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.

`abund(x, f = 0.2)`# S3 method for abund
extract(e, n, left = TRUE, ...)
# S3 method for abund
identify(x, label.pts = FALSE, lvert = TRUE, lvars = TRUE, col = 2, lty = 2, ...)
# S3 method for abund
lines(x, n = x$n, lvert = TRUE, lvars = TRUE, col = 2, lty = 2, ...)
# S3 method for abund
plot(x, n = x$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 abund
print(x, ...)
# S3 method for summary.abund
print(x, ...)
# S3 method for abund
summary(object, ...)

An object of type 'abund' is returned. It has methods `print()`

,

`summary()`

, `plot()`

, `lines()`

, `identify()`

, `extract()`

.

- 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

Philippe Grosjean (phgrosjean@sciviews.org), Frédéric Ibanez (ibanez@obs-vlfr.fr)

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.

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.

`escouf`

```
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)
```

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