mobr (version 3.0.0)

plot_rarefaction: Plot rarefaction curves for each treatment group

Description

Plot rarefaction curves for each treatment group

Usage

plot_rarefaction(
  mob_in,
  group_var,
  ref_level = NULL,
  method,
  spat_algo = NULL,
  dens_ratio = 1,
  scales = c("alpha", "gamma", "study"),
  raw = TRUE,
  smooth = FALSE,
  avg = FALSE,
  col = NULL,
  lwd = 3,
  log = "",
  leg_loc = "topleft",
  one_panel = FALSE,
  ...
)

Arguments

mob_in

a 'mob_in' class object produced by 'make_mob_in'

group_var

String that specifies which field in mob_in$env the data should be grouped by

ref_level

String that defines the reference level of group_var to which all other groups are compared with, defaults to NULL. If NULL then the default contrasts of group_var are used.

method

a character string that specifies the method of rarefaction curve construction it can be one of the following:

• 'IBR' ... individual-based rarefaction in which species are accumulated by randomly sampling individuals

• 'SBR' ... sample-based rarefaction in which species are accumulated by randomly sampling samples (i.e., plots). Note that within plot spatial aggregation is maintained with this approach. Although this curve is implemented here, it is not used in the current version of the MoB framework

• 'nsSBR' ... non-spatial, sampled-based rarefaction in which species are accumulated by randomly sampling samples that represent a spatially random sample of individuals (i.e., no with-in plot spatial aggregation). The argument dens_ratio must also be set otherwise this sampling results in a curve identical to the IBR (see Details).

• 'sSBR' ... spatial sample-based rarefaction in which species are accumulated by including spatially proximate samples first.

• 'spexSBR' ... spatially-explicit sample-based rarefaction in which species are accumulated as in 'sSBR' but sampling effort is not measured by no. of samples, but by cumulative distance or cumulative area as specified by 'spat_algo' (see details)

spat_algo

character string that can be either: 'kNN', 'kNCN', or 'convexhull' for k-nearest neighbor, k-nearest centroid neighbor sampling, or convex-hull polygon calculation respectively. It defaults to k-nearest neighbor which is a more computationally efficient algorithm that closely approximates the potentially more correct k-NCN algo (see Details). Currently, 'kNN' and 'k-NCN' are available for method 'ssBR', while 'kNN' 'convexhull' are available for method 'spexSBR'.

dens_ratio

the ratio of individual density between a reference group and the community data (i.e., x) under consideration. This argument is used to rescale the rarefaction curve when estimating the effect of individual density on group differences in richness.

scales

character string which defaults to c('alpha', 'gamma', 'study') indicating that rarefaction curves at the alpha (i.e., single plot), gamma (i.e., group of plots), and study (i.e., all plots) scales should be computed and plotted.

raw

boolean. Defaults to TRUE so that raw rarefaction curves without averaging or smoothing are plotted

smooth

boolean. Defaults to FALSE. If set to TRUE a lowess smoother is used on the 'alpha' scale curves. Has no effect at gamma or study scales

avg

boolean. Defaults to FALSE. If set to TRUE then the average richness across the groups is computed and plotted.

col

optional vector of colors.

lwd

a number which specifies the width of the lines

log

a string that specifies if any axes are to be log transformed, options include 'x', 'y' or 'xy' in which either the x-axis, y-axis, or both axes are log transformed respectively

leg_loc

a string that specifies the location of the legend, options include: 'lowerleft', 'topleft', 'loweright','topright'

one_panel

boolean. Defaults to FALSE. If set to TRUE then the alpha scale and gamma scale curves are put on the same graph.

...

other arguments to provide to rarefaction

Examples

data(inv_comm)
data(inv_plot_attr)
inv_mob_in = make_mob_in(inv_comm, inv_plot_attr, coord_names = c('x', 'y'))
# random individual based rarefaction curves
par(mfrow=c(1,2))
plot_rarefaction(inv_mob_in, 'group', 'uninvaded', 'IBR',
                 leg_loc='bottomright')
plot_rarefaction(inv_mob_in, 'group', 'uninvaded', 'IBR',
                 log='xy')
# random sample based rarefaction curves 
plot_rarefaction(inv_mob_in, 'group', 'uninvaded', 'SBR', log='xy',
                 leg_loc='bottomright')
# spatial sample based rarefaction curves 
plot_rarefaction(inv_mob_in, 'group', 'uninvaded', 'sSBR', log='xy',
                 leg_loc='bottomright', avg = TRUE, smooth = TRUE)