AmeriFlux

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 Variable
Applies to All
Optional Variable
Ⓒ Combinations
Examples

Required

Optional

Canopy Height

HEIGHTC

HEIGHTC_STATISTIC Ⓒ

HEIGHTC_SPP Ⓒ

HEIGHTC_VEGTYPE Ⓒ

HEIGHTC_STATISTIC_METHOD Ⓒ

HEIGHTC_STATISTIC_NUMBER

Understory Height

HEIGHTC_U

HEIGHTC_U_STATISTIC Ⓒ

HEIGHTC_U_SPP Ⓒ

HEIGHTC_U_VEGTYPE Ⓒ

HEIGHTC_U_STATISTIC_METHOD Ⓒ

HEIGHTC_U_STATISTIC_NUMBER

Applies to All

HEIGHTC_DATE Ⓒ

HEIGHTC_DATE_START Ⓒ

HEIGHTC_DATE_END

HEIGHTC_APPROACH

HEIGHTC_DATE_UNC

HEIGHTC_COMMENT

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:

Required Variable
Applies to All
Optional Variable
Ⓒ Combinations
Examples

Variable
Requirements

Units

Description

HEIGHTC
1-Required

Canopy height
Height of the canopy. In a forest ecosystem, canopy height is the distribution of overstory trees that see light at the top of the canopy. Forest understory canopy height is reported in HEIGHTC_U. If overstory / understory distinction is necessary for non-forest ecosystems, describe details in Approach.

HEIGHTC_SPP
Ⓒ 1-Optional-a

Scientific name

Canopy height species (taxa)
Vegetation species being described by the measurement. To enter a plant species, use the scientific name (Genus species Author or Genus Author). Please refer to www.theplantlist.org for current scientific names and authors. If the measurement includes all vegetation present, do not enter a value. Do not use SPP if reporting VEGTYPE.

HEIGHTC_VEGTYPE
Ⓒ 1-Optional-a

LIST(VEGTYPE) Show

Canopy height vegetation type
Use the predefined list to indicate the type of vegetation being described by the measurement (e.g., Grass, Evergreen Tree, Deciduous Tree, etc). If the measurement includes all vegetation present, do not enter a value. If vegetation type is not in predfined list, enter "Other/Not in list" and describe briefly in Approach. Do not use VEGTYPE if reporting SPP.

VEGTYPE Options×

Option	Description
Grass
C3 Grass
C4 Grass
Grass / Graminoid	Grasses, Sedges, Rushes, and other grass-like monocots (member of order Poales)
Crop
Herbaceous Crop
Woody Crop
Tree
Deciduous Tree	Trees that shed their entire canopy seasonallly. Drought or cold avoidence are common reasons for deciduousness.
Evergreen Tree	Trees that do not seasonally shed their full canopies.
Shrub
Herb / Forb
Annual Herb / Forb
Perennial Herb / Forb
Aerenchymatous Plants
Liana / vine
Succulant	Cactus, Euphorbs, including CAM
Non-vascular	Moss, lichen
Other/Not in list	Only use this option if a major vegetation group is not included already included in the predefined list. If an existing vegetation group is not specific enough, use the existing vegetation option and add details in Approach (rather than using the "Other/Not in list" option).
No vegetation	Bare ground, water, or rock. Use only with SPP_PERC_O and SPP_PERC_U
Water	Water (perennially submerged ground)

HEIGHTC_STATISTIC
Ⓒ 1-Required

LIST(STATISTIC) Show

Canopy height statistic
The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc).

STATISTIC Options×

Option	Description
Mean	Average (mean) value of sample population
Standard Deviation	Standard deviation may be reported from a sample population that consists of individual or aggregated samples (observations). If the distinction is important, specify in STATISTIC_METHOD or Comments.
Minimum	Minimum value
1st Percentile	Quantile at 1% of distribution
5th Percentile	Quantile at 5% of distribution
10th Percentile	Quantile at 10% of distribution
25th Percentile	Quantile at 25% of distribution
Median - 50th Percentile	Median - Quantile at 50% of distribution
75th Percentile	Quantile at 75% of distribution
90th Percentile	Quantile at 90% of distribution
95th Percentile	Quantile at 95% of distribution
99th Percentile	Quantile at 99% of distribution
Maximum	Maximum value
Single observation	Single observation that is not a calculated statistic of replicates either to get a robust estimate or for spatial variability analysis. For example a single biomass observation may be the vegetation harvested in a single 1 x 1 meter area.
Measurement Uncertainty	Report uncertainty as a plus or minus value in the measurement units. For example, enter 1.5 for +/- 1.5 units. Uncertainty may be reported from the instrument's specifications, determined empirically, or estimated by the tower team. Please describe such details in Approach. For uncertainty values that are better described by a range, a percent, or other, please enter information in Comments.

HEIGHTC_STATISTIC_METHOD
Ⓒ 1-Optional

LIST(STATISTIC_METHOD) Show

Canopy height 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.

STATISTIC_METHOD Options×

Option	Description
Aggregate of individual observations	The statistic is aggregated from individual observations located within the site. Observations may be grouped into sample areas (e.g., plots) within the site but those groupings are ignored. Statistics generated from individual observations directly yield information on the site generally. The statistic 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	The statistic is aggregated from aggregated individual observations located in sample areas within the site. For example, individual observations are made in 5 sample plots within a site. "Aggregate of sample aggregates" is used if a plot statistic (e.g., Mean) is first calculated, and then the plot values are aggregated to calculate the site statistic. 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	Estimate made by expert familiar with site

HEIGHTC_STATISTIC_NUMBER
1-Optional

integer number

Number of observations used to determine canopy height statistic
Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement.

HEIGHTC_U
2-Required

Understory canopy height
Canopy height of the understory. Typically reported only for forest ecosystems. Describe how understory was determined in Approach. If HEIGHTC_U is reported for non-forest ecosystems, clearly describe ecosystem and methodological details in Approach.

HEIGHTC_U_SPP
Ⓒ 2-Optional-b

Scientific name

Understory canopy height species (taxa)
Vegetation species being described by the measurement. To enter a plant species, use the scientific name (Genus species Author or Genus Author). Please refer to www.theplantlist.org for current scientific names and authors. If the measurement includes all vegetation present, do not enter a value. Do not use SPP if reporting VEGTYPE.

HEIGHTC_U_VEGTYPE
Ⓒ 2-Optional-b

LIST(VEGTYPE) Show

Understory canopy height vegetation type
Use the predefined list to indicate the type of vegetation being described by the measurement (e.g., Grass, Evergreen Tree, Deciduous Tree, etc). If the measurement includes all vegetation present, do not enter a value. If vegetation type is not in predfined list, enter "Other/Not in list" and describe briefly in Approach. Do not use VEGTYPE if reporting SPP.

VEGTYPE Options×

Option	Description
Grass
C3 Grass
C4 Grass
Grass / Graminoid	Grasses, Sedges, Rushes, and other grass-like monocots (member of order Poales)
Crop
Herbaceous Crop
Woody Crop
Tree
Deciduous Tree	Trees that shed their entire canopy seasonallly. Drought or cold avoidence are common reasons for deciduousness.
Evergreen Tree	Trees that do not seasonally shed their full canopies.
Shrub
Herb / Forb
Annual Herb / Forb
Perennial Herb / Forb
Aerenchymatous Plants
Liana / vine
Succulant	Cactus, Euphorbs, including CAM
Non-vascular	Moss, lichen
Other/Not in list	Only use this option if a major vegetation group is not included already included in the predefined list. If an existing vegetation group is not specific enough, use the existing vegetation option and add details in Approach (rather than using the "Other/Not in list" option).
No vegetation	Bare ground, water, or rock. Use only with SPP_PERC_O and SPP_PERC_U
Water	Water (perennially submerged ground)

HEIGHTC_U_STATISTIC
Ⓒ 2-Required

LIST(STATISTIC) Show

Understory canopy height statistic
The statistic for the measurement reported. Use predefined list (e.g., mean, min / max, standard deviation, etc).

STATISTIC Options×

Option	Description
Mean	Average (mean) value of sample population
Standard Deviation	Standard deviation may be reported from a sample population that consists of individual or aggregated samples (observations). If the distinction is important, specify in STATISTIC_METHOD or Comments.
Minimum	Minimum value
1st Percentile	Quantile at 1% of distribution
5th Percentile	Quantile at 5% of distribution
10th Percentile	Quantile at 10% of distribution
25th Percentile	Quantile at 25% of distribution
Median - 50th Percentile	Median - Quantile at 50% of distribution
75th Percentile	Quantile at 75% of distribution
90th Percentile	Quantile at 90% of distribution
95th Percentile	Quantile at 95% of distribution
99th Percentile	Quantile at 99% of distribution
Maximum	Maximum value
Single observation	Single observation that is not a calculated statistic of replicates either to get a robust estimate or for spatial variability analysis. For example a single biomass observation may be the vegetation harvested in a single 1 x 1 meter area.
Measurement Uncertainty	Report uncertainty as a plus or minus value in the measurement units. For example, enter 1.5 for +/- 1.5 units. Uncertainty may be reported from the instrument's specifications, determined empirically, or estimated by the tower team. Please describe such details in Approach. For uncertainty values that are better described by a range, a percent, or other, please enter information in Comments.

HEIGHTC_U_STATISTIC_METHOD
Ⓒ 2-Optional

LIST(STATISTIC_METHOD) Show

Understory canopy height 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.

STATISTIC_METHOD Options×

Option	Description
Aggregate of individual observations	The statistic is aggregated from individual observations located within the site. Observations may be grouped into sample areas (e.g., plots) within the site but those groupings are ignored. Statistics generated from individual observations directly yield information on the site generally. The statistic 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	The statistic is aggregated from aggregated individual observations located in sample areas within the site. For example, individual observations are made in 5 sample plots within a site. "Aggregate of sample aggregates" is used if a plot statistic (e.g., Mean) is first calculated, and then the plot values are aggregated to calculate the site statistic. 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	Estimate made by expert familiar with site

HEIGHTC_U_STATISTIC_NUMBER
2-Optional

integer number

Number of observations used to determine understory canopy height statistic
Number of observations (samples / replicates) used to calculate the STATISTIC for the reported measurement.

HEIGHTC_APPROACH
Optional

free text

Canopy height measurement approach

HEIGHTC_DATE
Ⓒ Required-c

YYYYMMDDHHMM

Canopy height measurement date
Please report the date at the precision known. Allowed reporting precisions are YYYY, YYYYMM, YYYYMMDD, and YYYYMMDDHHMM. For measurements conducted during a campaign or for temporal averages, use DATE_START and DATE_END instead of DATE.

HEIGHTC_DATE_START
Ⓒ Required-c

YYYYMMDDHHMM

Start date of canopy height measurment
Start date of a measurement campaign or start date of a temporal average. Please report the date at the precision known. Allowed reporting precisions are YYYY, YYYYMM, YYYYMMDD, and YYYYMMDDHHMM. Do not use DATE_START if DATE is used.

HEIGHTC_DATE_END
Required

YYYYMMDDHHMM

End date of canopy height measurment
End date of a measurement campaign or end date of a temporal average. Please report the date at the precision known. Allowed reporting precisions are YYYY, YYYYMM, YYYYMMDD, and YYYYMMDDHHMM. Do not use DATE_END if DATE is used.

HEIGHTC_DATE_UNC
Optional

days

Uncertainty in the canopy height measurement date, start date, and/or end date
If uncertainty in the start date differs than end date, report the uncertainty for start date here in DATE_UNC and the uncertainty for end date in Comments.

HEIGHTC_COMMENT
Optional

free text

Canopy height 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: .

Required Variable
Applies to All
Optional Variable
Ⓒ Combinations
Examples

Canopy Height

HEIGHTC

HEIGHTC_SPP Ⓒ

HEIGHTC_VEGTYPE Ⓒ

HEIGHTC_STATISTIC Ⓒ

HEIGHTC_STATISTIC_METHOD Ⓒ

HEIGHTC_STATISTIC_NUMBER

Understory Height

HEIGHTC_U

HEIGHTC_U_SPP Ⓒ

HEIGHTC_U_VEGTYPE Ⓒ

HEIGHTC_U_STATISTIC Ⓒ

HEIGHTC_U_STATISTIC_METHOD Ⓒ

HEIGHTC_U_STATISTIC_NUMBER

Applies to All

HEIGHTC_APPROACH

HEIGHTC_DATE Ⓒ

HEIGHTC_DATE_START Ⓒ

HEIGHTC_DATE_END

HEIGHTC_DATE_UNC

HEIGHTC_COMMENT

Click a variable marked with to see examples.

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:
Mean, Minimum, Maximum, Percentiles
Standard Deviation, Measurement Uncertainty
Single observation

var_STATISTIC_METHOD
Optional

The method of aggregation used to generate the statistic.

Options:
Aggregate of individual observations
The statistic is aggregated from individual observations located within the site. Observations may be grouped into sample areas (e.g., plots) within the site but those groupings are ignored.

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
The statistic is aggregated from aggregated individual observations located in sample areas within the site. For example, individual observations are made in 5 sample plots within a site. “Aggregate of sample aggregates” is used if a plot statistic (e.g., Mean) is first calculated, and then the plot values are aggregated to calculate the site statistic.

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
Estimate made by expert familiar with site

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

var_STATISTIC
Required

The type of value reported.

Options:
Mean, Minimum, Maximum, Percentiles
Standard Deviation, Measurement Uncertainty
Single observation

var_STATISTIC_METHOD
Optional

The method of aggregation used to generate the statistic.

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
Estimate made by expert familiar with site

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

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:

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

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.

Open/Close

Select

Canopy Height

Required

Optional

HEIGHTC

HEIGHTC_SPP Ⓒ

Both

Neither

HEIGHTC_STATISTIC_NUMBER

Understory Height

Required

Optional

HEIGHTC_U

Both

Neither

HEIGHTC_U_STATISTIC_NUMBER

Applies to All

Required

Optional

HEIGHTC_DATE Ⓒ

HEIGHTC_DATE_END

Both

HEIGHTC_APPROACH

HEIGHTC_DATE_UNC

HEIGHTC_COMMENT

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

BADM Group: HEIGHTC

BADM Group Overview

BADM variables: Definitions, Units, Requirements

BADM Examples

HEIGHTC

SPP and VEGTYPE Variables

STATISTIC Variables

STATISTIC Basics

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

SPP and VEGTYPE Variables

STATISTIC Variables

STATISTIC Basics

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

DATE Variables

DATE or DATE_START / DATE_END

DATE_UNC

Customize and Download CSV for BADM Submission