[Drop Sampling Data - Port Fourchon, LA 2022] - Species counts, site-level information and environmental context sampled near Port Fourchon, Louisiana from September 23 - 29, 2022. (CAREER: Integrating Seascapes and Energy Flow: learning and teaching about energy, biodiversity, and ecosystem function on the frontlines of climate change)

This dataset provides species count data collected during the Fall 2022 drop sampling season at 52 sites near Port Fourchon, Louisiana. The sampling effort aimed to assess the abundance and composition of estuarine nekton species across a landscape experiencing significant climate-driven habitat change, including mangrove encroachment and marsh loss. Species counts were obtained using a drop sampler with a 1.2 m² area, deployed along the marsh edge at each site. Nekton within the sampler were captured using a suction pump and dipnets, sorted into taxonomic groups, and enumerated.The data are presented alongside site-level information, including approximate geolocation, date, and environmental context (e.g., habitat classification derived from drone and satellite imagery).

The purpose of this dataset is to evaluate how species abundances respond to habitat structure at multiple spatial scales, particularly in relation to landscape metrics such as land-to-water ratio, edge area, and mangrove cover. This dataset is useful for ecologists, resource managers, and conservation scientists interested in habitat suitability, estuarine ecology, and the impacts of climate-driven habitat changes on coastal nekton communities.

This dataset is part of a study exploring the effect of habitat scale on models linking species abundance to landscape metrics. This was collected by Herbert Leavitt, Dr. James Nelson, and Alex Thomas. Affiliation at time of sampling was University of Louisiana at Lafayette.

cdm_data_type = Other
VARIABLES:
site_date_key (unitless)
site_number (unitless)
sample_date (unitless)
sample_trip (unitless)
water_depth (cm)
temperature (degrees Celcius (°C))
salinity (parts per thousand (ppt or ‰))
latitude (degrees_north)
longitude (degrees_east)
... (49 more variables)


[DYEatom: Metatranscriptome accessions and assembled contigs] - DYEatom Metatranscriptome metadata from RV/Point Sur cruise PS1312 in the Monterey Bay area, June-July 2013 (Linking physiological and molecular aspects of diatom silicification in field populations)

Metadata for assembled contigs and ORFS from metatranscriptome analysis from CTD casts in the Monterey Bay area on RV/Point Sur cruise PS1312, June-July 2013. Assembled contigs files are also available; see Supplemental Files.

cdm_data_type = Other
VARIABLES:
BioProject_type (Bio Project Type, unitless)
BioProject_id (Bio Project Id, unitless)
BioSample (Bio Sample, unitless)
Sample_name (unitless)
SRA_id (unitless)
Package_type (unitless)
version (unitless)
Accession (unitless)
ID (unitless)
cruise_id (unitless)
CTD_cast (unitless)
latitude (degrees_north)
longitude (degrees_east)
Date_collection (unitless)
station (unitless)
depth (m)


[Eastern Shore bottom water analysis] - Chemical analysis from sediment core bottom water samples collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017 (Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2)

This dataset includes results of analysis on sediment core bottom water samples collected in the back barrier island bays on Virginia\u2019s Eastern Shore in July 2017 - initial pH, alkalinity, sulfate, DIC, and DOC.

cdm_data_type = Other
VARIABLES:
sample_id (unitless)
site (unitless)
latitude (degrees_north)
longitude (degrees_east)
num_replicate_bottles (bottles)
initial_pH (Initial P H, NBS scale)
initial_pH_stdev (Initial P H Stdev, NBS scale)
Alk (milliMoles)
Alk_stdev (milliMoles)
Sulfate (milliMoles)
Sulfate_stdev (milliMoles)
DIC (microMoles)
DIC_stdev (microMoles)
DOC (microMoles)
DOC_stdev (microMoles)


[Eastern Shore pore water analysis] - Chemical analysis from sediment core pore water samples collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017 (Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2)

This dataset includes results of analysis on sediment cores collected in the back barrier island bays on Virginia\u2019s Eastern Shore in July 2017 - initial pH, alkalinity, sulfate, DIC, Fe, NH4, sulfide, and DOC.

cdm_data_type = Other
VARIABLES:
site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Core (unitless)
Depth_cm (Depth, centimeters)
Initial_pH (Initial P H, NBS scale)
Alkalinity_mM (Alkalinity M M, milliMoles)
Sulfate_mM (Sulfate M M, milliMoles)
DIC_mM (DIC M M, milliMoles)
Fe_uM (Fe U M, microMoles)
NH4_uM (NH4 U M, microMoles)
Sulfide_uM (Sulfide U M, microMoles)
DOC_uM (DOC U M, microMoles)


[Eastern Shore sediment core metadata] - Sediment core sample metadata collected July 2017 in the back barrier island bays on Virginia’s Eastern Shore (Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2)

This dataset includes metadata on sediment cores collected during July 2017 in the back barrier island bays on Virginia\u2019s Eastern Shore - location, date and time of sample collection and processing, and which analyses were performed on each core.

cdm_data_type = Other
VARIABLES:
site (unitless)
latitude (degrees_north)
longitude (degrees_east)
core (unitless)
date_processed (unitless)
PW (unitless)
Ox (unitless)
phi (unitless)
Pb210 (unitless)
sol (unitless)


[Eastern Shore sediment core oxygen profiles] - Oxygen profiles from sediment core samples collected in the back barrier island bays on Virginia’s Eastern Shore in July 2017 (Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2)

This dataset includes oxygen profiles from sediment core samples collected in the back barrier island bays on Virginia\u2019s Eastern Shore in July 2017.

cdm_data_type = Other
VARIABLES:
site (unitless)
latitude (degrees_north)
longitude (degrees_east)
core (unitless)
profile (unitless)
ISO_DateTime_Local_collected (ISO Date Time Local Collected, unitless)
ISO_DateTime_Local_scan (ISO Date Time Local Scan, unitless)
depth_cm (Depth, centimeters)
O2_uM (O2 U M, microMoles)


[Ebullition on VA Eastern Shore] - Bubble flux measurements and concentrations at two sites on the Virginia Eastern Shore, July 2017 (Toward an Improved Understanding of Blue Carbon: The Role of Seagrasses in Sequestering CO2)

Bubble flux measurements and concentrations at two sites on the Virginia Eastern Shore, July 2017.

cdm_data_type = Other
VARIABLES:
date_local (unitless)
time_local (unitless)
time (ISO Date Time Local, seconds since 1970-01-01T00:00:00Z)
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Traps (traps)
Deployment_duration (hours)
Gas_Flux (microMol/meter^2/hour (mMol/m2/h))
Gas_Flux_stdev (microMol/meter^2/hour (mMol/m2/h))
Gas_samples (samples)
O2_Optode (percent)
O2_Optode_stdev (percent)
O2_Ar (unitless)
O2_Ar_stdev (unitless)
d18O (D18 O, parts per thousand (ppt))
d18O_stdev (D18 O Stdev, parts per thousand (ppt))


[Ecological monitoring Natividad 2006-2021: Algae] - Ecological monitoring of algae on Isla Natividad from 2006 to 2021 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)

This dataset encompasses information about algae transects between 2006 to 2021 in Isla Natividad, Baja California Sur, Mexico. Abundances of algae and the number of stipes of each individual algae can be found in the data set. Also, the dates when the transects were done, the site, the name of the diver, the depth the transect was laid, if the site was a marine reserve or not, if the site is inside a marine protected area or not, the latitude and longitude of the sites, the temperature of the water, the number of transect from where the information was counted, and the species name of algae counted.

Ecological monitoring is important to collect data of species that inhabit an specific ecosystem. For this data set, we present all the data form 2006 to 2021 on algae, marine invertebrates, fish and uniform point contact at six different sites in Isla Natividad off the coast of Baja California Sur, Mexico. Data was collected once a year by trained divers as a collaborative effort from Stanford University, non-governmental organizations, and fishing cooperative federations. These data provides the abundaces of algae, invertebrates, fish and substrate  of Isla Natividad over the spam of 15 years and may be use to assess changes in the ecosystems after shocks such as hypoxic events or marine heatwaves.

cdm_data_type = Other
VARIABLES:
ID (unitless)
DAY (unitless)
MONTH (unitless)
YEAR (unitless)
STATE (unitless)
COMMUNITY (unitless)
SITE (unitless)
LAT (degrees_north)
longitude (Long, degrees_east)
HABITAT (unitless)
ZONE (unitless)
PROTECTION (unitless)
... (18 more variables)


[Ecological monitoring Natividad 2006-2021: Fish] - Ecological monitoring of fish on Isla Natividad from 2006 to 2021 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)

This dataset encompasses information about fish transects between 2006 to 2021 in Isla Natividad. Abundances, sex and size of fish can be found in the data set. Also, the dates when the transects were done, the site, the name of the diver, the depth the transect was laid, if the site was a marine reserve or not, if the site is inside a marine protected area or not, the latitude and longitude of the sites, the temperature of the water, the number of transect from where the information was counted, and the species name of the fish counted.

Ecological monitoring is important to collect data of species that inhabit an specific ecosystem. For this data set, we present all the data form 2006 to 2021 on algae, marine invertebrates, fish and uniform point contact at six different sites in Isla Natividad off the coast of Baja California Sur, Mexico. Data was collected once a year by trained divers as a collaborative effort from Stanford University, non-governmental organizations, and fishing cooperative federations. These data provides the abundaces of algae, invertebrates, fish and substrate  of Isla Natividad over the spam of 15 years and may be use to assess changes in the ecosystems after shocks such as hypoxic events or marine heatwaves.

cdm_data_type = Other
VARIABLES:
ID (unitless)
DAY (unitless)
MONTH (unitless)
YEAR (unitless)
STATE (unitless)
COMMUNITY (unitless)
SITE (unitless)
LAT (degrees_north)
longitude (Long, degrees_east)
HABITAT (unitless)
ZONE (unitless)
PROTECTION (unitless)
MPA (unitless)
... (15 more variables)


[Ecological monitoring Natividad 2006-2021: Invertebrates] - Ecological monitoring of marine invertebrates on Isla Natividad from 2006 to 2021 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)

This dataset encompasses information about marine invertebrates transects between 2006 to 2021 in Isla Natividad. Abundances of invertebrates can be found in the data set. Also, the dates when the transects were done, the site, the name of the diver, the depth the transect was laid, if the site was a marine reserve or not, if the site is inside a marine protected area or not, the latitude and longitude of the sites, the temperature of the water, the number of transect from where the information was counted, and the species name of each invertebrate counted.

Ecological monitoring is important to collect data of species that inhabit an specific ecosystem. For this data set, we present all the data form 2006 to 2021 on algae, marine invertebrates, fish and uniform point contact at six different sites in Isla Natividad off the coast of Baja California Sur, Mexico. Data was collected once a year by trained divers as a collaborative effort from Stanford University, non-governmental organizations, and fishing cooperative federations. These data provides the abundaces of algae, invertebrates, fish and substrate  of Isla Natividad over the spam of 15 years and may be use to assess changes in the ecosystems after shocks such as hypoxic events or marine heatwaves.

cdm_data_type = Other
VARIABLES:
ID (unitless)
DAY (unitless)
MONTH (unitless)
YEAR (unitless)
STATE (unitless)
COMMUNITY (unitless)
SITE (unitless)
LAT (degrees_north)
longitude (Long, degrees_east)
HABITAT (unitless)
ZONE (unitless)
PROTECTION (unitless)
MPA (unitless)
... (13 more variables)


[Ecological monitoring Natividad 2006-2021: UPC] - Uniform point contact (UPC) transect data from Isla Natividad from 2006 to 2021 (Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability)

This dataset encompasses information about Uniform point contact (UPC) transects between 2006 to 2021 in Isla Natividad. UPC refers to the information about the substrate where the transect is laid. Every meter (along the 30m transect) you identify what type of substrate there is (e.g., sand, cobble, boulder, reef, other such as anthropogenic), what type of cover there is (e.g., none, brown algae, green algae, red algae, crustose coralline algae, mobile invertebrates, sessile invertebrates or seagrass) and the height of the relief (e.g., less than 10cm, between 10cm and 1m, between 1m and 2m or more than 2m). With this information you can assess the kelp forest ecosystem. This dataset also has information about the dates when the transects were done, site, the name of the diver, the depth the transect was laid, if the site was a marine reserve or not, if the site is inside a marine protected area or not, the latitude and longitude of the sites, the temperature of the water, the number of transect from where the information was counted and the total of substrate, cover and relief points.

Ecological monitoring is important to collect data of species that inhabit an specific ecosystem. For this data set, we present all the data form 2006 to 2021 on algae, marine invertebrates, fish and uniform point contact at six different sites in Isla Natividad off the coast of Baja California Sur, Mexico. Data was collected once a year by trained divers as a collaborative effort from Stanford University, non-governmental organizations, and fishing cooperative federations. These data provides the abundaces of algae, invertebrates, fish and substrate  of Isla Natividad over the spam of 15 years and may be use to assess changes in the ecosystems after shocks such as hypoxic events or marine heatwaves.

cdm_data_type = Other
VARIABLES:
ID (unitless)
DAY (unitless)
MONTH (unitless)
YEAR (unitless)
STATE (unitless)
COMMUNITY (unitless)
SITE (unitless)
... (40 more variables)


[EcoMon Plankton 100m3] - EcoMon plankton counts (100-m3) from Bongo tows, including MARMAP data multiple cruises in the Northeast Continental Shelf of the United States from 1977-2015 (EcoMon Zooplankton project) (EcoMon Zooplankton)

EcoMon plankton counts from Bongo tows. Includes MARMAP data.

cdm_data_type = Other
VARIABLES:
year
cruiseid
station
date (seconds since 1970-01-01T00:00:00Z)
month
day
time2 (Time)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
zoo_gear
ich_gear
sfc_temp
sfc_salt
btm_temp
btm_salt
volume_100m3
taxon
count


[EcoMon Plankton 10m2] - EcoMon plankton counts (10-m2) from Bongo tows, including MARMAP data from multiple cruises in the Northeast Continental Shelf of the United States from 1977-2015 (EcoMon Zooplankton project) (EcoMon Zooplankton)

EcoMon plankton counts (10-m2) from Bongo tows, including MARMAP data from multiple cruises in the Northeast Continental Shelf of the United States from 1977-2015 (EcoMon Zooplankton project)

cdm_data_type = Other
VARIABLES:
year
cruiseid
station
date (seconds since 1970-01-01T00:00:00Z)
month
day
time2 (Time)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
zoo_gear
ich_gear
sfc_temp
sfc_salt
btm_temp
btm_salt
volume_1m2
taxon
count


[Edmunds and Lasker MEPS 2019 Fig 1a: Density pooled taxa and one year] - Octocoral colony density by pooled taxa, life stage, and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony density pooled by taxon and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure 1.

cdm_data_type = Other
VARIABLES:
Site (unitless)
Quad (unitless)
Life_stage (unitless)
Taxon (unitless)
Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig 1b: Height pooled taxa and one year] - Octocoral colony height pooled by taxon and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony height pooled by taxon and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017.  These data were used in Edmunds and Lasker (2019) Figure 1.

cdm_data_type = Other
VARIABLES:
Year (untiless)
Taxon (untiless)
Site (untiless)
Height (centimeters (cm))


[Edmunds and Lasker MEPS 2019 Fig 2a: Density by taxon and year] - Octocoral colony density by pooled taxa, life stage, and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony density pooled by taxon and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure 2.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Life_stage (unitless)
Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig 2b: Height by taxon and year] - Octocoral colony height by pooled pooled taxa and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony height pooled by taxon and year from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure 2.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Life_stage (unitless)
Height (centimeters (cm))


[Edmunds and Lasker MEPS 2019 Fig 3: Community NMDS] - Octocoral colony density by pooled taxa, site, and quadrat from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral community NMDS from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure 3, Community non-metric multidimensional scaling (NMDS).

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Life_Stage (unitless)
Mean_density (number per quadrat)
SE_Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig S1: Sampling effort] - Octocoral sampling effort (density by pooled taxa and site) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral sampling effort (density by pooled taxa and site) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure S1.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Number_of_quadrats (unitless)
Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig S3: Sampling effort, juveniles] - Octocoral sampling effort (density of juveniles pooled taxa, year, site, and quadrat) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral sampling effort (density of juveniles pooled taxa, year, site, and quadrat) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure S3.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Quadrat (unitless)
Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig S4: Colony sizes] - Octocoral colony sizes (height by pooled taxa, site, and year) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony sizes (height by pooled taxa, site, and year) from surveys conducted in St. John, US Virgin Islands from 2014 to 2017. These data were used in Edmunds and Lasker (2019) Figure S4.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Height (cenitmeters (cm))


[Edmunds and Lasker MEPS 2019 Fig S5a: Density] - Octocoral colony density by taxon, year, site, and life stage from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony density by taxon, year, site, and life stage from surveys conducted in St. John, US Virgin Islands from 2014 to 2017.  These data were used in Edmunds and Lasker (2019) Figure S5.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Life_stage (unitless)
Density (number per quadrat)


[Edmunds and Lasker MEPS 2019 Fig S5b: Height] - Octocoral colony height by taxon, year, site, and life stage from surveys conducted in St. John, US Virgin Islands from 2014 to 2017 (Collaborative Research: Pattern and process in the abundance and recruitment of Caribbean octocorals)

Octocoral colony height by taxon, year, site, and life stage from surveys conducted in St. John, US Virgin Islands from 2014 to 2017.  These data were used in Edmunds and Lasker (2019) Figure S5.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Taxon (unitless)
Site (unitless)
Life_stage (unitless)
Height (centimeters (cm))


[Edmunds et al. 2019b: Sizes of organisms fixed to flume floor] - Sizes of organisms fixed to flume floor from back reef community flume experiments conducted in Moorea, French Polynesia, from Nov 2015 to Nov 2016 (Collaborative Research: Ocean Acidification and Coral Reefs: Scale Dependence and Adaptive Capacity)

These data describe the fauna that was secured to a metal grid in the bottom of the flume.  These data are results of an experiment incubating a back reef community from Moorea, French Polynesia, for one year at high pCO2 (published in Edmunds et al. 2019) from Nov of 2015 to Nov of 2016.

cdm_data_type = Other
VARIABLES:
Flume (unitless)
ID_number (unitless)
Species (unitless)
Initial (grams (g))
Final (grams (g))


[Edmunds et al. 2019b: Sizes of organisms not fixed to flume floor] - Sizes of organisms not fixed to flume floor from back reef community flume experiments conducted in Moorea, French Polynesia, from Nov 2015 to Nov 2016 (Collaborative Research: Ocean Acidification and Coral Reefs: Scale Dependence and Adaptive Capacity)

These data describe the mobile fauna in the flumes that were not fixed to the bottom of the flume. These data are results of an experiment incubating a back reef community from Moorea, French Polynesia, for one year at high pCO2 (published in Edmunds et al. 2019) from Nov of 2015 to Nov of 2016.

cdm_data_type = Other
VARIABLES:
Flume (unitless)
ID_number (unitless)
Species (unitless)
Month_Number (unitless)
Mass (grams (g))
Month (unitless)
Year (unitless)


[Edmunds et al. 2019b: Sizes of organisms used to calculate growth and for community analysis ] - Sizes of organisms used to calculate growth and for community analysis from back reef community flume experiments conducted in Moorea, French Polynesia, from Nov 2015 to Nov 2016 (Collaborative Research: Ocean Acidification and Coral Reefs: Scale Dependence and Adaptive Capacity)

These data include sizes of organisms used to calculate growth and for community analysis and percent cover of each organism described from planar photographs. These data are results of an experiment incubating a back reef community from Moorea, French Polynesia, for one year at high pCO2 (published in Edmunds et al. 2019) from Nov of 2015 to Nov of 2016.

cdm_data_type = Other
VARIABLES:
Flume (unitless)
Analysis (unitless)
Month_Number (unitless)
Year (unitless)
Month (unitless)
ID (unitless)
Taxon (unitless)
AREA (percent (%))


[Edmunds et al. 2020 ICES: pCO2 flume - Coral area] - Coral area from a study of year-long effects of high pCO2 on the community structure of a tropical fore reef assembled in outdoor flumes in Moorea, French Polynesia from 2017 to 2018 (RUI: Ocean Acidification- Category 1- The effects of ocean acidification on the organismic biology and community ecology of corals, calcified algae, and coral reefs)

This coral calcification dataset includes the areas of corals as they changed over a year-long experiment. Flume physical and chemical conditions are provided as a supplemental file. These data are part of a study of year-long effects of high pCO2 on the community structure of a tropical fore reef assembled in outdoor flumes in Moorea, French Polynesia from 2017 to 2018.

These coral calcification data support publication (Edmunds et al., 2020; doi:10.1093/icesjms/fsaa015) with the following abstract:

In this study, fore reef coral communities were exposed to high pCO2 for a year to explore the relationship between net accretion (Gnet) and community structure (planar area growth). Coral reef communities simulating the fore reef at 17-m depth on Mo'orea, French Polynesia, were assembled in three outdoor flumes (each 500 l) that were maintained at ambient (396 matm), 782 matm, and 1434 matm pCO2, supplied with seawater at 300 l h 1, and exposed to light simulating 17-m depth. The communities were constructed using corals from the fore reef, and the responses of massive Porites spp., Acropora spp., and Pocillopora verrucosa were assessed through monthly measurements of Gnet and planar area. High pCO2 depressed Gnet but did not affect colony area by taxon, although the areas of Acropora spp. and P. verrucosa summed to cause multivariate community structure to differ among treatments. These results suggest that skeletal plasticity modulates the effects of reduced Gnet at high pCO2 on planar growth, at least over a year. The low sensitivity of the planar growth of fore reef corals to the effects of ocean acidification.

cdm_data_type = Other
VARIABLES:
Flume (unitless)
Year_Month (unitless)
Sample (unitless)
Type (unitless)
Species (unitless)
percent_area (percent (%))


[Edmunds et al. 2020 ICES: pCO2 flume - Coral weight] - Coral weight from a study of year-long effects of high pCO2 on the community structure of a tropical fore reef assembled in outdoor flumes in Moorea, French Polynesia from 2017 to 2018 (RUI: Ocean Acidification- Category 1- The effects of ocean acidification on the organismic biology and community ecology of corals, calcified algae, and coral reefs)

This coral calcification dataset includes the weight of the corals as used to report net changes in mass (Gnet). Flume physical and chemical conditions are provided as a supplemental file.  These data are part of a study of year-long effects of high pCO2 on the community structure of a tropical fore reef assembled in outdoor flumes in Moorea, French Polynesia from 2017 to 2018.

These coral calcification data support publication (Edmunds et al., 2020; doi:10.1093/icesjms/fsaa015) with the following abstract:

In this study, fore reef coral communities were exposed to high pCO2 for a year to explore the relationship between net accretion (Gnet) and community structure (planar area growth). Coral reef communities simulating the fore reef at 17-m depth on Mo'orea, French Polynesia, were assembled in three outdoor flumes (each 500 l) that were maintained at ambient (396 matm), 782 matm, and 1434 matm pCO2, supplied with seawater at 300 l h 1, and exposed to light simulating 17-m depth. The communities were constructed using corals from the fore reef, and the responses of massive Porites spp., Acropora spp., and Pocillopora verrucosa were assessed through monthly measurements of Gnet and planar area. High pCO2 depressed Gnet but did not affect colony area by taxon, although the areas of Acropora spp. and P. verrucosa summed to cause multivariate community structure to differ among treatments. These results suggest that skeletal plasticity modulates the effects of reduced Gnet at high pCO2 on planar growth, at least over a year. The low sensitivity of the planar growth of fore reef corals to the effects of ocean acidification.

cdm_data_type = Other
VARIABLES:
Flume (unitless)
Year_Month (unitless)
Sample (unitless)
Type (unitless)
Functional_group (unitless)
Species (unitless)
LTER_Site (unitless)
Weight (grams (g))


[Edmunds et al. 2023 Oecologia: Chlorophyll Concentration] - Seawater chlorophyll concentration offshore from Moorea, French Polynesia from 2008 to 2020 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

Seawater chlorophyll concentration (mg/m3) offshore from Moorea, French Polynesia from 2008 to 2020.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Month (unitless)
Chlorophyll (milligrams per meters cubed (mg/m3))


[Edmunds et al. 2023 Oecologia: Coral Cover] - Percentage cover of the benthos by live coral at 10 m depth at sites in Moorea Moorea, French Polynesia from 2008 to 2021 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

These data describe the percentage cover of the benthos by live coral at 10 m depth at sites LTER1 and LTER2 in Moorea.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Site (unitless)
depth (m)
Quad (unitless)
Pocillopora (percent (%))
All_stony_corals (percent (%))


[Edmunds et al. 2023 Oecologia: Flow Speeds] - Flow speed on the north shore of Moorea, French from 2007 to 2021 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

These data describe bottom and surface flow speed on the north shore of Moorea from 2007 to 2021.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Month (unitless)
Bottom_flow (meters per second (m/s))
Surface_flow (meters per second (m/s))


[Edmunds et al. 2023 Oecologia: Seawater Temperature] - Benthic seawater temperature at 10m depth in Moorea, French Polynesia from 2005 to 2021 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

Benthic seawater temperature from bottom-mounted thermistors deployed in Moorea, French Polynesia.
 These seawater temperature data support the temperature analysis in Edmunds et al. (2023).

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Site (unitless)
Data_Source (unitless)
ISO_Date (unitless)
... (4 more variables)


[Edmunds et al. 2023 Oecologia: Settler Density] - Density of coral settlers detected on settlement tiles each year at two 10m sites on the north shore of Moorea, French Polynesia from 2008 to 2020 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

These data describe the number of coral settlers detected on settlement tiles each year, with annual settlement determined by adding mean recruits on tiles retrieved in Jan/Feb to mean density on tiles retrieved Aug/Sept.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Site (unitless)
All_corals (number of settlers per tile)
Pocillopora (number of settlers per tile)


[Edmunds et al. 2023 Oecologia: Small Coral Density] - Density of small corals at two 10m sites on the north shore of Moorea, French Polynesia from 2005 to 2021 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

These data describe the density of small corals (colonies ≤ 4 cm diameter) in quadrats (0.5 x 0.5 m) in size on the benthos at 10 m depth at LTER1 and LTER2 on the north shore of Moorea.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Site (unitless)
Quadrat (unitless)
Pocillopora (per colony)
All_corals (per colony)


[Edmunds et al. 2023 Oecologia: Water Clarity] - Seawater clarity in Moorea, French Polynesia from 2003 to 2022 (Moorea Coral Reef Long-Term Ecological Research site)

Data Abstract:

These data describe seawater clarity (as measured through Kd490) with data accessed 15 March 2022.

Results paper abstract, Edmunds et al. (2023) :
* [See "Related Datasets" section for access to related datasets discussed here]

Understanding population dynamics is a long-standing objective of ecology, but the need for progress in this area has become urgent. For coral reefs, achieving this objective is impeded by a lack of information on settlement versus post-settlement events in determining recruitment and population size. Declines in coral abundance are often inferred to be associated with reduced densities of recruits, which could arise from mechanisms occurring at larval settlement, or throughout post-settlement stages. This study uses annual measurements from 2008 to 2021 of coral cover, the density of coral settlers (S), the density of small corals (SC), and environmental conditions, to evaluate the roles of settlement versus post-settlement events in determining rates of coral recruitment and changes in coral cover at Moorea, French Polynesia. Coral cover, S, SC, and the SC:S ratio (a proxy for post-settlement success), and environmental conditions, were used in generalized additive models (GAMs) to show that: (a) coral cover was more strongly related to SC and SC:S than S, and (b) SC:S was highest when preceded by cool seawater, low concentrations of Chlorophyll a, and low flow speeds, and S showed evidence of declining with elevated temperature. Together, these results suggest that changes in coral cover in Moorea are more strongly influenced by post-settlement events than settlement. The key to understanding coral community resilience may lie in elucidating the factors attenuating the bottleneck between settlers and small corals.

cdm_data_type = Other
VARIABLES:
UTC_time (unitless)
Kd490 (m-1)


[Edmunds et al. MarBio 2019a: Data in support of energy budget calculations] - Light data from surveys in St. John, US Virgin Islands in 2017 used to calculate photosynthetic input to coral energy budget as in Edwards et al. (2019) (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)

Light data from surveys in Great Lameshur Bay, St. John, US Virgin Islands in 2017 used to calculate photosynthetic input to coral energy budget as in Edwards et al. (2019). These data were used in Edmunds et al. (2019).

cdm_data_type = Other
VARIABLES:
Day (unitless)
Surface_Light (micromoles per square meter per second (µmol quanta/m2/s))
Kd (unitless)
Underwater_Light_at_19_m (micromoles per square meter per second (µmol quanta/m2/s))
Underwater_Light_at_10_m (micromoles per square meter per second (µmol quanta/m2/s))


[Edmunds et al. MarBio 2019a: Kd data] - Light data (Kd) from surveys conducted in St. John, US Virgin Islands in 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)

Light data (Kd) from surveys conducted in Great Lameshur Bay, St. John, US Virgin Islands in 2017. These data were used in Edmunds et al. (2019) in Figure 2.

cdm_data_type = Other
VARIABLES:
DateTime_Local (Date Time Local, unitless)
Surface_Light (micromoles per square meter per second (µmol quanta/m2/s))
Underwater_Light (micromoles per square meter per second (µmol quanta/m2/s))
Kd (unitless)
Transmition_Percent (percent)
time (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)


[Edmunds et al. MarBio 2019a: Light and rainfall data] - Light and rainfall data from surveys conducted in St. John, US Virgin Islands in 2016 and 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)

Light and rainfall data from surveys conducted at Windswept Beach and Great Lameshur Bay, St. John, US Virgin Islands in 2016 and 2017. These data were used in Edmunds et al. (2019) in Figure 1.

cdm_data_type = Other
VARIABLES:
Date (unitless)
Rainfall (centimeters (cm))
Surface_Daily_Integrated (moles per square meter per second (mol quanta/m2/s))
Underwater_1300hrs_Max_Intensity (micromoles per square meter per second (µmol quanta/m2/s))
Underwater_24H_integrated (Underwater 24 H Integrated, moles per square meter per second (mol quanta/m2/s))


[Edmunds et al. MarBio 2019a: Transmission data] - Light data (transmission) from surveys conducted in St. John, US Virgin Islands in 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)

Light data (transmission) from surveys conducted in Great Lameshur Bay, St. John, US Virgin Islands in 2017. These data were used in Edmunds et al. (2019) in Figure 2.

cdm_data_type = Other
VARIABLES:
Underwater_Date_Local (unitless)
Underwater_Time_Local (unitless)
Underwater_Light (micromoles per square meter per second (µmol quanta/m2/s))
Surface_DateTime_Local (Surface Date Time Local, unitless)
Surface_Light (micromoles per square meter per second (µmol quanta/m2/s))
Transmition_Percent (percent)
time (Surface Date Time ISO UTC, seconds since 1970-01-01T00:00:00Z)


[Eelgrass seed phenotypes] - Number and mass of eelgrass seeds collected from sediment cores in shallow and deep zones at four coastal sites in Massachusetts, USA in 2019 (RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina)

This dataset includes the number and mass of eelgrass seeds collected from sediment cores in shallow and deep zones at four different sites in Massachusetts, USA in 2019. The four sites were West Beach in Beverly (N 42.55921, W 70.80578), Curlew Beach in Nahant (N 42.42009, W 70.91553), Lynch Park in Beverly (N 42.54488, W 70.85842), and Niles Beach in Gloucester (N 42.59711, W 70.65592). Like many marine foundation species, eelgrass often spans strong environmental gradients over relatively small spatial scales - this data set provides information on seed retention and seed size across the depth gradient at multiple sites in the Gulf of Maine. Seeds measured and counted in this dataset were subsequently genotyped to infer source.

cdm_data_type = Other
VARIABLES:
Date (unitless)
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth (unitless)
Permanent_Quad (unitless)
Core (unitless)
Seed_number (unitless)
Mass (grams (g))
RAD_name (unitless)


[Eelgrass shoot density and above-ground biomass] - Quadrat-based measurements of eelgrass shoot density and above-ground biomass for plants growing in shallow and deep zones at four coastal sites in Massachusetts, USA in 2019 (RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina)

This dataset includes quadrat-based measurements of eelgrass shoot density and above-ground biomass for plants growing in shallow and deep zones at four different sites in Massachusetts, USA in 2019. The four sites were West Beach in Beverly (N 42.55921, W 70.80578), Curlew Beach in Nahant (N 42.42009, W 70.91553), Lynch Park in Beverly (N 42.54488, W 70.85842), and Niles Beach in Gloucester (N 42.59711, W 70.65592). Like many marine foundation species, eelgrass often spans strong environmental gradients over relatively small spatial scales - this data set provides information on phenotypic differentiation across the depth gradient at multiple sites in the Gulf of Maine.

cdm_data_type = Other
VARIABLES:
Date (unitless)
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth (unitless)
Permanent_Quadrat (unitless)
Vegetative_Density (number/0.25m^2)
Flowering_Density (number/0.25m^2)
Total_Density (number/0.25m^2)
Biomass (grams (g))


[Eelgrass shoot lengths] - Eelgrass shoot lengths measured at two depths within each of four coastal sites in Massachusetts, USA in 2019 (RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina)

This dataset includes eelgrass shoot lengths measured at two depths within each of four different sites in Massachusetts, USA in late June and early July 2019. Like many marine foundation species, eelgrass often spans strong environmental gradients over relatively small spatial scales - this data set provides information on phenotypic differentiation across the depth gradient at multiple sites in the Gulf of Maine.

cdm_data_type = Other
VARIABLES:
Date (unitless)
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth (unitless)
Permanent_Quadrat (unitless)
Sample_Quadrat (unitless)
Height (centimeters (cm))


[Effect of lionfish density on native reef fishes] - Effect of lionfish densities on native coral-reef fishes from Lee Stocking Island, Bahamas during 2009-2012 (Biodiversity Loss Effects Lionfish project) (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Effect of lionfish densities on native coral-reef fishes from Lee Stocking Island, Bahamas during 2009-2012 (Biodiversity Loss Effects Lionfish project)

cdm_data_type = Other
VARIABLES:
year (unitless)
reef_type (unitless)
month (unitless)
visit_number (unitless)
day (unitless)
reef_number (unitless)
time_start (unitless)
time_end (unitless)
lionfish_density_initial (count per meter squared)
lionfish_density_mean (count per meter squared)
species (unitless)
length_max_1 (count)
length_max_2 (count)
length_max_3 (count)
length_max_4 (count)
length_max_5 (count)
length_max_10 (count)
length_max_15 (count)
length_max_20 (count)
length_max_25 (count)
length_max_30 (count)
length_max_35 (count)
length_max_40 (count)
length_max_45 (count)
length_max_50 (count)
length_max_100 (count)
length_max_150 (count)
invert_count (count)
notes (unitless)


[Effect of lionfish in main seagrass habitats] - Effect of lionfish presence on native fish abundance in main reefs where lionfish resided on Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project) (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Effect of lionfish presence on native fish abundance in main reefs where lionfish resided on Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project)

cdm_data_type = Other
VARIABLES:
year (unitless)
month (unitless)
visit_number (unitless)
day (unitless)
treatment (unitless)
reef (unitless)
start (unitless)
end (unitless)
species (unitless)
length_max_1 (count)
length_max_2 (count)
length_max_3 (count)
length_max_4 (count)
length_max_5 (count)
length_max_6 (count)
length_max_7 (count)
length_max_8 (count)
length_max_9 (count)
length_max_10 (count)
length_max_15 (count)
length_max_20 (count)
length_max_25 (count)
length_max_30 (count)
length_max_35 (count)
length_max_40 (count)
length_max_45 (count)
eel_shark_count (count)
notes (unitless)


[Effect of lionfish in seagrass open area habitats] - Effect of lionfish presence on native fish abundance in open areas of seagrass habitat in Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project) (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Effect of lionfish presence on native fish abundance in open areas of seagrass habitat in Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project)

cdm_data_type = Other
VARIABLES:
year (unitless)
month (unitless)
visit_number (unitless)
day (unitless)
reef (unitless)
treatment (unitless)
time_start (unitless)
time_end (unitless)
transect_number (unitless)
transect_direction (degrees)
transect_distance (meters)
habitat (unitless)
present (unitless)
species (unitless)
length_max_1 (count)
length_max_2 (count)
length_max_3 (count)
length_max_4 (count)
length_max_5 (count)
length_max_6 (count)
length_max_7 (count)
length_max_8 (count)
length_max_9 (count)
length_max_10 (count)
length_max_15 (count)
notes (unitless)


[Effect of lionfish in seagrass satellite coral head habitats] - Effect of lionfish presence on native fish abundance on satellite coral heads in seagrass habitats on Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project) (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Effect of lionfish presence on native fish abundance on satellite coral heads in seagrass habitats on Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project)

cdm_data_type = Other
VARIABLES:
year (unitless)
month (unitless)
visit_number (unitless)
day (unitless)
treatment (unitless)
reef (unitless)
start (unitless)
end (unitless)
satellite_number (unitless)
satellite_distance (meters)
satellite_size (meters squared)
species (unitless)
length_max_1 (count)
length_max_2 (count)
length_max_3 (count)
length_max_4 (count)
length_max_5 (count)
length_max_6 (count)
length_max_7 (count)
length_max_8 (count)
length_max_9 (count)
length_max_10 (count)
length_max_15 (count)
length_max_20 (count)
length_max_25 (count)
length_max_30 (count)
... (5 more variables)


[Effect of lionfish in standardized habitat units in seagrass] - Effect of lionfish presence on native fish abundance in standardized habitat units in seagrass in Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project) (Mechanisms and Consequences of Fish Biodiversity Loss on Atlantic Coral Reefs Caused by Invasive Pacific Lionfish)

Effect of lionfish presence on native fish abundance in standardized habitat units in seagrass in Eleuthera, Bahamas during 2013 (Biodiversity Loss Effects Lionfish project)

cdm_data_type = Other
VARIABLES:
year (unitless)
survey_type (unitless)
month (unitless)
visit_number (unitless)
day (unitless)
treatment (unitless)
reef (unitless)
time_start (unitless)
time_end (unitless)
shu_row (unitless)
distance (meters)
presence (unitless)
species (unitless)
length_max_1 (count)
length_max_2 (count)
length_max_3 (count)
length_max_4 (count)
length_max_5 (count)
length_max_6 (count)
length_max_7 (count)
length_max_8 (count)
length_max_9 (count)
length_max_10 (count)
length_max_15 (count)
notes (unitless)


[Effect of phenotypic variation on dogwhelk morphology during eco-evolutionary field experiment] - Effect of phenotypic variation on dogwhelk morphology during an eco-evolutionary field experiment (Coastal mosaics of local adaptation and the eco-evolutionary dynamics of a marine predator-prey interaction)

Although there is a growing body of work indicating that ecological and evolutionary processes can have reciprocal feedbacks on one another, few studies have tested these feedbacks in natural field settings at the community level. We tested the ecological consequences of selection on intra-population variation in dogwhelk drilling. We reared juvenile dogwhelks (Nucella canaliculata) on four early-life diet treatments (thin-shelled Mytilus trossulus, two treatments of M. californianus from two populations known to differ in adult shell thickness, and acorn barnacles) and then outplanted the dogwhelks to field cages to quantify the community effects of variation in drilling phenotype on mussel bed succession over a year. Changes in Nucella canaliculata morphology (change in length) were determined over the course of the experiment.

cdm_data_type = Other
VARIABLES:
Block (unitless)
Plot_Number (unitless)
Plot_Tidal_Height (meters (m))
Family (unitless)
Site_Latitude (degrees_north)
longitude (Site_longitude, degrees_east)
Treatment (unitless)
Family_x_Treatment (unitless)
Snail_ID (unitless)
Snail_Tag (unitless)
Sex (unitless)
Length_initial (millimeters (mm))
Length_final (millimeters (mm))
Length_change (millimeters (mm))
Dead_vs_Replaced_vs_Never_found (unitless)
Date_dead_or_replaced (unitless)


[Effects of early-life diet on mortality of juvenile Nucella canaliculata] - Effects of early-life diet on mortality of juvenile Nucella canaliculata quantified in the laboratory after 3 months on experimental diets (Coastal mosaics of local adaptation and the eco-evolutionary dynamics of a marine predator-prey interaction)

The field of eco-evolutionary dynamics analyzes the reciprocal impacts that ecological and evolutionary processes have on one another on contemporary timescales. A promising approach for studying eco-evolutionary dynamics is to explore whether variation acting over rapid timescales can impose selection on existing within population-variation in functional traits. The Bodega Marine Reserve population of the Channeled Dogwhelk, Nucella canaliculata, contains a mix of drilling phenotypes. A selection experiment was performed to determine the effects of four early-life diet treatments (thin-shelled Mytilus trossulus mussels, two treatments of M. californianus from two populations known to differ in shell thickness, and acorn barnacles) on N. canaliculata phenotype. Dogwhelks were hatched in the laboratory and mortality of juvenile dogwhelks was quantified in the laboratory after 3 months on the experimental diets.

cdm_data_type = Other
VARIABLES:
Family (unitless)
Population (unitless)
Site_Latitude (degrees_north)
longitude (Site_longitude, degrees_east)
Treatment (unitless)
Three_Month_Mortality (percent (%))


[Effects of early-life diet on Nucella canaliculata drilling phenotype] - Effects of early-life diet on Nucella canaliculata drilling phenotype quantified in the laboratory after rearing on different prey treatments (Coastal mosaics of local adaptation and the eco-evolutionary dynamics of a marine predator-prey interaction)

The growing field of eco-evolutionary dynamics has highlighted the importance of reciprocal feedbacks between evolutionary and ecological processes. We tested whether selection could act on existing within-population variation in a predatory trait in the marine dogwhelk, Nucella canaliculata. We reared newly hatched dogwhelks on four prey treatments (thin-shelled Mytilus trossulus, two treatments of M. californianus from two populations known to differ in adult shell thickness, and acorn barnacles). To quantify dogwhelk phenotype, we tested the surviving adult dogwhelks on their ability to drill mid-sized (5-7cm long) M. californianus. We found evidence that dogwhelk phenotype varied among the early-life diet treatments.

cdm_data_type = Other
VARIABLES:
Container (unitless)
Round (unitless)
Population (unitless)
Site_Latitude (degrees_north)
longitude (Site_longitude, degrees_east)
Family (unitless)
Treatment (unitless)
Family_x_Treatment (unitless)
Snail (unitless)
Drilled_Binary (unitless)
Total_Drilled (unitless)
Check_1 (unitless)
Check_2 (unitless)
Check_3 (unitless)
Check_4 (unitless)
Check_5 (unitless)
Dead (unitless)


[Effects of intra-population variation in dogwhelk drilling on the abundance and size of Mytilus californianus mussels] - Effects of intra-population variation in dogwhelk drilling on the abundance and size of Mytilus californianus mussels (Coastal mosaics of local adaptation and the eco-evolutionary dynamics of a marine predator-prey interaction)

Few eco-evolutionary studies have analyzed the impacts that evolutionary processes have on community dynamics in a natural field setting. We studied the effects of intra-population variation in predation in a marine dogwhelk (Nucella canaliculata) on mussel bed succession. We outplanted dogwhelks that were reared on four early-life diet treatments and showed evidence of differential mortality and variation in drilling capacity in the lab to experimental field cages and followed the trajectory of succession over the course of a year. At the end of the experiment, the organisms within the cages were collected and the mussels (Mytilus californianus) were measured. Mussels represent the end stage of succession, thus we studied whether variation in drilling traits would impact the size and structure of the mussel bed.

cdm_data_type = Other
VARIABLES:
Block (unitless)
Plot_Number (unitless)
Site_Latitude (degrees_north)
longitude (Site_longitude, degrees_east)
Date (unitless)
Length (millimeters (mm))
Live_vs_Dead (unitless)


[Effects of protists on HBx predation] - Population changes in Halobacteriovorax cultured with protist & prey (Excellence in Research: Assessing the Control by Multiple Micropredators on Bacterial Communities in Estuarine Environments and Characterization of Prey Lysis Products Resulting from Each Predator)

Here, we investigate the growth trajectory and predation dynamics of protists, and HBx micro-predators in co-culture with a common prey, V. parahaemolyticus, in a time-series study in marine water microcosms. The microcosms were established with water samples collected from the Apalachicola Bay in northwest Florida, USA and amended with a suspension of prey bacteria. Samples were taken at a high temporal resolution (3-hour intervals for 5 days) to capture detailed measurements and changes in the growth responses of HBx and protists, using both culture- and molecular-based methods. The protists were counted by qPCR and flow cytometry. The HBx were counted by qPCR and a culture plating method

cdm_data_type = Other
VARIABLES:
Treatment (unitless)
Time (hours)
Optical_Density (OD units)
Protists (counts per ml)
Vibrio (gene copies per reaction)
Halobacteriovorax (gene copies per reaction)


[Egg sizes and macromere allocation] - Egg sizes and macromere allocation for diverse annelids and molluscs (Feeding by the ciliated larvae of marine invertebrates: effects of diverse particle capture mechanisms on feeding performance)

Egg sizes and macromere allocation for annelids and molluscs used in a comparative analysis of allocation of cytoplasm to macromeres. Many of these data were obtained from the literature, but some were obtained directly by the authors.

cdm_data_type = Other
VARIABLES:
taxon (unitless)
species (unitless)
nutrition (unitless)
taxa (unitless)
egg_diameter (micrometers (um))
egg_volume (cubic micrometer (um3))
allocation (unitless)
alloc_pcnt (unitless)
log_egg_diameter (micrometers (um))
log_egg_volume (cubic micrometer (um3))
logit_allocation (unitless)


[Ehux elemental composition across thermal range] - Elemental stoichiometry for Emiliania huxleyi across a range of 12 temperatures from 8.5-28.6C (How does intensity and frequency of environmental variability affect phytoplankton growth?)

This dataset includes elemental stoichiometry for Emiliania huxleyi across a range of 12 temperatures from 8.5-28.6C. Global warming will be combined with predicted increases in thermal variability in the future surface ocean, but how temperature dynamics will affect phytoplankton biology and biogeochemistry is largely unknown. Here, we examine the responses of the globally important marine coccolithophore Emiliania huxleyi to thermal variations at two frequencies (1 d and 2 d) at low (18.5 \u00b0C) and high (25.5 \u00b0C) mean temperatures. Elevated temperature and thermal variation decreased growth, calcification and physiological rates, both individually and interactively. The 1 d thermal variation frequencies were less inhibitory than 2 d variations under high temperatures, indicating that high-frequency thermal fluctuations may reduce heat-induced mortality and mitigate some impacts of extreme high-temperature events. Cellular elemental composition and calcification was significantly affected by both thermal variation treatments relative to each other and to the constant temperature controls. The negative effects of thermal variation on E. huxleyi growth rate and physiology are especially pronounced at high temperatures. These responses of the key marine calcifier E. huxleyi to warmer, more variable temperature regimes have potentially large implications for ocean productivity and marine biogeochemical cycles under a future changing climate.

cdm_data_type = Other
VARIABLES:
Temperature (degrees Celsius)
TPC_PON (unitless)
PIC_POC (unitless)
Chla_POC (Concentration Of Chlorophyll In Sea Water, milligrams/gram)
POC_PON (unitless)


[Ehux growth rates for thermal response curve] - Growth rates for Emiliania huxleyi thermal response curve across 12 temperatures from 8.5-28.6C (How does intensity and frequency of environmental variability affect phytoplankton growth?)

This dataset presents growth rates for Emiliania huxleyi thermal response curve across 12 temperatures from 8.5-28.6C.Global warming will be combined with predicted increases in thermal variability in the future surface ocean, but how temperature dynamics will affect phytoplankton biology and biogeochemistry is largely unknown. Here, we examine the responses of the globally important marine coccolithophore Emiliania huxleyi to thermal variations at two frequencies (1 d and 2 d) at low (18.5 \u00b0C) and high (25.5 \u00b0C) mean temperatures. Elevated temperature and thermal variation decreased growth, calcification and physiological rates, both individually and interactively. The 1 d thermal variation frequencies were less inhibitory than 2 d variations under high temperatures, indicating that high-frequency thermal fluctuations may reduce heat-induced mortality and mitigate some impacts of extreme high-temperature events. Cellular elemental composition and calcification was significantly affected by both thermal variation treatments relative to each other and to the constant temperature controls. The negative effects of thermal variation on E. huxleyi growth rate and physiology are especially pronounced at high temperatures. These responses of the key marine calcifier E. huxleyi to warmer, more variable temperature regimes have potentially large implications for ocean productivity and marine biogeochemical cycles under a future changing climate.

cdm_data_type = Other
VARIABLES:
Temperature (degrees Celsius)
Growth_Rate (per day)


[Ehux growth rates under thermal variation] - Growth rates under low and high temperatures for Emiliania huxleyi in constant and fluctuating thermal environments (How does intensity and frequency of environmental variability affect phytoplankton growth?)

This dataset includes the growth rates under low and high temperatures for E. huxleyi in constant and fluctuating thermal environments. Global warming will be combined with predicted increases in thermal variability in the future surface ocean, but how temperature dynamics will affect phytoplankton biology and biogeochemistry is largely unknown. Here, we examine the responses of the globally important marine coccolithophore Emiliania huxleyi to thermal variations at two frequencies (1 d and 2 d) at low (18.5 \u00b0C) and high (25.5 \u00b0C) mean temperatures. Elevated temperature and thermal variation decreased growth, calcification and physiological rates, both individually and interactively. The 1 d thermal variation frequencies were less inhibitory than 2 d variations under high temperatures, indicating that high-frequency thermal fluctuations may reduce heat-induced mortality and mitigate some impacts of extreme high-temperature events. Cellular elemental composition and calcification was significantly affected by both thermal variation treatments relative to each other and to the constant temperature controls. The negative effects of thermal variation on E. huxleyi growth rate and physiology are especially pronounced at high temperatures. These responses of the key marine calcifier E. huxleyi to warmer, more variable temperature regimes have potentially large implications for ocean productivity and marine biogeochemical cycles under a future changing climate.

cdm_data_type = Other
VARIABLES:
Growth_Rate (per day)
Temperature (degrees Celsius)
variation (unitless)


[Ehux physiology under thermal variation] - Intracellular elemental quotas under low and high temperatures for E. huxleyi in constant and fluctuating thermal environments (How does intensity and frequency of environmental variability affect phytoplankton growth?)

Intracellular elemental quotas under low and high temperatures for E. huxleyi in constant and fluctuating thermal environments. This dataset includes the growth rates under low and high temperatures for E. huxleyi in constant and fluctuating thermal environments. Global warming will be combined with predicted increases in thermal variability in the future surface ocean, but how temperature dynamics will affect phytoplankton biology and biogeochemistry is largely unknown. Here, we examine the responses of the globally important marine coccolithophore Emiliania huxleyi to thermal variations at two frequencies (1 d and 2 d) at low (18.5 \u00b0C) and high (25.5 \u00b0C) mean temperatures. Elevated temperature and thermal variation decreased growth, calcification and physiological rates, both individually and interactively. The 1 d thermal variation frequencies were less inhibitory than 2 d variations under high temperatures, indicating that high-frequency thermal fluctuations may reduce heat-induced mortality and mitigate some impacts of extreme high-temperature events. Cellular elemental composition and calcification was significantly affected by both thermal variation treatments relative to each other and to the constant temperature controls. The negative effects of thermal variation on E. huxleyi growth rate and physiology are especially pronounced at high temperatures. These responses of the key marine calcifier E. huxleyi to warmer, more variable temperature regimes have potentially large implications for ocean productivity and marine biogeochemical cycles under a future changing climate.

cdm_data_type = Other
VARIABLES:
Temperature (degrees Celsius)
variation (unitless)
POC (Particulate Organic Carbon, picograms/cell)
PIC (Particulate Inorganic Carbon, picograms/cell)
PON (picograms/cell)
TPC (picograms/cell)
POP (picograms/cell)
Chla (Concentration Of Chlorophyll In Sea Water, picograms/cell)
carbon_fix_rate (10 -7 umol Carbon cell-1 hr-1)
photosyn_rate (10 -7 umol Carbon cell-1 hr-1)
... (7 more variables)


[EK80 Antarctic Krill Swarms] - Krill swarms detected with active acoustic EK80 onboard small boat surveys in Palmer Deep Canyon, Antarctica during January-March 2020 (Collaborative Research: Physical Mechanisms Driving Food Web Focusing in Antarctic Biological Hotspots)

These data include identified krill swarms observed by a hull-mounted SIMRAD EK80 single-beam, single frequency (120 kHz) echo sounder (Kongsberg Maritime) hereby referred to as “EK80”. Data were collected in Palmer Deep Canyon, Antarctica during January-March 2020. Small boat surveys were conducted twice weekly over known penguin foraging areas. EK80 data were processed using Echoview software and backscattering zooplankton were identified as krill when within a target strength of -70 dB to -30 dB.

The EK80 survey was designed in concert with the ACROBAT, HFR and mooring observations to provide a wholistic view of the food web. Observing the distribution of krill swarms and their correlation with other ecosystem variables is important for understanding how the Palmer Deep ecosystem, and other coastal ecosystems globally, respond to complex coastal ocean currents and ways this system may be resilient to rapid warming. The collection and processing of these data was headed by Ashley Hann and Dr. Kim Bernard.

cdm_data_type = Other
VARIABLES:
Date_M (unitless)
Time_M (unitless)
time (Iso8601, seconds since 1970-01-01T00:00:00Z)
longitude (Lon_m, degrees_east)
latitude (Lat_m, degrees_north)
depth (Depth_mean, m)
Sv_mean (dB)
NASC (m²/nmi²)
Height_mean (Meters (m))
Thickness_mean (Meters (m))
Length (Meters (m))
mld (Meters (m))
surface (Binary)


[Elacatinus lori habitat preferences] - Preferences of E. Lori settlers on sponge habitat in South Water Caye, Belize during 2011 and 2017. (Collaborative Research: The Role of Larval Orientation Behavior in Determining Population Connectivity)

Preferences of E. Lori settlers on sponge habitat in South Water Caye, Belize during 2011 and 2017.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Exp (unitless)
Cues (unitless)
Trial_n (unitless)
Settler_origin (unitless)
SL (millimeters)
Choice_nochoice (unitless)
Habitat_choice (unitless)
Bearing (degrees)
Current_direction (degrees)
Current_speed (centimeters per second)


[Electrochemical Data CL2015] - Electrochemical data from sediments collected on R/V Savannah cruise SAV-15-18 at the Cape Lookout Continental Shelf and Slope during July 2015 (Source, Composition, and Stability of Soluble Iron Fluxing from Continental Margin Sediments)

Electrochemistry data from sediments collected on R/V Savannah cruise SAV-15-18 at the Cape Lookout Continental Shelf and Slope during July 2015.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Month (unitless)
Day (unitless)
Collection_Type (unitless)
Station (unitless)
longitude (degrees_east)
latitude (degrees_north)
Sediment_depth (millimeters (mm))
O2 (micromolar (uM))
sdO2 (Sd O2, micromolar (uM))
Mn_II (micromolar (uM))
sdMn_II (Sd Mn II, micromolar (uM))
Fe_II (micromolar (uM))
sdFe_II (Sd Fe II, micromolar (uM))
Org_Fe_III (nA)
sdOrgFe_III (Sd Org Fe III, nA)
FeS_aq (Fe S Aq, nA)
sdFeS_aq (Sd Fe S Aq, nA)
SH2S (SH2 S, micromolar (uM))
sdSH2S (SD SH2 S, micromolar (uM))
time (seconds since 1970-01-01T00:00:00Z)


[Electrochemical Data CL2016] - Electrochemical data from sediments collected on R/V Savannah cruise SAV-16-16 at the Cape Lookout Continental Shelf and Slope during May 2016 (Source, Composition, and Stability of Soluble Iron Fluxing from Continental Margin Sediments)

Electrochemical data from sediments collected on R/V Savannah cruise SAV-16-16 at the Cape Lookout Continental Shelf and Slope during May 2016.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Month (unitless)
Day (unitless)
Collection_Type (unitless)
Station (unitless)
longitude (degrees_east)
latitude (degrees_north)
Sediment_depth (millimeters (mm))
O2 (uM (micromolar))
sdO2 (Sd O2, uM (micromolar))
Mn_II (uM (micromolar))
sdMn_II (Sd Mn II, uM (micromolar))
Fe_II (uM (micromolar))
sdFe_II (Sd Fe II, uM (micromolar))
Org_Fe_III (nA)
sdOrgFe_III (Sd Org Fe III, nA)
FeS_aq (Fe S Aq, nA)
sdFeS_aq (Sd Fe S Aq, nA)
SH2S (SH2 S, uM (micromolar))
sdSH2S (SD SH2 S, uM (micromolar))
date (unitless)


[Electrochemical Data GoM2017] - Electrochemical data from sediments collected on R/V Savannah cruise SAV-17-15 in the Gulf of Mexico during July and August 2017 (Source, Composition, and Stability of Soluble Iron Fluxing from Continental Margin Sediments)

Electrochemical data from sediments collected on R/V Savannah cruise SAV-17-15 in the Gulf of Mexico during July and August 2017.

cdm_data_type = Other
VARIABLES:
Year (unitless)
Month (unitless)
Day (unitless)
Collection_Type (unitless)
Station (unitless)
longitude (degrees_east)
latitude (degrees_north)
Sediment_depth (millimeters (mm))
O2 (uM (micromolar))
sdO2 (Sd O2, uM (micromolar))
Mn_II (uM (micromolar))
sdMn_II (Sd Mn II, uM (micromolar))
Fe_II (uM (micromolar))
sdFe_II (Sd Fe II, uM (micromolar))
Org_Fe_III (nA)
sdOrgFe_III (Sd Org Fe III, nA)
SH2S (SH2 S, micromolar (uM))
sdSH2S (SD SH2 S, micromolar (uM))
FeS_aq (Fe S Aq, nA)
sdFeS_aq (Sd Fe S Aq, nA)
S2O3 (S2 O3, micromolar (uM))
sdS2O3 (Sd S2 O3, micromolar (uM))
date (unitless)


[Electron microprobe elemental bulk composition from seafloor sulfide deposits East Pacific Rise 9-10 North] - Electron microprobe elemental bulk composition from seafloor sulfide deposits East Pacific Rise 9-10 North (Collaborative Research: From hot to cold in the dark - shifts in seafloor massive sulfide microbial communities as physical and geochemical conditions change after venting ceases)

Electron microprobe elemental bulk composition were collected for seafloor sulfide deposits. Seafloor sulfide mineral samples were collected from hydrothermally active chimneys and inactive off-axis massive sulfide deposits at East Pacific Rise (EPR) 9.50°N in 2019-2021 on cruises AT42-09, AT42-21 and RR2102. Samples were collected using the HOV Alvin or ROV JASON II. Samples were placed in a positive-pressure glove bag flushed with N2 (g), sparged with N2, heat-sealed into mylar bags containing Anaeropaks, and stored at -20°C.

Epoxy embedded petrographic thin sections were created using these samples. Subsamples were dried for 24 hours under N2 (g), vacuum embedded in epoxy resin (Struers EpoFix Resin, 1L kit: Part #40200030) following manufacturer's guidelines, and cured under N2 (g) for 24 hours. Each epoxy-embedded sample was pre-cut using a wafering saw then sent to Spectrum Petrographics, Inc. (Washington, USA) for preparation as 30 micron thick, double-polished thin sections mounted on quartz slides using methods to limit sample exposure to water and ambient air. When not in use, thin-sections were stored under N2 (g) to limit oxidation. Thin sections were analyzed for electron microprobe bulk elemental data using a JEOL JXA-8530FPlus Electron Probe Microanalyzer at the Electron Microprobe Laboratory, Earth and Environmental Sciences-Twin Cities, University of Minnesota.

cdm_data_type = Other
VARIABLES:
Sample_name (unitless)
Map_name (unitless)
replicate_ID (unitless)
original_source_filename (unitless)
latitude (Latitude_dd, degrees_north)
longitude (Longitude_dd, degrees_east)
depth (Depth_mbs, m)
Heading_deg (degrees)
Date_collected_MMDDYYYY (unitless)
Time_collected (unitless)
weight_concentration_percentage_O (weight percent (wt %))
... (33 more variables)


[Emergence trap sampling of gnathiid isopods at Lizard Island 2016-2018] - Emergence trap sampling of gnathiid isopods at Lizard Island, GBR, Australia from 2016-2018 (Beyond Cleaning and Symbiosis: Ecology of 'Ticks of the Sea' on Coral Reefs)

This dataset contains abundance data for Gnathiid isopods, as well as collection metadata. These data were collected as part of a long-term monitoring study of fish-parasitic gnathiid isopods on shallow patch reefs at Lizard Island, Great Barrier Reef, Australia. The data cover the period from 2000 to 2018. Gnathiid isopods, which spend most of their life free-living, were collected using 1-meter square by 1-meter high pyramid-shaped emergence traps placed randomly on the substrate. The total soak time for the traps was approximately 24 hours, divided into day vs night periods. Some of the patch reefs had cleaner fish, which are known predators of gnathiid isopods, removed over the course of the study (removal) while for others, cleaner fish remained (control).

cdm_data_type = Other
VARIABLES:
Area_sampled_identifier (unitless)
Sampling_date_identifier (unitless)
Sampling_trip_number (unitless)
Trap_identity (unitless)
Monthyear (unitless)
Site (unitless)
Reef_identity (unitless)
Cleaner_presence_treatment (unitless)
Daynight (unitless)
Vial_identity (unitless)
Isopod_count (unitless)
Time_of_day (unitless)
Soaktime (unitless)
Fullmoondate (unitless)
Lunation_number (unitless)
Fullmoondate_number (unitless)
Day_sampled (unitless)


[emet_W15_1995] - Meteorology and sea surface (MET) 15 minute averaged data from eleven R/V Endeavor cruises  in the Gulf of Maine and Georges Bank area during 1995 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface (MET) 15 minute averaged data from eleven R/V Endeavor cruises  in the Gulf of Maine and Georges Bank area during 1995.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W15_1996] - Meteorology and sea surface temperature (MET) 15 minute averaged data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 15 minute averaged data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W15_1997] - Meteorology and sea surface temperature (MET) 15 minute averaged data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 15 minute averaged data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W15_1998] - Meteorology and sea surface temperature (MET) 15 minute averaged data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 15 minute averaged data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W15_1999] - Meteorology and sea surface temperature (MET) 15 minute averaged data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 15 minute averaged data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W1_1995] - Meteorology and sea surface temperature (MET) 1 minute data from eleven R/V Endeavor cruises in the Gulf of Maine and Georges Bank area during 1995 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 1 minute data from eleven R/V Endeavor cruises in the Gulf of Maine and Georges Bank area during 1995.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
speed_trim (meters/second)
... (4 more variables)


[emet_W1_1996] - Meteorology and sea surface temperature (MET) 1 minute data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 1 minute data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
speed_trim (meters/second)
... (4 more variables)


[emet_W1_1997] - Meteorology and sea surface temperature (MET) 1 minute data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 1 minute data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
speed_trim (meters/second)
... (4 more variables)


[emet_W1_1998] - Meteorology and sea surface temperature (MET) 1 minute data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 1 minute data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
speed_trim (meters/second)
... (4 more variables)


[emet_W1_1999] - Meteorology and sea surface temperature (MET) 1 minute data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 1 minute data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
speed_trim (meters/second)
... (4 more variables)


[emet_W60_1995] - Meteorology and sea surface (MET) 60 minute averaged data from eleven R/V Endeavor cruises in the Gulf of Maine and Georges Bank area during 1995 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface (MET) 60 minute averaged data from eleven R/V Endeavor cruises in the Gulf of Maine and Georges Bank area during 1995.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/mete r^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W60_1996] - Meteorology and sea surface temperature (MET) 60 minute averaged data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 60 minute averaged data from six R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1996.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W60_1997] - Meteorology and sea surface temperature (MET) 60 minute averaged data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 60 minute averaged data from fourteen R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1997.

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W60_1998] - Meteorology and sea surface temperature (MET) 60 minute averaged data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 60 minute averaged data from eight R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1998

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[emet_W60_1999] - Meteorology and sea surface temperature (MET) 60 minute averaged data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999 (GB project) (U.S. GLOBEC Georges Bank)

Meteorology and sea surface temperature (MET) 60 minute averaged data from twenty R/V Endeavor and R/V Oceanus cruises in the Gulf of Maine and Georges Bank area during 1999

cdm_data_type = Other
VARIABLES:
cruiseid
year
si
month_gmt
day_gmt
time_gmt (hoursandminutes)
latitude (degrees_north)
longitude (degrees_east)
depth_w (Depth, meters)
depth_cs (Depth, meters)
wind_speed_c (Wind Speed, meters/second)
wind_dir_c (Wind From Direction, degrees)
wind_speed_r (Wind Speed, meters/second)
wind_dir_r (Wind From Direction, degrees)
temp_air (degreesC)
humidity (percent)
press_bar (millibars)
precip_level (centimeters)
ed_sw (watts/meter^2/second)
ed_lw (watts/meter^2/second)
temp_ss1 (degreesC)
temp_ss3 (degreesC)
temp_ss5 (degreesC)
cond_mM (Cond M M, mmho/centimeter)
sal_ss3 (PSU)
yrday_gmt (decimalday)
numb_records


[Emiliania size and chemical characteristics] - Cell size and chemical characteristics of five strains of coccolithophore Emiliania huxleyi (Protist signaling project) (Environmental stress and signaling based on reactive oxygen species among planktonic protists)

Cell size and chemical characteristics of five strains of coccolithophore Emiliania huxleyi (Protist signaling project)

cdm_data_type = Other
VARIABLES:
data_type (unitless)
CCMP1516 (unitless)
CCMP3268 (unitless)
CCMP3266 (unitless)
CCMP2668 (unitless)
NEZH (unitless)


[EN321fcmbact] - Bacteria counts from Flow Cytometry from R/V Endeavor cruise EN321 to the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program (GB project) (U.S. GLOBEC Georges Bank)

Bacteria counts from Flow Cytometry from R/V Endeavor cruise EN321 to the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program.

cdm_data_type = Other
VARIABLES:
cast
month_gmt
day_gmt
time_gmt (hours and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
number (cells per milliliter)


[EN321fcmnano] - Nanoplankton from flow cytometry from R/V Endeavor cruise EN321 to the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program (GB project) (U.S. GLOBEC Georges Bank)

Nanoplankton from flow cytometry from R/V Endeavor cruise EN321 to the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program.

cdm_data_type = Other
VARIABLES:
cast
month_gmt
day_gmt
time_gmt (hours and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
cell_lt2um (cells per milliliter)
cell_2to10um (cells per milliliter)
cell_gt10um (cells per milliliter)
crypto (cells per milliliter)
cyano (cells per milliliter)
pico_euks (cells per milliliter)


[EN325fcmbact] - Bacteria counts from flow cytometry on R/V Endeavor cruise EN325 in the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program (GB project) (U.S. GLOBEC Georges Bank)

Bacteria counts from flow cytometry on R/V Endeavor cruise EN325 in the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program.

cdm_data_type = Other
VARIABLES:
cast
month_gmt
day_gmt
time_gmt (hours and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
number (cells per milliliter *106)