accumresult {BiodiversityR} | R Documentation |

## Alternative Species Accumulation Curve Results

### Description

Provides alternative methods of obtaining species accumulation results than provided by functions `specaccum`

and `plot.specaccum`

(vegan).

### Usage

```
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", cex.lab=1, cex.axis=1, ...)
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", cex.lab=1, cex.axis=1, ...)
```

### Arguments

`x` |
Community data frame with sites as rows, species as columns and species abundance as cell values. |

`y` |
Environmental data frame. |

`factor` |
Variable of the environmental data frame that defines subsets to calculate species accumulation curves for. |

`level` |
Level of the variable to create the subset to calculate species accumulation curves. |

`scale` |
Continuous variable of the environmental data frame that defines the variable that scales the horizontal axis of the species accumulation curves. |

`method` |
Method of calculating the species accumulation curve (as in function |

`permutations` |
Number of permutations to calculate the species accumulation curve (as in function |

`conditioned` |
Estimation of standard deviation is conditional on the empirical dataset for the exact SAC (as in function |

`gamma` |
Method for estimating the total extrapolated number of species in the survey area (as in |

`addit` |
Add species accumulation curve to an existing graph. |

`xr` |
Result from |

`col` |
Colour for drawing lines of the species accumulation curve (as in function |

`labels` |
Labels to plot at left and right of the species accumulation curves. |

`ci` |
Multiplier used to get confidence intervals from standard deviatione (as in function |

`pch` |
Symbol used for drawing the species accumulation curve (as in function |

`type` |
Type of plot (as in function |

`cex` |
Character expansion factor (as in function |

`xlim` |
Limits for the X = horizontal axis. |

`ylim` |
Limits for the Y = vertical axis. |

`xlab` |
Label for the X = horizontal axis (as in function |

`ylab` |
Label for the Y = vertical axis (as in function |

`cex.lab` |
The magnification to be used for X and Y labels relative to the current setting of |

`cex.axis` |
The magnification to be used for axis annotation relative to the current setting of |

`plotit` |
Plot the results. |

`labelit` |
Label the species accumulation curves with the levels of the categorical variable. |

`legend` |
Add the legend (you need to click in the graph where the legend needs to be plotted). |

`rainbow` |
Use rainbow colouring for the different curves. |

`...` |
Other items passed to function |

### Details

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.

### Value

The functions provide alternative methods of obtaining species accumulation curve results, although results are similar as obtained by functions `specaccum`

and `plot.specaccum`

.

### Author(s)

Roeland Kindt (World Agroforestry Centre)

### References

Kindt, R. & Coe, R. (2005) Tree diversity analysis: A manual and software for common statistical methods for ecological and biodiversity studies.

https://www.worldagroforestry.org/output/tree-diversity-analysis

https://rpubs.com/Roeland-KINDT

### See Also

### Examples

```
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)
Accum.2 <- accumcomp(dune, y=dune.env, factor='Management', method='exact',
legend=FALSE, conditioned=TRUE, scale='site.totals')
## CLICK IN THE GRAPH TO INDICATE WHERE THE LEGEND NEEDS TO BE PLACED FOR
## OPTION WHERE LEGEND=TRUE (DEFAULT).
## Not run:
# ggplot2 plotting method
data(warcom)
data(warenv)
Accum.3 <- accumcomp(warcom, y=warenv, factor='population',
method='exact', conditioned=F, plotit=F)
library(ggplot2)
# possibly need for extrafont::loadfonts(device="win") to have Arial
# as alternative, use library(ggThemeAssist)
BioR.theme <- theme(
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid = element_blank(),
axis.line = element_line("gray25"),
text = element_text(size = 12, family="Arial"),
axis.text = element_text(size = 10, colour = "gray25"),
axis.title = element_text(size = 14, colour = "gray25"),
legend.title = element_text(size = 14),
legend.text = element_text(size = 14),
legend.key = element_blank())
accum.long3 <- accumcomp.long(Accum.3, ci=NA, label.freq=5)
plotgg1 <- ggplot(data=accum.long3, aes(x = Sites, y = Richness, ymax = UPR, ymin= LWR)) +
scale_x_continuous(expand=c(0, 1), sec.axis = dup_axis(labels=NULL, name=NULL)) +
scale_y_continuous(sec.axis = dup_axis(labels=NULL, name=NULL)) +
geom_line(aes(colour=Grouping), size=2) +
geom_point(data=subset(accum.long3, labelit==TRUE),
aes(colour=Grouping, shape=Grouping), size=5) +
geom_ribbon(aes(colour=Grouping), alpha=0.2, show.legend=FALSE) +
BioR.theme +
scale_color_brewer(palette = "Set1") +
labs(x = "Trees", y = "Loci", colour = "Population", shape = "Population")
plotgg1
## End(Not run) # dontrun
```

*BiodiversityR*version 2.16-1 Index]