ht.fvs.ni.m: Predicts height (m) from diameter (cm) by species, using...

In FAwR: Functions and Datasets for "Forest Analytics with R"

Description

This vectorized function uses models and parameter estimates from Wykoff et al. (1982) to predict tree heights given over-bark diameter measurements (cm) taken at 1.37 m (4'6”). The function ht.fvs.ni.ft performs the computation in imperial units, and ht.fvs.ni.m is a wrapper for convenience.

Usage

ht.fvs.ni.ft(spp, dbh.in)
ht.fvs.ni.m(spp, dbh.cm)

Arguments

spp	Tree species. Must be one of: WP, WL, DF, GF, WH, WC, LP, ES, SF, PP, MH
dbh.cm	Tree diameter, cm, measured at 1.37 m. from the ground.
dbh.in	Tree diameter, in., measured at 1.37 m. from the ground.

Details

The species are: WP = white pine, WL = western larch, DF = Douglas-fir, GF = grand fir, WH = western hemlock, WC = western red cedar, LP = lodgepole pine, ES = Engelmann spruce, SF = subalpine fir, PP = ponderosa pine, and MH = mountain hemlock.

The function was fitted using least squares regression; the resposne variable was log of height and the predictor variable 1 / (DBH + 1).

Value

The function returns a vector of tree heights, in metres.

Note

The function doesn't perform any input checks. Caveat computator.

Author(s)

Andrew Robinson <[e-mail]>

References

Robinson, A.P., and J.D. Hamann. 2010. Forest Analytics with R: an Introduction. Springer.

Wykoff, W. R., Crookston, N. L., Stage, A. R., 1982. User's Guide to the Stand Prognosis Model. GTR-INT 133, USDA Forest Service, Ogden, UT.

Examples

ht.fvs.ni.m(c("DF, WH"), c(25, 27))

Example output

Loading required package: MASS
Loading required package: lattice
Loading required package: glpkAPI
using GLPK version 4.65
[1] NA NA

FAwR documentation built on Jan. 13, 2021, 7:45 a.m.