Description Usage Arguments Value See Also Examples
This function calibrates new allometric equations from sampling previous ones. New allometric equations are calibrated for each species and location by resampling the original compiled equations; equations with a larger sample size, and/or higher taxonomic rank, and climatic similarity with the species and location in question are given a higher weight in this process.
1 2 3 4 5 6 7 8 9  est_params(
genus,
coords,
species = NULL,
new_eqtable = NULL,
wna = 0.1,
w95 = 500,
nres = 10000
)

genus 
a character vector, containing the genus (e.g. "Quercus") of each tree. 
coords 
a numeric vector of length 2 with longitude and latitude (if all trees were measured in the same location) or a matrix with 2 numerical columns giving the coordinates of each tree. 
species 
a character vector (same length as genus), containing the
species (e.g. "rubra") of each tree. Default is 
new_eqtable 
Optional. An equation table created with the

wna 
a numeric vector, this parameter is used in the 
w95 
a numeric vector, this parameter is used in the 
nres 
number of resampled values. Default is "1e4". 
An object of class "data.frame" of fitted coefficients (columns) of the nonlinear leastsquare regression:
AGB = a * dbh ^ b + e, with e ~ N(0, sigma^2)
weight_allom()
, new_equations()
.
1 2 3 4 5 6 7  # calibrate new allometries for all Lauraceae species
lauraceae < subset(scbi_stem1, Family == "Lauraceae")
est_params(
genus = lauraceae$genus,
species = lauraceae$species,
coords = c(78.2, 38.9)
)

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