simulate_harvesting {MLFS}

A sub model to simulate harvesting within the MLFS

Description

Harvesting is based on probability sampling, which depends on the selected parameters and the seize of a tree. Bigger trees have higher probability of being harvested when final cut is applied, while smaller trees have higher probability of being sampled in the case of thinning.

Usage

simulate_harvesting(
  df,
  harvesting_sum,
  df_thinning_weights_species = NULL,
  df_final_cut_weights_species = NULL,
  df_thinning_weights_plot = NULL,
  df_final_cut_weights_plot = NULL,
  harvesting_type = "random",
  share_thinning = 0.8,
  final_cut_weight = 1e+07,
  thinning_small_weight = 1e+05,
  harvest_sum_level = 1,
  plot_upscale_type,
  plot_upscale_factor,
  forest_area_ha
)

Arguments

df

a data frame with individual tree data, which include basal areas in the middle of a simulation step, species name and code

harvesting_sum

a value, or a vector of values defining the harvesting sums through the simulation stage. If a single value, then it is used in all simulation steps. If a vector of values, the first value is used in the first step, the second in the second step, etc.

df_thinning_weights_species

data frame with thinning weights for each species. The first column represents species code, each next column consists of species-specific thinning weights

df_final_cut_weights_species

data frame with final cut weights for each species. The first column represents species code, each next column consists of species-specific final cut weights

df_thinning_weights_plot

data frame with harvesting weights related to plot IDs, used for thinning

df_final_cut_weights_plot

data frame with harvesting weights related to plot IDs, used for final cut

harvesting_type

character, it could be 'random', 'final_cut', 'thinning' or 'combined'. The latter combines 'final_cut' and 'thinning' options, where the share of each is specified with the argument 'share_thinning'

share_thinning

numeric, a number between 0 and 1 that specifies the share of thinning in comparison to final_cut. Only used if harvesting_type is 'combined'

final_cut_weight

numeric value affecting the probability distribution of harvested trees. Greater value increases the share of harvested trees having larger DBH. Default is 10.

thinning_small_weight

numeric value affecting the probability distribution of harvested trees. Greater value increases the share of harvested trees having smaller DBH. Default is 1.

harvest_sum_level

integer with value 0 or 1 defining the level of specified harvesting sum: 0 for plot level and 1 for regional level

plot_upscale_type

character defining the upscale method of plot level values. It can be 'area' or 'upscale factor'. If 'area', provide the forest area represented by all plots in hectares (forest_area_ha argument). If 'factor', provide the fixed factor to upscale the area of all plots. Please note: forest_area_ha/plot_upscale_factor = number of unique plots. This argument is important when harvesting sum is defined on regional level.

plot_upscale_factor

numeric value to be used to upscale area of each plot

forest_area_ha

the total area of all forest which are subject of the simulation

Value

a data frame with updated status (code) of all individual trees based on the simulation of harvesting

Examples

library(MLFS)
data(data_v5)

data_v5 <- simulate_harvesting(df = data_v5,
            harvesting_sum = 5500000,
            harvesting_type = "combined",
            share_thinning = 0.50,
            harvest_sum_level = 1,
            plot_upscale_type = "factor",
            plot_upscale_factor = 1600,
            final_cut_weight = 5,
            thinning_small_weight = 1)