[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)


[EN556 bulk peptidase hydrolysis rates - plate reader] - Hydrolysis rates from bulk samples, plate reader results from RV/Endeavor EN556, 2015 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

This dataset includes polysaccharide hydrolysis rates to measure microbial enzyme activities and bacterial productivity, from bulk samples, plate reader results from RV/Endeavor EN556, 2015.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_no (Depth, unitless)
depth (m)
substrate (unitless)
rep1_rate (nanomol monosaccharide/liter/hour)
rep2_rate (nanomol monosaccharide/liter/hour)
rep3_rate (nanomol monosaccharide/liter/hour)
average (nanomol monosaccharide/liter/hour)
std_dev (nanomol monosaccharide/liter/hour)


[EN556 bulk water polysaccharide hydrolysis rates] - Hydrolysis rates from bulk water sample incubations from R/V Endeavor cruise EN556 in 2015 (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

This dataset includes polysaccharide hydrolysis rates to measure microbial enzyme activities and bacterial productivity.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_no (Depth, unitless)
depth (m)
substrate (unitless)
timepoint (unitless)
time_elapsed_hr (hours)
rep1_rate (nanomol monosaccharide/liter/hour)
rep2_rate (nanomol monosaccharide/liter/hour)
rep3_rate (nanomol monosaccharide/liter/hour)
average (nanomol monosaccharide/liter/hour)
std_dev (nanomol monosaccharide/liter/hour)


[EN556 gravity filtered particle-associated bacterial production] - Bacterial protein production on particles obtained by gravity filtration of water collected on RV/Endeavor EN556 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

Experiments on (operationally defined) particles were carried out by gravity-filtering water through 3 micron pore size filters. Bacterial protein production was measured from 3H-leucine incorporation by heterotrophic bacteria. See Niskin Bottle and Cast List EN556 to link specific casts and bottles to each experiment: https://www.bco-dmo.org/dataset/717427.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
cast (unitless)
station (unitless)
depth_id (Depth, unitless)
depth (m)
lat_degdecmin (Latitude, degrees and decimal minutes)
lon_degdecmin_W (Longitude, degrees and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature, degrees Celsius)
salinity (Sea Water Practical Salinity, per mil)
timepoint (unitless)
time_elapsed_hr (hours)
Leu_3H_rep_1 (Leu 3 H Rep 1, picomol leucine/liter/hour)
Leu_3H_rep_2 (Leu 3 H Rep 2, picomol leucine/liter/hour)
Leu_3H_rep_3 (Leu 3 H Rep 3, picomol leucine/liter/hour)


[EN556 gravity filtered peptidase hydrolysis rates - plate reader] - Hydrolysis rates from incubations on particles obtained by gravity filtration of water collected on RV/Endeavor EN556 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

This dataset includes polysaccharide hydrolysis rates to measure microbial enzyme activities and bacterial productivity at multiple time points. The water was from gravity filtration samples.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_no (Depth, unitless)
depth (m)
substrate (unitless)
timepoint (unitless)
time_elapsed_hr (hours)
rep1_rate (nanomol monosaccharide/liter/hour)
rep2_rate (nanomol monosaccharide/liter/hour)
average (nanomol monosaccharide/liter/hour)
std_dev (nanomol monosaccharide/liter/hour)
filter_um (microns)


[EN556 gravity filtered polysaccharide/glucosidase hydrolysis rates] - Hydrolysis rates from gravity filtered samples, plate reader results from RV/Endeavor EN556, 2015 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

This dataset includes polysaccharide hydrolysis rates to measure microbial enzyme activities and bacterial productivity. The water was from gravity filtration samples.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_no (Depth, unitless)
depth (m)
substrate (unitless)
rep1_1_rate (nanomol monosaccharide/liter/hour)
rep2_1_rate (nanomol monosaccharide/liter/hour)
rep3_1_rate (nanomol monosaccharide/liter/hour)
rep1_2_rate (nanomol monosaccharide/liter/hour)
rep2_2_rate (nanomol monosaccharide/liter/hour)
rep3_2_rate (nanomol monosaccharide/liter/hour)
average (nanomol monosaccharide/liter/hour)
std_dev (nanomol monosaccharide/liter/hour)
filter_um (microns)


[EN556 LV incubations: DOC, bacterial cell concentration, and bacterial production] - Large volume incubation: DOC, bacterial cell concentration and production from RV/Endeavor EN556, June 2015 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

Bacterial protein production, cell counts, and DOC were measured in mesocosm incubations after half the mesocosms were amended with Thalasiosira. See Niskin Bottle and Cast List EN556 to link specific casts and bottles to each experiment: https://www.bco-dmo.org/dataset/717427.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
timepoint (unitless)
time_elapsed_hr (hours)
depth_id (Depth, unitless)
depth (m)
lat_degdecmin (Latitude, degrees and decimal minutes)
lon_degdecmin_W (Longitude, degrees and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
cast (unitless)
temp (Temperature, degrees Celsius)
salinity (Sea Water Practical Salinity, per mil)
treatment (unitless)
meso_no (unitless)
DOC_uM (DOC U M, micromolar)
cells_per_mL (Cells Per M L, cells/milliliter)
Leu_3H_rep_1 (Leu 3 H Rep 1, pico mol leucine/hour)


[EN556 seawater measurements and initial conditions] - Measurements of nutrients, bacterial cell concentration and bacterial production from RV/Endeavor EN556, June 2015 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

Nutrients, bacterial cell counts, and bacterial protein production as measured by 3H-leucine incorporation from the 'bulk water experiments'. Water was collected on EN556. See Niskin Bottle and Cast List EN556 to link specific casts and bottles to each experiment: https://www.bco-dmo.org/dataset/717427.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_id (Depth, unitless)
depth (m)
lat_degdecmin (Latitude, degrees and decimal minutes)
lon_degdecmin_W (Longitude, degrees and decimal minutes)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature, degrees Celsius)
salinity (Sea Water Practical Salinity, per mil)
timepoint (unitless)
time_elapsed_hr (hours)
NO2_NO3_uM (Mole Concentration Of Nitrate In Sea Water, micromolar)
NH4_uM (Mole Concentration Of Ammonium In Sea Water, micromolar)
PO4_uM (Mass Concentration Of Phosphate In Sea Water, micromolar)
DOC_uM (DOC U M, micromolar)
cells_per_mL (Cells Per M L, cells/milliliter)
Leu_3H_rep_1 (Leu 3 H Rep 1, pico mol leucine/hour)
Leu_3H_rep_2 (Leu 3 H Rep 2, pico mol leucine/hour)


[EN584 LV polysaccharide hydrolysis rates] - Measurements of polysaccharide hydrolase activities in large volume mesocosm incubations RV/Endeavor EN584, July 2016 (Patterns of activities project) (Latitudinal and depth-related contrasts in enzymatic capabilities of pelagic microbial communities: Predictable patterns in the ocean?)

Measurements of polysaccharide hydrolase activities in large volume mesocosm incubations RV/Endeavor EN584, July 2016. See Niskin Bottle and Cast List EN584 to link specific casts and bottles to each experiment: https://www.bco-dmo.org/dataset/717427.

cdm_data_type = Other
VARIABLES:
cruise_id (unitless)
station (unitless)
cast (unitless)
depth_id (Depth, unitless)
depth (m)
treatment (unitless)
meso_no (unitless)
substrate (unitless)
timepoint (unitless)
time_elapsed_hr (hours)
rep1_rate (nanomol monosaccharide/liter/hour)
rep2_rate (nanomol monosaccharide/liter/hour)
rep3_rate (nanomol monosaccharide/liter/hour)
average (nanomol monosaccharide/liter/hour)
std_dev (nanomol monosaccharide/liter/hour)


[EN589 Aerosol and seawater chemical composition] - Chemical composition of 'model' Primary Marine Aerosol (mPMA) and seawater measured on R/V Endeavor EN589 during Sept. - Oct. 2016 (Collaborative Research: Coupled Ocean-Atmosphere Recycling of Refractory Dissolved Organic Carbon in Seawater)

This dataset describes the ionic composition of western North Atlantic seawater and the corresponding chemical composition of mPMA produced from that seawater in a high-capacity generator over ranges of operating conditions. Measurements were taken during cruise EN589 on RV/Endeavor during September and October 2016.

cdm_data_type = Other
VARIABLES:
Campaign_Sequence_Number (unitless)
Sample_Type (unitless)
Sample_ID (unitless)
CI_50_Aerodynamic_Cut_Diam (micrometers)
S_Sample_Location (unitless)
latitude (degrees_north)
longitude (degrees_east)
time (ISO Date Time Local Start, seconds since 1970-01-01T00:00:00Z)
ISO_DateTime_local_end (ISO Date Time Local End, unitless)
Cl (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
Br (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
SO4 (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
Na (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
K (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
Mg (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
Ca (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
OCwe (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
OCwe_STD (nanomol/cubic meter (nmol m-3) for mPMA; micromol (µM) for S)
Comments (unitless)


[EN589 Marine Aerosol Generator Operating Conditions] - Configuration and Operation of Marine Aerosol Generator Deployed on R/V Endeavor EN589 during Sept.- Oct. 2016 (Collaborative Research: Coupled Ocean-Atmosphere Recycling of Refractory Dissolved Organic Carbon in Seawater)

This dataset describes the operating conditions for the high-capacity generator that produced primary marine aerosol from western North Atlantic seawater during cruise EN589 on RV/Endeavor during September and October 2016.

cdm_data_type = Other
VARIABLES:
ID_Number (unitless)
Sample_Type (unitless)
Start_Date_local (unitless)
Start_Time_local (unitless)
End_Date_local (unitless)
End_time_local (unitless)
water_depth_type (unitless)
Generator_Seawater_flowrate (liters/minute)
Jet_Flowrate (liters/minute)
Sweep_Bubble_Air_rate (liters/minute)
plumes_Venturi (unitless)
Venturi_Air_flowrate (liters/minute)
Venturi_Seawater_flowrate (liters/minute)
Rel_Humidity (unitless)


[EN614 HPLC Pigments] - Phytoplankton diagnostic pigments from HPLC from samples collected on R/V Endeavor cruise EN614 in the tropical North Atlantic during May 2018 (Collaborative Research: Impact of the Amazon River Plume on Nitrogen Availability and Planktonic Food Web Dynamics in the Western Tropical North Atlantic)

Phytoplankton diagnostic pigments from HPLC from samples collected on R/V Endeavor cruise EN614 in the tropical North Atlantic during May 2018. Note: these data are also available through NASA's SeaBASS repository at https://seabass.gsfc.nasa.gov/archive/COLUMBIA_U/subramaniam/LAMONT_ATL/may18atl/archive

cdm_data_type = Other
VARIABLES:
Sample (unitless)
volfilt (liters (L))
Station (unitless)
depth (m)
Year (meters (m))
month (unitless)
Day (unitless)
sdy (unitless)
time2 (Time, unitless)
time (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)
longitude (degrees_east)
latitude (degrees_north)
Tot_Chl_a (Concentration Of Chlorophyll In Sea Water, milligrams per cubic meter (mg/m^3))
Tot_Chl_b (milligrams per cubic meter (mg/m^3))
Tot_Chl_c (milligrams per cubic meter (mg/m^3))
Alpha_beta_Car (milligrams per cubic meter (mg/m^3))
But_fuco (milligrams per cubic meter (mg/m^3))
Hex_fuco (milligrams per cubic meter (mg/m^3))
Allo (milligrams per cubic meter (mg/m^3))
Diadino (milligrams per cubic meter (mg/m^3))
Diato (milligrams per cubic meter (mg/m^3))
Fuco (milligrams per cubic meter (mg/m^3))
Perid (milligrams per cubic meter (mg/m^3))
Zea (milligrams per cubic meter (mg/m^3))
MV_Chl_a (Concentration Of Chlorophyll In Sea Water, milligrams per cubic meter (mg/m^3))
... (28 more variables)


[EN614 Hydrography] - Hydrographic data collected during casts with a CTD-rosette system on R/V Endeavor cruise EN614 from May to June 2018 (Collaborative Research: Impact of the Amazon River Plume on Nitrogen Availability and Planktonic Food Web Dynamics in the Western Tropical North Atlantic)

Hydrographic data collected during casts with a CTD-rosette system on R/V Endeavor cruise EN614 from May to June 2018.

cdm_data_type = Other
VARIABLES:
Cruise (unitless)
Station (unitless)
Site (unitless)
Stn_Event (unitless)
Filename (unitless)
Scan (Unitless)
TimeJ (Time J, unitless)
TimeS (Time S, seconds)
time (Date ODV, seconds since 1970-01-01T00:00:00Z)
PrDM (PR DM, decibars (db))
depth (Dep SM, m)
T090C (T090 C, degrees Celsius)
T190C (T190 C, degrees Celsius)
T2_T190C (T2 T190 C, degrees Celsius)
C0S_m (C0 S M, Siemens per meter (S/m))
C1S_m (C1 S M, Siemens per meter (S/m))
C2_C1S_m (C2 C1 S M, Siemens per meter (S/m))
V0 (volts)
CStarAt0 (CStar At0, reciprocal meters (1/m))
CStarTr0 (CStar Tr0, unitless (percent))
V1 (volts)
FlECO_AFL (Fl ECO AFL, milligrams per cubic meter (mg/m^3))
V2 (volts)
AltM (Alt M, meters (m))
V3 (volts)
Par (Downwelling Photosynthetic Photon Radiance In Sea Water, micromoles photons per square meter per second (umol photons/m^2/sec))
... (25 more variables)


[EN669 Bottle Data] - Carbonate chemistry analyses (total alkalinity, DIC, and d13C of DIC) from discrete bottle samples and CTD data from 12 stations sampled during R/V Endeavor cruise EN669 in the Gulf of Maine during August 2021 (CAREER: Gulf of Maine Temperature Trends and Variability from the early Holocene to the Present)

This dataset includes seawater properties observed during cruise EN669 on the R/V Endeavor in the Gulf of Maine, conducted in August 2021 by PI Katherine Allen and the shipboard science party. Included are data from twelve CTD/Niskin rosette casts at twelve different stations accompanied by carbonate chemistry analyses (total alkalinity, DIC, and d13C of DIC) from discrete bottle samples collected during each cast. Bottle samples were analyzed by Adam Subhas at the Woods Hole Oceanographic Institution after the cruise was complete. Data from CTD casts were collected by the Endeavor's shipboard scientific party. These Gulf of Maine seawater observations provide constraints on growth conditions of synchronously collected foraminifera, enabling geochemical paleo-proxies to be assessed and refined for regional paleoceanographic reconstructions.

cdm_data_type = Other
VARIABLES:
CTD_Cast (unitless)
Niskin (unitless)
PotTemp (degrees Celsius)
Sal (unitless)
Depthm (meters (m))
DIC_Bottle (unitless)
DICumolkg (micromoles per kilogram seawater)
d13Cpermil (permille vs PDB)
talkumolkg (micromoles per kilogram seawater)
DICsd (micromoles per kilogram seawater)
d13Csd (permille vs PDB)
talksd (micromoles per kilogram seawater)
Scan (unitless)
TimeJ (days)
TimeS (seconds)
PrDM (meters (m))
T090C (degrees Celsius)
T190C (degrees Celsius)
T2_T190C (degrees Celsius)
... (39 more variables)


[End members metadata] - Metadata (location, depth, water temperature, salinity, etc.) describing end members compared to blue particles found in Oceanic Flux Program (OFP) traps (OCE-PRF:  Towards Quantifying Calcium Carbonate Sediment Dissolution During Marine Diagenesis)

This dataset includes metadata for end members (fish, bryzoan, serpulid worm, red algae, and coccolithophore) that were compared to blue particles found in OFP traps. Data include species, location, depth, water temperature, salinity, and date of collection.

cdm_data_type = Other
VARIABLES:
Sample_type (unitless)
Feeding_state_diet (unitless)
Species (unitless)
Location (unitless)
latitude (degrees_north)
longitude (degrees_east)
Water_temperature (degrees  Celsius)
Salinity (parts per thousand (ppt))
Collection_date (unitless)


[Environmental data FGB March 2023] - Water quality metrics collected from reef water in the Flower Garden Banks National Marine Sanctuary in Mar 2023 (Collaborative Research: RAPID: A multi-scale approach to predicting coral disease spread: leveraging an outbreak on coral-dense isolated reefs)

These data include water quality metrics collected at a depth of around 20 meters in the Flower Garden Banks National Marine Sanctuary in March 2023. Measurements were taken in the West Flower Garden Banks near Buoy #5. Microbial cell abundances, total organic carbon concentrations, and total nitrogen concentrations were measured from water collected 2 m above the reefs. Understanding the physical and chemical properties of reef water is important for understanding the microbial conditions of coral reefs, which is important for understanding disease dynamics.

cdm_data_type = Other
VARIABLES:
Mission (unitless)
Site (unitless)
time (Sampling_datetime_utc, seconds since 1970-01-01T00:00:00Z)
depth_f (Sampling_depth_ft, feet)
depth (Sampling_depth_m, m)
Lab_ID_for_cell_abundances (unitless)
pro (cells/ml)
syn (cells/ml)
peuk (cells/ml)
hbact (cells/ml)
Lab_ID_for_TON_TOC (unitless)
npoc (uM)
tn (uM)


[Environmental data] - Environmental data from long-term monitoring sites in St. John, USVI. (LTREB Long-term coral reef community dynamics in St. John, USVI: 1987-2019)

Environmental data from long-term monitoring sites in St. John, USVI.

cdm_data_type = Other
VARIABLES:
year (unitless)
dhm (degrees)
hurricane (unitless)


[Environmental Sensory Data] - Environmental, sensory data  (temperature, light intensity, salinity, pH, dissolved oxygen, depth) sampled in August 2019 in Carrie Bow Caye, Belize (Collaborative research: Is hybridization among threatened Caribbean coral species the key to their survival or the harbinger of their extinction?)

Environmental, sensory data  (temperature, light intensity, salinity, pH, dissolved oxygen, depth) sampled in August 2019 in Carrie Bow Caye, Belize

cdm_data_type = Other
VARIABLES:
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
time (ISO Date Time Local, seconds since 1970-01-01T00:00:00Z)
ISO_DateTime_UTC (ISO Date Time UTC, unitless)
Temperature (degrees Celcius (°C))
Light_Intensity (lux (lx))
Instrument (unitless)
depth (m)
Salinity (Sea Water Practical Salinity, parts per thousand)
Dissolved_Oxygen (Volume Fraction Of Oxygen In Sea Water, milligram per liter (mg/l))
pH (Sea Water Ph Reported On Total Scale, molar concentrations of H ions)


[Epibenthic community abundance] - Epibenthic community abundance in Aleutian Island kelp forests, June 2016 and July 2017 (Kelp Forest Ecosystem Engineer Loss project) (Collaborative Research: Changes in ecosystem production and benthic biodiversity following the widespread loss of an ecosystem engineer)

Epibenthic community abundance in Aleutian Island kelp forests, June 2016 and July 2017.

cdm_data_type = Other
VARIABLES:
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Island (unitless)
Habitat (unitless)
Region (unitless)
Year (unitless)
Depth_avg_ft (Depth, feet)
Depth_stdev (Depth, feet)
Acanthodoris_spp (number/meter^2)
Acmaea_mitra (number/meter^2)
Acropora_spp (number/meter^2)
Actiniaria_spp (number/meter^2)
Agarum_clathratum (number/meter^2)
Agarum_clathrus (number/meter^2)
Alaria_marginata (number/meter^2)
Alcyonacea_spp (number/meter^2)
Alcyonidium_gelatinosum (number/meter^2)
Alcyonium_spp (number/meter^2)
Aleutiaster_schefferi (number/meter^2)
Amphipoda_spp (number/meter^2)
Annelida_spp (number/meter^2)
Anthozoa_spp (number/meter^2)
Arctomelon_tamikoae (number/meter^2)
Ariadnaria_insignis (number/meter^2)
Ascidiacea_spp (number/meter^2)
Balanus_spp (number/meter^2)
... (162 more variables)


[Epibenthic community biomass] - Epibenthic community biomass in Aleutian Island kelp forests, June 2016 and July 2017 (Kelp Forest Ecosystem Engineer Loss project) (Collaborative Research: Changes in ecosystem production and benthic biodiversity following the widespread loss of an ecosystem engineer)

Epibenthic community biomass in Aleutian Island kelp forests, June 2016 and July 2017.

cdm_data_type = Other
VARIABLES:
Site (unitless)
Island (unitless)
Habitat (unitless)
Region (unitless)
Year (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth_avg_ft (Depth, feet)
Depth_stdev (Depth, feet)
Acanthodoris_spp (kilograms/meter^2)
Acarnus_erithacus (kilograms/meter^2)
Acmaea_mitra (kilograms/meter^2)
Acropora_spp (kilograms/meter^2)
Actiniaria_spp (kilograms/meter^2)
Agarum_clathratum (kilograms/meter^2)
Agarum_clathrus (kilograms/meter^2)
Alaria_marginata (kilograms/meter^2)
Alcyonacea_spp (kilograms/meter^2)
Alcyonidium_gelatinosum (kilograms/meter^2)
Alcyonidium_spp (kilograms/meter^2)
Alcyonium_spp (kilograms/meter^2)
Aleutiaster_schefferi (kilograms/meter^2)
Amphipoda_spp (kilograms/meter^2)
Annelida_spp (kilograms/meter^2)
Anthozoa_spp (kilograms/meter^2)
Arctomelon_tamikoae (kilograms/meter^2)
Ariadnaria_insignis (kilograms/meter^2)
... (221 more variables)


[Epibenthic community percent cover] - Epibenthic community percent cover in Aleutian Island kelp forests, June 2016 and July 2017 (Kelp Forest Ecosystem Engineer Loss project) (Collaborative Research: Changes in ecosystem production and benthic biodiversity following the widespread loss of an ecosystem engineer)

Epibenthic community percent cover in Aleutian Island kelp forests, June 2016 and July 2017

cdm_data_type = Other
VARIABLES:
Island (unitless)
Habitat (unitless)
Region (unitless)
Year (unitless)
Site (unitless)
latitude (degrees_north)
longitude (degrees_east)
Quad (unitless)
sample (unitless)
Holdfast_cover (unitless)
Suspension_Feeders_cover (unitless)
Encrusting_Corralline_cover (unitless)
Clathromorphum_cover (unitless)
BareRock_cover (Bare Rock Cover, unitless)
Codium_cover (unitless)
Other_cover (unitless)


[Epibenthic community sampling locations] - Epibenthic community sampling locations from Aleutian Island kelp forest community study, June 2016 and July 2017 (Kelp Forest Ecosystem Engineer Loss) (Collaborative Research: Changes in ecosystem production and benthic biodiversity following the widespread loss of an ecosystem engineer)

This dataset includes epibenthic community sampling locations from Aleutian Island kelp forest community study, June 2016 and July 2017: site name, island name, habitat, location, and depth.

cdm_data_type = Other
VARIABLES:
Site (unitless)
Island (unitless)
Habitat (unitless)
date (unitless)
latitude (degrees_north)
longitude (degrees_east)
Depth_avg_ft (Depth, feet)
Depth_stdev (Depth, feet)
Region (unitless)


[Epibenthic community taxonomy] - Table of taxonomic hierarchy and the sampling method for organisms collection in Aleutian Island kelp forests, June 2016 and July 2017 (Kelp Forest Ecosystem Engineer Loss project) (Collaborative Research: Changes in ecosystem production and benthic biodiversity following the widespread loss of an ecosystem engineer)

This dataset includes the taxonomic hierarchy for epibenthic community organisms collected in Aleutian Island kelp forests, based on biomass data. It also lists the method used to sample, either by a scrape collection or by a visual count along a swath.

cdm_data_type = Other
VARIABLES:
Taxon (unitless)
Kingdom (unitless)
Phylum (unitless)
Class (unitless)
Order_Subclass (unitless)
Family (unitless)
Genus (unitless)
Species (unitless)
Sampling_method (unitless)


[epiflu] - Bacterial Cell Counts, biovolumes and biomass per taxon from epifluorescence microscopy from R/V Endeavor cruise EN321 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)

Bacterial Cell Counts, biovolumes and biomass per taxon from epifluorescence microscopy from R/V Endeavor cruise EN321 in the Gulf of Maine and Georges Bank in 1999 as part of the U.S. GLOBEC program.

cdm_data_type = Other
VARIABLES:
cruiseid
year
cast
day_local
month_local
time_local (hours/minutes)
latitude (degrees_north)
longitude (degrees_east)
taxon
depth_w (Depth, meters)
depth (m)
num_class
number (cells/milliliter)
biomass_C (micrograms C/liter)
mean_biovolume (cubic microns)