Accessing BCO-DMO data
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BCO-DMO ERDDAP
Accessing BCO-DMO data |
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| Dataset Title: | [Epiphytic bacteria methane production data] - MPn-derived methane production by epiphytic bacteria on pelagic Sargassum seaweed from 2017- 2019 (Cyanobacteria Hydrocarbons project) (Collaborative Research: Do Cyanobacteria Drive Marine Hydrocarbon Biogeochemistry?) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_911212_v1) |
| Information: | Summary
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Attributes {
s {
Order {
String long_name "Order";
String units "unitless";
}
Date {
String long_name "Date";
String units "unitless";
}
Trial {
Int32 actual_range 1, 6;
String long_name "Trial";
String units "unitless";
}
Condition {
String long_name "Condition";
String units "unitless";
}
Number_of_Replicates {
Int32 actual_range 3, 6;
String long_name "Number_of_replicates";
String units "count";
}
Initial_MPn {
String long_name "Initial_mpn";
String units "nM";
}
Additional_Amendments {
String long_name "Additional_amendments";
String units "unitless";
}
Bottle {
Int32 actual_range 1, 5;
String long_name "Bottle";
String units "unitless";
}
T1_Timepoint {
Float32 actual_range 0.05, 2.8;
String long_name "T1_timepoint";
String units "days";
}
T1_Timepoint_mean_CH4_production {
Float32 actual_range -0.6898152, 199.3329;
String long_name "T1_timepoint_mean_ch4_production";
String units "nmol g^-1";
}
T1_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -4.72617, 1333.872;
String long_name "T1_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
T2_Timepoint {
Float32 actual_range 0.09, 4.1;
String long_name "T2_timepoint";
String units "days";
}
T2_Timepoint_mean_CH4_production {
Float32 actual_range -1.155659, 72.40018;
String long_name "T2_timepoint_mean_ch4_production";
String units "nmol g^-1";
}
T2_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -1.85365, 100.8861;
String long_name "T2_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
T3_Timepoint {
Float32 actual_range 0.12, 5.8;
String long_name "T3_timepoint";
String units "days";
}
T3_Timepoint_CH4_production {
Float32 actual_range -0.05916093, 116.3678;
String long_name "T3_timepoint_ch4_production";
String units "nmol g^-1";
}
T3_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -1.21176, 265.3319;
String long_name "T3_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
T4_Timepoint {
Float32 actual_range 0.17, 5.2;
String long_name "T4_timepoint";
String units "days";
}
T4_Timepoint_CH4_production {
Float32 actual_range -0.1520578, 157.9983;
String long_name "T4_timepoint_ch4_production";
String units "nmol g^-1";
}
T4_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -2.140631, 272.8168;
String long_name "T4_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
T5_Timepoint {
Float32 actual_range 0.21, 2.6;
String long_name "T5_timepoint";
String units "days";
}
T5_Timepoint_CH4_production {
Float32 actual_range -0.4020275, 109.1992;
String long_name "T5_timepoint_ch4_production";
String units "nmol g^-1";
}
T5_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -0.6946699, 195.7267;
String long_name "T5_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
T6_Timepoint {
Float32 actual_range 0.25, 4.2;
String long_name "T6_timepoint";
String units "days";
}
T6_Timepoint_CH4_production {
Float32 actual_range -0.1338867, 129.2932;
String long_name "T6_timepoint_ch4_production";
String units "nmol g^-1";
}
T6_Timepoint_CH4_no_sig_fig_rounding {
Float32 actual_range -1.785769, 204.8212;
String long_name "T6_timepoint_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
TFinal_Trial_Duration {
Float32 actual_range 0.3, 7.9;
String long_name "Tfinal_trial_duration";
String units "days";
}
TFinal_Final_CH4 {
Float32 actual_range -0.6898152, 1089.737;
String long_name "Tfinal_final_ch4";
String units "nmol g^-1";
}
TFinal_Final_CH4_no_sig_fig_rounding {
Float32 actual_range -4.183262, 1333.872;
String long_name "Tfinal_final_ch4_no_sig_fig_rounding";
String units "nmol g^-1";
}
TFinal_Percentage_MPn_Addition_Utilized {
Float32 actual_range -0.2671333, 410.6284;
String long_name "Tfinal_percentage_mpn_addition_utilized";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_m {
Float32 actual_range -2.709495, 533.5488;
String long_name "Best_fit_rate_by_bottle_m";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_b {
Float32 actual_range -11.03668, 11.89003;
String long_name "Best_fit_rate_by_bottle_b";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_R {
Float32 actual_range -1.0, 1.0;
String long_name "Best_fit_rate_by_bottle_r";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_R_squared {
Float32 actual_range 2.09383e-6, 1.0;
String long_name "Best_fit_rate_by_bottle_r_squared";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_N {
Int32 actual_range 2, 8;
String long_name "Best_fit_rate_by_bottle_n";
String units "unitless";
}
Best_Fit_Rate_by_Bottle_P {
Float32 actual_range 0.002846886, 0.9857358;
String long_name "Best_fit_rate_by_bottle_p";
String units "unitless";
}
Mode {
String long_name "Mode";
String units "nmol g^-1";
}
Skewness_Score {
Float32 actual_range -1.789868, 2.22749;
String long_name "Skewness_score";
String units "unitless";
}
Skewness_Interpretation {
String long_name "Skewness_interpretation";
String units "unitless";
}
Kurtosis_Score {
Float32 actual_range -3.504572, 4.969325;
String long_name "Kurtosis_score";
String units "unitless";
}
Kurtosis_Interpretation {
String long_name "Kurtosis_interpretation";
String units "unitless";
}
JB_test_Statistic {
Float32 actual_range 0.001676315, 9.279383;
String long_name "Jb_test_statistic";
String units "unitless";
}
P_value {
Float32 actual_range 0.009660681, 0.9991622;
String long_name "P_value";
String units "unitless";
}
Mean {
Float32 actual_range -0.4927252, 435.8947;
String long_name "Mean";
String units "nmol g^-1";
}
Median {
Float32 actual_range -0.4151078, 435.1051;
String long_name "Median";
String units "nmol g^-1";
}
Standard_Deviation {
Float32 actual_range 0.0, 80.4854;
String long_name "Standard_deviation";
String units "nmol g^-1";
}
Coefficient_of_Variation {
Float32 actual_range 0.02969571, 1.88685206e+11;
String long_name "Coefficient_of_variation";
String units "unitless";
}
Standard_Error {
Float32 actual_range 0.0, 40.2427;
String long_name "Standard_error";
String units "unitless";
}
Percent_Error {
Float32 actual_range 1.714483, 1.08937504e+13;
String long_name "Percent_error";
String units "unitless";
}
Range {
Float32 actual_range 0.0, 193.729;
String long_name "Range";
String units "nmol g^-1";
}
Interquartile_Range {
Float32 actual_range 0.0, 75.79935;
String long_name "Interquartile_range";
String units "nmol g^-1";
}
Best_Fit_Rate_by_Condition_m {
Float32 actual_range -0.6738074, 435.8947;
String long_name "Best_fit_rate_by_condition_m";
String units "unitless";
}
Best_Fit_Rate_by_Condition_b {
Float32 actual_range -16.5368, 28.68123;
String long_name "Best_fit_rate_by_condition_b";
String units "unitless";
}
Best_Fit_Rate_by_Condition_R {
Float32 actual_range -0.7223194, 0.9969308;
String long_name "Best_fit_rate_by_condition_r";
String units "unitless";
}
Best_Fit_Rate_by_Condition_R_squared {
Float32 actual_range 0.0, 0.993871;
String long_name "Best_fit_rate_by_condition_r_squared";
String units "unitless";
}
Best_Fit_Rate_by_Condition_N {
Int32 actual_range 0, 22;
String long_name "Best_fit_rate_by_condition_n";
String units "unitless";
}
Best_Fit_Rate_by_Condition_P {
Float32 actual_range 0.0, 0.9248095;
String long_name "Best_fit_rate_by_condition_p";
String units "unitless";
}
}
NC_GLOBAL {
String cdm_data_type "Other";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_url "https://www.bco-dmo.org/";
String doi "10.26008/1912/bco-dmo.911212.1";
String history
"2024-11-21T08:41:03Z (local files)
2024-11-21T08:41:03Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_911212_v1.html";
String infoUrl "https://www.bco-dmo.org/dataset/911212";
String institution "BCO-DMO";
String license
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
String sourceUrl "(local files)";
String summary "The essential nutrient phosphorus is biologically scarce in the Sargasso Sea, yet the pelagic macroalgae Sargassum, for which this area of the North Atlantic Ocean is named, thrives. We tested the hypothesis that Sargassum holobionts utilize methylphosphonate (MPn) as an alternative source of phosphorus, finding lysis liberated phosphonate-derived methane. The observed activity occurred at concentrations as low as 35 nM MPn and was inhibited by antibiotics, implicating microbial members of the holobiont capable of MPn lysis at realistic environmental concentrations. A survey of macroalgal species inhabiting the Sargasso Sea found a ubiquitous capacity for MPn lysis; such capacity was absent in species inhabiting phosphorus-replete waters of the California Current, pointing to phosphorous limitation as a selective pressure. These results suggest algal holobionts may conditionally acquire phosphorus from phosphonates while simultaneously serving as a source of atmospheric methane.";
String title "[Epiphytic bacteria methane production data] - MPn-derived methane production by epiphytic bacteria on pelagic Sargassum seaweed from 2017-2019 (Cyanobacteria Hydrocarbons project) (Collaborative Research: Do Cyanobacteria Drive Marine Hydrocarbon Biogeochemistry?)";
}
}
Data Access Protocol (DAP) and its
selection constraints.
The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.
Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names,
followed by a collection of
constraints (e.g., variable<value),
each preceded by '&' (which is interpreted as "AND").
For details, see the tabledap Documentation.