Provides alternative methods of obtaining species accumulation results than provided by functions specaccum
and plot.specaccum
(vegan).
accumresult(x,y="",factor="",level,scale="",method="exact",permutations=100,
conditioned=T, gamma="boot", ...)
accumplot(xr,addit=F,labels="",col=1,ci=2,pch=1,type="p",cex=1,xlim=c(1,xmax),
ylim=c(1,rich),xlab="sites",ylab="species richness",...)
accumcomp(x,y="",factor,scale="",method="exact",permutations=100,
conditioned=T, gamma="boot",plotit=T,labelit=T,legend=T,rainbow=T,
xlim=c(1,max),ylim=c(0,rich),type="p",xlab="sites",
ylab="species richness",...)
Community data frame with sites as rows, species as columns and species abundance as cell values.
Environmental data frame.
Variable of the environmental data frame that defines subsets to calculate species accumulation curves for.
Level of the variable to create the subset to calculate species accumulation curves.
Continuous variable of the environmental data frame that defines the variable that scales the horizontal axis of the species accumulation curves.
Method of calculating the species accumulation curve (as in function specaccum
). Method "collector" adds sites in the order they happen to be in the data, "random" adds sites in random order, "exact" finds the expected (mean) species richness, "coleman" finds the expected richness following Coleman et al. 1982, and "rarefaction" finds the mean when accumulating individuals instead of sites.
Number of permutations to calculate the species accumulation curve (as in function specaccum
).
Estimation of standard deviation is conditional on the empirical dataset for the exact SAC (as in function specaccum
).
Method for estimating the total extrapolated number of species in the survey area (as in specaccum
).
Add species accumulation curve to an existing graph.
Result from specaccum
or accumresult
.
Colour for drawing lines of the species accumulation curve (as in function plot.specaccum
).
Labels to plot at left and right of the species accumulation curves.
Multiplier used to get confidence intervals from standard deviatione (as in function plot.specaccum
).
Symbol used for drawing the species accumulation curve (as in function points
).
Type of plot (as in function plot
).
Character expansion factor (as in function plot
).
Limits for the horizontal axis.
Limits for the vertical axis.
Label for the horizontal axis.
Label for the vertical axis.
Plot the results.
Label the species accumulation curves with the levels of the categorical variable.
Add the legend (you need to click in the graph where the legend needs to be plotted).
Use rainbow colouring for the different curves.
Other items passed to function specaccum
or plot.specaccum
.
The functions provide alternative methods of obtaining species accumulation curve results, although results are similar as obtained by functions specaccum
and plot.specaccum
.
These functions provide some alternative methods of obtaining species accumulation results, although function specaccum
is called by these functions to calculate the actual species accumulation curve.
Functions accumresult
and accumcomp
allow to calculate species accumulation curves for subsets of the community and environmental data sets. Function accumresult
calculates the species accumulation curve for the specified level of a selected environmental variable. Method accumcomp
calculates the species accumulation curve for all levels of a selected environmental variable separatedly. Both methods allow to scale the horizontal axis by multiples of the average of a selected continuous variable from the environmental dataset (hint: add the abundance of each site to the environmental data frame to scale accumulation results by mean abundance).
Functions accumcomp
and accumplot
provide alternative methods of plotting species accumulation curve results, although function plot.specaccum
is called by these functions. When you choose to add a legend, make sure that you click in the graph on the spot where you want to put the legend.
Kindt, R. & Coe, R. (2005) Tree diversity analysis: A manual and software for common statistical methods for ecological and biodiversity studies.
http://www.worldagroforestry.org/output/tree-diversity-analysis
# NOT RUN {
library(vegan)
data(dune.env)
data(dune)
dune.env$site.totals <- apply(dune,1,sum)
Accum.1 <- accumresult(dune, y=dune.env, scale='site.totals', method='exact', conditioned=TRUE)
Accum.1
accumplot(Accum.1)
accumcomp(dune, y=dune.env, factor='Management', method='exact', legend=FALSE, conditioned=TRUE)
## CLICK IN THE GRAPH TO INDICATE WHERE THE LEGEND NEEDS TO BE PLACED FOR
## OPTION WHERE LEGEND=TRUE (DEFAULT).
# }
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