral (Pocillopora verrucosa) growth and tissue mortality from experimental field plots in Moʻorea, French Polynesia in 2021 (Positive Effects of Coral Biodiversity on Coral Performance: Patterns, Processes, and Dynamics)

Hundreds of studies now document positive relationships between biodiversity and critical ecosystem processes, but as ecological communities worldwide shift towards new species configurations, less is known regarding how biodiversity of undesirable species will shape the functioning of ecosystems or foundation species. We manipulated macroalgal species richness in experimental field plots to test whether and how identity and diversity of competing macroalgae affected the growth, survival, and microbiome of a common coral in Moʻorea, French Polynesia. These data include coral (Pocillopora verrucosa) percent growth and tissue mortality among corals outplanted into 25 cm x 21 cm experimental plots in the back reef lagoon on the north coast of Moʻorea, French Polynesia (17°28′37″S 149°50′21″W). We varied the macroalgal community on the upper surface of each plot by outplanting monocultures holding similar masses of: (1) Sargassum pacificum, (2) Turbinaria ornata, or (3) Amansia rhodantha, as well as (4) polycultures containing all three species (12 plots per treatment; Figure 1 of Clements et al., 2024). There were also two additional treatments: (5) plots with plastic algal mimics to control for effects of shading or abrasion unrelated to the biotic properties of live seaweeds and 6) control plots where corals, but not living algae or physical mimics, were present (n = 12 plots/treatment).

This dataset includes coral (Pocillopora verrucosa) growth and tissue mortality at 9 weeks for plots with no algae (control), plastic algal mimics, monocultures of Amansia rhodantha, Turbinaria ornata, or Sargassum pacificum, and polycultures containing all three algal species.

cdm_data_type = Other
VARIABLES:
ID (unitless)
Treatment (unitless)
Plot (unitless)
Colony (unitless)
Position (unitless)
Growth_percent (unitless)
Mortality_percent (unitless)


[Macrofauna Sediment Community Matrix, AT37-13 & AT42-03] - Matrix of taxon by sample for sediment push cores collected by HOV Alvin during R/V Atlantis cruise AT37-13 and AT42-03 in the Pacific margin of Costa Rica in 2017 and 2018 (Collaborative research: Quantifying the biological, chemical, and physical linkages between chemosynthetic communities and the surrounding deep sea)

Matrix of taxon (columns) by sample (rows) for sediment push cores collected by HOV Alvin during R/V Atlantis cruise AT37-13 in the Pacific margin of Costa Rica from May to June 2017

cdm_data_type = Other
VARIABLES:
dive_core (unitless)
Ampharetidae (unitless)
Ampharetidae_sp_1 (unitless)
Ampharetidae_sp_2 (unitless)
Ampharetidae_sp_3 (unitless)
Ampharetidae_sp_4 (unitless)
Ampharetidae_sp_5 (unitless)
Ampharetidae_sp_6 (unitless)
Amphisamytha_sp_1 (unitless)
Amphisamytha_sp_2 (unitless)
Amphinomidae (unitless)
Amphinomidae_sp_3 (unitless)
Amphinomidae_sp_4 (unitless)
Amphinomidae_sp_5 (unitless)
Amphinomidae_sp_6 (unitless)
Amphinomidae_sp_7 (unitless)
Aphroditidae (unitless)
Capitellidae (unitless)
Capitellidae_sp_2 (unitless)
Capitellidae_sp_3 (unitless)
Capitellidae_sp_4 (unitless)
Capitellidae_sp_5 (unitless)
Capitellidae_sp_6 (unitless)
Capitellidae_sp_7 (unitless)
Capitellidae_sp_8 (unitless)
Capitellidae_sp_9 (unitless)
... (309 more variables)


[Macronutrients from a 2014 IRNBRU cruise Rosette Data] - Macronutrient concentrations from samples collected using rosette on R/V Melville MV1405 (IRN-BRU) cruise in the California Current System in July 2014 (Accomplishment Based Renewal:   An iron limitation mosaic within the central California Current System)

This dataset includes macronutrient concentrations from seawater samples collected on R/V Melville MV1405 while investigating the mosaic of the California Current System in July 2014 using the shipboard rosette. It includes depth profiles of an active upwelling site nearshore over the shelf in northern California (Station 2), a more aged upwelling site offshore of the shelf break in southern Oregon (Station 28), a station in the Santa Barbara Basin that got suboxic in the lower depths of the water column (Station 29), and a set of stations (9, 12 and 15) that show two cyclonic eddies, one two months younger (station 9) than the other (station 15), but both coming from roughly the same place and moving offshore, with station 12 in between them in an offshoot of the California Current.

The chief scientist of the cruise was Ken Bruland. Nutrient samples were analyzed by Tyler Coale. See related datasets for additional macronutrient concentrations and dissolved trace metal concentrations found in GoFlo and surface samples collected on MV1405.

cdm_data_type = Other
VARIABLES:
Sample_date (unitless)
latitude (degrees_north)
longitude (degrees_east)
Station_number (unitless)
Station_notes (unitless)
depth (m)
Phosphate (umol/kg)
Silicic_acid (umol/kg)
Nitrate_plus_nitrite (umol/kg)
Nitrate_plus_nitrite_flag (unitless)
Nitrite (umol/kg)
Nitrate (umol/kg)


[Macrophytes' amelioration of seawater acidity: Comparison among species] - Macrophytes' amelioration of seawater acidity: Comparison among four species of marine macrophytes (Ulva lactuca, Zostera marina, Fucus vesiculosus and Saccharina latissima) from the Gulf of Maine from June to July 2015 (REU Site: Bigelow Laboratory for Ocean Sciences - Undergraduate Research Experience in the Gulf of Maine and the World Ocean)

An experiment examining the effects of increased CO2 concentrations upon the capacity of the different species of marine macrophytes to ameliorate seawater acidity via several assays in enclosed well-mixed, airtight chambers with no headspace, was conducted indoors at the Bigelow Laboratory for Ocean Sciences (Maine, USA), in June-July 2015. We explored the individual capacities of four species of marine macrophytes (Ulva lactuca, Zostera marina, Fucus vesiculosus and Saccharina latissima) to ameliorate seawater acidity in experimentally elevated pCO2.

This dataset includes data from experiment 1, comparison among species, described in the manuscript: Optimizing marine macrophyte capacity to locally ameliorate ocean acidification under variable light and flow regimes: Insights from an experimental approach (Ricart, A. M. et al. 2023).

cdm_data_type = Other
VARIABLES:
Sample (unitless)
Species (unitless)
latitude (degrees_north)
longitude (degrees_east)
date_start (unitless)
date_end (unitless)
Treatment (microatmospheres)
Liters (liters (L))
Hours (unitless)
Dry_Weight (grams (g))
Salinity (unitless)
Temperature (degrees Celcius (°C))
Initial_Dissolved_Oxygen (micromolar per liter (uM/L))
Initial_pH (total scale)
Initial_ALK (micromolar per kilogram (uM/kg))
Initial_pCO2 (microatmospheres)
delta_DO_norm (unitless)
delta_DIC_norm (unitless)
delta_pH_norm (unitless)
delta_omega_norm (unitless)


[Macrophytes' amelioration of seawater acidity: Residence time and irradiance] - Macrophytes' amelioration of seawater acidity: Water residence time and irradiance of Saccharina latissima from the Gulf of Maine in November 2018 (REU Site: Bigelow Laboratory for Ocean Sciences - Undergraduate Research Experience in the Gulf of Maine and the World Ocean)

An experiment examining the effects of water residence time upon Saccharina latissima capacity to ameliorate seawater acidity under ambient and simulated future scenarios of climate change in a gradient of irradiance was conducted indoors using tanks with a flow-through seawater system based at the Bigelow facilities in November 2018. In a previous experiment (experiment 1), we explored the individual capacities of four species of marine macrophytes (Ulva lactuca, Zostera marina, Fucus vesiculosus and Saccharina latissima) to ameliorate seawater acidity in experimentally elevated pCO2. Then in this experiment 2, we used the most responsive species (i.e., Saccharina latissima) to assess the effects of high and low water residence time on the amelioration of seawater acidity in ambient and simulated future scenarios of climate change across a gradient of irradiance.

This dataset includes data from experiment 2, residence time and irradiance, described in the manuscript: Optimizing marine macrophyte capacity to locally ameliorate ocean acidification under variable light and flow regimes: Insights from an experimental approach (Ricart, A. M. et al. 2023).

cdm_data_type = Other
VARIABLES:
Species (unitless)
latitude (degrees_north)
longitude (degrees_east)
Date (unitless)
Aquaria (unitless)
Future_Ambient (unitless)
Kelp_Control (unitless)
Kelp_biomass_wet (grams (g))
Kelp_biomass_dry (grams (g))
PAR (micromols m-2 s-1 (uM m-2 s-1))
Flow_level (unitless)
Salinity (unitless)
Temperature (degrees Celsius (°C))
... (7 more variables)


[Major inorganic ions in Primary Marine Aerosol (PMA) generated near the BATS station, cruises AE2113 and AE2303] - Major inorganic ions in Primary Marine Aerosols (PMA) generated from seawater collected near the BATS station during R/V Atlantic Explorer cruises AE2113 (July 2021) and AE2303 (January 2023) (Collaborative Research: Seasonal Variability in refractory dissolved organic carbon fluxes associated with primary marine aerosol emitted from the oceans)

This dataset includes the concentrations of seven major inorganic ions determined in primary marine aerosol (PMA) samples collected from the Bermuda Atlantic Time-series Study (BATS) station during a summer cruise in 2021 and a winter cruise in 2023 aboard the R/V Atlantic Explorer. The major ions in PMA samples were collected using a high-capacity aerosol generator and the major ions were quantified using a Dionex dual channel model ICS 6000 high-performance ion chromatograph (ICS-6000 DP). This dataset was generated and prepared by Dr. Lei Xue under the supervision of Dr. David Kieber at the State University of New York, College of Environmental Science and Forestry. These data were used to determine the enrichment of major ions in PMA samples and to calculate the enrichment factors of protein/peptides and carbohydrates in PMA samples relative to bulk seawater and the associated seasonal variability. This work is part of a larger study to understand the seasonal variability in the fraction of refractory organic carbon in primary marine aerosol at the BATS station.

cdm_data_type = Other
VARIABLES:
Cruise_ID (unitless)
Sample_Type (unitless)
Sample_ID (unitless)
latitude (degrees_north)
longitude (degrees_east)
Chloride_Ion (nmol/m3 air sampled)
Bromide_Ion (nmol/m3 air sampled)
Sulfate_Ion (nmol/m3 air sampled)
Sodium_Ion (nmol/m3 air sampled)
Potassium_Ion (nmol/m3 air sampled)
Magnesium_Ion (nmol/m3 air sampled)
Calcium_Ion (nmol/m3 air sampled)
ISO_DateTime_Local_Start (unitless)
ISO_DateTime_Local_Stop (unitless)
time (Iso_datetime_utc_start, seconds since 1970-01-01T00:00:00Z)
ISO_DateTime_UTC_Stop (seconds since 1970-01-01T00:00:00Z)


[Major inorganic ions in seawater near the BATS station, cruises AE2113 and AE2303] - Major inorganic ions from seawater collected near the BATS station during R/V Atlantic Explorer cruises AE2113 (July 2021) and AE2303 (January 2023) (Collaborative Research: Seasonal Variability in refractory dissolved organic carbon fluxes associated with primary marine aerosol emitted from the oceans)

This dataset includes the concentrations of seven major inorganic ions determined in near surface (approximately 5 m) seawater samples collected from the Bermuda Atlantic Time-series Study (BATS) station during a summer cruise in 2021 (AE2113) and a winter cruise in 2023 (AE2303) aboard the R/V Atlantic Explorer. The major ions in each sample were quantified using a Dionex dual channel model ICS 6000 high-performance ion chromatograph (ICS-6000 DP). This dataset was generated and prepared by Dr. Lei Xue under the supervision of Dr. David Kieber at the State University of New York, College of Environmental Science and Forestry. These data were used to determine the enrichment factor of major ions in primary marine aerosol (PMA) samples and to calculate the enrichment factors of protein/peptides and carbohydrates in PMA samples relative to seawater and the associated seasonal variability. This work is part of a larger study to understand the seasonal variability in the fraction of refractory organic carbon in primary marine aerosol at the BATS station.

cdm_data_type = Other
VARIABLES:
Cruise_ID (unitless)
time (Iso_datetime_utc, seconds since 1970-01-01T00:00:00Z)
CTD_filename (unitless)
latitude (degrees_north)
longitude (degrees_east)
Station (unitless)
Cast (unitless)
CTD_Bottle (unitless)
Temperature (degree Celsius)
depth (Sampling_depth, m)
Chloride_Ion (Part per thousand (ppt))
Bromide_Ion (Part per thousand (ppt))
Sulfate_Ion (Part per thousand (ppt))
Sodium_Ion (Part per thousand (ppt))
Potassium_Ion (Part per thousand (ppt))
Magnesium_Ion (Part per thousand (ppt))
Calcium_Ion (Part per thousand (ppt))


[Mangrove disease survey] - Disease incidence survey and site descriptions on Abaco Island, Bahamas in 2015-2016 (Mangrove Die-off project) (An interdisciplinary approach to elucidating the causes of widespread mangrove die-off)

Disease incidence survey and site descriptions on Abaco Island, Bahamas in 2015-2016 (Mangrove Die-off project)

cdm_data_type = Other
VARIABLES:
location (unitless)
latitude (degrees_north)
longitude (degrees_east)
lesionedLeaves_count (Lesioned Leaves Count, count)
deadTrees_presence (Dead Trees Presence, unitless)
site_description (unitless)


[Manually annotated reef halos from 6 study areas] - Manually annotated reef halos based on sattelite imagery from 6 study areas as training and test data for a deep learning model (CAREER: Decoding seascape-scale vegetation patterns on coral reefs to understand ecosystem health: Integrating research and education from organismal to planetary scales)

Reef halos are rings of bare sand that surround coral reef patches. Halo formation is likely to be the indirectly result of interactions between relatively healthy predator and herbivore populations. To reduce the risk of predation, herbivores preferentially graze close to the safety of the reef, potentially affecting the presence and size of the halo. Reef halos are readily visible in remotely sensed imagery, and monitoring their presence and changes in size may therefore offer clues as to how predator and herbivore populations are faring. However, manually identifying and measuring halos is slow and limits the spatial and temporal scope of studies. There are currently no existing tools to automatically identify single reef halos and measure their size to speed up their identification and improve our ability to quantify their variability over space and time.

Here we present a set of convolutional neural networks aimed at identifying and measuring reef halos from very high-resolution satellite imagery (i.e., ∼0.6 m spatial resolution). We show that deep learning algorithms can successfully detect and measure reef halos with a high degree of accuracy (F1 = 0.824), thereby enabling faster, more accurate spatio-temporal monitoring of halo size. This tool will aid in the global study of reef halos, and potentially coral reef ecosystem monitoring, by facilitating our discovery of the ecological dynamics underlying reef halo presence and variability.

cdm_data_type = Other
VARIABLES:
AOI (unitless)
Object_Id (unitless)
SkySate_image_ID (unitless)
Classname (unitless)
latitude (Mean_latitude, degrees_north)
longitude (Mean_longitude, degrees_east)
Subset (unitless)


[Mapping information and signs for individual diseased corals] - Data describing every diseased coral record from surveys in the Caribbean during 2012 (Contagious coral diseases project) (Are coral diseases contagious?)

Data describing every diseased coral record from surveys in the Caribbean during 2012 (Contagious coral diseases project)

cdm_data_type = Other
VARIABLES:
temp_level (unitless)
location (unitless)
reef (unitless)
site_number (unitless)
depth_max (Depth, meters)
meter (unitless)
genus (unitless)
species (unitless)
UIN (unitless)
sign_1 (unitless)
sign_2 (unitless)
sign_3 (unitless)
sign_4 (unitless)


[MarBio. 2016: calcification and biomass] - Calcification Rates and Biomass of 4 Coral Species, 2 Temperatures and 2 pCO2 Levels from Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_Corals project) (RUI: Ocean Acidification- Category 1- The effects of ocean acidification on the organismic biology and community ecology of corals, calcified algae, and coral reefs)

Area-normalized calcification (mg cm-2 d-1) and biomass normalized
calcification (mg mg-1) for Pocillopora meandrina, massive Porites spp.,
Acropora pulchra and Millepora platyphylla, as a function of pCO2 (408
\u00b5atm versus 913 \u00b5atm) and temperature (28.0\u00b0C and 30.1\u00b0C),
collected in Moorea 2011.

Related Reference:
 Darren Brown, Peter J. Edmunds. Differences in the responses of three
scleractinians and the hydrocoral Millepora platyphylla to ocean
acidification. Marine Biology, 2016 (in press).

Related Dataset:
[MarBio. 2016: tank conditions](\\https://www.bco-dmo.org/dataset/641759\\)

cdm_data_type = Other
VARIABLES:
location (unitless)
latitude (degrees_north)
longitude (degrees_east)
species (unitless)
pCO2 (P CO2, unitless)
temp (Temperature, unitless)
tank (unitless)
treatment (unitless)
calcification (cm-2 day-1)
biomass (mg mg-1)


[MarBio. 2016: tank conditions] - Tank seawater conditions from Coral/Temperature/pCO2 Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_Corals project) (RUI: Ocean Acidification- Category 1- The effects of ocean acidification on the organismic biology and community ecology of corals, calcified algae, and coral reefs)

Summary of conditions in the eight tanks assigned randomly to create four
treatments of AT-ACO2.

Related Reference:
 Darren Brown, Peter J. Edmunds. Differences in the responses of three
scleractinians and the hydrocoral Millepora platyphylla to ocean
acidification. Marine Biology, 2016 (in press).

Related Dataset:
[MarBio. 2016: calcification and biomass](\\http://www.bco-
dmo.org/dataset/641479\\)

cdm_data_type = Other
VARIABLES:
location (unitless)
latitude (degrees_north)
longitude (degrees_east)
pCO2 (P CO2, unitless)
tank (unitless)
temp (Temperature, unitless)
treatment (unitless)
pCO2_uatm (P CO2 Uatm, micro-atmospheres)


[Mariana Back-arc Macrofauna 2014] - Macrofauna collected on colonization panels at Snail Vent Field on the Mariana Back-arc in 2014 (RAPID: Larval Abundance, Behavior and Dispersal at Deep-sea Hydrothermal Vents in the Southern Mariana Trough)

This dataset indicates organisms, identified to varying levels of taxonomic granularity, present on colonization surfaces deployed at deep-sea vents in the West Pacific.

cdm_data_type = Other
VARIABLES:
occurrenceID (Occurrence ID, none)
kingdom (none)
phylum (none)
scientificName (Scientific Name, none)
scientificNameID (Scientific Name ID, none)
taxonRank (Taxon Rank, none)
identificationRemarks (Identification Remarks, none)
identificationQualifier (Identification Qualifier, none)
occurrenceStatus (Occurrence Status, none)
basisOfRecord (Basis Of Record, none)
eventDate (Event Date, none)
longitude (degrees_east)
latitude (degrees_north)
depth (Maximum Depth In Meters, m)
minimumDepthInMeters (Minimum Depth In Meters, meters)
waterBody (Water Body, none)
locality (none)
countryCode (Country Code, none)
identifiedBy (Identified By, none)
associatedMedia (Associated Media, none)
total_sorted (individuals)
associatedSequences (Associated Sequences, none)


[Mark Recapture] - Mark recapture data for introduced crab in Seadrift Lagoon 2011-2018 (RAPID: A rare opportunity to examine overcompensation resulting from intensive harvest of an introduced predator)

Mark recapture data for introduced crab in Seadrift Lagoon (Central California coast, shallow subtidal (<3 m depth)) in 2015.

cdm_data_type = Other
VARIABLES:
lagoon (unitless)
latitude (degrees_north)
longitude (degrees_east)
date (unitless)
site (unitless)
size (millimeters (mm))
sex (unitless)
grav (unitless)
injury (unitless)
recap_mark (unitless)
species_code (unitless)
species (unitless)


[Marsh consumer diversity effects on multifunctionality] - Marsh consumer diversity effects on multifunctionality from experiments conducted by manipulating the presence of crabs, snails, and fungus in Spartina plots on Sapelo Island, Georgia ( Small Grazers, Multiple Stressors and the Proliferation of Fungal Disease in Marine Plant Ecosystems)

The effect of consumer diversity on the ecosystem functioning of salt marshes on Sapelo Island, Georgia.

cdm_data_type = Other
VARIABLES:
treat (S = snails present,C = crabs present,F = fungus present, NS = no snails,etc)
rep (1-8, number of repetition)
live (g of Spartina/ sq meter)
dead (g of Spartina/ sq meter)
g_lost (g of Spartina decomposed over 1 month)
perco (Liters of water absorbed per hour)
multi (mean % functioning of all ecosystem functions per plot)
no_cons (no between 1 and 3)


[Marsh Pond noble gases] - Noble gas concentrations and saturations from Marsh Pond in Massachusetts, USA from 2014. (Eutrophication Effects on Sediment Metabolism and Benthic Algal-bacterial Coupling: An Application of Novel Techniques in a LTER Estuary)

Noble gas concentrations and saturations from Marsh Pond in Massachusetts, USA from 2014.

cdm_data_type = Other
VARIABLES:
date (unitless)
time2 (Time, unitless)
time (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
He (micromoles per kilogram (umol/Kg))
He_stdev (umol/Kg)
He_sat (umol/Kg)
He_sat_stdev (umol/Kg)
dHe (D He, percent)
dHe_stdev (D He Stdev, percent)
He_flag (unitless)
Ne (umol/Kg)
Ne_stdev (umol/Kg)
Ne_sat (umol/Kg)
Ne_sat_stdev (umol/Kg)
dNe (D Ne, percent)
dNe_stdev (D Ne Stdev, percent)
Ne_flag (unitless)
Ar (umol/Kg)
Ar_stdev (umol/Kg)
Ar_sat (umol/Kg)
Ar_sat_stdev (umol/Kg)
dAr (D Ar, percent)
dAr_stdev (D Ar Stdev, percent)
Ar_flag (unitless)
Kr (umol/Kg)
... (14 more variables)


[Mask R-CNN and U-Net models and reef halo ouput calculations] - Mask R-CNN and U-Net model and output of coral reef halo measurements based on global multispectral satellite imagery (CAREER: Decoding seascape-scale vegetation patterns on coral reefs to understand ecosystem health: Integrating research and education from organismal to planetary scales)

Reef halos are rings of bare sand that surround coral reef patches. Halo formation is likely to be the indirectly result of interactions between relatively healthy predator and herbivore populations. To reduce the risk of predation, herbivores preferentially graze close to the safety of the reef, potentially affecting the presence and size of the halo. Reef halos are readily visible in remotely sensed imagery, and monitoring their presence and changes in size may therefore offer clues as to how predator and herbivore populations are faring. However, manually identifying and measuring halos is slow and limits the spatial and temporal scope of studies. There are currently no existing tools to automatically identify single reef halos and measure their size to speed up their identification and improve our ability to quantify their variability over space and time.

Here we present a set of convolutional neural networks aimed at identifying and measuring reef halos from very high-resolution satellite imagery (i.e., ∼0.6 m spatial resolution). We show that deep learning algorithms can successfully detect and measure reef halos with a high degree of accuracy (F1 = 0.824), thereby enabling faster, more accurate spatio-temporal monitoring of halo size. This tool will aid in the global study of reef halos, and potentially coral reef ecosystem monitoring, by facilitating our discovery of the ecological dynamics underlying reef halo presence and variability.

cdm_data_type = Other
VARIABLES:
AOI (unitless)
object_id (unitless)
hArea_m2 (square meter (m2))
rArea_m2 (square meter (m2))
log_hArea_m2 (square meter (m2))
log_rArea_m2 (square meter (m2))


[Maximum distances at which Stegastes planiforms attacked invasive lionfish] - Experimental results describing the maximum distances at which Stegastes planiforms attacked Pterois volitans and native predators in the Cayman Islands and the Bahamas during 2011 (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Experimental results describing the maximum distances at which Stegastes planiforms attacked Pterois volitans and native predators in the Cayman Islands and the Bahamas during 2011

cdm_data_type = Other
VARIABLES:
location (unitless)
latitude (degrees_north)
longitude (degrees_east)
bottle_treatment (unitless)
habitat (unitless)
damsel_number (unitless)
depth (m)
damsel_size (unitless)
distance (centimeters)


[MBRS coral survey 2014] - Coral species identifications, size, condition from the Belize Mesoamerican Barrier Reef System (MBRS), November 2014 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

This dataset contains coral species identifications, size, and condition from the Belize Mesoamerican Barrier Reef System (MBRS), November 2014. These data were reported in Baumann et al. (2016), https://doi.org/10.1371/journal.pone.0162098.

cdm_data_type = Other
VARIABLES:
method (unitless)
site (unitless)
type (unitless)
lat_code (unitless)
lat_location (Latitude, unitless)
transect (unitless)
diver (unitless)
life_hist (unitless)
spp_code (unitless)
percent_of_cover (unitless)
length (centimeters)
width (centimeters)
area (centimeters)
pale (unitless)
bleached (unitless)
total_pb (unitless)
percent_pb (unitless)
new (unitless)
trans (unitless)
old (unitless)
percent_mort (unitless)
disease (corals)
percentdisease (unitless)


[MBRS in situ temperature] - In situ temperature and light time-series from HOBO data loggers, Belize Mesoamerican Barrier Reef System (MBRS), Nov. 2014 - Oct. 2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

This dataset contains temperature and light data obtained from in situ HOBO V2 data loggers situated at each study site. These data were used in a coral study in Baumann et al. (2016) DOI: 10.1371/journal.pone.0162098.

cdm_data_type = Other
VARIABLES:
site (unitless)
latitude (degrees_north)
longitude (degrees_east)
type (unitless)
description (unitless)
time (ISO Date Time Local, seconds since 1970-01-01T00:00:00Z)
date (unitless)
month (unitless)
day (unitless)
year (unitless)
time2 (Time, unitless)
hobo_logger_temp (degrees Celsius)
hobo_pendant_temp (degrees Celsius)
light (lumens/ft2)


[MBRS reef sites] - Site locations for coral thermal response study at Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

Site locations for coral thermal response study at Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015.

cdm_data_type = Other
VARIABLES:
site (unitless)
description (unitless)
latitude (degrees_north)
longitude (degrees_east)
comments (unitless)


[MBRS SST 2003-2015: MUR and HOBO] - Sea surface temperature data for coral Symbiodinium study from in situ data loggers and JPL MUR data, Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

This dataset contains sea surface temperature data obtained from daily 1-km horizontal resolution SST estimates acquired from the Jet Propulsion Laboratory\u2019s Multi-Scale High Resolution SST (JPL MUR SST) records via the Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the NASA JPL, Pasadena, CA (https://podaac.jpl.nasa.gov) as well as in situ temperature from HOBO data loggers.

cdm_data_type = Other
VARIABLES:
site (unitless)
transect (unitless)
type (unitless)
latitude (degrees_north)
longitude (degrees_east)
year (unitless)
date (unitless)
month (unitless)
day (unitless)
MURtemp (degrees Celsius)
MURsd (degrees Celsius)
HOBOtemp (degrees Celsius)
HOBOsd (degrees Celsius)


[MBRS SST 2003-2015: MUR] - Sea surface temperature JPL MUR data, Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

This dataset contains sea surface temperature data obtained from daily 1-km horizontal resolution SST estimates acquired from the Jet Propulsion Laboratory\u2019s Multi-Scale High Resolution SST (JPL MUR SST) records via the Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the NASA JPL, Pasadena, CA (https://podaac.jpl.nasa.gov).\r\n\r\nNOTE: Data from 2012 are given twice at each site; only the first set, along with the 2003-2011 data,  was used in the original analysis in Baumann et al (2016). The 2012-2015 data were only available following revision in the peer review process. It became useful for making comparisons between the in-situ data and satellite data.\r\n\r\nThese data were used in a coral study in: Baumann JH, Townsend JE, Courtney TA, Aichelman HE, Davies SW, Lima FP, et al. (2016) Temperature Regimes Impact Coral Assemblages along Environmental Gradients on Lagoonal Reefs in Belize. PLoS ONE 11(9): e0162098. https://doi.org/10.1371/journal.pone.0162098.

cdm_data_type = Other
VARIABLES:
site (unitless)
lat (Latitude, decimal degrees)
longitude (degrees_east)
date (unitless)
temp (Temperature, degrees Celsius)
temp_se (degrees Celsius)


[MBRS Symbiodinium OTU] - OTU molecular abundances for coral Symbiodinium, Belize Mesoamerican Barrier Reef System (MBRS), 2014-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)

This dataset contains relative abundance (counts?) of operational taxonomic units (OTUs) from Sumbiodinium samples collected from three coral species (S. siderea, S. radians, and P. strigosa) at nine sites across four latitudes along the Belize MBRS in 2014 and 2015. These sites were previously characterized into three thermally distinct regimes (lowTP, modTP, highTP) and exhibited variations in coral species diversity and richness.

cdm_data_type = Other
VARIABLES:
species (unitless)
species_code (unitless)
Sample (unitless)
site (unitless)
thermal_type (unitless)
lat_location (Latitude, unitless)
illumina_run (unitless)
otu_diversity (OTU's)
C1_I (unitless)
B1_I (unitless)
C1_II (unitless)
C1_III (unitless)
D1a (unitless)
B1_II (unitless)
G3 (unitless)
A4a (unitless)
B_BG (unitless)
C3 (unitless)


[mcm_ps] - Bedford Institute of Oceanography Moored Current Meter Data deployed during cruises to the Eastern Gulf of Maine/Scotian Shelf from Canadian ships R/V Parizeau and R/V Hudson from 1993-1999 as part of the U.S. GLOBEC Georges Bank project (GB project) (U.S. GLOBEC Georges Bank)

Bedford Institute of Oceanography Moored Current Meter Data deployed during cruises to the Eastern Gulf of Maine/Scotian Shelf from Canadian ships R/V Parizeau and R/V Hudson from 1993-1999 as part of the U.S. GLOBEC Georges Bank project (GB project)

cdm_data_type = Other
VARIABLES:
cruiseid
year
site
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth (m)
yrday_utc (fractional day)
temp (Temperature, degrees C)
sal
curr_dir_abs (degrees true)
curr_speed_abs (centimeters/second)


[McMurdo Sound acoustic backscatter krill and silverfish] - Acoustic backscatter from krill and silverfish in McMurdo Sound from 2014-2015 (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

Krill and fish were sampled acoustically and visually beneath the fast ice
using the tethered SCINI ROV, which was deployed and operated through a 25 cm
diameter hole drilled through the sea ice. SCINI contained cameras and
thrusters, and towed a sensor package consisting of a WET Labs fluorometer
(ECO-AFL/FL) and a single-beam Biosonics 120 kHz DT-X echosounder. Visual
targets were identified to the lowest taxon possible; these observations were
used primarily to verify classification of acoustic signals. The echosounder
operated at a nominal ping rate of 1 ping s-1; however, this rate was
occasionally adjusted if false bottom signals were observed. The general
profile of a dive included a surface transect of ~300 m horizontal distance,
where the acoustic transducer faced downward, and also a dive to ~120 m if
conditions allowed. Echogram data were saved to a depth of 500 m, and
background noise was removed. Given the effective range of the transducer of
approximately 100 m (resolving -80 dB targets), surveys characterized the
upper 200 m of the water column.

cdm_data_type = Other
VARIABLES:
group (unitless)
sitenum (unitless)
bin_depth (meters (m))
depth (m)
sv_mean (per meter (m-1))


[McMurdo Sound acoustic backscatter site] - Acoustic backscatter from sites in McMurdo Sound from 2014-2015 (McMurdo Predator Prey project) (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

Krill and fish were sampled acoustically and visually beneath the fast ice
using the tethered SCINI ROV, which was deployed and operated through a 25 cm
diameter hole drilled through the sea ice. SCINI contained cameras and
thrusters, and towed a sensor package consisting of a WET Labs fluorometer
(ECO-AFL/FL) and a single-beam Biosonics 120 kHz DT-X echosounder. Visual
targets were identified to the lowest taxon possible; these observations were
used primarily to verify classification of acoustic signals. The echosounder
operated at a nominal ping rate of 1 ping s-1; however, this rate was
occasionally adjusted if false bottom signals were observed. The general
profile of a dive included a surface transect of ~300 m horizontal distance,
where the acoustic transducer faced downward, and also a dive to ~120 m if
conditions allowed. Echogram data were saved to a depth of 500 m, and
background noise was removed. Given the effective range of the transducer of
approximately 100 m (resolving -80 dB targets), surveys characterized the
upper 200 m of the water column.

cdm_data_type = Other
VARIABLES:
site (unitless)
sitenum (unitless)
datetime (unitless)
Group (unitless)
latitude (degrees_north)
longitude (degrees_east)
dn (days)
sv_linear_sum (m^-1)
n (unitless)
effort (unitess)
sv_mean (decibel at reference level 1 meter (dB re 1 m-1))
depth (m)
sv_mean_effort (decibel at reference level 1 meter (dB re 1 m-1))


[McMurdo Sound chlorophyll] - Chlorophyll data from McMurdo Sound, Antarctica from 2012 to 2015 (McMurdo Predator Prey project) (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

This dataset includes chlorophyll, phaeopigments, depth, lat, lon, and station
from McMurdo Sound, Antarctica collected between the austral years 2012/2013
and 2014/2015.

cdm_data_type = Other
VARIABLES:
station (unitless)
date (unitless)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
chl (micrograms per liter (ug/L))
phaeo (micrograms per liter (ug/L))


[McMurdo Sound CTDs] - CTD data from McMurdo Sound, Antarctica from 2012 to 2015  (McMurdo Predator Prey project) (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

This dataset includes temperature, salinity, conductivity, oxygen, depth,
sound velocity, chlorophyll fluorescence, and pH measurements from McMurdo
Sound, Antarctica. \u00a0Data were collected by CTD, fluorescence, and pH
sensors during austral years 2012/2013 and 2014/2015

cdm_data_type = Other
VARIABLES:
austral_year (unitless)
station (unitless)
cast (unitless)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
time (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)
date_local (unitless)
time_local (unitless)
time_zone_offset (unitless)
temp (Temperature, degrees Celsius)
potemp (degrees Celsius)
sal (practical salinity unit (PSU))
cond_S_m (Siemens per meter (S/m))
cond_mS_cm (Cond M S Cm, millisiemens per centimeter (mS/cm))
density (kilograms per meter cubed (kg/m^3))
sigma_theta (Sea Water Sigma Theta, kilograms per meters cubed)
sigma_t (kilograms per meters cubed)
press (decibars (db))
O2_mL_L (O2 M L L, milliliters per liter (ml/l))
O2_mg_L (milligrams per liter (mg/l))
O2_umol_kg (micromoles per kilogram (umol/kg))
O2_sat (percent)
fluor (milligrams per meter cubed (mg/m^3))
... (8 more variables)


[McMurdo Sound icebreaker dates and ice edge distance] - Icebreaker dates and ice edge distance in McMurdo Sound, Antarctica from austral years 1956/1957 to 2014/2015 (McMurdo Predator Prey project) (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

This dataset contains dates of icebreaker start and arrival at McMurdo Station
in McMurdo Sound, Antarctica between austral years 1956/1957 and 2014/2015.
\u00a0It also includes the distance\u00a0between the fast ice edge and McMurdo
Station on the date of ship arrival at the fast ice edge.

cdm_data_type = Other
VARIABLES:
latitude (degrees_north)
longitude (degrees_east)
austral_year (unitless)
start_year (unitless)
start_month (unitless)
start_day (unitless)
arrival_year (unitless)
arrival_month (unitless)
arrival_day (unitless)
edge_distance (kilometers)
ships (unitless)


[McMurdo Sound sea ice movement dates] - Dates of sea ice movement and sea ice distance in McMurdo Sound, Antarctica from MODIS and SSMI imagery between 1978-2015 (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

This dataset contains dates relevant to sea ice movement including dates of initial ice retreat, final ice retreat, ice minimum, general ice minimum, ice minimum for the west of McMurdo Sound, ice minimum for the east of McMurdo Sound, and refreeze start.  It also includes the minimum distance to the ice edge from McMurdo Station.  \r\n\r\nDates were derived from Moderate-resolution Imaging Spectroradiometers (MODIS) collected between 2003 and 2015 and Scanning Multichannel Microwave Radiometer and Special Sensor Microwave Imager-family passive microwave sensors (SSM/I) imagery collected between 1978 and 2015.

cdm_data_type = Other
VARIABLES:
image_source (unitless)
latitude (degrees_north)
longitude (degrees_east)
austral_year (unitless)
retreat_initial_year (unitless)
retreat_initial_month (unitless)
retreat_initial_day (unitless)
retreat_final_year (unitless)
retreat_final_month (unitless)
retreat_final_day (unitless)
ice_min_year (unitless)
ice_min_month (unitless)
ice_min_day (unitless)
edge_dist_min (kilometers)
ice_min_west_year (unitless)
ice_min_west_month (unitless)
ice_min_west_day (unitless)
ice_min_east_year (unitless)
ice_min_east_month (unitless)
ice_min_east_day (unitless)
refreeze_begin_year (unitless)
refreeze_begin_month (unitless)
refreeze_begin_day (unitless)


[McMurdo Sound sea ice thickness] - Sea ice parameters near McMurdo Station, Antarctica from 1986 to 2013 (Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound)

This dataset contains\u00a0sea ice thickness, sea ice temperature, and air
temperature at the sea ice runway near McMurdo Station, Antarctica, from
1986-2013.\u00a0

cdm_data_type = Other
VARIABLES:
latitude (degrees_north)
longitude (degrees_east)
date (unitless)
year (unitless)
month (unitless)
day (unitless)
ice_thickness_median (centimeters)
ice_temp_median (degrees Celsius)
air_temp (degrees Celsius)


This dataset contains sea ice thickness, sea ice temperature, and air temperature at the sea ice runway near McMurdo Station, Antarctica, from 1986-2013.

cdm_data_type = Other
VARIABLES:
lat_approx (degrees_north)
longitude (Lon_approx, degrees_east)
date (unitless)
year (unitless)
month (unitless)
day (unitless)
ice_thickness_median (centimeters)
ice_temp_median (degrees Celsius)
air_temp (degrees Celsius)


[MCR_HIGH RES_DOC] - High Resolution sampling of dissolved organic matter (DOM) around Mo'orea coupled with macroalgal collections (Coral DOM2 project) (Collaborative Research: Dissolved organic matter feedbacks in coral reef resilience: The genomic & geochemical basis for microbial modulation of algal phase shifts)

Data was collected here in collaboration with the MCR-LTER group in July 2016. Dissolved organic carbon (DOC) samples were collected for us during an existing field project (Turbinaria tissue collections). The primary goal was to collect water from as many of ~180 Lagoon sites as possible to obtain high-resolution surface DOC dataset. This dataset includes dissolved organic carbon (DOC) measurements around the periphery of Mo'orea Island from July 26 to September 1, 2016. Samples were taken at 1-meter depth.

cdm_data_type = Other
VARIABLES:
SAMPLE_ID (unitless)
CRUISE (unitless)
STATION (unitless)
TYPE (unitless)
time (ISO Date Time Local, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
DOC_FINAL_uM (DOC FINAL U M, Micromol Carbon)
DOC_SD (Micromol Carbon)
FLAG (unitless)


[MCTD Lake Michigan 2017, 2018 & 2019] - Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019. (Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders)

Turbulent microstructure profiles were collected near Milwaukee, WI, during 2018 between April 5 \u2013 April 20, 2018 at a 55m depth site. Microstructure measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.), which measures velocity shear, temperature, turbidity, and chlorophyll concentrations. High resolution velocity shear (512 Hz) measurements were used to estimate turbulent kinetic energy dissipation throughout the water column. Microstructure profiles were collected during fair weather conditions on April 5th, 12th, and 20th.

cdm_data_type = Other
VARIABLES:
profile_name (unitless)
latitude (degrees_north)
longitude (degrees_east)
DOY_GMT (unitless)
time (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)
pressure (decibar (dbar))
temp (Temperature, degrees Celsius)
S2 (1/s2)
turb (FTU)
chlor (ppb)
dissipation (Watts per kilogram (W/kg))


[Mean Plot-Level Responses] - Mean plot-level responses observed in an experiment conducted at Zeke's Island National Estuarine Research Reserve where abundance of the seaweed Gracilaria vermiculophylla was manipulated to assess impact on multiple ecosystem functions ( Small Grazers, Multiple Stressors and the Proliferation of Fungal Disease in Marine Plant Ecosystems)

These data represent the time-averaged value of each variable measured monthly in each plot over the course of a 10 month experiment carried out on intertidal mud and sandflats located within the Zeke\u2019s Island National Estuarine Research Reserve (33.95 N, 77.94 W), North Carolina, USA.

cdm_data_type = Other
VARIABLES:
Plot (unitless)
TrtPeg (Trt Peg, unitless (count))
Gcvr (unitless (percent))
Epi (number per square meter (# m^-2))
EpiRich (Epi Rich, taxa per square meter (taxa m^-2))
Dsln (grams per day (g d^-1))
DslnFlip (Dsln Flip, grams per day (g d^-1))
Sed (centimeters per month (cm mo^-1))
Nrsy (number per square meter (# m^-2))
NrsyRich (Nrsy Rich, taxa per square meter (taxa m^-2))
Dcmp (grams per month  (g mo^-1))
Infa_sr (number per liter (# L^-1))
InfaRich_sr (Infa Rich Sr, taxa per liter (taxa L^-1))
Rays_sr (number per square meter per day (# m^-2 d^-1))
RaysFlip_sr (Rays Flip Sr, number per square meter per day (# m^-2 d^-1))
Wfwl_sr (number per square meter per hour (# m^-2 h^-1))


[Measurements of treatment tub seawater conditions: pH and total alkalinity] - pH and total alkalinity measurements of treatment tub seawater during lab experiments conducted in spring 2022. (Influence of environmental pH variability and thermal sensitivity on the resilience of reef-building corals to acidification stress)

Ocean acidification (OA) resulting from anthropogenic CO2 emissions is impairing the reproduction of marine organisms. While parental exposure to OA can protect offspring via carryover effects, this phenomenon is poorly understood in many marine invertebrate taxa. We examined how parental exposure to acidified (pH 7.40) versus ambient (pH 7.72) seawater influenced reproduction and offspring performance across six gametogenic cycles (13 weeks) in the estuarine sea anemone Nematostella vectensis. This dataset contains data resulting from measurements of treatment tub seawater conditions, including pH and total alkalinity.

cdm_data_type = Other
VARIABLES:
Date (unitless)
Treatment (unitless)
pH (Arbitrary on pH scale)
mV (millivolts (mV))
Salinity (unitless)
Temperature (Degrees Celsius)
TA_1 (umol/kg)
TA_2 (umol/kg)
TA_average (umol/kg)
TA (mol/kg)
Alkalinity (mol/kg*10^-3)


[Megafauna counts by taxon in image surveys at inactive sulfides on the East Pacific Rise] - Megafauna counts by taxon in images collected during three surveys (December 25, 2019, April 7 and 9, 2021) with deep-submergence vehicles at inactive sulfide mounds on the East Pacific Rise. (Collaborative Research: Life after Death: Do Inactive Sulfides Fuel a Unique Ecosystem at the Deep Seafloor?)

This dataset includes counts by taxon for megafauna in images collected during surveys with deep-submergence vehicles at inactive sulfide mounds near the 9 50' N hydrothermal vent field on the East Pacific Rise. Images were collected with a down-looking digital still camera. We provide image areas for estimating megafauna density (counts per area of seafloor). Here we provide data from three surveys: one during HOV Alvin Dive 5044 at Lucky's Mound on 25 December 2019 on cruise AT42-21 and two during ROV Jason II Dives 1309 and 1311, on the oceanic rise (between Lucky's Mound and Sentry Spire) on 7 April 2021 and at Sentry Spire on 9 April 2021, respectively, on cruise RR2102. Megafauna were manually annotated to morphotype using ImageJ software. Morphotypes were identified to the lowest taxonomic level and assigned to a feeding mode. This dataset is provided in two formats: long-format comma-separated variable (csv) file and wide-format Excel (xlsx) file. This dataset is analyzed in a manuscript by Meneses et al. (2024).

cdm_data_type = Other
VARIABLES:
File_Name (unitless)
Site (unitless)
Habitat (unitless)
Corrected_Area_m2 (meters squared)
verbatimIdentification (unitless)
Feeding_Mode (unitless)
individualCount (integer count)
WoRMS_scientificName (unitless)
WoRMS_scientificNameID (unitless)
eventDate (unitless)
latitude (Decimallatitude, degrees_north)
longitude (Decimallongitude, degrees_east)
depth (Depth_m, m)
Vehicle_Altitude_m (meters)
AngleCategory (unitless)
Adjustment_Value (unitless)
Useable_Proportion_of_Image (unitless)


[Mesocosm CB 2021 Light and Temperature] - Light and temperature data for mesocosm incubation experiment simulating a phytoplankton bloom in Chesapeake Bay August 2021 (Marine Diatom-Parasite Relationships in Upwelling Systems)

A mesocosm experiment was performed in August 2021 on the R/V Hugh Sharp, cruise HRS2110, at a station near the mouth of Chesapeake Bay to simulate a phytoplankton bloom and to assess changes in assemblage and biogeochemical processes while excluding changes due to advection. Three 20-L carboys were filled with filtered bay water, inoculated with surface water and sampled daily for a week. Nutrient concentrations, nitrate and bicarbonate uptake rates, pigment concentrations and samples for 18S rRNA gene sequence analysis were collected once or more times per day. 15NO3- and H13CO3- tracer incubations were performed alongside pigment and DNA sampling to compare temporal trends in community composition and primary productivity (nitrogen (N) and carbon (C) transport rates). These results address the nature of phytoplankton blooms, and present a more complex relationship between bloom progression and phytoplankton diversity that usually assumed or detected by traditional methods. This dataset contains the light and temperature data logged for the three replicate mesocosms over the course of the simulated bloom. These data were collected by Jenna Lee from Princeton University.

cdm_data_type = Other
VARIABLES:
time (Datetime, seconds since 1970-01-01T00:00:00Z)
Temp (degrees Celsius)
Lux (lux (lx))
Logger (unitless)


[Mesocosm CB 2021 Nutrients] - Nutrient data for mesocosm incubation experiment simulating a phytoplankton bloom in Chesapeake Bay August 2021 (Marine Diatom-Parasite Relationships in Upwelling Systems)

A mesocosm experiment was performed in August 2021 on the R/V Hugh Sharp, cruise HRS2110, at a station near the mouth of Chesapeake Bay to simulate a phytoplankton bloom and to assess changes in assemblage and biogeochemical processes while excluding changes due to advection. Three 20-L carboys were filled with filtered bay water, inoculated with surface water and sampled daily for a week. Nutrient concentrations, nitrate and bicarbonate uptake rates, pigment concentrations and samples for 18S rRNA gene sequence analysis were collected once or more times per day. 15NO3- and H13CO3- tracer incubations were performed alongside pigment and DNA sampling to compare temporal trends in community composition and primary productivity (nitrogen (N) and carbon (C) transport rates). These results address the nature of phytoplankton blooms, and present a more complex relationship between bloom progression and phytoplankton diversity that usually assumed or detected by traditional methods. This dataset contains the nutrient data for the three replicate mesocosms over the course of the simulated bloom. These data were collected by Jenna Lee from Princeton University.

cdm_data_type = Other
VARIABLES:
Samp_No (unitless)
Carboy (unitless)
Rep (unitless)
Date_Local (unitless)
Time_Local (unitless)
time (Iso_datetime_utc, seconds since 1970-01-01T00:00:00Z)
Nitrite (micromolar (µM))
Nitrate (micromolar (µM))
Phosphate (micromolar (µM))
Silicate (micromolar (µM))
Notes (unitless)


[Mesocosm CB 2021 Pigments] - Pigment concentration data for mesocosm incubation experiment simulating a phytoplankton bloom in Chesapeake Bay August 2021 (Marine Diatom-Parasite Relationships in Upwelling Systems)

A mesocosm experiment was performed in August 2021 on the R/V Hugh Sharp, cruise HRS2110, at a station near the mouth of Chesapeake Bay to simulate a phytoplankton bloom and to assess changes in assemblage and biogeochemical processes while excluding changes due to advection. Three 20-L carboys were filled with filtered bay water, inoculated with surface water and sampled daily for a week. Nutrient concentrations, nitrate and bicarbonate uptake rates, pigment concentrations and samples for 18S rRNA gene sequence analysis were collected once or more times per day. 15NO3- and H13CO3- tracer incubations were performed alongside pigment and DNA sampling to compare temporal trends in community composition and primary productivity (nitrogen (N) and carbon (C) transport rates). These results address the nature of phytoplankton blooms, and present a more complex relationship between bloom progression and phytoplankton diversity that usually assumed or detected by traditional methods. This dataset contains the measured pigment concentrations for the three replicate mesocosms over the course of the simulated bloom. These data were collected by Jenna Lee from Princeton University.

cdm_data_type = Other
VARIABLES:
Samp_No (unitless)
Carboy (unitless)
Rep (unitless)
Day (day)
Date_Local (unitless)
Time_Local_Collected (unitless)
Time_Local_Filtered (unitless)
time (Iso_datetime_utc_collection, seconds since 1970-01-01T00:00:00Z)
Samp_Vol (liters)
Chl_c1c2 (micrograms of pigment  per liter (µg L-1))
Perid (micrograms of pigment  per liter (µg L-1))
ButFuc_19 (micrograms of pigment  per liter (µg L-1))
Fuco (micrograms of pigment  per liter (µg L-1))
HexFuc_19 (micrograms of pigment  per liter (µg L-1))
Zeax (micrograms of pigment  per liter (µg L-1))
... (4 more variables)


[Mesocosm CB 2021 Uptake Rates] - Nitrogen and carbon uptake rates for mesocosm incubation experiment simulating a phytoplankton bloom in Chesapeake Bay August 2021 (Marine Diatom-Parasite Relationships in Upwelling Systems)

A mesocosm experiment was performed in August 2021 on the R/V Hugh Sharp, cruise HRS2110, at a station near the mouth of Chesapeake Bay to simulate a phytoplankton bloom and to assess changes in assemblage and biogeochemical processes while excluding changes due to advection. Three 20-L carboys were filled with filtered bay water, inoculated with surface water and sampled daily for a week. Nutrient concentrations, nitrate and bicarbonate uptake rates, pigment concentrations and samples for 18S rRNA gene sequence analysis were collected once or more times per day. 15NO3- and H13CO3- tracer incubations were performed alongside pigment and DNA sampling to compare temporal trends in community composition and primary productivity (nitrogen (N) and carbon (C) transport rates). These results address the nature of phytoplankton blooms, and present a more complex relationship between bloom progression and phytoplankton diversity that usually assumed or detected by traditional methods. This dataset contains the measured nitrogen and carbon uptake rates for the three replicate mesocosms over the course of the simulated bloom. These data were collected by Jenna Lee from Princeton University.

cdm_data_type = Other
VARIABLES:
Samp_ID (unitless)
Carboy (unitless)
Rep (unitless)
Date_Local (unitless)
Tracer_Vol_13C (milliliters (mL))
Tracer_Vol_15N (milliliters (mL))
Time_Local_Collected (unitless)
Time_Local_Added (unitless)
Time_Local_Filtered (unitless)
Samp_Vol (milliliters)
Rinse (unitless)
POC (micromolar (µM))
PON (micromolar (µM))
C_transport (micromolar per day (µM d-1)))
N_transport (micromolar per day (µM d-1)))
Notes (unitless)
time (Iso_datetime_utc_collected, seconds since 1970-01-01T00:00:00Z)


[Mesocosm Growth Data] - Size of Bugula neritina colonies with and without symbiont grown at different temperatures in laboratory mesocosms at Georgia Tech (Biogeography of a marine defensive microbial symbiont: relative importance of host defense vs. abiotic factors)

Size of Bugula neritina colonies with and without symbiont grown at different temperatures in laboratory mesocosms at Georgia Tech.

cdm_data_type = Other
VARIABLES:
temperature (degrees Celsius)
colony_num (unitless)
genotype (unitless)
cont_avg (unitless)
cont_sd (unitless)
cont_N (unitless)
treat_avg (unitless)
treat_sd (unitless)
treat_N (unitless)


[mesozoo biomass by size class] - Mesozooplankton community biomass (wet and dry weight) for 5 size classes and total for samples collected by ring net tows on R/V Melville cruise MV1008 in the Costa Rica Dome in 2010 (CRD FLUZiE project) (Costa Rica Dome FLUx and Zinc Experiments)

Mesozooplankton community biomass (wet weight and dry weight), for 5 size classes (0.2-0.5, 0.5-1, 1-2, 2-5, and >5 mm) and total. Samples were collected during ring net tows on the MV1008 cruise in the Costa Rica Dome (CRD) region of the Eastern Tropical Pacific Ocean.

cdm_data_type = Other
VARIABLES:
event (integer)
tow (integer)
cycle (text)
time_of_day (code)
date_local (unitless)
time_local (HHMM)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
size_class (millimeters (mm))
dry_biomass (grams per square meter (g m-2))
wet_biomass (grams per square meter (g m-2))


[mesozoo grazing by size class] - Mesozooplankton community grazing for 5 size classes and total for samples collected by ring net tows on R/V Melville cruise MV1008 in the Costa Rica Dome in 2010 (CRD FLUZiE project) (Costa Rica Dome FLUx and Zinc Experiments)

Mesozooplankton community grazing, expressed as ug pigment m-2 h-1, for 5 size classes (2-0.5, 0.5-1, 1-2, 2-5, and >5 mm) and total. Samples were collected during ring net tows on the MV1008 cruise in the Costa Rica Dome (CRD) region of the Eastern Tropical Pacific Ocean.

cdm_data_type = Other
VARIABLES:
event (integer)
tow (integer)
cycle (text)
time_of_day (code)
date_local (unitless)
time_local (HHMM)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
size_class (millimeters (mm))
grazing_rate (micrograms chlorophyll-a equivalents per square meter per hour (ug Chl a equiv m-2 h -1))


[mesozooplankton biomass] - Mesozooplankton biomass from MOCNESS tows collected during R/V Oceanus cruises OC415-01, OC415-03, OC404-01, OC404-04 in the Sargasso Sea, 2004-2005 (EDDIES project) (Eddies Dynamics, Mixing, Export, and Species composition)

Zooplankton biomass estimates were determined from 1 m^2, 150 micron mesh
MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System) tows.
The following discrete depth intervals were sampled on the upcast: 0-50,
50-100, 100-150, 150-200, 200-300, 300-400, 400-500, 500-600, and 600-700 m.
Generally paired tows during the day (9:30-15:00 local time) and night
(21:30-03:00) were performed at each station. A single tow generaly covered
5-15 km.\u00a0 The nominal position (lat_n and lon_n) for each tow is the
position at the mid depth 200-300m sampling interval.\u00a0 Table 1 ([pg 1362
PDF](\\http://ocb.whoi.edu/EDDIES/PI-
NOTES/Goldthwait_Steinberg_2008_Table1.pdf\\)) of Goldthwait and Steinberg
(2008) is a sequential list of all MOCNESS mesozooplankton tows and includes
eddy identification number and location.

Each sample was size-fractionated using nested sieves of 0.15 mm, 0.5 mm, 1
mm, 2mm, and 5 mm mesh. Zooplankton in each size class were transferred onto
pre-weighed 0.15 mm nitex mesh filters and rinsed with deionized water.
Samples were then dried for 24 hours at 60 degrees C and weighed.

Data were prepared by Sarah Goldthwait of Humboldt State University
([https://fresca.calstate.edu/faculty/98](\\https://fresca.calstate.edu/faculty/98\\))

Publication: Goldthwait, S. and D.K. Steinberg. 2008. Elevated Biomass of
Mesozooplankton and Enhanced Fecal Pellet Flux in Cold-Core and Mode-Water
Eddies in the Sargasso Sea. Deep Sea Research Part II: Topical Studies in
Oceanography 55: pp. 1360-1377. DOI:
[https://dx.doi.org/10.1016/j.dsr2.2008.01.003](\\https://dx.doi.org/10.1016/j.dsr2.2008.01.003\\)

cdm_data_type = Other
VARIABLES:
Cruise_ID (dimensionless)
date (unitless)
... (16 more variables)


[Metabarcoding zooplankton at station ALOHA: NCBI SRA accession numbers] - NCBI Sequence Read Archive (SRA) accession numbers for fastq sequence files for each zooplankton community sample (Plankton Population Genetics project) (Basin-scale genetics of marine zooplankton)

These data include sample information and accession links to sequence data at
The National Center for Biotechnology Information (NCBI) Sequence Read Archive
(SRA).

This data submission consists of metabarcoding data for the zooplankton
community in the epipelagic, mesopelagic and upper bathypelagic zones
(0-1500m) of the North Pacific Subtropical Gyre. The goal of this study was to
assess the hidden diversity present in zooplankton assemblages in midwaters,
and detect vertical gradients in species richness, depth distributions, and
community composition of the full zooplankton assemblage. Samples were
collected in June 2014 from Station ALOHA (22.75, -158) using a 1 meter square
Multiple Opening and Closing Nets and Environmental Sampling System (MOCNESS,
200um mesh), on R/V Falkor cruise FK140613. \u00a0Next generation sequence
data (Illumina MiSeq, V3 chemistry, 300-bp paired-end) of the zooplankton
assemblage derive from amplicons of the V1-V2 region of 18S rRNA (primers
described in Fonseca et al. 2010). The data includes sequences and read count
abundance information for molecular OTUs from both holoplanktonic and
meroplanktonic taxa

Related dataset containing OTU tables and fasta sequences (representative /
most abundance read for each OTU):
[Metabarcoding zooplankton at ](\\http://www.bco-
dmo.org/dataset/700279\\)[station](\\http://www.bco-
dmo.org/dataset/700279\\)[ ALOHA: OTU tables and ](\\http://www.bco-
dmo.org/dataset/700279\\)[fasta](\\http://www.bco-
dmo.org/dataset/700279\\)[ files](\\http://www.bco-
dmo.org/dataset/700279\\)

cdm_data_type = Other
VARIABLES:
analysis_name (unitless)
... (15 more variables)


[Metabarcoding zooplankton at station ALOHA: OTU tables and fasta files] - Metabarcoding zooplankton at station ALOHA: Operational taxonomic unit (OTU) tables and fasta files for representative sequences from each OTU (Plankton Population Genetics project) (Basin-scale genetics of marine zooplankton)

Metabarcoding data for the zooplankton community in the epipelagic, mesopelagic and upper bathypelagic zones (0-1500m) of the North Pacific Subtropical Gyre. The goal of this study was to assess the hidden diversity present in zooplankton assemblages in midwaters, and detect vertical gradients in species richness, depth distributions, and community composition of the full zooplankton assemblage. Samples were collected in June 2014 from Station ALOHA (22.75, -158) using a 1-meter square Multiple Opening and Closing Nets and Environmental Sampling System (MOCNESS, 200um mesh), on R/V Falkor cruise FK140613. Next generation sequence data (Illumina MiSeq, V3 chemistry, 300-bp paired-end) of the zooplankton assemblage derive from amplicons of the V1-V2 region of 18S rRNA (primers described in Fonseca et al. 2010). The data includes sequences and read count abundance information for molecular OTUs from both holoplanktonic and meroplanktonic taxa.  All results derive from analyses in mothur v1.36.1 (Schloss et al. 2009, Kozich et al. 2013).

cdm_data_type = Other
VARIABLES:
analysis_name (unitless)
latitude (degrees_north)
longitude (degrees_east)
analysis_description (unitless)
OTU_ID (unitless)
FA3_N1_SF1 (per OTU)
FA3_N1_SF2 (per OTU)
FA3_N1_SF3 (per OTU)
FA3_N2_SF1 (per OTU)
FA3_N2_SF2 (per OTU)
FA3_N2_SF3 (per OTU)
FA3_N3_SF1 (per OTU)
FA3_N3_SF2 (per OTU)
FA3_N3_SF3 (per OTU)
FA3_N4_SF1 (per OTU)
FA3_N4_SF2 (per OTU)
FA3_N4_SF3 (per OTU)
... (68 more variables)


[Metadata for longread sequencing of Carcinus maenas] - Metadata for longread sequencing of Carcinus maenas collected from Buzzard's Bay, Massachusetts from May 2022 to Aug 2022 (Collaborative Research: Tracking fine-scale selection to temperature at the invasion front of a highly dispersive marine predator)

This project explores genomic changes in the invasive European green crab (Carcinus maenas), including at a putative inversion polymorphism. To begin to explore structural variation without a reference genome, we conducted semi-targeted longread sequencing of the C. maenas genome using MinION sequencing. This dataset includes individual metadata for 6 raw MinION reads, archived at GenBank's SRA under BioProject PRJNA1171011. This sequencing was conducted using crabs from Massachusetts waters.

cdm_data_type = Other
VARIABLES:
sample_name (unitless)
Collection_date (unitless)
SRA_accession (unitless)
biosample_accession (unitless)
embayment (unitless)
state (unitless)
sex (unitless)
life_stage (unitless)
run_ID (unitless)
sequencing_date (unitless)
run_day (days)
probe_set (unitless)


[Metadata for RNASeq of green crabs in the northeast Pacific] - Metadata for RNASeq of green crabs collected in the northeast Pacific from Apr 2017 to Aug 2021 (Collaborative Research: Tracking fine-scale selection to temperature at the invasion front of a highly dispersive marine predator)

This project explores genomic changes in the invasive European green crab (Carcinus maenas) in the northeast Pacific. It tracks the earliest stages of green crab invasion into a new environment where the species is predicted to have substantial ecological and economic impacts. Samples span time and space across the species range in the northeast Pacific, with a focus on areas where the species is currently expanding. This dataset includes individual metadata for 127 raw RNA-Seq reads, archived at GenBank's SRA under BioProject PRJNA1170986.

cdm_data_type = Other
VARIABLES:
sample_name (unitless)
SRA_accession (unitless)
biosample_accession (unitless)
embayment (unitless)
site (unitless)
state (unitless)
sex (unitless)
size_CW (Millimeters (mm))
color (unitless)
collection_date (unitless)
latitude (degrees_north)
longitude (degrees_east)
collector (unitless)
collector_affiliation (unitless)


[Metadata for targeted genotyping of green crabs in the northeast Pacific] - Metadata for targeted genotyping of green crabs collected in the northeast Pacific from Aug 2016 to Oct 2022 (Collaborative Research: Tracking fine-scale selection to temperature at the invasion front of a highly dispersive marine predator)

This project explores genetic changes in the invasive European green crab (Carcinus maenas) in the northeast Pacific, using targeted genotyping of SNPs identified in prior high-resolution population genomics in the region. It tracks the early stages of green crab invasion into a new environment, particularly through repeated sampling of multiple size-classes of crabs from the same sites over multiple years. Samples span time and space across the species range in the northeast Pacific, with a focus on the coast of Washington and Oregon. This dataset includes individual collection and accession metadata for 1,662 crabs, for which raw demultiplexed reads are archived at GenBank's SRA under BioProject PRJNA1177418.

cdm_data_type = Other
VARIABLES:
sample_name (unitless)
SRA_accession (unitless)
biosample_accession (unitless)
embayment (unitless)
site (unitless)
state (unitless)
sex (unitless)
size_CW (Millimeters (mm))
color (unitless)
collection_date (unitless)
latitude (degrees_north)
longitude (degrees_east)
collector (unitless)
collector_affiliation (unitless)


[Metadata from meta-analysis on CovGE in phenotypic results] - Metadata for studies from meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results (RCN: Evolution in Changing Seas)

Covariance can exist between the genetic and environmental influences on phenotype (CovGE) and can have an important role in ecological and evolutionary processes in nature and population responses to environmental change. CovGE is commonly called countergradient variation (CnGV; negative CovGE)or cogradient variation (CoGV; positive CovGE)and has been recognized in classic studies that have established several long-standing hypotheses about CnGV and CoGV. For instance, it is hypothesized that CnGV is more prevalent in nature than CoGV, that CnGV is more prevalent in fish, amphibian, and invertebrate taxa, across latitudinal or altitudinal environmental gradients, and more frequently occurs in metabolic compensation traits, including development, growth, feeding, metabolism, and activity, while CoGV is more commonly observed in morphological traits. The recent development of a standardized method to measure CovGE allows for the first rigorous quantitative exploration of these hypotheses. We use meta-analysis and apply the novel quantitative method to test whether the above hypotheses are supported in the literature. We found no differences in frequency of CnGV and CoGV, and no systematic patterns relative to taxa, environmental gradient, or trait type. However, our analyses suggest that CovGE may be as common as gene by environment (GxE) interactions. Given that CovGE is likely to have a strong impact on future outcomes for organisms experiencing environmental change, that significant CovGE occurred frequently, and the lack of systematic patterns in the occurrence of CovGE, we encourage a more widespread application of measuring CovGE.

cdm_data_type = Other
VARIABLES:
STUDY_ID (unitless)
First_Author (unitless)
Data_file_name (unitless)
G_match_E (unitless)
natural_env_type (unitless)
GxE_sig (unitless)
phylum_division (unitless)
genus (unitless)
species (unitless)
gen_number (unitless)
... (19 more variables)


[Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities] - Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities collected on cruises AT42-22, TN405, and NA108 from May 2019 to Jun 2022 (Collaborative Research: Microbes need frenemies: unveiling microbial relationships with protists and viruses that support deep-sea hydrothermal vent food webs)

This dataset is a collection of sample metadata, identified for all samples, and NCBI accession information for samples and sequence runs produced as part of the "Microbes need frenemies" project. This project examines trophic interactions among microbial eukaryotes, viruses, bacteria, and archaea at deep-sea hydrothermal vents using metagenomics and metatranscriptomics and characterizes these ecologically-significant interactions, such as mutualism, predator-prey, or virus-host.

We sequenced samples collected during the 2020 expedition AT42-22 to the Mid-Cayman Rise hydrothermal vent fields, as well as from the 2019 expedition NA108 to the Gorda Ridge and the 2022 expedition TN405 to the Axial seamount. Sequencing targeted archaea, bacteria, and viruses with metagenomics and microbial eukaryotes with metatranscriptomics. We plan to use these data to identify ecologically-significant interactions among protists, viruses, bacteria, and archaea, with a specific emphasis on microbial mortality via viral lysis and eukaryotic grazing. Archived samples were also included in the analysis.

cdm_data_type = Other
VARIABLES:
SAMPLE_ID (unitless)
SHORT_SAMPLE_ID (unitless)
SAMPLE_NAME (unitless)
LAB_NUM (unitless)
CRUISE_ID (unitless)
FIELD_REGION (unitless)
YEAR (unitless)
FIELD_YEAR (unitless)
VENT (unitless)
latitude (degrees_north)
longitude (degrees_east)
ORIGIN_TYPE (unitless)
ORIGIN_DESCRIPTION (unitless)
FRENEMIES_PROJ (unitless)
... (11 more variables)


[Metagenome sequencing samples] - Contextual data for samples collected for metagenome sequencing from the deep subseafloor biosphere as accessed via CORKs along the Juan de Fuca Ridge flank in the Northeast Pacific Ocean between 2008 and 2014 (Collaborative Research: Illuminating microbes and their viruses within the dark ocean crust through strain-level approaches)

This dataset provides contextual information about samples used for metagenome sequencing. These samples were collected from pristine crustal fluids sampled via CORK observatories along the Juan de Fuca Ridge flank in the Northeast Pacific Ocean off the coast of North America. Also included are metadata for seawater and sediment metagenomes that have been sequenced as controls. All of the data are publicly available via the National Center for Biotechnology Information (NCBI) accession numbers provided in the dataset (BioProject numbers PRJNA655018 to PRJNA655040).

cdm_data_type = Other
VARIABLES:
Sample_Type (unitless)
Sample_Name (unitless)
DNA_Isolation_Method (unitless)
Collection_Date (unitless)
Collection_Year (unitless)
Collection_Month (unitless)
Collection_Day (unitless)
Sample_Source (unitless)
Fluid_Delivery_Line (unitless)
Environment (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth (msb)
Area (unitless)
Full_Sample_Name_and_Description (unitless)
IMG_Genome_ID (unitless)
NCBI_Bioproject_Accession (unitless)
NCBI_Biosample_Accession (unitless)
SRA_ID (unitless)


[Metagenome] - Metagenomic data from samples collected on cruise Chikyu-331 in the Okinawa Trough, Japan from September to October 2010 (An In-Depth analysis of the subvent biosphere within Okinawa Backarc Basin (IODP 331, Iheya North Hydrothermal Field) sediments)

The purpose these metagenomic data was to capture a distinct changeover of microbial assemblages between the mesophilic horizons above 10 mbsf and the hottest (55C) hydrothermal clay horizon. In this section of the dynamic Iheya North Hydrothermal system, the temperature gradient was estimated to be ~3C/m. These metagenomes provide functional evidence to this model, demonstrating that molecular signals represent a responsive microbial community to the increasingly demanding environmental conditions.

cdm_data_type = Other
VARIABLES:
Cruise_ID (unitless)
Sample_Name (unitless)
latitude (degrees_north)
longitude (degrees_east)
Water_depth (meters)
Top_Depth (meters below seafloor)
Bottom_Depth (meters below seafloor)
Sediment_type (unitless)
Estimated_Temp (degrees Celsius)
MGRAST_Name (unitless)
MGRAST_ID (unitless)
Notes (unitless)


[Metal quotas of Line P diatoms in added Zn and Co incubation studies] - Metal quotas of NE Pacific and Altantic diatom isolates measured via ICP-MS after growth in zinc and cobalt media amendments in experiments with cultures collected from R/V Thomas G. Thompson cruise TN280, along Line P in the NE Pacific, in May of 2012 (US GEOTRACES PMT: Cobalt Biogeochemical Cycling and Connections to Metalloenzymes in the Pacific Ocean)

Metal quotas of two NE Pacific Line P diatom isolates and one Atlantic diatom isolate measured via ICP-MS after growth in zinc and cobalt media amendments.  Experiments with cultures collected from the GeoMICS expedition on the R/V Thomas G. Thompson (cruise TN280), along Line P in the NE Pacific, in May of 2012.

cdm_data_type = Other
VARIABLES:
Culture (unitless)
Added_Zn (nanomoles per liter (nmol/L))
Added_Co (nanomoles per liter (nmol/L))
Total_Zn (nanomoles per liter (nmol/L))
Total_Co (nanomoles per liter (nmol/L))
log_Zn2plus (moles per liter (mol/L))
log_Co2plus (moles per liter (mol/L))
CO_to_P_avg (dimensionless)
ZN_to_P_avg (dimensionless)
CD_to_P_avg (dimensionless)
MN_to_P_avg (dimensionless)
FE_to_P_avg (dimensionless)
NI_to_P_avg (dimensionless)
CU_to_P_avg (dimensionless)
MO_to_P_avg (dimensionless)


[Metatranscriptomic nutrient response experiments - 2021 DY131] - Data from nutrient manipulation experiments (conducted on EXPORTS cruise DY131) aimed at relieving or inducing nutrient stress in phytoplankton and quantifying these responses using metatranscriptomic sequencing (Collaborative Research: Diatoms, Food Webs and Carbon Export - Leveraging NASA EXPORTS to Test the Role of Diatom Physiology in the Biological Carbon Pump)

This dataset includes data from nutrient manipulation experiments aimed at relieving or inducing nutrient stress in phytoplankton and quantifying these responses using metatranscriptomic sequencing. Experiments were conducted by adding key macronutrients (N, P, Si) and Fe in different combinations over different growth periods, simulating potential alleviation of in situ nutrient stress or the induction of nutrient stress. Experiments were conducted on the EXports Processes in the Oceans from RemoTe Sensing (EXPORTS) cruise DY131 in the North Atlantic during May of 2021.

cdm_data_type = Other
VARIABLES:
Cruise (unitless)
time (Iso_datetime_utc, seconds since 1970-01-01T00:00:00Z)
Date_UTC (unitless)
Time_UTC (unitless)
Event (unitless)
Activity (unitless)
Station (unitless)
latitude (degrees_north)
longitude (degrees_east)
exp_id (unitless)
Incubation (unitless)
Treatment (unitless)
replicate (unitless)
BioProject (unitless)
BioSample (unitless)
SRA_sample (unitless)
Phosphate (millimoles per cubic meter (mmol m^3))
Phosphate_flag (unitless)
Silicate (millimoles per cubic meter (mmol m^3))
Silicate_flag (unitless)
Nitrite (millimoles per cubic meter (mmol m^3))
Nitrite_flag (unitless)
... (8 more variables)


[Meteorological Data] - Meteorological data from the Tudor Hill Marine Atmospheric Observatory, Bermuda in 2017 to 2024 (Operation of a Community Marine-Atmospheric Sampling Facility at Tudor Hill, Bermuda)

The BIOS Tudor Hill Marine Atmospheric Observatory (THMAO) has been supported by the NSF Chemical Oceanography and Atmospheric Chemistry Programs following a major refit in 2003. Since that time it has provided a unique research facility for the scientific community. The specific objectives are:

1) To operate and maintain a state-of-the-art marine atmospheric sampling and observing facility at Tudor Hill, Bermuda, available for use by the wider U.S. and international research community;
2) To continue the collection of continuous meteorological data and weekly bulk-aerosol and rainwater samples, which will be archived at BIOS and made freely available to other researchers;
3) To collect additional atmospheric samples and data for other investigators (primarily in longer-term time-series programs), and to provide for the use of the facility in person by other investigators (primarily in shorter-term intensive programs).

cdm_data_type = Other
VARIABLES:
TIMESTAMP (unitless)
RECORD (unitless)
Mean_WS (meters per second (m/s))
VectorMean_WS (meters per second (m/s))
VectorMean_WD (degrees)
StdDev_WD (degrees)
SonicU (meter per second (m/sec))
SonicV (meter per second (m/sec))
SonicW (meter per second (m/sec))
SonicTemp_C (degrees Celsius)
batt_volt_Min (volts direct current (VDC))
Rain_Tot (millimeters (mm))
AirTempC_Avg (degrees Celsius)
RH_Avg (percent (%))
BP_mmHg_Avg (millimeters of mercury (mm Hg))
SlrW (W/m2)
SlrW_Avg (W/m2)
SlrW_Max (W/m2)


[Meteorological Data] - Meteorological data from the Tudor Hill Marine Atmospheric Observatory, Bermuda in 2017, 2019, 2020, 2021 and 2022 (Operation of a Community Marine-Atmospheric Sampling Facility at Tudor Hill, Bermuda)

The BIOS Tudor Hill Marine Atmospheric Observatory (THMAO) has been supported by the NSF Chemical Oceanography and Atmospheric Chemistry Programs following a major refit in 2003. Since that time it has provided a unique research facility for the scientific community. The specific objectives are:

1) To operate and maintain a state-of-the-art marine atmospheric sampling and observing facility at Tudor Hill, Bermuda, available for use by the wider U.S. and international research community;
2) To continue the collection of continuous meteorological data and weekly bulk-aerosol and rainwater samples, which will be archived at BIOS and made freely available to other researchers;
3) To collect additional atmospheric samples and data for other investigators (primarily in longer-term time-series programs), and to provide for the use of the facility in person by other investigators (primarily in shorter-term intensive programs).

cdm_data_type = Other
VARIABLES:
TIMESTAMP (untiless)
RECORD (unitless)
Mean_WS (meters per second (m/s))
ResultantMean_WS (meters per second (m/s))
ResultantMean_WD (degrees)
StdDev_WD (degrees)
SonicU (meter per second (m/sec))
SonicV (meter per second (m/sec))
SonicW (meter per second (m/sec))
SonicTemp_C (degrees Celsius)
batt_volt_Min (volts direct current (VDC))
Rain_Tot (millimeters (mm))
AirTempC_Avg (degrees Celsius)
RH_Avg (percent (%))
BP_mmHg_Avg (millimeters of mercury (mmHg))


[Meteorological observations from NOAA station 8761724] - Meteorological observations from NOAA station 8761724, Grande Isle, LA from September 20, 2022, to September 29, 2024. (CAREER: Integrating Seascapes and Energy Flow: learning and teaching about energy, biodiversity, and ecosystem function on the frontlines of climate change)

Subset of the NOAA Tides and Currents NOAA webpage. It includes meteorological observations of wind speed and direction which, in conjunction with landscape data, are used as a rough calculation of fetch distance in this study. Ultimately, the fetch distance variable was not included in the final analysis.

cdm_data_type = Other
VARIABLES:
latitude (degrees_north)
longitude (degrees_east)
Date (unitless)
Time_GMT (unitless)
time (Iso_datetime_utc, seconds since 1970-01-01T00:00:00Z)
Wind_Speed_kn (knots)
Wind_Dir_deg (degrees)
Wind_Gust_kn (knots)
Air_Temp_F (Degrees Fahrenheit)
Baro_mb (millibar)
Humidity_perc (percentage (%))
Visibility_nm (nanometers)


[Methane Seep Macrofaunal Morphospecies] - Macrofaunal morphospecies from hard substrate samples at methane seeps collected from R/V Atlantis cruise AT50-12 in the Southern California Borderland from July 16-28, 2023 (Collaborative Research: Redefining the footprint of deep ocean methane seepage for benthic ecosystems)

Hard substrate samples (carbonate, phosphorite, and wood) were collected at methane seeps off Southern California with the HOV Alvin from July 16-28, 2023 during R/V Atlantis cruise AT50-12 for macrofaunal analyses. This dataset contains counts for fauna identified to morphospecies as well as collection and sample metadata.

cdm_data_type = Other
VARIABLES:
Alvin_Dive (unitless)
Date_Deployed (unitless)
Date_Recovered (unitless)
Site (unitless)
Experiment (unitless)
Substrate_Type (unitless)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
Depth_Category (unitless)
Oxygen (micromoles per kilogram (umol/kg))
Oxygen_Category (unitless)
Seepage_Category (unitless)
Sample_Number (unitless)
Surface_Area (square centimetres (cm^2))
Sample_ID (count)
Acari_sp_1 (count)
Actiniaria_unidentified_isotopes (count)
Actiniaria_sp_1 (count)
Actiniaria_sp_2 (count)
Actiniaria_sp_3 (count)
Actiniaria_sp_4 (count)
Actiniaria_sp_5 (count)
Agathotanaidae_sp_1 (count)
... (250 more variables)


[Micro-satellite genotypes 2012] - Microsatellite genotypes and geolocation data from the Belizean Barrier reef collected in 2012. (An Integrative Investigation of Population Connectivity Using a Coral Reef Fish)

Microsatellite genotypes and geolocation data from the Belizean Barrier reef collected in 2012.

cdm_data_type = Other
VARIABLES:
individual_ID (unitless)
site_id (unitless)
year (unitless)
latitude (degrees_north)
longitude (degrees_east)
Locus1_1419triBA (Locus1 1419tri BA, count)
Locus1_1419triBB (Locus1 1419tri BB, count)
Locus2_14528tetYA (Locus2 14528tet YA, count)
Locus2_14528tetYB (Locus2 14528tet YB, count)
Locus3_18144triGA (Locus3 18144tri GA, count)
Locus3_18144triGB (Locus3 18144tri GB, count)
Locus4_21378triGA (Locus4 21378tri GA, count)
Locus4_21378triGB (Locus4 21378tri GB, count)
Locus5_23415tetRA (Locus5 23415tet RA, count)
Locus5_23415tetRB (Locus5 23415tet RB, count)
Locus6_23889triBA (Locus6 23889tri BA, count)
Locus6_23889triBB (Locus6 23889tri BB, count)
Locus7_25362triGA (Locus7 25362tri GA, count)
Locus7_25362triGB (Locus7 25362tri GB, count)
Locus8_25632tetRA (Locus8 25632tet RA, count)
Locus8_25632tetRB (Locus8 25632tet RB, count)
Locus9_25745tetBA (Locus9 25745tet BA, count)
Locus9_25745tetBB (Locus9 25745tet BB, count)
Locus10_29109tetBA (Locus10 29109tet BA, count)
Locus10_29109tetBB (Locus10 29109tet BB, count)
Locus11_6231tetBA (Locus11 6231tet BA, count)
Locus11_6231tetBB (Locus11 6231tet BB, count)
... (6 more variables)


[Microbial Cellular Abundance Epifluorescent Microscopy] - Microbial cellular abundance growth response through epifluorescent microscopy from the Neuse River Estuary, North Carolina USA from 2021-2022 (Bacteria as Biosensors of Carbon and Energy Flow in Marine Ecosystems: Quantitative Links Between Substrates, Transcripts, and Metabolism)

Microbial cellular abundance was enumerated for two microcosm incubation experiments to track the growth response of the microbial community. This dataset targets bacterial and phytoplankton abundance through epiflorescent microscopy. Sample water originated from the West Bay of the Neuse River Estuary, North Carolina USA in 2021 and 2022. The microcosms were 60-L, conducted in biological duplicates under three light treatment incubations: 12 h light-dark cycle of photosynthetically active radiation (PAR), 12 h light-dark cycle of UV-B radiation, or darkness. Unfiltered sample water was stained with SYBR Green I (Fall 2021 experiment) or DAPI (Spring 2022 experiment) for enumeration at 60x for bacterial and cyanobacterial abundance. Autofluorescence from excitation at 620 nm and 60x was used to enumerate small phytoplankton and cyanobacteria. This dataset highlights patterns in microbial growth across treatments over the course of the incubation and is used to generate cell-specific, normalized rates for associated datasets in the project.

cdm_data_type = Other
VARIABLES:
Experiment_Name (unitless)
latitude (degrees_north)
longitude (degrees_east)
Date (unitless)
Incubation_Day (days)
Treatment (unitless)
Tank_ID (unitless)
Method (unitless)
Stain (unitless)
Excitation (nanometers (nm))
Magnification (unitless)
Size_Fraction (micrometers (um))
cells_per_L_avg (cells L-1)
cells_per_L_sd (cells L-1)
ratio_620_tot (unitless)
ratio_err (unitless)


[Microbial community composition of the Cinder Cones Cold Seep] - Microbial community composition from 16s V4 region amplicon sequencing of the methane Seep at the Cinder Cones Cold Seep site, Nov 2016 (EAGER: Elucidating the Antarctic Methane Cycle at the Cinder Cones Reducing Habitat)

This dataset includes microbial community composition from 16s V4 region amplicon sequencing on 151 marine sediment community samples collected from the Cinder Cones Cold Seep site [-77.8, 166.666] in the Ross Sea region, Antarctica in November 2016. Data are uploaded to the NCBI Sequence Read Archive under submission SUB2655615 [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA387720] with a subset of the data from that archive originating from this project.

cdm_data_type = Other
VARIABLES:
accession (unitless)
sample_name (unitless)
organism (unitless)
host (unitless)
time (Collection Date, seconds since 1970-01-01T00:00:00Z)
geo_loc_name (unitless)
latitude (degrees_north)
longitude (degrees_east)
Replicate (unitless)
Sediment_Depth_cm (centimeters)
Habitat (unitless)


[Microbial eukaryotic diversity: Mid-Cayman Rise SRA dataset] - 18S rRNA amplicon sequencing of microbial eukaryotes from the Mid-Cayman Rise acquired Jan-Feb, 2020 (Probing subseafloor microbial interactions via hydrothermal vent fluids: A focus on protists)

Single-celled microbial eukaryotes inhabit deep-sea hydrothermal vent environments and play critical ecological roles in the vent-associated microbial food web. 18S rRNA amplicon sequencing of diffuse venting fluids from two geochemically-distinct hydrothermal vent fields was applied to investigate community diversity patterns among protistan assemblages. Piccard and Von Damm vent fields are situated 20 km apart at the Mid-Cayman Rise in the Caribbean Sea. We describe species diversity patterns with respect to hydrothermal vent field and sample type, identify putative vent endemic microbial eukaryotes, and test how vent fluid geochemistry may influence microbial community diversity. Individual vent fields supported distinct and highly diverse assemblages of protists that included potentially endemic or novel vent-associated strains. This data adds to our growing knowledge of the biogeography of deep-sea microbial eukaryotes.

cdm_data_type = Other
VARIABLES:
Experiment_Accession (unitless)
Experiment_Title (unitless)
Organism_Name (unitless)
Instrument (unitless)
Study_Accession (unitless)
Study_Title (unitless)
Sample_Accession (unitless)
Total_Size_Mb (Mb)
Total_Bases (bp)
Library_Name (unitless)
Library_Strategy (unitless)
Library_Source (unitless)
Library_Selection (unitless)
Vent_field (unitless)
Collection (unitless)
Vent_name (unitless)
DiveID (unitless)


[Microbial eukaryotic focused metatranscriptome data] - Microbial eukaryotic focused metatranscriptome data from seawater collected in coastal California in May of 2015 (Protistan, prokaryotic, and viral processes at the San Pedro Ocean Time-series)

Seawater was collected via Niskin bottles mounted with a CTD from the San Pedro Ocean Time-series (SPOT) station off the coast of Southern California near the surface (5 m), 150 and 890 m, in late May 2015. Raw sequence data was generated as part of a metatranscriptome study targeting the protistan community.  Raw sequences are available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (SRA Study ID: SRP110974, BioProject: PRJNA391503).  Sequences for BioProject PRJNA608423 will be available at NCBI on Jan 1st, 2021.\r\n\r\nThese data were published in Hu et al. (2018).

cdm_data_type = Other
VARIABLES:
SRA_run (unitless)
SRA_run_link (unitless)
SRA_study (unitless)
bioproject_accession (unitless)
biosample_accession (unitless)
library_ID (unitless)
title (unitless)
sample_name (unitless)
library_strategy (unitless)
library_source (unitless)
library_selection (unitless)
library_layout (unitless)
platform (unitless)
instrument_model (unitless)
design_description (unitless)
filetype (unitless)
filename (unitless)
filename2 (unitless)


[Microbial Respiration] - Microbial respiration from microcosm experiments conducted under three light treatments using water originating from West Bay of the Neuse River Estuary, North Carolina USA in 2021 and 2022 (Bacteria as Biosensors of Carbon and Energy Flow in Marine Ecosystems: Quantitative Links Between Substrates, Transcripts, and Metabolism)

Microbial respiration assays were conducted for two microcosm incubation experiments. Sample water originated from West Bay of the Neuse River Estuary, North Carolina USA in 2021 and 2022. The microcosms were 60-liters, conducted in biological duplicates under three light treatment incubations: 12-hour light-dark cycle of photosynthetically active radiation (PAR), 12-hour light-dark cycle of UV-B radiation, or darkness. Respiration assays of the unfiltered and 5-micron filtered community were initiated every few days using foil-membrane optodes to examine light effects on community respiration.

cdm_data_type = Other
VARIABLES:
Experiment_Name (unitless)
Date (unitless)
Time_EDT (unitless)
Incubation_day (days)
Treatment (unitless)
Tank_ID (unitless)
Size_fraction_um (micrometers (um))
respiration_uM_O2_d_1 (micromoles O2 per day (uM O2 d-1))
respiration_uM_C_d_1 (micromoles C per day (uM C d-1))
r2 (unitless)
RSE (unitless)
No_pts (unitless)
ISO_DateTime_Local (unitless)


[Microbiome dynamics of coral reef and cleanerfish] - Microbiome dynamics of coral reef and cleanerfish from ecological surveys, in situ manipulations, and laboratory experiments conducted from 2020-2021 (Collaborative Research: Cleaning stations as hubs for the maintenance and recovery of microbial diversity on coral reefs.)

Coral reefs host some of the most iconic symbiotic interactions in nature and are host to the highest diversity of life on the planet. Cleaning symbiosis, wherein small fish or shrimp remove external parasites and associated microorganisms from specific clients, is common on coral reefs. Sites on the reef occupied by cleaners, or "cleaning stations", attract a wide variety of fish species that engage in direct physical contact with the cleaner. In this study, we used a combination of ecological surveys, in situ manipulations, and laboratory experiments to examine the unique features of cleaning stations to understand transfer of bacterial and archaeal symbionts amongst fish and within coral reef environment. We used microbial 16S rRNA gene amplicons, environmental parameters, and other molecular tools to evaluate the dynamics between coral microbiomes, cleanerfish skin microbiomes, and the environment. This dataset contains metadata describing sequenced samples, including sample name, data deposition accession records, and measurements at the time of sample collection.

cdm_data_type = Other
VARIABLES:
BioProject_accession (unitless)
BioSample_accession (unitless)
sample_name (unitless)
SRA_accession (unitless)
collection_date (unitless)
geo_loc_name (unitless)
host (unitless)
lat (degrees_north)
longitude (degrees_east)
isolation_source (unitless)
host_common_name (unitless)
host_disease (unitless)
host_condition (unitless)
host_coral_cleaner_goby_pretreatment (unitless)
host_coral_reef_id (unitless)
location_survey_date (unitless)
... (13 more variables)