MAIN FUNCTION: iNEXT()
We first describe the main function iNEXT() with default arguments:
The arguments of this function are briefly described below, and will be explained in more details by illustrative examples in later text. This main function computes diversity estimates of order q, the sample coverage estimates and related statistics for K (if
knots=K) evenly‐spaced knots (sample sizes) between size 1 and the
endpoint, where the endpoint is described below. Each knot represents a particular sample size for which diversity estimates will be calculated. By default, endpoint = double the reference sample size (total sample size for abundance data; total sampling units for incidence data). For example, if
endpoint = 10,
knot = 4, diversity estimates will be computed for a sequence of samples with sizes (1, 4, 7, 10).
x
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a matrix, data.frame, lists of species abundances, or lists of incidence frequencies (see data format/information below).
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q
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a number or vector specifying the diversity order(s) of Hill numbers.
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datatype
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type of input data, “abundance”, “incidence_raw” or “incidence_freq”.
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size
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an integer vector of sample sizes for which diversity estimates will be computed. If NULL, then diversity estimates will be calculated for those sample sizes determined by the specified/default endpoint and knots.
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endpoint
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an integer specifying the sample size that is the endpoint for R/E calculation; If NULL, then endpoint=double the reference sample size.
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knots
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an integer specifying the number of equally‐spaced knots between size 1 and the endpoint.
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se
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a logical variable to calculate the bootstrap standard error and conf confidence interval.
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conf
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a positive number < 1 specifying the level of confidence interval.
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nboot
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an integer specifying the number of bootstrap replications.
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This function returns an "iNEXT" object which can be further used to make plots using the function ggiNEXT() to be described below.
GRAPHIC DISPLAYS: FUNCTION ggiNEXT()
The function ggiNEXT(), which extends ggplot2 to the "iNEXT" object with default arguments, is described as follows:
Here x is an "iNEXT" object. Three types of curves are allowed:
Sample-size-based R/E curve (type=1): see Figs. 1a and 2a in the main text. This curve plots diversity estimates with confidence intervals (if se=TRUE) as a function of sample size up to double the reference sample size, by default, or a user‐specified endpoint.
Sample completeness curve (type=2) with confidence intervals (if se=TRUE): see Figs. 1b and 2b in the main text. This curve plots the sample coverage with respect to sample size for the same range described in (1).
Coverage-based R/E curve (type=3): see Figs. 1c and 2c in the main text. This curve plots the diversity estimates with confidence intervals (if se=TRUE) as a function of sample coverage up to the maximum coverage obtained from the maximum size described in (1).
The argument facet.var=("none", "order", "site" or "both") is used to create a separate plot for each value of the specified variable. For example, the following code displays a separate plot (in Figs 1a and 1c) for each value of the diversity order q. The user may also use the argument grey=TRUE to plot black/white figures. The usage of color.var is illustrated in the incidence data example described in later text. The ggiNEXT() function is a wrapper around ggplot2 package to create a R/E curve using a single line of code. The resulting object is of class "ggplot", so can be manipulated using the ggplot2 tools.
out <- iNEXT(spider, q=c(0, 1, 2), datatype="abundance", endpoint=500)
# Sample‐size‐based R/E curves, separating by "site""
ggiNEXT(out, type=1, facet.var="site")
## Not run:
# Sample‐size‐based R/E curves, separating by "order"
ggiNEXT(out, type=1, facet.var="order")
# display black‐white theme
ggiNEXT(out, type=1, facet.var="order", grey=TRUE)
## End(Not run)
The argument facet.var="site" in ggiNEXT function creates a separate plot for each site as shown below:
The argument facet.var="order" and color.var="site" creates a separate plot for each diversity order site, and within each plot, different colors are used for two sites.
The following commands return the sample completeness curve in which different colors are used for the two sites:
The following commands return the coverage‐based R/E sampling curves in which different colors are used for the two sites (facet.var="site") and for three orders (facet.var="order")
INCIDENCE DATA
For illustration, we use the tropical ant data (in the dataset ant included in the package) at five elevations (50m, 500m, 1070m, 1500m, and 2000m) collected by Longino & Colwell (2011) from Costa Rica. The 5 lists of incidence frequencies are shown below. The first entry of each list must be the total number of sampling units, followed by the species incidence frequencies.
The argument color.var = ("none", "order", "site" or "both") is used to display curves in different colors for values of the specified variable. For example, the following code using the argument color.var="site" displays the sampling curves in different colors for the five sites. Note that theme_bw() is a ggplot2 function to modify display setting from grey background to black‐and‐white. The following commands return three types R/E sampling curves for ant data.
POINT ESTIMATION FUNCTION: estimateD()
We also supply the function
to compute diversity estimates with q = 0, 1, 2 for any particular level of sample size (base="size") or any specified level of sample coverage (base="coverage") for either abundance data (datatype="abundance") or incidence data (datatype="incidence_freq" or "incidence_raw"). If level=NULL, this function computes the diversity estimates for the minimum sample size/coverage among all sites.
For example, the following command returns the species diversity with a specified level of sample coverage of 98.5% for the ant data. For some sites, this coverage value corresponds to the rarefaction part whereas the others correspond to extrapolation, as indicated in the method of the output.
