cwd_biomass_nfi() function estimates volume, carbon storage and carbon dioxide storage of Coarse Woody Debris (CWD).
It can estimate individual plots, the entire study area, or specific groups within the study area using parameters byplot
, plotgrp
and treegrp
.
Users can choose the criteria for post-stratification using the strat
parameter.
Users can specify whether to focus only on Stocked land using the stockedland
parameter.
Usage
cwd_biomass_nfi(
data,
byplot = FALSE,
plotgrp = NULL,
treegrp = NULL,
continuousplot = FALSE,
strat = "FORTYP_SUB",
stockedland = TRUE
)
Arguments
- data
: A
list
generated byread_nfi
that contains 'plot' and 'cwd' data frames.- byplot
: A logical flag (default FALSE); if TRUE, calculates statistics for each plot separately. If FALSE, calculates for the entire dataset.
- plotgrp
: A character vector; variables from 'plot' tables for grouping. Use
c()
to combine multiple variables.- treegrp
: A character vector; variables from 'tree' tables for grouping. Use
c()
to combine multiple variables.- continuousplot
: A logical flag (default TRUE); if TRUE, includes only plots that have been continuously measured in all NFI cycles (5th, 6th, etc.). If FALSE, includes plots regardless of missing cycle measurements.
- strat
: A character vector; the variable used for post-stratification. In the National Forest Inventory of Korea, it is typically used by forest type.
- stockedland
: A logical flag (default TRUE); if TRUE, includes only stocked land. If FALSE, includes all land types.
Value
A data.frame
that includes CWD biomass for plot or study areas.
The structure depends on the input parameters:
If
byplot = TRUE
, each row represents a plot.If
byplot = FALSE
, each row represents the entire dataset or a group specified byplotgrp
andtreegrp
Details
This function calculates CWD biomass using methodologies employed for national statistics (mean, variance, standard error, relative standard error):
Applies national carbon emission factors to calculate CWD biomass at the individual tree level.
Estimates biomass per hectare at the plot level.
Uses the Double Sampling for Post-stratification (DSS) method to derive annual statistics.
Applies the Weighted Moving Average (WMA) method to integrate annual statistics from the 20% of plots surveyed each year into a single time point.
Note
Biomass calculation involves dividing the data into groups based on plotgrp
and then applying post-stratification to each group.
As a result, if the data for each group is not sufficiently large, the relative standard error (RSE) may be high.
It is important to check the RSE and other statistical measures in the biomass results.
References
Son, Y., Kim, R., Lee, K., Pyo, J., Kim, S., Hwang, J., Lee, S., & Park, H. (2014). Carbon emission factors and biomass allometric equations by species in Korea. Korea Forest Research Institute. Yim, J., Moon, G., Lee, M., Kang, J., Won, M., Ahn, E., & Jeon, J. (2021). 2020 Forest inventory of Korea. Korea Forest Research Institute.
Examples
data("nfi_donghae")
# Basic usage
cwd <- cwd_biomass_nfi(nfi_donghae, continuousplot = TRUE)
# Calculate CWD biomass grouped by administrative district and decay class
cwd_grp <- cwd_biomass_nfi(nfi_donghae, plotgrp = "SGG", treegrp = "DECAY", continuousplot = TRUE)
# Calculate CWD biomass for each plot
plot_biomass <- cwd_biomass_nfi(nfi_donghae, byplot = TRUE)
#> Warning: param 'byplot' has priority over param 'strat'