abund: Sort variables by abundance

In pastecs: Package for Analysis of Space-Time Ecological Series

Sort variables by abundance

Description

Sort variables (usually species in a species x stations matrix) in function of their abundance, either in number of non-null values, or in number of individuals (in log). The f coefficient allows adjusting weight given to each of these two criteria.

Usage

abund(x, f = 0.2)

## S3 method for class 'abund'
extract(e, n, left = TRUE, ...)
## S3 method for class 'abund'
identify(x, label.pts = FALSE, lvert = TRUE, lvars = TRUE, col = 2, lty = 2, ...)
## S3 method for class 'abund'
lines(x, n = x$n, lvert = TRUE, lvars = TRUE, col = 2, lty = 2, ...)
## S3 method for class 'abund'
plot(x, n = x$n, lvert = TRUE, lvars = TRUE, lcol = 2, llty = 2, all = TRUE,
    dlab = c("cumsum", "% log(ind.)", "% non-zero"), dcol = c(1,2,4),
    dlty = c(par("lty"), par("lty"), par("lty")), dpos = c(1.5, 20), type = "l",
    xlab = "variables", ylab = "abundance",
    main = paste("Abundance sorting for:",x$data, "with f =", round(x$f, 4)), ...)
## S3 method for class 'abund'
print(x, ...)
## S3 method for class 'summary.abund'
print(x, ...)
## S3 method for class 'abund'
summary(object, ...)

Arguments

x	A data frame containing the variables to sort according to their abundance in columns for abund, or an 'abund' object for the methods
f	Weight given to the number of individuals criterium (strictly included between 0 and 1; weight for the non-null values is 1-f. The default value, f=0.2, gives enough weight to the number of non-null values to get abundant species according to this criterium first, but allowing to get at the other extreme rare, but locally abundant species
object	An 'abund' object returned by abund
e	An 'abund' object returned by abund
n	The number of variables selected at left
type	the type of graph to plot. By default, lines with 'l'
lvert	If TRUE then a vertical line separate the n variables at left from the others
lvars	If TRUE then the x-axis labels of the n left variables are printed in a different color to emphasize them
lcol	The color to use to draw the vertical line (lvert=TRUE) and the variables labels (lvars=TRUE) at left af the nth variable. By default, color 2 is used
llty	The style used to draw the vertical line (lvert=TRUE). By default, a dashed line is used
xlab	the label of the x-axis
ylab	the label of the y-axis
main	the main title of the graph
all	If TRUE then all lines are drawn (cumsum, %log(ind.) and %non-null). If FALSE, only the cumsum line is drawn
dlab	The legend labels
dcol	Colors to use for drawing the various curves on the graph
dlty	The line style to use for drawing the various curves on the graph
dpos	The position of the legend box on the graph (coordinates of its top-left corner). A legend box is drawn only if all=TRUE
col	The color to use to draw lines
lty	The style used to draw lines
...	additional parameters
label.pts	Do we have to label points on the graph or to chose an extraction level with the identify() method?
left	If TRUE, the n variables at left are extracted. Otherwise, the total-n variables at right are extracted

Details

Successive sorts can be applied. For instance, a first sort with f = 0.2, followed by an extraction of rare species and another sort with f = 1 allows to collect only rare but locally abundant species.

Value

An object of type 'abund' is returned. It has methods print(), summary(), plot(), lines(), identify(), extract().

Author(s)

Philippe Grosjean ([e-mail]), Frédéric Ibanez ([e-mail])

References

Ibanez, F., J.-C. Dauvin & M. Etienne, 1993. Comparaison des évolutions à long terme (1977-1990) de deux peuplements macrobenthiques de la baie de Morlaix (Manche occidentale): relations avec les facteurs hydroclimatiques. J. Exp. Mar. Biol. Ecol., 169:181-214.

See Also

escouf

Examples

data(bnr)
bnr.abd <- abund(bnr)
summary(bnr.abd)
plot(bnr.abd, dpos=c(105, 100))
bnr.abd$n <- 26
# To identify a point on the graph, use: bnr.abd$n <- identify(bnr.abd)
lines(bnr.abd)
bnr2 <- extract(bnr.abd)
names(bnr2)

pastecs documentation built on May 29, 2024, 5:56 a.m.