Predict All Individual Biomass Components for Trees — silv_predict_biomass

Predicts all available individual biomass components (e.g., stem, bark, branches, roots) for the given trees in a single call, returning a wide data frame.

Usage

silv_predict_biomass_components(
  species,
  diameter,
  height = NULL,
  model_fn,
  ntrees = NULL,
  rcd = NULL,
  bp = NULL,
  quiet = TRUE
)

Arguments

species: A character vector specifying the scientific names of the tree species.
diameter: A numeric vector of tree diameters at breast height (in cm).
height: An optional numeric vector of tree heights (in m). Defaults to NULL.
model_fn: A function or character string. The constructer function of the model (e.g., eq_biomass_ruiz_peinado_2011) or the model ID string (e.g., "ruiz-peinado-2011").
ntrees: An optional numeric vector indicating the number of trees in each class. Defaults to NULL.
rcd: An optional numeric vector of root collar diameters (in cm).
bp: An optional numeric vector of biomass packing values (in m³).
quiet: A logical value. If TRUE, suppresses any informational messages.

Value

A data.frame with the columns species, diameter (cm), height (m, if provided), and one additional numeric column (in kg) for each individual biomass component available for the selected species and model.

Examples

# 1. Vector-based calculation: predict all components for Pinus pinaster
comp_results <- silv_predict_biomass_components(
  species = c("Pinus pinaster", "Pinus pinaster"),
  diameter = c(20, 25),
  height = c(12, 15),
  model_fn = eq_biomass_ruiz_peinado_2011
)
print(comp_results)
#>          species diameter height     stem thick and medium branches
#> 1 Pinus pinaster       20     12  72.8882                  4.650078
#> 2 Pinus pinaster       25     15 134.1258                  9.372480
#>   small branches and leaves    roots
#> 1                  13.45796 19.74563
#> 2                  22.58450 36.91533

# 2. Dataset-based tutorial: apply to a forest inventory data frame
inventory <- data.frame(
  tree_id  = 1:3,
  species  = c("Pinus pinaster", "Pinus pinaster", "Pinus pinaster"),
  dbh_cm   = c(18.5, 22.1, 29.4),
  height_m = c(14.0, 16.5, 19.0)
)

# Predict components for the entire dataset
comp_df <- silv_predict_biomass_components(
  species  = inventory$species,
  diameter = inventory$dbh_cm,
  height   = inventory$height_m,
  model_fn = "ruiz-peinado-2011"
)

# Combine and display results (excluding repeated identifier columns)
inventory_with_components <- cbind(
  inventory, 
  comp_df[, -(1:3)]
)
print(inventory_with_components)
#>   tree_id        species dbh_cm height_m     stem thick and medium branches
#> 1       1 Pinus pinaster   18.5     14.0  67.9861                  3.640084
#> 2       2 Pinus pinaster   22.1     16.5 109.6073                  6.362988
#> 3       3 Pinus pinaster   29.4     19.0 218.7102                 15.595667
#>   small branches and leaves    roots
#> 1                  11.23125 15.86838
#> 2                  16.96601 26.12516
#> 3                  32.89694 58.16060