dplR (version 1.7.0)

skel.plot: Skeleton Plot

Description

Automatically generates a skeleton plot of tree-ring data.

Usage

skel.plot(rw.vec, yr.vec = NULL, sname = "", filt.weight = 9,
          dat.out = FALSE, master = FALSE, plot = TRUE)

Arguments

rw.vec

a numeric vector of a tree-ring chronology or series

yr.vec

optional numeric vector giving years for the tree-ring data

sname

an optional character string giving the ID for the data. The width of the string, often identical to the number of characters, must be less than 8.

filt.weight

filter length for the Hanning filter, defaults to 9

dat.out

logical flag indicating whether to return a data.frame containing the data.

master

logical flag indicating whether to make the plot with the segments inverted to ease pattern matching. If TRUE the segments will be plotted from the top down and the labels on the x axes will be on the bottom.

plot

logical flag indicating whether to make a plot.

Value

This function is invoked primarily for its side effect, which is to produce a plot. If dat.out is TRUE then a data.frame is returned with the years and height of the skeleton plot segments as columns.

Details

This makes a skeleton plot <U+2013> a plot that gives the relative growth for year t relative to years t-1 and t+1. Note that this plot is a standard plot in dendrochronology and typically made by hand for visually cross-dating series. This type of plot might be confusing to those not accustomed to visual cross-dating. See references for more information. The implementation is based on Meko<U+2019>s (2002) skeleton plotting approach.

The skeleton plot is made by calculating departures from high frequency growth for each year by comparing year t to the surrounding three years (t-1,t,t+1). Low frequency variation is removed using a hanning filter. Relative growth is scaled from one to ten but only values greater than three are plotted. This function<U+2019>s primary effect is to create plot with absolute units that can be printed and compared to other plots. Here, anomalous growth is plotted on a 2mm grid and up to 120 years are plotted on a single row with a maximum of 7 rows (840 years). These plots are designed to be plotted on standard paper using an appropriate device, e.g., postscript with defaults or to pdf with plot width and height to accommodate a landscape plot, e.g., width = 10, height = 7.5, paper = "USr". These plots are designed to be printable and cut into strips to align long series. Statistical cross-dating is possible if the data are output but more easily done using the functions xskel.plot and xskel.ccf.plot.

References

Stokes, M. A. and Smiley, T. L. (1968) An Introduction to Tree-Ring Dating. The University of Arizona Press. ISBN-13: 978-0-8165-1680-3.

Sheppard, P. R. (2002) Crossdating Tree Rings Using Skeleton Plotting. http://www.ltrr.arizona.edu/skeletonplot/introcrossdate.htm.

Meko, D. (2002) Tree-Ring MATLAB Toolbox. http://www.mathworks.com/matlabcentral/.

See Also

Devices, hanning, xskel.plot, xskel.ccf.plot

Examples

Run this code
# NOT RUN {
library(utils)
data(co021)
x <- co021[,33]
x.yrs <- time(co021)
x.name <- colnames(co021)[33]
## On a raw ring width series - undated
skel.plot(x)
## On a raw ring width series - dated with names
skel.plot(x, yr.vec = x.yrs, sname = x.name, master = TRUE)
# }
# NOT RUN {
library(grDevices)
## Try cross-dating
y <- co021[, 11]
y.yrs <- time(co021)
y.name <- colnames(co021)[11]

## send to postscript - 3 pages total
fname1 <- tempfile(fileext=".ps")
print(fname1) # tempfile used for PS output
postscript(fname1)
## "Master series" with correct calendar dates
skel.plot(x, yr.vec = x.yrs, sname = x.name, master = TRUE)
## Undated series, try to align with last plot
skel.plot(y)
## Here's the answer...
skel.plot(y, yr.vec = y.yrs, sname = y.name)
dev.off()

unlink(fname1) # remove the PS file

## alternatively send to pdf
fname2 <- tempfile(fileext=".pdf")
print(fname2) # tempfile used for PDF output
pdf(fname2, width = 10, height = 7.5, paper = "USr")
skel.plot(x, yr.vec = x.yrs, sname = x.name, master = TRUE)
skel.plot(y)
skel.plot(y, yr.vec = y.yrs, sname = y.name)
dev.off()

unlink(fname2) # remove the PDF file
# }

Run the code above in your browser using DataCamp Workspace