BCO-DMO ERDDAP
Accessing BCO-DMO data 		log in    
Brought to you by BCO-DMO    
 
 
griddap Subset tabledap Make A Graph wms files Accessible Title Summary FGDC ISO 19115 Info Background Info RSS Email Institution Dataset ID
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_953999_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_953999_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_953999_v1/ public [16S microbiome data for artificial reef sponges and seawater] - 16S microbiome metadata collected from shallow artificial reef sponges and seawater in the Florida Keys, USA from Apr 2021 to Aug 2021 (Collaborative Research: Investigations into microbially mediated ecological diversification in sponges) Sponges are a dominant component of coral reefs worldwide and in the Caribbean, where their biomass exceeds that of reef-building corals. For almost a quarter century, the success of sponges in the Caribbean has been linked to their filter-feeding ability. However, recent work demonstrated that coexisting sponges on Caribbean reefs host unique communities of bacteria that might allow sponges to access multiple pools of nutrients that are not available to other organisms. In this project, the investigators will test the hypothesis that ecologically dominant sponge species in the Caribbean have unique metabolic strategies that are mediated by their associations with microbes that live within the sponge body.\n\nIn this dataset, we present the 16S rRNA microbiome NCBI accession and sample collection metadata for an artificial reef experiment where sponges of 10 species were placed on this temporary reef from April to August of 2021 and sampled using VacuSIP. VacuSIP methods capture incurrent (In) and excurrent (Ex) water from each sponge specimen. Incurrent represents the bacteria that are available for the sponge to consume via filter feeding and excurrent represents the bacteria that remain once sponges have consumed their preferred taxa. Additionally, we have provided microbiome metadata for the host sponges for several of these paired In/Ex samples. See the related dataset, NCBI Bioproject PRJNA1179970, for all sequence data. Microbiome data was generated using protocols from the Earth Microbiome project and sequencing was conducted on an Illumina MiSeq at Middle Tennessee State University. The data available at NCBI represents raw sequencing data, and no quality checks or sequencing filtering has been done on the uploaded sequences.\n\ncdm_data_type = Other\nVARIABLES:\ncollection_date (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\naccession (unitless)\nsample_name (unitless)\nspecies_ab (unitless)\nsample_type (unitless)\norganism (unitless)\n... (6 more variables)\n https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_953999_v1_fgdc.xml https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_953999_v1_iso19115.xml https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_953999_v1/index.htmlTable https://www.bco-dmo.org/dataset/953999 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_953999_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_953999_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_953999_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925689_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925689_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_925689_v1/ public [Allometric scaling of calcification for Mytilus californianus] - Allometric scaling of calcification data for Mytilus californianus from 2021-2022 (OA decoupling project) (Invertebrate calcification and behavior in seawater of decoupled carbonate chemistry) Calcification rates of mussels spanning a range of sizes. These data were used to determine a biomass scaling function for the main incubation dataset (Incubation data for Mytilus californianus calcification).\n\ncdm_data_type = Other\nVARIABLES:\nspecies (unitless)\nAphiaID (unitless)\nLSID (unitless)\ndate_local (unitless)\nstart_time_local (unitless)\nISO_Start_DateTime_UTC (unitless)\nduration (hours (h))\nsalinity (PSU)\ntemperature (degrees Celcius (c))\ncalcification (umol hr^-1 g^-0.71592)\ntissue_mass (grams (g))\nshell_mass (grams (g))\nwet_mass (grams (g))\nTA (umol kg-1)\nph (unitless)\ndo (umol kg-1)\nci (umol kg-1)\nincubation_water_mass (kilograms (kg))\nbyssal_threads (threads hr-1)\ndelta_ta (umol kg-1)\ndelta_nh3 (umol kg-1)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_925689_v1/index.htmlTable https://www.bco-dmo.org/dataset/925689 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_925689_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_925689_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_925689_v1
log in [Apostichopus californicus 16S rRNA V4 Sequences] - 16S rRNA V4 sequence metadata from Apostichopus californicus-associated flavivirus experiment under suboxic conditions and organic matter amendment (Exploring the role of boundary layer microbial remineralization in flavivirus-host dynamics) Microbial activities at the animal-water interface are hypothesized to influence viral replication and possibly contribute to pathology of echinoderm wasting diseases due to hypoxic stress. We assessed the impacts of enhanced microbial production and suboxic stress on Apostichopus californicus (urn:lsid:marinespecies.org:taxname:529363) associated flavivirus (PcaFV) load in a mesocosm experiment. This dataset contains 16S rRNA V4 amplicon sequencing metadata for this experiment. Organic matter amendment and suboxic stress resulted in lower PcaFV load, which also correlated negatively with animal mass loss and microbial activity at the animal-water interface. These data suggest that PcaFV replication and persistence was best supported in healthier specimens. Our results do not support the hypothesis that suboxic stress or microbial activity promote PcaFV replication, but rather that PcaFV appears to be a neutral or beneficial symbiont of Apostichopus californicus.\n\ncdm_data_type = Other\nVARIABLES:\nsample_name (unitless)\nbioproject_accession (unitless)\nbiosample (unitless)\norganism (unitless)\nspecimen_collection_date (unitless)\nswab_collection_date (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nhost (unitless)\nhost_subject_id (unitless)\nreplicate_ID (unitless)\nhost_tissue_sampled (unitless)\nhost_NCBI_taxid (unitless)\nAphiaID (unitless)\nLSID (unitless)\n BCO-DMO bcodmo_dataset_984835_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925714_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925714_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_925714_v1/ public [Control incubation data during calcification experiments] - Control incubation data during Mytilus californianus calcification experiments from 2020 to 2022 (OA decoupling project) (Invertebrate calcification and behavior in seawater of decoupled carbonate chemistry) These data support Incubation data for Mytilus californianus calcification. These incubations did not contain mussels and demonstrate that background alkalinity changes during experimental modules were minor. These data support Incubation data for Mytilus californianus calcification. These data demonstrate that background alkalinity changes during experimental modules were minor.\n\ncdm_data_type = Other\nVARIABLES:\nspecies (units)\nAphiaID (unitless)\nLSID (unitless)\nmodule (unitless)\ndate_local (unitless)\nstart_time_local (unitless)\nISO_start_DateTime_UTC (unitless)\nduration (hours (h))\nsalinity (PSU)\ntemperature (degrees Celcius (c))\nTA (umol kg-1)\nph (unitless)\nhco3 (umol kg-1)\nco3 (umol kg-1)\nomega (unitless)\npco2 (uatm)\ndic (umol kg-1)\ndo (umol kg-1)\nincubation_water_mass (kilograms (kg))\ndelta_ta (umol kg-1)\ndelta_nh3 (umol kg-1)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_925714_v1/index.htmlTable https://www.bco-dmo.org/dataset/925714 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_925714_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_925714_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_925714_v1
log in [Flow cytometry data from Incurrent and Excurrent flow] - Flow cytometry data from Incurrent and Excurrent flow samples collected from shallow artificial reef sponges and seawater in the Florida Keys, USA from Apr 2021 to Aug 2021 (Collaborative Research: Investigations into microbially mediated ecological diversification in sponges) Sponges are a dominant component of coral reefs worldwide and in the Caribbean, where their biomass exceeds reef-building corals. For almost a quarter century, the success of sponges in the Caribbean has been linked to their filter-feeding ability. However, recent work demonstrated that coexisting sponges on Caribbean reefs host unique communities of bacteria that might allow sponges to access multiple pools of nutrients unavailable to other organisms. In this project, the investigators will test the hypothesis that ecologically dominant sponge species in the Caribbean have unique metabolic strategies mediated by their associations with microbes living within the sponge body. In this dataset, we present flow cytometry data for an artificial reef experiment where sponges of 10 species were placed on this temporary reef from April to August 2021 and sampled using a VacuSIP. VacuSIP methods capture incurrent (In) and excurrent (Ex) water from each sponge specimen. Incurrent represents the microbes available for the sponge to consume via filter feeding, and excurrent represents the microbes that remain once sponges have consumed their preferred taxa. Flow cytometry data was generated with the help of Bigelow Laboratory for Ocean Sciences. Samples were analyzed for the presence of photosynthetic microbes (Synechococcus, Prochlorococcus, photosynthetic eukaryotes) and heterotrophic bacteria (high nucleic acid and low nucleic acid). The present data represents raw data provided by the Bigelow Laboratory for Ocean Sciences, as well as the collection metadata, water sample type, and sponge species information.\n\ncdm_data_type = Other\nVARIABLES:\nCollection_Date (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nSample_ID (unitless)\nSpecies (unitless)\nSpecies_Abbreviation (unitless)\nIn_or_Ex (unitless)\nReplicate (unitless)\nCollection_day (unitless)\nTotPhyto_Conc (mL-1)\nSyn_Conc (mL-1)\n... (7 more variables)\n BCO-DMO bcodmo_dataset_969846_v1
log in [Global Seabird Breeding Success] - Annual seabird productivity at breeding colonies around the world from 1964 to 2023 (Stratification Impacts on Seabirds Project) (Global analysis of stratification impacts on seabirds through food resources ) This global dataset on breeding productivity represents a compilation of individual time series from species and sites (seabird breeding colonies) across the world. Each time series was contributed by a Global Seabird Working Group (GSWG) collaborator. It contains the number of offspring produced per nesting female per year, which is a variable measured similarly by researchers. Seabird breeding productivity is typically measured by monitoring individual nest sites through time within each breeding season. Data from multiple females are then averaged to produce estimates of annual productivity for each species at each site, resulting in “species-site” time series. Typically, measurements are made for multiple species at each site, so data are often available for a portion of the full seabird community, including species feeding at different trophic levels and in different parts of the water column. Variance for species-site breeding productivity is estimated as the standard error across years for each time series. Here, there are 202 time series encompassing 87 sites and 73 seabird species.\n\ncdm_data_type = Other\nVARIABLES:\nyear (unitless)\nsite (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nspeciesnum (unitless)\nspecies (unitless)\nScientificName_accepted (unitless)\nAphiaID (unitless)\nLSID (unitless)\nbreeding_success (reproduction_rate)\nn (individuals)\n BCO-DMO bcodmo_dataset_985565_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925598_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925598_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_925598_v1/ public [Incubation data for Mytilus californianus calcification] - Incubation data for Mytilus californianus calcification from January to April 2022 (OA decoupling project) (Invertebrate calcification and behavior in seawater of decoupled carbonate chemistry) Calcification is vital to marine organisms that produce calcium carbonate shells and skeletons. However, how calcification is impacted by ongoing environmental changes, including ocean acidification, remains incompletely understood due to complex relationships among the carbonate system variables hypothesized to drive calcification. \n\nHere, we experimentally decouple these drivers in an exploration of shell formation in adult marine mussels, Mytilus californianus. In contrast to models that focus on single parameters like calcium carbonate saturation state, our results implicate two independent factors, bicarbonate concentration and seawater pH, in governing calcification. While qualitatively similar to ideas embodied in the related substrate-inhibitor ratio (bicarbonate divided by hydrogen ion concentration), our data highlight that merging bicarbonate ion and hydrogen ion concentrations into a simple quotient obscures important features of calcification. Considering a dual-parameter framework improves mechanistic understanding of how calcifiers interact with complex and changing chemical conditions.\n\ncdm_data_type = Other\nVARIABLES:\nspecies (unitless)\nAphiaID (unitless)\nLSID (unitless)\nmodule (unitless)\ndate_local (unitless)\nstart_datetime_local (unitless)\nISO_Start_DateTime_UTC (unitless)\nduration (hours)\nsalinity (PSU)\ntemperature (degrees Celcius (c))\ncalcification (umol hr^-1 g^-0.71592)\ntissue_mass (grams (g))\nshell_mass (grams (g))\nwet_mass (grams (g))\n... (24 more variables)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_925598_v1/index.htmlTable https://www.bco-dmo.org/dataset/925598 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_925598_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_925598_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_925598_v1
log in [Ocean Conditions at Seabird Colony Sites] - Seasonally and spatially averaged stratification mixed layer temperature and chlorophyll-a around Northern Hemisphere seabird colonies from 1993 to 2019 (Stratification impacts on seabirds project) (Global analysis of stratification impacts on seabirds through food resources ) This dataset provides seasonal averages of mixed layer temperature, water column stratification, and mixed layer chlorophyll-a content for coastal marine regions around the world using the Marine Ecoregions of the World (MEOW) framework. The MEOW framework spatially partitions coastal marine areas into a hierarchical, nested structure based on biogeographic and environmental characteristics. Seven ecosystems are represented in the dataset: the Arctic, Cold Temperate Northeast Pacific, Cold Temperate Northwest Pacific, Warm Temperate Northeast Pacific, Hawaii, Northern European Seas, and Cold Temperate Northwest Atlantic, which are roughly equivalent to Large Marine Ecosystems. Environmental data was extracted for the domain of these seven ecosystems using the GLORYS12V1 global ocean reanalysis, which resolves monthly ocean conditions at 1/12-degree, daily resolution across 50 vertical depth levels. This state-of-the-art reanalysis assimilates historical data from multiple sources, including satellite observations and buoy data, and covers the period from 1993 to 2019. We extracted temperature, mixed layer depth, and salinity for the upper 200 m of the water column, which were used to calculate coastal stratification. Stratification was quantified using the Potential Energy Anomaly (PEA), a robust metric that measures the energy required to thoroughly mix the water column and reflects seasonal stratification patterns. All environmental variables were spatially averaged over corresponding ecoregions and temporally averaged over the pre-breeding and breeding seasons of seabird colonies within the ecoregion. By offering detailed classifications and environmental characterizations, this dataset serves as a valuable resource for analyzing regional oceanographic patterns and understanding how physical processes shape seabird populations and marine ecosystems.\n\ncdm_data_type = Other\nVARIABLES:\nidnum (exp_id)\nyear (years)\nspp (unitless)\nScientificName_accepted (unitless)\nAphiaID (unitless)\nLSID (unitless)\nsite (unitless)\nsppsite (unitless)\n... (27 more variables)\n BCO-DMO bcodmo_dataset_985768_v1
log in [Palau Coral Reef Experiment 2018: Biometrics] - Coral biometrics data from a heating experiment using samples collected from Nikko Bay and Rebotel Reef in Palau in the spring of 2018 (Collaborative Research: Stability, flexibility, and functionality of thermally tolerant coral symbioses) Using samples collected from Nikko Bay and Rebotel Reef in Palau in the spring of 2018, this dataset examines coral physiology of two species of coral, Psammacora digitata and Pocillopora verrucosa, as part of a short-term heating experiment.\n\ncdm_data_type = Other\nVARIABLES:\nLocation_Name (unitless)\nlongitude (degrees_east)\nlatitude (degrees_north)\nSpecies (unitless)\nLSID (units)\nDate (unitless)\nDay (unitless)\nSymbiont (unitless)\nTreatment (Degrees Celcius (°C))\nColony (unitless)\nCell_Density (number of cells per square centimeter of coral)\nChl_a (picograms chlorophyll a per algal cell)\nHost_protein (micrograms soluble protein per square centimeter of coral skeleton)\nGross_photosynthesis (micrograms of oxygen per algal cell per hour)\nRespiration (milligrams oxygen per milligrams animal protein per hour)\nPhotosynthesis_Respiration (unitless)\n BCO-DMO bcodmo_dataset_855036_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_947067_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_947067_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_947067_v1/ public [Seasonal fatty acid profiles of marine algae and invertebrates from Sitka Sound, Alaska in 2019] - Seasonal fatty acid profiles of marine algae and invertebrates from Sitka Sound, Alaska in 2019 (CAREER: Energy fluxes and community stability in a dynamic, high-latitude kelp ecosystem) These data include fatty acid compositions of select marine macroalgae and macroinvertebrate grazers collected in Sitka Sound, Alaska in January 2019 and July 2019. Samples were collected using SCUBA at three sites, all within 6 km of each other in Sitka Sound: Harris Island (N 57.03165, W 135.27754), Breast Island (N 57.03896, W 135.33309), and Samsing Pinnacle (N 56.98750, W 135.35718). Sampled species included six seaweeds, including three Laminarian kelps (Ochrophyta) and three red algae from the Gigartinales and Ceramiales, that are present in both seasons in these sites: Neoagarum fimbriatum, Macrocystis pyrifera, Hedophyllum nigripes, Cryptopleura ruprechtiana, Opuntiella californica, and Osmundia spectabilis. They also include six macro-invertebrates (two each of gastropods, crustaceans, echinoderms) that are present and dominant herbivores in these sites: Haliotis kamtschatkana, Tegula pulligo, Pentidotea resecata, Pugettia producta, Mesocentrotus franciscanus, and Strongylocentrotus droebachiensis. \nUnderstanding seasonal variation in fatty acid trophic biomarkers between dominant macrophyte resources and their benthic herbivores can help reveal how producers and their primary consumers may respond to future environmental change. These unique data from a high latitude kelp forest ecosystem were collected by a collaborative team of marine ecologists: Dr. Reyn Yoshioka, Dr. Aaron Galloway, Dr. Julie Schram, Dr. Kristy Kroeker, and Dr. Lauren Bell.\n\ncdm_data_type = Other\nVARIABLES:\nsampleID (unitless)\nseason (unitless)\nsite (unitless)\nYear_Month (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nspCode (unitless)\ntype (unitless)\ngenus (unitless)\nspecies (unitless)\nLSID (unitless)\nlengthDia_comment (unitless)\n... (65 more variables)\n https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_947067_v1_fgdc.xml https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_947067_v1_iso19115.xml https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_947067_v1/index.htmlTable https://www.bco-dmo.org/dataset/947067 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_947067_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_947067_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_947067_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925664_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_925664_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_925664_v1/ public [Shell dissolution data for Mytilus californianus] - Shell dissolution data for Mytilus californianus from March to July 2020 (OA decoupling project) (Invertebrate calcification and behavior in seawater of decoupled carbonate chemistry) This dataset supports the main incubation data. These data document shell dissolution rates for Mytilus californianus which were used to convert net calcification rates of mussels into gross calcification rates.\n\ncdm_data_type = Other\nVARIABLES:\nspecies (unitless)\nAphiaID (unitless)\nLSID (unitless)\nmodule (unitless)\ndatetime_local (unitless)\nstart_time_local (unitless)\nISO_Start_DateTime_UTC (unitless)\nduration (hours)\nsalinity (PSU)\ntemperature (degrees Celcius)\nshell_mass (grams (g))\nTA (umol kg-1)\nph (unitless)\nhco3 (umol kg-1)\nco3 (umol kg-1)\nomega (unitless)\nco2 (umol kg-1)\npco2 (uatm)\ndic (umol kg-1)\nincubation_water_mass (kilograms (kg))\ndelta_ta (umol kg-1)\ndiss_rate (umol hr-1 g-1)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_925664_v1/index.htmlTable https://www.bco-dmo.org/dataset/925664 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_925664_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_925664_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_925664_v1
https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_964174_v1 https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_964174_v1.graph https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_964174_v1/ public [Targeted metabolomics data from coral and sea anemone larvae exposed to normoxic or hypoxic conditions] - Targeted metabolomics data from coral and sea anemone larvae exposed to normoxic or hypoxic conditions in lab and field experiments performed in USA and Bermuda during 2023-2024 (CAREER: Helping or hindering? Determining the influence of repetitive marine heatwaves on acclimatization of reef-building corals across biological scales) These data arose from larvae of the sea anemone Nematostella vectensis and corals Galaxea fascicularis and Porites astreoides exposed to normoxic (i.e., control) or hypoxic conditions. Larvae were sampled in groups of 20-30 and these samples were processed for targeted metabolomics at the University of Pennsylvania Metabolomics Core. The dataset contains the species from which metabolomics data originate, experimental treatment (normoxia or hypoxia), experiment metadata, and abundance of each metabolite in each sample.\n\ncdm_data_type = Other\nVARIABLES:\nSpecies (units)\nTreatment (units)\nCohort (units)\nGroup (units)\nLife_stage (units)\nHours_post_treatment (hours)\nADP (nmol mg protein-1)\nAMP (nmol mg protein-1)\nATP (nmol mg protein-1)\ncAMP (nmol mg protein-1)\nCMP (nmol mg protein-1)\nCTP (nmol mg protein-1)\nGDP (nmol mg protein-1)\nGMP (nmol mg protein-1)\nGTP (nmol mg protein-1)\nITP (nmol mg protein-1)\nNAD (nmol mg protein-1)\nNADP (nmol mg protein-1)\nNAM (nmol mg protein-1)\nNMN (nmol mg protein-1)\nTTP (nmol mg protein-1)\nUMP (nmol mg protein-1)\n... (67 more variables)\n https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_964174_v1/index.htmlTable https://osprey.bco-dmo.org/dataset/964174 (external link) https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_964174_v1.rss https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_964174_v1&showErrors=false&email= BCO-DMO bcodmo_dataset_964174_v1
log in [Winter temp and nutrient coral measurements] - Energy reserve and stable isotope data from 3 species of Australian coral exposed to increased temperature and nutrients treatment in 2008 (EAPSI:  How Do Coastal Eutrophication and Elevated Ocean Temperature Impact On Reef Corals) In this project, we tested the effects of elevated temperature and moderate nutrients for 21 days during the winter on Montipora monasteriata, Acropora formosa, and Pocillopora damicornis in a fully factorial experiment with two seawater temperatures (average winter temperature of 20°C and projected winter temperature later this century of 24°C) and two nutrient levels (ambient nutrients at 1.28 μmol L-1 NO3- and 0.14 μmol L-1 PO4-3, and moderate nutrients at 5.44 μmol L-1 NO3- and 0.36 μmol L-1 PO4-3). \n\nThis dataset includes coral and endosymbiont tissue δ15N, δ13C, coral energy reserves (protein, lipid, carbohydrates), and temperature data. The experiment was conducted in collaboration with Dr. Kenneth Anthony at the University of Queensland at Heron Island, Australia. These data were collected by Dr. Stephen Levas at The Ohio State University and The University of Wisconsin - Whitewater.\n\ncdm_data_type = Other\nVARIABLES:\nID (unitless)\nSpecies (unitless)\nTemp (unitless)\nNutrient (unitless)\nT_Chla (ug/cm²)\nd13C_Animal (per mil)\nd13C_Zoox (per mil)\nd13C_Animal_d13C_Zoox (per mil)\nd15N_Animal (per mil)\nd15N_Zoox (per mil)\nd15N_Animal_d15N_Zoox (per mil)\nProtein (Joules per mg ash free dry weight)\nCarbs (Joules per mg ash free dry weight)\nLipid (Joules per mg ash free dry weight)\nTotal_EnRes (Joules per mg ash free dry weight)\nTotal_Biomass (mg/cm2)\nAphiaID (unitless)\nLSID (unitless)\n BCO-DMO bcodmo_dataset_959971_v1

 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact