plot.mob_out {mobr}

Plot the multiscale MoB analysis output generated by get_delta_stats.

Description

Plot the multiscale MoB analysis output generated by get_delta_stats.

Usage

## S3 method for class 'mob_out'
plot(
  x,
  stat = "b1",
  log2 = "",
  scale_by = NULL,
  display = c("S ~ effort", "effect ~ grad", "stat ~ effort"),
  eff_sub_effort = TRUE,
  eff_log_base = 2,
  eff_disp_pts = TRUE,
  eff_disp_smooth = FALSE,
  ...
)

Arguments

x

a mob_out class object

stat

a character string that specifies what statistic should be used in the effect size plots. Options include: c('b0', 'b1', 'r', 'r2', 'r2adj', 'f') for the beta-coefficients, person correlation coefficient, r-squared, adjusted r-squared, and F-statistic respectively. If the explanatory variable is a factor then 'b1' is the only reasonable option. The default is set to the regression slope 'b1' because this appears to have the strongest statistical power.

log2

a character string specifying if the x- or y-axis should be rescale by log base 2. Only applies when display == 'S ~ effort' | 'S ~ effort'. Options include: c('', 'x', 'y', 'xy') for no rescaling, x-axis, y-axis, and both x and y-axes respectively. Default is set to no rescaling.

scale_by

a character string specifying if sampling effort should be rescaled. Options include: NULL, 'indiv', and 'plot' for no rescaling, rescaling to number of individuals, and rescaling to number of plots respectively. The rescaling is carried out using mob_out$density_stat.

display

a string that specifies what graphical panels to display. Options include:

• S ~ expl ... plot of S versus the explanatory variable

• S ~ effort ... plot of S versus sampling effort (i.e., a rarefaction curve)

• effect ~ expl ... plot of agg., N, and SAD effect size versus explanatory variable

• stat ~ effort ... plot of summary statistic versus sampling effort

Defaults to 'S ~ effort', 'effect ~ expl', and 'stat ~ effort'.

eff_sub_effort

Boolean which determines if only a subset of efforts will be considered in the plot of effect size (i.e., when display = 'effect ~ expl'. Defaults to TRUE to declutter the plots.

eff_log_base

a positive real number that determines the base of the logarithm that efforts were be distributed across, the larger this number the fewer efforts will be displayed.

eff_disp_pts

Boolean to display the raw effect points, defaults to TRUE

eff_disp_smooth

Boolean to display the regressions used to summarize the linear effect of the explanatory variable on the effect sizes, defaults to FALSE

...

parameters passed to other functions

Value

plots the effect of the SAD, the number of individuals, and spatial aggregation on the difference in species richness

Author(s)

Dan McGlinn and Xiao Xiao

Examples

data(inv_comm)
data(inv_plot_attr)
inv_mob_in = make_mob_in(inv_comm, inv_plot_attr, coord_names = c('x', 'y'))
inv_mob_out = get_delta_stats(inv_mob_in, 'group', ref_level='uninvaded',
                              type='discrete', log_scale=TRUE, n_perm=4)
plot(inv_mob_out, 'b1') 
 
plot(inv_mob_out, 'b1', scale_by = 'indiv')