[{"dataset_parameter_nid":"729370","supplied_name":"deploy_date","supplied_units":"unitless","value_format":null,"description":"\u003Cp\u003EDate of deployment; yyyy\/mm\/dd\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1070","parameter_description":"\u003Cp\u003Edate; generally reported in GMT as YYYYMMDD (year; month; day); also as MMDD (month; day); EqPac dates are local Hawaii time. ISO_Date format is YYYY-MM-DD (\u003Ca href=\u0022http:\/\/www.iso.org\/iso\/home\/standards\/iso8601.htm\u0022 target=\u0022_blank\u0022\u003Ehttp:\/\/www.iso.org\/iso\/home\/standards\/iso8601.htm\u003C\/a\u003E)\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":null,"parameter_official_name":"date","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/ADATAA01\/","parameter_short_description":"date","parameter_short_name":"date","parameter_units":null,"parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729371","supplied_name":"depth","supplied_units":"meters","value_format":null,"description":"\u003Cp\u003EThe nominal depth of the NBST. During the July 2013 deployment the NBSTs were programmed to hold depth within +\/-25 m of the measurement depth while in subsequent deployments this band was narrowed to +\/-10 m.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"808","parameter_description":"\u003Cp\u003EObservation\/sample depth below the sea surface. Units often reported as: meters, feet.\u003C\/p\u003E\n\u003Cp\u003E\nWhen used in a JGOFS\/GLOBEC dataset the depth is a best estimate; usually but not always calculated from pressure; calculated either from CTD pressure using Fofonoff and Millard (1982; UNESCO Tech Paper #44) algorithm adjusted for 1980 equation of state for seawater (EOS80) or simply equivalent to nominal depth as recorded during sampling if CTD pressure was unavailable.\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"depth","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P09\/current\/DEPH\/","parameter_short_description":"depth","parameter_short_name":"depth","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729372","supplied_name":"deploy_lat","supplied_units":"decimal degrees","value_format":null,"description":"\u003Cp\u003ELatitude of the deployment\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"730","parameter_description":"\u003Cp\u003Elatitude, in decimal degrees, North is positive, negative denotes South; Reported in some datasets as degrees, minutes\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"latitude","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P09\/current\/LATX\/","parameter_short_description":"latitude","parameter_short_name":"lat","parameter_units":"decimal degrees","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729373","supplied_name":"deploy_lon","supplied_units":"decimal degrees","value_format":null,"description":"\u003Cp\u003ELongitude of the deployment\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"731","parameter_description":"\u003Cp\u003Elongitude, in decimal degrees, East is positive, negative denotes West; Reported in some datsets as degrees, minutes\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"longitude","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P09\/current\/LONX\/ ","parameter_short_description":"longitude","parameter_short_name":"lon","parameter_units":"decimal degrees","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729374","supplied_name":"recover_lat","supplied_units":"decimal degrees","value_format":null,"description":"\u003Cp\u003ELatitude of the point of recovery\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"730","parameter_description":"\u003Cp\u003Elatitude, in decimal degrees, North is positive, negative denotes South; Reported in some datasets as degrees, minutes\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"latitude","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P09\/current\/LATX\/","parameter_short_description":"latitude","parameter_short_name":"lat","parameter_units":"decimal degrees","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729375","supplied_name":"recover_lon","supplied_units":"decimal degrees","value_format":null,"description":"\u003Cp\u003ELongitude of the point of recovery\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"731","parameter_description":"\u003Cp\u003Elongitude, in decimal degrees, East is positive, negative denotes West; Reported in some datsets as degrees, minutes\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"longitude","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P09\/current\/LONX\/ ","parameter_short_description":"longitude","parameter_short_name":"lon","parameter_units":"decimal degrees","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729376","supplied_name":"deploy_length","supplied_units":"days","value_format":null,"description":"\u003Cp\u003EDays between deployment of NBST and tube lid closure\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"555754","parameter_description":"\u003Cp\u003EDuration of treatment, observation or sampling\u003C\/p\u003E\n","parameter_max_value":"","parameter_min_value":"0","parameter_nd_value":"nd","parameter_official_name":"duration","parameter_external_identifier":"","parameter_short_description":"duration","parameter_short_name":"duration","parameter_units":"various","parameter_units_external_identifier":"","order":null},{"dataset_parameter_nid":"729377","supplied_name":"no_replicates","supplied_units":"number","value_format":null,"description":"\u003Cp\u003ENumber of tubes averaged to obtain mean TC and TN flux measurements at a single depth\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1079","parameter_description":"\u003Cp\u003ENumber of items or individuals counted in sample or sample fraction\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":null,"parameter_official_name":"count","parameter_external_identifier":null,"parameter_short_description":"count","parameter_short_name":"count","parameter_units":null,"parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729378","supplied_name":"TC_f","supplied_units":"milligrams of carbon per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal carbon flux of the sinking fraction operationally defined as particles \u0026lt;350 um. The carbon measured in all process blanks from the five cruises was averaged to determine the mean process blank in sediment trap tubes for the field program (0.11 +\/-0.2 mg C). This mean process blank was subtracted from the total carbon measured in each trap sample, and the result was divided by the trap collection area (0.0113 m^2) and the deployment length to yield flux. Reported fluxes are the mean of measurements from 2 or 3 tubes.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1211","parameter_description":"\u003Cp\u003Etotal organic Carbon\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TOC","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/CORGCOTX\/","parameter_short_description":"total organic Carbon","parameter_short_name":"TOC","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729379","supplied_name":"TC_f_err","supplied_units":"milligrams of carbon per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal carbon flux error; Uncertainties are propagated from the standard deviation of the process blanks from the five cruises (0.2 mg C) and the standard deviation or range of the two or three TC measurements per NBST deployment: TC_f_err = (STD tubes^2 + STD blanks^2)^1\/2 \/ deployment length \/ trap area; For depths with only two replicate analyses the range of the TC fluxes measured in each tube is used in place of STDtubes in the above equation.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1211","parameter_description":"\u003Cp\u003Etotal organic Carbon\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TOC","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/CORGCOTX\/","parameter_short_description":"total organic Carbon","parameter_short_name":"TOC","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729380","supplied_name":"N_f","supplied_units":"milligrams of nitrogen per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal nitrogen flux of the sinking fraction operationally defined as particles \u0026lt;350 um. The nitrogen measured in all process blanks from the five cruises was averaged to determine the mean process blank in sediment trap tubes for the field program (0.015 +\/- 0.006 mg N). This mean process blank was subtracted from the total nitrogen measured in each trap sample and the result was divided by the trap collection area (0.0113 m^2) and the deployment length to yield flux. Reported fluxes are the mean of measurements from 2 or 3 tubes.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1213","parameter_description":"\u003Cp\u003Etotal organic Nitrogen\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TON","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/NTOTZZZZ\/","parameter_short_description":"total organic Nitrogen","parameter_short_name":"TON","parameter_units":"micromoles\/liter","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729381","supplied_name":"N_f_err","supplied_units":"milligrams of nitrogen per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal nitrogen flux error; Uncertainties are propagated from the standard deviation of the process blanks from the five cruises (0.006 mg N) and the standard deviation or range of the two or three TN measurements per NBST deployment.\u003Cbr \/\u003E\n TN_f_err = (STD tubes^2 + STD blanks^2)^1\/2 \/ deployment length \/ trap area;\u003Cbr \/\u003E\nFor depths with only two replicate analyses the range of the TN fluxes measured in each tube is used in place of STDtubes in the above equation.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1213","parameter_description":"\u003Cp\u003Etotal organic Nitrogen\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TON","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/NTOTZZZZ\/","parameter_short_description":"total organic Nitrogen","parameter_short_name":"TON","parameter_units":"micromoles\/liter","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729382","supplied_name":"TC_f_swimmer","supplied_units":"milligrams of carbon per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal carbon flux of the \u0026gt;350-um screened fraction presumed to be zooplankton that actively entered the trap. Calculated as for \u0026#039;total carbon flux\u0026#039; above using a \u0026gt;350-um process blank of 0.05 +\/- 0.04 mg C.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1211","parameter_description":"\u003Cp\u003Etotal organic Carbon\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TOC","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/CORGCOTX\/","parameter_short_description":"total organic Carbon","parameter_short_name":"TOC","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729383","supplied_name":"TC_f_err_swimmer","supplied_units":"milligrams of carbon per square meter per day","value_format":null,"description":"\u003Cp\u003ESwimmer total carbon flux error; Calculated for the \u0026gt;350-um screened fraction as for \u0026#039;total carbon flux error\u0026#039; above using a \u0026gt;350-um process blank standard deviation of 0.04 mg C.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1211","parameter_description":"\u003Cp\u003Etotal organic Carbon\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TOC","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/CORGCOTX\/","parameter_short_description":"total organic Carbon","parameter_short_name":"TOC","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729384","supplied_name":"N_f_swimmer","supplied_units":"milligrams of nitrogen per square meter per day","value_format":null,"description":"\u003Cp\u003ETotal nitrogen flux of the \u0026gt;350-um screened fraction presumed to be zooplankton that actively entered the trap. Calculated as for \u0026#039;total nitrogen flux\u0026#039; above using a \u0026gt;350-um process blank of 0.005 +\/- 0.003 mg N.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1213","parameter_description":"\u003Cp\u003Etotal organic Nitrogen\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TON","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/NTOTZZZZ\/","parameter_short_description":"total organic Nitrogen","parameter_short_name":"TON","parameter_units":"micromoles\/liter","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729385","supplied_name":"N_f_err_swimmer","supplied_units":"milligrams of nitrogen per square meter per day","value_format":null,"description":"\u003Cp\u003ESwimmer total nitrogen flux error; Calculated for the \u0026gt;350-um screened fraction as for \u0026#039;total nitrogen flux error\u0026#039; above using a \u0026gt;350-um process blank standard deviation of 0.003 mg N.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"1213","parameter_description":"\u003Cp\u003Etotal organic Nitrogen\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"TON","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P01\/current\/NTOTZZZZ\/","parameter_short_description":"total organic Nitrogen","parameter_short_name":"TON","parameter_units":"micromoles\/liter","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729386","supplied_name":"A","supplied_units":"unitless","value_format":null,"description":"\u003Cp\u003EFlux particle size distribution magnitude and slope parameters\u00a0(parameter names \u2018A\u2019, \u2018B\u2019):\u00a0\u003C\/p\u003E\n\u003Cp\u003EParticles imaged in each gel at the same magnification were identified, enumerated and measured using an analysis macro created using ImageJ software. Using this macro, images were processed by 1) converting images to greyscale, 2) removing\u00a0background, 3) adjusting brightness\/contrast to a consistent degree, 4) thresholding using the \u201cIntermodes\u201d technique, 5) filling holes, and 6) measuring particles.\u00a0 Particles imaged from the same field of view but different focal planes were grouped together and the equivalent spherical diameter (ESD) of each particle was calculated based on the measured two-dimensional surface area. Particles were divided into 26 base-2, log-spaced size classes ranging from 1 um to 8192 um based on their ESD. Counting error was calculated as the square root of the number of particles counted in each size category. Size classes with 4 or fewer counted particles (\u226550% error) were excluded from analysis. The abundance of particles in each size bin was calculated by normalizing the number of particles counted by the size\u00a0bin\u00a0width and by the percentage of the gel surface counted. The optimal magnification to calculate the abundance of a particle size category was defined as the magnification where the observed abundance most closely followed a power-law distribution. The abundance of 11\u201345 um particles\u00a0was\u00a0quantified at 63\u00d7 magnification, the abundance of 45\u2013128 um particles\u00a0was\u00a0quantified at 16\u00d7 magnification, and the abundance of \u0026gt;128 um particles was quantified at 7\u00d7 magnification. Three samples had slightly different size detection limits at each magnification and required different size ranges to quantify a power law distribution of particle abundance. For the 200-m sample collected in August, optimal particle size ranges were 11\u201364 um (63\u00d7), 64\u201390 um (16\u00d7), and \u0026gt;90 um (7\u00d7). For the 500-m samples collected in October and March, the optimal size ranges were 11\u201345 um (63\u00d7), 45\u201364 um (16\u00d7), and \u0026gt;64 um (7\u00d7). The particle abundance of all five gel trap process blanks\u00a0were\u00a0measured and averaged together, and the average was subtracted from the particle abundance measured in each gel trap sample. Particle number flux was calculated by dividing blank-subtracted particle abundance by the trap deployment time.\u003C\/p\u003E\n\u003Cp\u003EThe slope of each particle size distribution (B) was calculated by fitting the observations of particle number flux (Num_f) to a differential power law size distribution model (Jackson et al., 1997),\u003C\/p\u003E\n\u003Cp\u003ENum_f(ESD) = A(ESDr) \u00d7 (ESD\/ESDr)\u2212B\u003C\/p\u003E\n\u003Cp\u003Ewhere A(ESDr) equals the number flux of particles in the reference size category ESDr\u00a0(here 300 um). B indicates the slope of the power law function; higher values have steeper slopes and a higher proportion of small particles relative to large particles. The \u201coptim\u201d function in R (R. Development Core Team, 2008) was used to find the least-squares, best-fit values of \u0391(ESDr) and \u0392 describing particle number fluxes measured in each gel trap.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":null,"parameter_nid":"1073","parameter_description":"\u003Cp\u003EAn association with a community-wide standard parameter has not yet been made.\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":null,"parameter_official_name":"no_bcodmo_term","parameter_external_identifier":null,"parameter_short_description":"No BCO-DMO term","parameter_short_name":"no_bcodmo_term","parameter_units":null,"parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729387","supplied_name":"B","supplied_units":"unitless","value_format":null,"description":"\u003Cp\u003EFlux particle size distribution magnitude and slope parameters\u00a0(parameter names \u2018A\u2019, \u2018B\u2019):\u00a0\u003C\/p\u003E\n\u003Cp\u003EParticles imaged in each gel at the same magnification were identified, enumerated and measured using an analysis macro created using ImageJ software. Using this macro, images were processed by 1) converting images to greyscale, 2) removing\u00a0background, 3) adjusting brightness\/contrast to a consistent degree, 4) thresholding using the \u201cIntermodes\u201d technique, 5) filling holes, and 6) measuring particles.\u00a0 Particles imaged from the same field of view but different focal planes were grouped together and the equivalent spherical diameter (ESD) of each particle was calculated based on the measured two-dimensional surface area. Particles were divided into 26 base-2, log-spaced size classes ranging from 1 um to 8192 um based on their ESD. Counting error was calculated as the square root of the number of particles counted in each size category. Size classes with 4 or fewer counted particles (\u226550% error) were excluded from analysis. The abundance of particles in each size bin was calculated by normalizing the number of particles counted by the size\u00a0bin\u00a0width and by the percentage of the gel surface counted. The optimal magnification to calculate the abundance of a particle size category was defined as the magnification where the observed abundance most closely followed a power-law distribution. The abundance of 11\u201345 um particles\u00a0was\u00a0quantified at 63\u00d7 magnification, the abundance of 45\u2013128 um particles\u00a0was\u00a0quantified at 16\u00d7 magnification, and the abundance of \u0026gt;128 um particles was quantified at 7\u00d7 magnification. Three samples had slightly different size detection limits at each magnification and required different size ranges to quantify a power law distribution of particle abundance. For the 200-m sample collected in August, optimal particle size ranges were 11\u201364 um (63\u00d7), 64\u201390 um (16\u00d7), and \u0026gt;90 um (7\u00d7). For the 500-m samples collected in October and March, the optimal size ranges were 11\u201345 um (63\u00d7), 45\u201364 um (16\u00d7), and \u0026gt;64 um (7\u00d7). The particle abundance of all five gel trap process blanks\u00a0were\u00a0measured and averaged together, and the average was subtracted from the particle abundance measured in each gel trap sample. Particle number flux was calculated by dividing blank-subtracted particle abundance by the trap deployment time.\u003C\/p\u003E\n\u003Cp\u003EThe slope of each particle size distribution (B) was calculated by fitting the observations of particle number flux (Num_f) to a differential power law size distribution model (Jackson et al., 1997),\u003C\/p\u003E\n\u003Cp\u003ENum_f(ESD) = A(ESDr) \u00d7 (ESD\/ESDr)\u2212B\u003C\/p\u003E\n\u003Cp\u003Ewhere A(ESDr) equals the number flux of particles in the reference size category ESDr\u00a0(here 300 um). B indicates the slope of the power law function; higher values have steeper slopes and a higher proportion of small particles relative to large particles. The \u201coptim\u201d function in R (R. Development Core Team, 2008) was used to find the least-squares, best-fit values of \u0391(ESDr) and \u0392 describing particle number fluxes measured in each gel trap.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":null,"parameter_nid":"1073","parameter_description":"\u003Cp\u003EAn association with a community-wide standard parameter has not yet been made.\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":null,"parameter_official_name":"no_bcodmo_term","parameter_external_identifier":null,"parameter_short_description":"No BCO-DMO term","parameter_short_name":"no_bcodmo_term","parameter_units":null,"parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729388","supplied_name":"zoop_conc","supplied_units":"individuals per square meter","value_format":null,"description":"\u003Cp\u003EZooplankton concentration; Recognizable zooplankton presumed to have actively entered the gel traps were counted manually in 40 fields of view at 32_ magnification on the stereomicroscope. The number of individuals counted was normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2).\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"735","parameter_description":"\u003Cp\u003EAmount (number, mass, diversity\/species variation) of the specific taxa\/group counted per unit area or volume\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"abundance","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P03\/current\/B070\/","parameter_short_description":"abundance ","parameter_short_name":"abundance","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729389","supplied_name":"zoop_conc_err","supplied_units":"individuals per square meter","value_format":null,"description":"\u003Cp\u003EZooplankton concentration error; Calculated as the square root of the number of individuals counted normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2).\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"735","parameter_description":"\u003Cp\u003EAmount (number, mass, diversity\/species variation) of the specific taxa\/group counted per unit area or volume\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"abundance","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P03\/current\/B070\/","parameter_short_description":"abundance ","parameter_short_name":"abundance","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729390","supplied_name":"zoop_f","supplied_units":"individuals per square meter per day","value_format":null,"description":"\u003Cp\u003EZooplankton flux; The zooplankton concentration calculated above was divided by the deployment length to yield flux.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"735","parameter_description":"\u003Cp\u003EAmount (number, mass, diversity\/species variation) of the specific taxa\/group counted per unit area or volume\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"abundance","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P03\/current\/B070\/","parameter_short_description":"abundance ","parameter_short_name":"abundance","parameter_units":"various","parameter_units_external_identifier":null,"order":null},{"dataset_parameter_nid":"729391","supplied_name":"zoop_f_err","supplied_units":"individuals per square meter per day","value_format":null,"description":"\u003Cp\u003EZooplankton flux error; Calculated as the square root of the number of individuals counted normalized by the percentage of gel surface counted and divided by the total surface area of the gel (0.0095 m^2) and the deployment length.\u003C\/p\u003E\n","no_data_value":"nd","conversion_necessary":"no","conversion_utility":"","parameter_nid":"735","parameter_description":"\u003Cp\u003EAmount (number, mass, diversity\/species variation) of the specific taxa\/group counted per unit area or volume\u003C\/p\u003E\n","parameter_max_value":null,"parameter_min_value":null,"parameter_nd_value":"nd","parameter_official_name":"abundance","parameter_external_identifier":"http:\/\/vocab.nerc.ac.uk\/collection\/P03\/current\/B070\/","parameter_short_description":"abundance ","parameter_short_name":"abundance","parameter_units":"various","parameter_units_external_identifier":null,"order":null}]