plot.ces | R Documentation |
Methods to quickly plot CES objects of different types.
## S3 method for class 'ces'
plot(x, sites = FALSE, graph = "X", N=20, sitelist=NULL, col=c('red', 'blue'), ...)
x |
A CES object |
sites |
Logical. If TRUE, for objects creates by |
graph |
Graph type for plotting results of |
N |
Integer. If plotting an object created by |
sitelist |
Character vector. If plotting an object created by |
col |
Character vector. If plotting an object created by |
... |
Additional arguments, see details |
Plots an appropriate summary graph (or graphs) for a ces object.
For 'raw' data (created by readces
), a summary of captures by year, visit, site and species (for the top N sites/species only) with bars indicating the inter-quartile range across years.
For 'plot' data (created by extract.coverage
), the number of sites operating in each year, and the number of sites operating for a particular number of years.
For 'count' data (created by extract.data
), the number of adults and juveniles caught of the species in each year (black bars indicate the number of expected birds had there been no missing visits) and the cumulative number of birds caught where sites are ranked from those catching the most to fewest.
For abundance/productivity results (created by index
) graphs of the annual values and parameter estimates; a single trend can be produced using the 'graph=' argument, but use plot.trend()
for prettier output. Will also accept 'ylab' and 'title'.
For capture history ('ch') data (created by extract.ch
), a plot of the capture histories, grouped by site, each line represents a group of individuals with the same encounter history, colored by whether they were caught or not on each occasion; darker lines indicate more frequent histories. Also accepts xlab, ylab, cex (on the y-axis, possibly to fit more site labels in) and main.
None
In the ch plots, because birds are possibly caught twice in their first year, 'Occasion' (the x-axis) is not quite the same as Year.
Rob Robinson, the ch plot was inspired by one of Marc Kery's.
plot_trend
data(ukdata)
plots <- extract.coverage(ukdata)
robin.dat <- extract.data(ukdata, species=10990, plots=plots)
plot(robin.dat)
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