BADM Group Overview
BADM variables in this group are organized into subgroups as shown below. The overview highlights what variables are required per subgroup. It also indicates which variables cannot be specified together ( OR ) in the same group entry. Variables in "Applies to All" are included with all subgroups. See BADM Basics for more details.
Multiple entries of this BADM group can be reported per site. However, combinations of Ⓒ variables must be unique. Read more:
Applies to All
Optional Variable
Ⓒ Combinations
Examples
Required  Optional  

Soil Organic Carbon Concentration  
Soil Total Nitrogen Concentration  
Soil NH4 Concentration  
Soil NO3 Concentration  
Soil Potassium Concentration  
Soil Phosphorus Concentration  
Soil Carbon/Nitrogen Ratio  
Soil pH by Salt  
Soil pH by H2O  
Soil Bulk Density  
Applies to All 
BADM variables: Definitions, Units, Requirements
See Overview tab or BADM Basics for explanation of Required and Optional variables.
Multiple entries of this BADM group can be reported per site. However, combinations of Ⓒ variables must be unique. Read more:
Applies to All
Optional Variable
Ⓒ Combinations
Examples
Variable Requirements  Units  Description 

SOIL_CHEM_C_ORG 1Required  g C kg soil1  Soil organic carbon concentration 
SOIL_CHEM_C_ORG_STATISTIC Ⓒ 1Required  LIST(STATISTIC) Show  Soil organic carbon concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_C_ORG_STATISTIC_METHOD Ⓒ 1Optional  LIST(STATISTIC_METHOD) Show  Soil organic carbon concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_C_ORG_STATISTIC_NUMBER 1Optional  integer number  Number of observations used to determine soil organic carbon concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_N_TOT 2Required  g N kg soil1  Soil total nitrogen concentration 
SOIL_CHEM_N_TOT_STATISTIC Ⓒ 2Required  LIST(STATISTIC) Show  Soil total nitrogen concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_N_TOT_STATISTIC_METHOD Ⓒ 2Optional  LIST(STATISTIC_METHOD) Show  Soil total nitrogen concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_N_TOT_STATISTIC_NUMBER 2Optional  integer number  Number of observations used to determine soil total nitrogen concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_NH4 3Required  g NH4 kg soil1  Soil ammonium concentration 
SOIL_CHEM_NH4_STATISTIC Ⓒ 3Required  LIST(STATISTIC) Show  Soil ammonium concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_NH4_STATISTIC_METHOD Ⓒ 3Optional  LIST(STATISTIC_METHOD) Show  Soil ammonium concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_NH4_STATISTIC_NUMBER 3Optional  integer number  Number of observations used to determine soil ammonium concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_NO3 4Required  g NO3 kg soil1  Soil nitrate concentration 
SOIL_CHEM_NO3_STATISTIC Ⓒ 4Required  LIST(STATISTIC) Show  Soil nitrate concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_NO3_STATISTIC_METHOD Ⓒ 4Optional  LIST(STATISTIC_METHOD) Show  Soil nitrate concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_NO3_STATISTIC_NUMBER 4Optional  integer number  Number of observations used to determine soil nitrate concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_K 5Required  g K kg soil1  Soil potassium concentration 
SOIL_CHEM_K_STATISTIC Ⓒ 5Required  LIST(STATISTIC) Show  Soil potassium concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_K_STATISTIC_METHOD Ⓒ 5Optional  LIST(STATISTIC_METHOD) Show  Soil potassium concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_K_STATISTIC_NUMBER 5Optional  integer number  Number of observations used to determine soil potassium concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_P 6Required  g P kg soil1  Soil phosphorus concentration 
SOIL_CHEM_P_STATISTIC Ⓒ 6Required  LIST(STATISTIC) Show  Soil phosphorus concentration statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_P_STATISTIC_METHOD Ⓒ 6Optional  LIST(STATISTIC_METHOD) Show  Soil phosphorus concentration statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_P_STATISTIC_NUMBER 6Optional  integer number  Number of observations used to determine soil phosphorus concentration statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_CN_RATIO 7Required  % by mass  Soil C/N ratio Soil carbon to nitrogen ratio. 
SOIL_CHEM_CN_RATIO_STATISTIC Ⓒ 7Required  LIST(STATISTIC) Show  Soil C/N ratio statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_CN_RATIO_STATISTIC_METHOD Ⓒ 7Optional  LIST(STATISTIC_METHOD) Show  Soil C/N ratio statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_CN_RATIO_STATISTIC_NUMBER 7Optional  integer number  Number of observations used to determine soil C/N ratio statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_PH_SALT 8Required  decimal number  Soil pH by CaCl2 or other salt If pH is determined with a salt other than CaCl2, specify the salt used in Approach. 
SOIL_CHEM_PH_SALT_STATISTIC Ⓒ 8Required  LIST(STATISTIC) Show  Soil pH by CaCl2 or other salt statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_PH_SALT_STATISTIC_METHOD Ⓒ 8Optional  LIST(STATISTIC_METHOD) Show  Soil pH by CaCl2 or other salt statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_PH_SALT_STATISTIC_NUMBER 8Optional  integer number  Number of observations used to determine soil pH by CaCl2 or other salt statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_PH_H2O 9Required  decimal number  Soil pH by H2O Soil pH determined in water. 
SOIL_CHEM_PH_H2O_STATISTIC Ⓒ 9Required  LIST(STATISTIC) Show  Soil pH by H2O statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_PH_H2O_STATISTIC_METHOD Ⓒ 9Optional  LIST(STATISTIC_METHOD) Show  Soil pH by H2O statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_PH_H2O_STATISTIC_NUMBER 9Optional  integer number  Number of observations used to determine soil pH by H2O statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_BD 10Required  g cm3  Soil bulk density 
SOIL_CHEM_BD_STATISTIC Ⓒ 10Required  LIST(STATISTIC) Show  Soil bulk density statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). 
SOIL_CHEM_BD_STATISTIC_METHOD Ⓒ 10Optional  LIST(STATISTIC_METHOD) Show  Soil bulk density statistic method Method used to generate the reported statistic (e.g., aggregate of individuals, aggregate of sample aggregates) from observations representing the same time period. Use predefined list. The aggregation method is not meant to describe temporal aggregations for example in calculations of higher frequency observations (e.g., subminute) to lower frequency observations (e.g., hourly) at a single location. 
SOIL_CHEM_BD_STATISTIC_NUMBER 10Optional  integer number  Number of observations used to determine soil bulk density statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. 
SOIL_CHEM_PROFILE_ZERO_REF Ⓒ Optional  LIST(PROFILE_ZERO_REF) Show  Soil chemistry profile zero reference Profile Zero Reference is the horizontal plane from which the soil profile minimum and maximum depths are measured. For example, top of mineral soil or top of litter layer. Use predefined list. 
SOIL_CHEM_PROFILE_MIN Ⓒ Optional  cm  Soil chemistry profile minimum depth Profile minimum depth is the vertical distance from profile zero reference to the top of soil layer being measured. 
SOIL_CHEM_PROFILE_MAX Ⓒ Optional  cm  Soil chemistry profile maximum depth Profile maximum depth is the vertical distance from profile zero reference to the bottom of soil layer being measured. 
SOIL_CHEM_HORIZON Optional  free text  Soil chemistry profile horizon Use soil horizon scheme best suited for your soil. Examples include O, Oa, B, Bt, C. 
SOIL_CHEM_APPROACH Optional  free text  Soil chemistry measurement approach Approach describes both sampling and processing methodologies. Please provide details that will improve intepretation of measurement/assessment, facilitate comparison with similar measures made with different approaches, and/or allow for quality checking. 
SOIL_CHEM_DATE Ⓒ Required  YYYYMMDDHHMM  Soil chemistry measurement sampling date Please report the date at the precision known. Allowed reporting precisions are YYYY, YYYYMM, YYYYMMDD, and YYYYMMDDHHMM. 
SOIL_CHEM_DATE_UNC Optional  days  Uncertainty in the Soil chemistry measurement sampling date 
SOIL_CHEM_COMMENT Optional  free text  Soil chemistry comments 
BADM Examples
Choose a variable marked with to show examples of how to submit and interpret these BADM. See BADM Basics for more details.
Combinations of Ⓒ variables must be unique. Read more: .
Applies to All
Optional Variable
Ⓒ Combinations
Examples
Soil Organic Carbon Concentration 
Soil Total Nitrogen Concentration 
Soil NH4 Concentration 
Soil NO3 Concentration 
Soil Potassium Concentration 
Soil Phosphorus Concentration 
Soil Carbon/Nitrogen Ratio 
Soil pH by Salt 
Soil pH by H2O 
Soil Bulk Density 
Applies to All 
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
STATISTIC Variables
Many BADM groups have a required and several optional STATISTIC variables. Specific examples of their use are given after an overview the variables basics.
STATISTIC Basics
BADM typically describe sitelevel descriptions and observations. The STATISTIC variables allow for full characterization of the reported information if desired. BADM groups, such as canopy height, LAI, soil chemistry, phenology, and biomass, contain the following STATISTIC variables:
var_STATISTIC Required  The type of value reported. Options: 
var_STATISTIC_METHOD Optional  The method of aggregation used to generate the statistic. Options: Statistics generated by this approach may represent spatial characteristics of the measurement within the site (e.g., spatial heterogeneity) and/or characteristics due to other factors (e.g., population variability). Aggregate of sample aggregates Statistics generated by this approach are often used to highlight the spatial characteristics within the site (i.e., the spatial heterogeneity of measurement within the site). Expert estimate See the Examples for more details. 
var_STATISTIC_NUMBER Optional  The number of observations used in calculating the statistic. 
STATISTIC Examples
Example 1: DBH calculated from a single sampling area
Example 2: DBH calculated from 8 plots
Example 3: DBH calculated from randomly selected trees within the site
Example 4: Biomass calculated from 8 plots each with 5 subplots
Example 5: Soil carbon calculated from replicate samples at 10 locations
Example 1: DBH calculated from a single sampling area
For DBH observations of individual trees in a single sample area at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 2: DBH calculated from 8 plots
For DBH observations of individual trees in 8 sample plots at the site:
If the individual DBH observations are first aggregated at the plot level and then the plot values are are used to calculate the sitelevel STATISTICs to highlight spatial variability:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If the individual DBH observations are aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 3: DBH calculated from randomly selected trees within the site
For DBH observations of individual trees randomly selected at the site:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = # of individual samples
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 4: Biomass calculated from 8 plots each with 5 subplots
For Biomass observations collected from 5 subplots located in each of 8 sample plots at the site:
In many cases, the subplot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the sitelevel STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudoreplication or spatial autocorrelation is not an issue, the subplot observations may be aggregated across all plots to calculate the sitelevel STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 40
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
Example 5: Soil carbon calculated from replicate samples at 10 locations
For replicate soil carbon observations at 10 randomlyselected points within the site:
To calculate Mean, Minimum, Maximum, Percentiles, and Standard Deviation, the replicates at each location should first be averaged. Then the average values at each location can be used to calculate the STATISTIC:
STATISTIC* = Mean, Minimum, Maximum, Percentiles, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 10
* Minimum, Maximum, and Percentiles should only be calculated if the sample size is adequately large.
The average difference between the replicates can be used to estimate the Measurement Uncertainty:
STATISTIC = Measurement Uncertainty
STATISTIC_METHOD = Aggregate of individual observations
STATISTIC_NUMBER = 10
DATE and DATE_UNC
DATE
Many groups require DATE to describe the time period that the metadata or ancillary data represents.
Dates should be entered at the precision known and most suitable to the observation. Supported precision include year, month, day, and minute in ISO formats: YYYY, YYYYMM, YYYYMMDD, YYYYMMDDHHMM.
Typical resolutions used for DATE are year, month, or day: YYYY, YYYYMM, YYYYMMDD.
DATE_UNC
Uncertainty in the DATE is an optional variable that can also be reported.
Report a date uncertainty that is commensurate with the DATE reported. For example if a day is reported for the DATE, date uncertainty should be on the order of days rather than months or years. If a year is reported for the DATE, date uncertainty should be greater than a year.
Customize and Download CSV for BADM Submission
Select variables from one or more subgroups to form a complete group. At a minimum, the required variables from the “Applies to All” subgroup must be included in every group. After selecting your desired variables, download the customized CSV file for submission of BADM. For additional submission details, see BADM Submission Instructions.
Multiple entries of this BADM group can be reported per site. However, combinations of Ⓒ variables must be unique. Read more: . See BADM Basics for more details.
Applies to All
Optional Variable
Ⓒ Combinations
Examples
Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Required  Optional  



Submit completed CSV file at Upload Data using the BADM option (login required).