cms {dplR} | R Documentation |
Detrend multiple ring-width series simultaneously using the C-method.
cms(rwl, po, c.hat.t = FALSE, c.hat.i = FALSE)
rwl |
a |
po |
a |
c.hat.t |
a |
c.hat.i |
a |
This method detrends and standardizes tree-ring series by calculating a growth curve based on constant annual basal area increment. The method is based on the “assumption that constant growth is expressed by a constant basal area increment distributed over a growing surface” (Biondi and Qeadan 2008). The detrending is the estimation and removal of the tree’s natural biological growth trend. The standardization is done by dividing each series by the growth trend to produce units in the dimensionless ring-width index (RWI).
This attempts to remove the low frequency variability that is due to biological or stand effects.
See the reference below for further details.
A data.frame
containing the dimensionless and detrended
ring-width indices with column names, row names and dimensions of
rwl
if c.hat.t
is FALSE
and
c.hat.i
is FALSE
.
Otherwise a list
of length 2 or 3 containing the RWI
data.frame
, a data.frame
containing the C-curves for
each tree (c.hat.t
), and/or a vector containing the
C-values for each tree (c.hat.i
) depending on the output
flags. See Eq. 12 in Biondi and Qeadan (2008) for more detail on
c.hat.t
, and c.hat.i
.
DendroLab website: https://dendrolaborg.wordpress.com/
Code provided by DendroLab based on programming by F. Qeadan and F. Biondi, University of Nevada Reno, USA and adapted for dplR by Andy Bunn. Patched and improved by Mikko Korpela.
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.
library(graphics)
library(utils)
data(gp.rwl)
data(gp.po)
gp.rwi <- cms(rwl = gp.rwl, po = gp.po)
gp.crn <- chron(gp.rwi)
crn.plot(gp.crn, add.spline = TRUE)
## c.hat
gp.rwi <- cms(rwl = gp.rwl, po = gp.po, c.hat.t = TRUE, c.hat.i = TRUE)
dotchart(gp.rwi$c.hat.i, ylab = "Series", xlab = expression(hat(c)[i]))
tmp <- gp.rwi$c.hat.t
plot(tmp[, 1], type = "n", ylim = range(tmp, na.rm = TRUE),
xlab = "Cambial Age", ylab = expression(hat(c)[t]))
apply(tmp, 2, lines)