bootree: Bootstrap Confidence Intervals for tree biomass samples

In adalardo/samplePlotR: Sample plots from a cartesian space and return descriptive statistics

Description

bootree return confidence interval for biomass (AGB) from samples of trees in a plot

Usage

bootree(plotdata, samplename = "fragpar", area = 100, varnames = c(dbh =
  "diameter.breast.height", H = "plant.height", wd = "wood.density"),
  alom = chave, quantil = c(0.025, 0.975), nsim = 1000,
  convtoMgha = TRUE)

Arguments

plotdata	a data frame with a forest sample plots data.
samplename	character vector with the name of the column in plotdata that indicate the plots codes.
area	numeric, plot size in square meters.
varnames	vector of names variables variable diameter at breast hight, plant height and wood density, note that they should be named as 'dbh', 'H' and 'wd' respectivelly. Put only those varibles that are in plotdata and needed for alometric calculation.
alom	alometric function to be used, possibilities are chave burgdeli, scatena and tiopolo. Those are functions so should be write without quotes.
quantil	Bootstrap quantiles to return, default is 95% limite confidence interval (0.25 and 0.975 quatiles);
nsim	numeric number of resamples from data to calculate bootstrap.
convtoMgha	logical, if true convert AGB to Mg (tons) per hectar, otherwise the variable is in Kg per sample size.

Details

Bootstrap resamples above ground biomass of each sample, reordering the sample tag.

Value

biomass calculation and bootstrap confidence interval, as well as standard deviation for the simulated bootstrap distribution

Author(s)

Alexandre Adalardo de Oliveira and Paulo Inacio Prado [e-mail]

References

SCATENA, F.N., SILVER, W., SICCAMA, T., JOHNSON, A. & SÁNCHEZ, M.J. 1993. Biomass and nutrient content of the Bisley Experimental Watersheds, Luquillo Experimental Forest, Puerto Rico, before and after Hurricane Hugo, 1989. Biotropica 25(1):15-27.

TIEPOLO, G., CALMON, M. & FERETTI, A.R. 2002. Measuring and Monitoring Carbon Stocks at the Guaraqueçaba Climate Action Project, Paraná, Brazil. In: International Symposium on Forest Carbon Sequestration and Monitoring. Extension Serie Taiwan Forestry Research Institute 153:98-115.

BURGER D.M.; DELITTI, W.B.C. allometric models for estimating the phytomass of a secondary Atlantic Forest area of southeastern Brazil. Biota Neotrop.8 (4)

See Also

chave scatena tiepolo burgdeli

Examples

## Not run: 
bio = data.frame(dbh = rnorm(10, 10, 2), H= runif(10, 2, 8),
                 wd = rep(0.52,10), plots = rep(c(1,2),5))
bootree(bio, samplename = "plot", varnames =c(dbh="dbh", H = "H", wd = "wd"), nsim = 10)
metaEr(cl=10, rw=10, f0=0.2, pi=0.2, ce=0.15, tmax=100)
metaCiEr(cl=10, rw=10, f0=0.2, ci=0.2, ce=0.15, tmax=100)

## End(Not run)

adalardo/samplePlotR documentation built on May 31, 2019, 10:46 p.m.