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:
| Required | Optional | |||||||
|---|---|---|---|---|---|---|---|---|
Sand Content | ||||||||
Silt Content | ||||||||
Clay Content | ||||||||
Rock Content | ||||||||
Water Holding Capacity | ||||||||
Wilting Point | ||||||||
Water Saturation Point | ||||||||
Field Capacity | ||||||||
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:
| Variable Requirements | Units | Description |
|---|---|---|
| SOIL_TEX_SAND1-Required | % | Sand content |
| SOIL_TEX_SAND_STATISTICⒸ 1-Required | LIST(STATISTIC) Show | Sand content statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_SAND_STATISTIC_METHODⒸ 1-Optional | LIST(STATISTIC_METHOD) Show | Sand content 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_SAND_STATISTIC_NUMBER1-Optional | integer number | Number of observations used to determine sand content statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_SILT2-Required | % | Silt content |
| SOIL_TEX_SILT_STATISTICⒸ 2-Required | LIST(STATISTIC) Show | Silt content statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_SILT_STATISTIC_METHODⒸ 2-Optional | LIST(STATISTIC_METHOD) Show | Silt content 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_SILT_STATISTIC_NUMBER2-Optional | integer number | Number of observations used to determine silt content statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_CLAY3-Required | % | Clay content |
| SOIL_TEX_CLAY_STATISTICⒸ 3-Required | LIST(STATISTIC) Show | Clay content statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_CLAY_STATISTIC_METHODⒸ 3-Optional | LIST(STATISTIC_METHOD) Show | Clay content 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_CLAY_STATISTIC_NUMBER3-Optional | integer number | Number of observations used to determine clay content statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_ROCK4-Required | % | Rock content (>2mm) |
| SOIL_TEX_ROCK_STATISTICⒸ 4-Required | LIST(STATISTIC) Show | Rock content (>2mm) statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_ROCK_STATISTIC_METHODⒸ 4-Optional | LIST(STATISTIC_METHOD) Show | Rock content (>2mm) 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_ROCK_STATISTIC_NUMBER4-Optional | integer number | Number of observations used to determine rock content (>2mm) statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_WATER_HOLD_CAP5-Required | %vol | Soil water holding capacity Amount of water in the soil that is held between field capacity and wilting point. |
| SOIL_TEX_WATER_HOLD_CAP_STATISTICⒸ 5-Required | LIST(STATISTIC) Show | Soil water holding capacity statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_WATER_HOLD_CAP_STATISTIC_METHODⒸ 5-Optional | LIST(STATISTIC_METHOD) Show | Soil water holding capacity 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_WATER_HOLD_CAP_STATISTIC_NUMBER5-Optional | integer number | Number of observations used to determine soil water holding capacity statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_WILT6-Required | %vol | Wilting point The amount of water in the soil at -1500 kPa (-15 Bar) or at which plants wilt. Please define in Approach. |
| SOIL_TEX_WILT_STATISTICⒸ 6-Required | LIST(STATISTIC) Show | Wilting point statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_WILT_STATISTIC_METHODⒸ 6-Optional | LIST(STATISTIC_METHOD) Show | Wilting point 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_WILT_STATISTIC_NUMBER6-Optional | integer number | Number of observations used to determine wilting point statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_SAT7-Required | %vol | Soil water saturation point The amount of water in soil at saturation (or when no pressure is required to remove water from the soil). |
| SOIL_TEX_SAT_STATISTICⒸ 7-Required | LIST(STATISTIC) Show | Soil water saturation point statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_SAT_STATISTIC_METHODⒸ 7-Optional | LIST(STATISTIC_METHOD) Show | Soil water saturation point 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_SAT_STATISTIC_NUMBER7-Optional | integer number | Number of observations used to determine soil water saturation point statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_FIELD_CAP8-Required | %vol | Field capacity Amount of water in the soil at -33 kPa (-0.33 Bar) or that remains after soil has been saturated and free drainage stops. Please define in Approach. |
| SOIL_TEX_FIELD_CAP_STATISTICⒸ 8-Required | LIST(STATISTIC) Show | Field capacity statistic The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc). |
| SOIL_TEX_FIELD_CAP_STATISTIC_METHODⒸ 8-Optional | LIST(STATISTIC_METHOD) Show | Field capacity 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., sub-minute) to lower frequency observations (e.g., hourly) at a single location. |
| SOIL_TEX_FIELD_CAP_STATISTIC_NUMBER8-Optional | integer number | Number of observations used to determine field capacity statistic Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement. |
| SOIL_TEX_PROFILE_ZERO_REFⒸ Optional | LIST(PROFILE_ZERO_REF) Show | Soil texture 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_TEX_PROFILE_MINⒸ Optional | cm | Soil texture profile minimum depth Profile minimum depth is the vertical distance from profile zero reference to the top of soil layer being measured. |
| SOIL_TEX_PROFILE_MAXⒸ Optional | cm | Soil texture profile maximum depth Profile maximum depth is the vertical distance from profile zero reference to the bottom of soil layer being measured. |
| SOIL_TEX_HORIZONOptional | free text | Soil texture profile horizon Use soil horizon scheme best suited for your soil. Examples include O, Oa, B, Bt, C. |
| SOIL_TEX_APPROACHOptional | free text | Soil texture measurement approach |
| SOIL_TEX_DATEⒸ Required | YYYYMMDDHHMM | Soil texture measurement date Please report the date at the precision known. Allowed reporting precisions are YYYY, YYYYMM, YYYYMMDD, and YYYYMMDDHHMM. |
| SOIL_TEX_DATE_UNCOptional | days | Uncertainty in the Soil texture measurement date |
| SOIL_TEX_COMMENTOptional | free text | Soil texture 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: .
| Sand Content |
| Silt Content |
| Clay Content |
| Rock Content |
| Water Holding Capacity |
| Wilting Point |
| Water Saturation Point |
| Field Capacity |
| 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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 site-level 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 sub-plots
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 site-level 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 site-level 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 sub-plots
For Biomass observations collected from 5 sub-plots located in each of 8 sample plots at the site:
In many cases, the sub-plot biomass observations are first aggregated at the plot level. Then the plot values are are used to calculate the site-level STATISTICs:
STATISTIC* = Mean, Minimum, Maximum, or Standard Deviation
STATISTIC_METHOD = Aggregate of sample aggregates
STATISTIC_NUMBER = 8
If pseudo-replication or spatial autocorrelation is not an issue, the sub-plot observations may be aggregated across all plots to calculate the site-level 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 randomly-selected 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.
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Submit completed CSV file at Upload Data using the BADM option (login required).