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Calculate biomass of Coarse Woody Debris

Source: R/cwd_biomass_nfi.R
cwd_biomass_nfi.Rd

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,
  strat = "FORTYP_SUB",
  stockedland = TRUE
)

Arguments

data

: A list generated by read_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.

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 by plotgrp and treegrp

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)

# Calculate CWD biomass grouped by administrative district and decay class
cwd_grp <- cwd_biomass_nfi(nfi_donghae, plotgrp = "SGG", treegrp = "DECAY")

# Calculate CWD biomass for each plot
plot_biomass <- cwd_biomass_nfi(nfi_donghae, byplot = TRUE)
#> Warning: param 'byplot' has priority over param 'strat'