Predict tree volume using Spanish National Forest Inventory equations

Computes four volume metrics (in dm^3) for one or more trees using the allometric equations from the 3rd and 4th Spanish National Forest Inventory (SNFI3/SNFI4), as documented by MITECO (Anexo 19).

Usage

silv_predict_snfi_volume(
  province,
  species,
  dbh = NULL,
  h = NULL,
  dnm = NULL,
  quality = "default",
  quiet = FALSE
)

Arguments

province: A character or numeric vector. Province name (e.g. "Cantabria") or province code (e.g. 39). See silv_snfi_provinces().
species: A character or numeric vector. Species scientific name (e.g. "Pinus radiata") or SNFI species code (e.g. 28). See silv_snfi_species().
dbh: A numeric vector of diameter at breast height in cm.
h: A numeric vector of tree heights in m. Optional for some models (e.g. SNFI3 model 14), but required by most VCC equations.
dnm: A numeric vector of mean plot diameter in cm. Required only when the IAVC equation uses model 13.
quality: A character or numeric vector. Quality/shape class (1-6). Use "default" (the default) to select the first available class.
quiet: A logical value. If TRUE, suppresses citation messages. Defaults to FALSE.

Value

A data.frame with one row per input tree and five columns:

vcc: Merchantable volume with bark (dm^3).
vsc: Merchantable volume without bark (dm^3).
iavc: Annual volume increment with bark (dm^3).
vle: Coarse firewood volume (dm^3).
snfi_version: Dataset used: "SNFI4" or "SNFI3".

Any component for which parameters are missing or a required input is NA returns NA for that column, without stopping execution.

Details

Model selection

For each province, SNFI4 data are preferred. When a province is not covered by SNFI4 (11 provinces), the function falls back to SNFI3 automatically. SNFI3 also provides a supplementary file for species not present in the standard provincial tables.

Equation models

Component	Models used
VCC	1, 11
VSC	7
IAVC	8, 13, 14, 16, 17, 18, 19, 20, 21, 25
VLE	10, 12

Full model equations are available in Anexo 19 of the MITECO SIG documentation (see References).

Units

Inputs: dbh and dnm in cm (converted to mm internally), h in m. All outputs in dm^3.

References

MITECO. 4th Spanish National Forest Inventory - SIG database codes. https://www.miteco.gob.es/content/dam/miteco/es/biodiversidad/temas/inventarios-nacionales/documentador_sig_tcm30-536622.pdf

MITECO. 3rd Spanish National Forest Inventory - SIG database codes. https://www.miteco.gob.es/content/dam/miteco/es/biodiversidad/servicios/banco-datos-naturaleza/documentador_bdcampo_ifn3_tcm30-282240.pdf

Examples

# 1. Vector-based calculation: single tree (Pinus radiata in Alava, province 1, code 28)
single_tree <- silv_predict_snfi_volume(
  province = 1,
  species  = 28,
  dbh      = 20,
  h        = 15,
  dnm      = 23
)
#> ℹ SNFI4 data used. Cite: MITECO SNFI4 SIG codes - <https://www.miteco.gob.es/content/dam/miteco/es/biodiversidad/temas/inventarios-nacionales/documentador_sig_tcm30-536622.pdf>
print(single_tree)
#>        vcc      vsc     iavc      vle snfi_version
#> 1 201.3054 146.1138 23.45224 13.60531        SNFI4

# 2. Vector-based calculation: multiple trees with province and species by name
multi_trees <- silv_predict_snfi_volume(
  province = c("Araba/Álava", "Cantabria"),
  species  = c("Pinus radiata", "Pinus radiata"),
  dbh      = c(20, 25),
  h        = c(15, 18),
  dnm      = c(23, 26)
)
#> ℹ SNFI4 data used. Cite: MITECO SNFI4 SIG codes - <https://www.miteco.gob.es/content/dam/miteco/es/biodiversidad/temas/inventarios-nacionales/documentador_sig_tcm30-536622.pdf>
print(multi_trees)
#>        vcc      vsc     iavc      vle snfi_version
#> 1 201.3054 146.1138 23.45224 13.60531        SNFI4
#> 2 342.0875 268.9089 20.02038 31.51750        SNFI4

# 3. Dataset-based tutorial: apply to a forest inventory data frame
inventory <- data.frame(
  tree_id   = 1:3,
  province  = c("Cantabria", "Cantabria", "Araba/Álava"),
  species   = c("Pinus radiata", "Pinus radiata", "Pinus sylvestris"),
  dbh_cm    = c(20.5, 28.0, 18.2),
  height_m  = c(15.2, 18.5, 12.0)
)

# Apply the SNFI volume estimation functions row-wise across the dataset
volume_results <- silv_predict_snfi_volume(
  province = inventory$province,
  species  = inventory$species,
  dbh      = inventory$dbh_cm,
  h        = inventory$height_m
)
#> ℹ SNFI4 data used. Cite: MITECO SNFI4 SIG codes - <https://www.miteco.gob.es/content/dam/miteco/es/biodiversidad/temas/inventarios-nacionales/documentador_sig_tcm30-536622.pdf>

# Combine and display results
inventory_with_volume <- cbind(inventory, volume_results)
print(inventory_with_volume)
#>   tree_id    province          species dbh_cm height_m      vcc      vsc
#> 1       1   Cantabria    Pinus radiata   20.5     15.2 209.4953 162.6728
#> 2       2   Cantabria    Pinus radiata   28.0     18.5 430.8241 340.2425
#> 3       3 Araba/Álava Pinus sylvestris   18.2     12.0 143.2249 108.9774
#>        iavc      vle snfi_version
#> 1 14.199498 22.05411        SNFI4
#> 2 24.359884 38.46379        SNFI4
#> 3  5.968649  8.47490        SNFI4