bai.in: Basal Area Increment (Inside Out)

In dplR: Dendrochronology Program Library in R

Description

Convert multiple ring-width series to basal area increment (i.e., ring area) going from the pith to the bark.

Usage

bai.in(rwl, d2pith = NULL)

Arguments

rwl

a data.frame with series as columns and years as rows such as that produced by read.rwl

d2pith

an optional vector containing two variables. If present, then variable one (series in the example below) gives the series ID as either characters or factors. These must exactly match colnames(rwl). Variable two (d2pith in the example below) gives the distance from the innermost measured ring to the pith of the tree in mm. If d2pith is NULL then the distance to pith is assumed to be zero for each series (column) in rwl.

Details

This converts ring-width series (mm) to ring-area series (mm squared) (aka basal area increments) based on the distance between the innermost measured ring and the pith of the tree. It is related to bai.out, which calculates each ring area starting from the outside of the tree and working inward. Both methods assume a circular cross section (Biondi 1999). See the references below for further details.

Value

A data.frame containing the ring areas for each series with column names, row names and dimensions of rwl.

Note

DendroLab website: http://dendrolab.org/

Author(s)

Code by Andy Bunn based on work from DendroLab, University of Nevada Reno, USA. Patched and improved by Mikko Korpela.

References

Biondi, F. (1999) Comparing tree-ring chronologies and repeated timber inventories as forest monitoring tools. Ecological Applications, 9(1), 216–227.

Biondi, F. and Qeadan, F. (2008) A theory-driven approach to tree-ring standardization: Defining the biological trend from expected basal area increment. Tree-Ring Research, 64(2), 81–96.

See Also

bai.out

Examples

library(graphics)
library(stats)
library(utils)
## Toy
n <- 100
## Make three fake tree-ring series to show that these funcs work on rwl objects
base.series <- 0.75 + exp(-0.2 * 1:n)
rwl <- data.frame(x1 = base.series + abs(rnorm(n, 0, 0.05)),
                  x2 = base.series + abs(rnorm(n, 0, 0.05)),
                  x3 = base.series + abs(rnorm(n, 0, 0.05)))

## The inside out method
foo <- bai.in(rwl = rwl)
## The outside in method
bar <- bai.out(rwl = rwl)

## Identical
head(bar)
head(foo)

## Use gp data
data(gp.rwl)
data(gp.d2pith)
foo <- bai.in(rwl = gp.rwl, d2pith = gp.d2pith)
foo.crn <- chron(foo)
yrs <- time(foo.crn)
plot(yrs, foo.crn[, 1], type = "n",
     xlab = "Year", ylab = expression(mm^2))
lines(yrs, foo.crn[, 1], col = "grey", lty = "dashed")
lines(yrs, ffcsaps(foo.crn[, 1], nyrs = 32), col = "red", lwd = 2)

Example output

         x1        x2        x3
1  7.923204  7.889906  8.380657
2 21.614002 21.199569 21.995239
3 30.485703 30.733817 31.762276
4 40.661058 37.593654 39.292309
5 45.222284 43.714669 45.807184
6 48.594832 48.562144 50.973255
         x1        x2        x3
1  7.923204  7.889906  8.380657
2 21.614002 21.199569 21.995239
3 30.485703 30.733817 31.762276
4 40.661058 37.593654 39.292309
5 45.222284 43.714669 45.807184
6 48.594832 48.562144 50.973255

dplR documentation built on May 2, 2019, 6:06 p.m.