dplR (version 1.4.9)

detrend.series: Detrend a Ring-Width Series

Description

Detrend a tree-ring series by one of two methods, a smoothing spline or a statistical model. The series and fits are plotted by default.

Usage

detrend.series(y, y.name = "", make.plot = TRUE,
  method = c("Spline", "ModNegExp", "Mean"), nyrs = NULL,
  f = 0.5, pos.slope = FALSE)

Arguments

y

a numeric vector. Usually a tree-ring series.

y.name

an optional character vector to name the series for plotting purposes.

make.plot

logical flag. Makes plots of the raw data and detrended data if TRUE.

method

a character vector to determine the detrending method. See details below. Possible values are Spline, ModNegExp, Mean, or subset of c(Spline, ModNegExp,

nyrs

a number giving the rigidity of the smoothing spline, defaults to 0.67 of series length if nyrs is NULL.

f

a number between 0 and 1 giving the frequency response or wavelength cutoff. Defaults to 0.5.

pos.slope

a logical flag. Will allow for a positive slope to be used in method ModNegExp. If FALSE the line will be horizontal.

Value

• If several methods are used, returns a data.frame containing the detrended series (y) according to the methods used. If only one method is selected, returns a vector.

Details

This detrends and standardises a tree-ring series. The detrending is the estimation and removal of the tree's natural biological growth trend. The standardisation is done by dividing each series by the growth trend to produce units in the dimensionless ring-width index (RWI). There are currently three methods available for detrending although more are certainly possible. The methods implemented are a smoothing spline via ffcsaps (method = Spline), a modified negative exponential curve (method = ModNegExp), or a simple horizontal line (method = Mean). The Spline approach uses an n-year spline where the frequency response is 0.50 at a wavelength of 0.67*n years unless specified differently using nyrs and f in the function ffcsaps. This attempts to remove the low frequency variability that is due to biological or stand effects. The ModNegExpapproach attempts to fit a classic nonlinear model of biological growth of the form Y ~ a * exp(b*1:length(Y)) + k using nls. See Fritts (2001) for details about the parameters. If a nonlinear model cannot be fit then a linear model is fit. That linear model can have a positive slope unless pos.slope is FALSE in which case method Mean is used. The Meanapproach fits a horizontal line using the mean of the series. These methods are chosen because they are commonly used in dendrochronology. It is, of course, up to the user to determine the best detrending method for their data. See the references below for further details on detrending.

References

Cook, E.R. and Kairiukstis, L.A. (1990) Methods of Dendrochronology: Applications in the Environmental Sciences. Springer. ISBN-13: 978-0792305866. Fritts, H.C. (2001) Tree Rings and Climate. Blackburn. ISBN-13: 978-1930665392.

See Also

detrend

Examples

# Using a plausible representation of a tree-ring series
  gt <- 0.5 * exp (-0.05 * 1:200) + 0.2
  noise <- c(arima.sim(model = list(ar = 0.7), n = 200, mean = 1, sd = 0.5))
  series <- gt * noise
  series.rwi <- detrend.series(y=series,y.name="Foo")
  # Use series CAM011 from the Campito dataset
  data(ca533)
  series <- ca533[,"CAM011"]
  names(series) <- rownames(ca533)
  series.rwi <- detrend.series(y = series, y.name = "CAM011")